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A variational formulation of the Harris functional as correction to approximate Kohn-Sham density functional theory


Fabian Belleflamme, Anna-Sophia Hehn, Marcella Iannuzzi, Juerg Hutter

  • Accurate descriptions of intermolecular interactions are of great importance in simulations of molecular liquids. We present an electronic structure method that combines the accuracy of the Harris functional approach with the computational efficiency of approximately linear-scaling density functional theory (DFT). The proposed method allows for simulations with accuracies close to the Kohn-Sham DFT reference. Embedded in the CP2K program package, the method is designed to enable ab initio molecular dynamics simulations of molecular solutions for system sizes of several thousands of atoms. As example of production applications we applied the method to molecular dynamics simulations in the isobaric-isothermal ensemble of the binary mixtures cyclohexane-methanol and toluene-methanol at different molar fractions of methanol. This record contains all CP2K input files necessary for the MD simulations, as well as 30ps trajectory files, and benchmark data of the energy correction.

Latest version: v2
Publication date: Nov 29, 2022

A Standard Solid State Pseudopotentials (SSSP) library optimized for precision and efficiency


Gianluca Prandini, Antimo Marrazzo, Ivano E. Castelli, Nicolas Mounet, Elsa Passaro, Jusong Yu, Nicola Marzari

  • Despite the enormous success and popularity of density functional theory, systematic verification and validation studies are still very limited both in number and scope. Here, we propose a universal standard protocol to verify publicly available pseudopotential libraries, based on several independent criteria including verification against all-electron equations of state and plane-wave convergence tests for phonon frequencies, band structure, cohesive energy and pressure. Adopting these criteria we obtain two optimal pseudopotential sets, namely the Standard Solid State Pseudopotential (SSSP) efficiency and precision libraries, tailored for high-throughput materials screening and high-precision materials modelling. As of today, the SSSP precision library is the most accurate open-source pseudopotential library available. This archive entry contains the database of calculations (phonons, cohesive energy, equation of state, band structure, pressure, etc.) together with the ...

Latest version: v8
Publication date: Nov 25, 2022

The role of metal adatoms in a surface-assisted cyclodehydrogenation reaction on a gold surface


Jonas Björk, Carlos Sánchez-Sánchez, Qiang Chen, Carlo A. Pignedoli, Johanna Rosen, Pascal Ruffieux, Xinliang Feng, Akimitsu Narita, Klaus Müllen, Roman Fasel

  • Dehydrogenation reactions are key steps in many metal-catalyzed chemical processes and in the on-surface synthesis of atomically precise nanomaterials. The principal role of the metal substrate in these reactions is undisputed, but the role of metal adatoms remains, to a large extent, unanswered, particularly on gold substrates. In a recent publication, we discuss their importance by studying the surface-assisted cyclodehydrogenation on Au(111) as an ideal model case. We choose a polymer theoretically predicted to give one of two cyclization products depending on the presence or absence of gold adatoms. Scanning probe microscopy experiments observe only the product associated with adatoms. We challenge the prevalent understanding of surface-assisted cyclodehydrogenation, unveiling the catalytic role of adatoms and their effect on regioselectivity. The study adds new perspectives to the understanding of metal catalysis and the design of on-surface synthesis protocols for novel ...

Latest version: v1
Publication date: Nov 24, 2022

Efficient and accurate defect level modelling in monolayer MoS₂ via GW+DFT with open boundary conditions


Guido Gandus, Youseung Lee, Leonard Deuschle, Daniele Passerone, Mathieu Luisier

  • Within the framework of many-body perturbation theory integrated with density functional theory (DFT), a novel defect-subspace projection GW method, the so-called p-GW, is proposed. By avoiding the periodic defect interference through open boundary self-energies, we show that the p-GW can efficiently and accurately describe quasi-particle correlated defect levels in two-dimensional (2D) monolayer MoS₂. By comparing two different defect states originating from sulfur vacancy and adatom to existing theoretical and experimental works, we show that our GW correction to the DFT defect levels is precisely modelled. Based on these findings, we expect that our method can provide genuine trap states for various 2D transition-metal dichalcogenide (TMD) monolayers, thus enabling the study of defect-induced effects on the device characteristics of these materials via realistic simulations.

Latest version: v1
Publication date: Nov 22, 2022

Spatiotemporal prediction of microstructure evolution with predictive recurrent neural network


Amir Abbas Kazemzadeh Farizhandi, Mahmood Mamivand

  • Prediction of microstructure evolution during material processing is essential to control the material properties. Simulation tools for microstructure evolution prediction based on physical concepts are computationally expensive and time-consuming. Therefore, they are not practical when either there is an urgent need for microstructure morphology during the process, or there is a need to generate big microstructure datasets. Essentially, microstructure evolution prediction is a spatiotemporal sequence prediction problem, where the prediction of material microstructure is difficult due to different process histories and chemistry. We propose a Predictive Recurrent Neural Network (PredRNN) model for the microstructure prediction, which extends the inner-layer transition function of memory states in LSTMs to spatiotemporal memory flow. As a case study, we used a dataset from spinodal decomposition simulation of FeCrCo alloy created by the phase-field method for training and ...

Latest version: v1
Publication date: Nov 21, 2022

Ab initio real-time quantum dynamics of charge carriers in momentum space


Zhenfa Zheng, Yongliang Shi, Jin-Jian Zhou, Oleg V. Prezhdo, Qijing Zheng, Jin Zhao

  • Application of the nonadiabatic molecular dynamics (NAMD) approach is severely limited to studying carrier dynamics in the momentum space, since a supercell is required to sample the phonon excitation and electron-phonon (e-ph) interaction at different momenta in a molecular dynamics simulation. Here, we develop an ab initio approach for the real-time quantum dynamics for charge carriers in the momentum space (NAMD_k) by directly introducing the e-ph coupling into the Hamiltonian based on the harmonic approximation. The NAMD_k approach maintains the quantum zero-point energy and proper phonon dispersion, and includes memory effects of phonon excitation. The application of NAMD_k to the hot carrier dynamics in graphene reveals the phonon-specific relaxation mechanism. An energy threshold of 0.2eV, defined by two optical phonon modes strongly coupled to the electrons, separates the hot electron relaxation into fast and slow regions with the lifetimes of pico- and nano-seconds, ...

Latest version: v1
Publication date: Nov 21, 2022

Symmetry-based computational search for novel binary and ternary 2D materials


Hai-Chen Wang, Jonathan Schmidt, Miguel A. L. Marques, Ludger Wirtz, Aldo H. Romero

  • We present a symmetry-based exhaustive approach to explore the structural and compositional richness of two-dimensional materials. We use a combinatorial engine' that constructs potential compounds by occupying all possible Wyckoff positions for a certain space group with combinations of chemical elements. These combinations are restricted by imposing charge neutrality and the Pauling test for electronegativities. The structures are then pre-optimized with a specially crafted universal neural-network force-field, before a final step of geometry optimization using density-functional theory is performed. In this way we unveil an unprecedented variety of two-dimensional materials, covering the whole periodic table in more than 30 different stoichiometries of form AnBm or AnBmCk. Among the found structures we find examples that can be built by decorating nearly all Platonic and Archimedean tesselations as well as their dual Laves or Catalan tilings. We also obtain a rich, and ...

Latest version: v1
Publication date: Nov 21, 2022

Dataset for fracture and impact toughness of high-entropy alloys


Xuesong Fan, Shiyi Chen, Baldur Steingrimsson, Weidong Li, Peter K. Liaw

  • Fracture dictates the service limits of metallic structures. Damage tolerance of materials may be characterized by fracture toughness rigorously developed from fracture mechanics, or less rigorous yet more easily obtained impact toughness (or impact energy as a variant). Given the promise of high-entropy alloys (HEAs) in structural and damage-tolerance applications, we compiled a dataset of fracture toughness and impact toughness/energy from the literature till mid-2022. The dataset is subdivided into three categories, i.e., fracture toughness, impact toughness, and impact energy, which contain 148, 14, and 78 distinct data records, respectively. On top of the alloy chemistry and measured fracture quantities, each data record also records the factors influential to fracture. Examples are material processing history, phase structure, grain size, uniaxial tensile properties such as yield strength and elongation, and testing conditions.

Latest version: v2
Publication date: Nov 21, 2022

Light-matter interactions in van der Waals photodiodes from first principles


Jiang Cao, Sara Fiore, Cedric Klinkert, Nicolas Vetsch, Mathieu Luisier

  • Strong light-matter interactions in van der Waals heterostructures (vdWHs) made of two-dimensional (2D) transition metal dichalcogenides (TMDs) provide a fertile ground for optoelectronic applications. Of particular interest are photoexcited interlayer electron-hole pairs, where electrons and holes are localized in different monolayers. Here, we present an ab initio quantum transport framework relying on maximally localized Wannier functions and the nonequilibrium Green's functions to explore light-matter interactions and charge transport in 2D vdWHs from first principles. Electron-photon scattering is accurately taken into account through dedicated self-energies. As testbed, the behavior of a MoSe₂−WSe₂ PIN photodiode is investigated under the influence of a monochromatic electromagnetic signal. Interlayer electron-hole pair generations are observed even in the absence of phonon-assisted processes. The origin of this phenomenon is identified as the delocalization of one valence band state over both monolayers composing the vdWH.

Latest version: v1
Publication date: Nov 18, 2022

Accurate and efficient band-gap predictions for metal halide perovskites at finite temperature


Haiyuan Wang, Alexey Tal, Thomas Bischoff, Patrick Gono, Alfredo Pasquarello

  • We develop a computationally efficient scheme to accurately determine finite-temperature band gaps. We here focus on materials belonging to the class ABX3 (A = Rb, Cs; B = Ge, Sn, Pb; and X = F, Cl, Br, I), which includes halide perovskites. First, an initial estimate of the band gap is provided for the ideal crystalline structure through the use of a range-separated hybrid functional, in which the parameters are determined nonempirically from the electron density and the high-frequency dielectric constant. Next, we consider two kinds of band-gap corrections to account for spin-orbit coupling and thermal vibrations including zero-point motions. In particular, the latter effect is accounted for through the special displacement method, which consists in using a single distorted configuration obtained from the vibrational frequencies and eigenmodes, thereby avoiding lengthy molecular dynamics. The sequential consideration of both corrections systematically improves the band gaps, ...

Latest version: v1
Publication date: Nov 18, 2022

Mott versus hybridization gap in the low-temperature phase of 1T-TaS₂


Francesco Petocchi, Christopher W. Nicholson, Bjoern Salzmann, Diego Pasquier, Oleg Yazyev, Claude Monney, Philipp Werner

  • We address the long-standing problem of the ground state of 1T-TaS₂ by computing the correlated electronic structure of stacked bilayers using the GW+EDMFT method. Depending on the surface termination, the semi-infinite uncorrelated system is either band insulating or exhibits a metallic surface state. For realistic values of the on-site and inter-site interactions, a Mott gap opens in the surface state, but it is smaller than the gap originating from the bilayer structure. Our results are consistent with recent scanning tunneling spectroscopy measurements for different terminating layers, and with our own photoemission measurements, which indicate the coexistence of spatial regions with different gaps in the electronic spectrum. By comparison to exact diagonalization data, we clarify the interplay between Mott insulating and band insulating behavior in this archetypal layered system.

Latest version: v1
Publication date: Nov 18, 2022

Probing magnetic orbitals and Berry curvature with circular dichroism in resonant inelastic X-ray scattering


Michael Schüler, Thorsten Schmitt, Philipp Werner

  • Resonant inelastic X-ray scattering (RIXS) can probe localized excitations at selected atoms in materials, including particle-hole transitions from valence to the conduction bands. These transitions are governed by fundamental prop- erties of the corresponding Bloch wave-functions, including orbital and mag- netic degrees of freedom, and quantum geometric properties such as the Berry curvature. In particular, orbital angular momentum (OAM), which is closely linked to the Berry curvature, can exhibit a nontrivial momentum dependence. We demonstrate how information on such OAM textures can be extracted from the circular dichroism in RIXS. Based on accurate modeling with first-principles treatment of the key ingredient – the light-matter interaction – we simulate dichroic RIXS spectra for the prototypical transition metal dichalcogenide MoSe₂ and the two-dimensional topological insulator 1T′-MoS₂ . Guided by an in- tuitive picture for the optical selection rules, we discuss how the ...

Latest version: v1
Publication date: Nov 16, 2022

Dynamics of van der Waals charge qubit in two-dimensional bilayer materials: Ab initio quantum transport and qubit measurement


Jiang Cao, Guido Gandus, Tarun Agarwal, Mathieu Luisier, Youseung Lee

  • A van der Waals (vdW) charge qubit, electrostatically confined within two-dimensional (2D) vdW materials, is proposed as a building block of future quantum computers. Its characteristics are systematically evaluated with respect to its two-level anticrossing energy difference (Δ). Bilayer graphene (Δ≈ 0) and a vdW heterostructure (Δ≫ 0) are used as representative examples. Their tunable electronic properties with an external electric field define the state of the charge qubit. By combining density functional theory and quantum transport calculations, we highlight the optimal qubit operation conditions based on charge stability and energy-level diagrams. Moreover, a single-electron transistor design based on trilayer vdW heterostructures capacitively coupled to the charge qubit is introduced as a measurement setup with low decoherence and improved measurement properties. It is found that a Δ greater than 20 meV results in a rapid mixing of the qubit states, which leads to a lower ...

Latest version: v1
Publication date: Nov 15, 2022

A machine learning model of chemical shifts for chemically and structurally diverse molecular solids


Manuel Cordova, Edgar A. Engel, Artur Stefaniuk, Federico Paruzzo, Albert Hofstetter, Michele Ceriotti, Lyndon Emsley

  • Nuclear magnetic resonance (NMR) chemical shifts are a direct probe of local atomic environments and can be used to determine the structure of solid materials. However, the substantial computational cost required to predict accurate chemical shifts is a key bottleneck for NMR crystallography. We recently introduced ShiftML, a machine-learning model of chemical shifts in molecular solids, trained on minimum-energy geometries of materials composed of C, H, N, O, and S that provides rapid chemical shift predictions with density functional theory (DFT) accuracy. Here, we extend the capabilities of ShiftML to predict chemical shifts for both finite temperature structures and more chemically diverse compounds, while retaining the same speed and accuracy. For a benchmark set of 13 molecular solids, we find a root-mean-squared error of 0.47 ppm with respect to experiment for 1H shift predictions (compared to 0.35 ppm for explicit DFT calculations), while reducing the computational cost by over four orders of magnitude.

Latest version: v1
Publication date: Nov 11, 2022

On-surface synthesis of porous graphene nanoribbons containing nonplanar [14]annulene pores


Murugan Rathamony Ajayakumar, Marco Di Giovannantonio, Carlo Antonio Pignedoli, Lin Yang, Pascal Ruffieux, Ji Ma, Roman Fasel, Xinliang Feng

  • The precise introduction of nonplanar pores in the backbone of graphene nanoribbon represents a great challenge. In a recent work, we explore a synthetic strategy toward the preparation of nonplanar porous graphene nanoribbon from a predesigned dibromohexabenzotetracene monomer bearing four cove-edges. Successive thermal annealing steps of the monomers indicate that the dehalogenative aryl-aryl homocoupling yields a twisted polymer precursor on a gold surface and the subsequent cyclodehydrogenation leads to a defective porous graphene nanoribbon containing nonplanar [14]annulene pores and five-membered rings as characterized by scanning tunneling microscopy and noncontact atomic force microscopy. Although the C–C bonds producing [14]annulene pores are not achieved with high yield, our results provide new synthetic perspectives for the on-surface growth of nonplanar porous graphene nanoribbons. The record contains data to support the results of our work

Latest version: v1
Publication date: Nov 11, 2022

Limits to scaling relations between adsorption energies?


Sudarshan Vijay, Georg Kastlunger, Karen Chan, Jens Nørskov

  • Linear scaling relations have led to an understanding of trends in catalytic activity and selectivity of many reactions in heterogeneous and electro-catalysis. Yet, linear scaling between the chemisorption energies of any two small molecule adsorbates is not guaranteed. A prominent example is the lack of scaling between the chemisorption energies of carbon and oxygen on transition metal surfaces. In this work, we show that this lack of scaling originates from different re-normalised adsorbate valence energies of lower-lying oxygen versus higher-lying carbon. We develop a model for chemisorption of small molecule adsorbates within the d-band model by combining a modified form of the Newns-Anderson hybridisation energy with an effective orthogonalization term. We develop a general descriptor to a priori determine if two adsorbates are likely to scale with each other. This record contains the AiiDA archive required to reproduce all calculations in the manuscript.

Latest version: v1
Publication date: Nov 10, 2022

Theory-guided design of high-strength, high-melting point, ductile, low-density, single-phase BCC high entropy alloys


You Rao, Carolina Baruffi, Anthony De Luca, Christian Leinenbach, William Curtin

  • The search for new high-temperature alloys that can enable higher-efficiency/lower-emissions power generation has accelerated with the discovery of body-centered cubic (bcc) refractory High Entropy Alloys (HEAs). These many-component, non-dilute alloys in the Cr-Mo-W-V-Nb-Ta-Ti-Zr-Hf-Al family hold the potential for combining high strength and thermodynamic stability at high temperature with low density and room-temperature ductility, but searching the immense compositional space is daunting. Here, very recent theories and expanded thermodynamic tools are used to guide the discovery of new alloys satisfying the required suite of properties. We present the dataset we generated in search for such alloys, including 5-component equicomposition alloys, as well as new quinary and quarternary alloys in the Hf-Mo-Nb-Ta-Ti space having even better overall properties (high strength, high strength retention, good ductility, light weight and single phase).

Latest version: v1
Publication date: Nov 10, 2022

Giant Chern number of a Weyl nodal surface without upper limit


Junzhang Ma, Shengnan Zhang, Jiangpeng Song, Quansheng Wu, Sandy Ekahana, Muntaser Naamneh, Milan Radovic, Vladimir Strocov, Shunye Gao, Tian Qian, Hong Ding, Ke He, Kaustuv Manna, Claudia Felser, Nicholas Plumb, Oleg Yazyev, Yimin Xiong, Ming Shi

  • Weyl nodes can be classified into zero-dimensional (0D) Weyl points, 1D Weyl nodal lines, and 2D Weyl nodal surfaces (WNS), which possess finite Chern numbers. Up to date, the largest Chern number of WPs identified in Weyl semimetals is 4, which is thought to be a maximal value for linearly crossing points in solids. On the other hand, whether the Chern numbers of nonzero-dimensional linear crossing Weyl nodal objects have one upper limit is still an open question. In this work, combining angle-resolved photoemission spectroscopy with density-functional theory calculations, we show that the chiral crystal AlPt hosts a cube-shaped charged WNS which is formed by the linear crossings of two singly degenerate bands. Different from conventional Weyl nodes, the cube-shaped nodal surface in AlPt is enforced by nonsymmorphic chiral symmetries and time-reversal symmetry rather than accidental band crossings, and it possesses a giant Chern number |C|=26. Moreover, our results and analysis ...

Latest version: v1
Publication date: Nov 10, 2022

Variational dynamics as a ground-state problem on a quantum computer


Stefano Barison, Filippo Vicentini, Ignacio Cirac, Giuseppe Carleo

  • We propose a variational algorithm to study the real time dynamics of quantum systems as a ground-state problem on quantum devices. The method is based on the original proposal of Feynman and Kitaev to encode time into a register of auxiliary qubits. We prepare the Feynman-Kitaev Hamiltonian acting on the composed system as a qubit operator and find an approximate ground state using the Variational Quantum Eigensolver. We apply the algorithm to the study of the dynamics of a transverse field Ising chain with an increasing number of spins and time steps, proving a favorable scaling in terms of the number of two qubit gates. Through numerical experiments, we investigate its robustness against hardware noise, showing that the method can be use to evaluate dynamical properties of quantum systems and detect the presence of dynamical quantum phase transitions by measuring Loschmidt echoes. The scripts provided implement the algorithm both in Python, using the Qiskit library, and in ...

Latest version: v1
Publication date: Nov 10, 2022

Conical spin order with chiral quadrupole helix in CsCuCl₃


Hiroki Ueda, Elizabeth Skoropata, Max Burian, Victor Ukleev, Gerard Sylvester Perren, Ludmila Leroy, Julien Zaccaro, Urs Staub

  • Here we report a resonant x-ray diffraction (RXD) study at the Cu L₃ edge on the multichiral system CsCuCl₃, exhibiting helical magnetic order in a chiral crystal structure. RXD is a powerful technique to disentangle electronic degrees of freedom due to its sensitivity to electric monopoles (charge), magnetic dipoles (spin), and electric quadrupoles (orbital). We characterize electric quadrupole moments around Cu ascribed to the unoccupied Cu 3d orbital, whose quantization axis is off the basal plane. Detailed investigation of magnetic reflections reveals additional sinusoidal modulations along the principal axis superimposed on the reported helical structure, i.e., a longitudinal conical (helical-butterfly) structure. The out-of-plane modulations imply significant spin-orbit interaction despite S=1/2 of Cu²⁺.

Latest version: v1
Publication date: Nov 10, 2022

Electron-phonon calculations using a wannier-based supercell approach: applications to the monolayer MoS₂ mobility


Jonathan Backman, Youseung Lee, Mathieu Luisier

  • We present a first-principles method to calculate electron-phonon coupling elements in atomic systems, and showcase its application to the evaluation of the phonon-limited mobility of n-type single-layer MoS₂. The method combines a density functional theory (DFT) plane-wave supercell approach with a real-space maximally localized Wannier basis. It enables the calculation of electronic structure, phonon displacements with their corresponding frequencies, and real-space electron-phonon coupling elements on the same footing, without the need for density functional perturbation theory (DFPT) or Wannier interpolation. We report a low-field, intrinsic mobility of 274 cm²/Vs at room temperature for MoS₂, and highlight its dependence on carrier density and temperature. In addition, we compare our findings to the latest available modeling data and put them in perspective with the experimentally measured values. Based on these observations, the mobilities presented in this work appear to be ...

Latest version: v1
Publication date: Nov 08, 2022

Novel techniques for characterising graphene nanoplatelets using Raman spectroscopy and machine learning


Vicente Orts Mercadillo, Happiness Ijije, Luke Chaplin, Ian Kinloch, Mark Bissett

  • A significant challenge for graphene nanoplatelet (GNP) suppliers is the meaningful characterisation of platelet morphology in an industrial environment. This challenge is further exacerbated to platelet surface chemistry when scalable functionalisation processes such as plasma treatment are used to modify the GNPs to improve the filler-matrix interphase in nanocomposites. The costly and complex suite of analytical equipment necessary for a complete material description makes quality control and process optimisation difficult. Raman spectroscopy is a facile and accessible characterisation technique with recent advancements unlocking fast mapping for rapid data collection. In this work we detail several big-data methodologies that extract full value out of Raman spectra so that GNP morphology and surface chemistry can be characterised. A unsupervised peak fitting and processing algorithm was used to extract crystallinity data rapidly and accurately and correlate it with ...

Latest version: v1
Publication date: Nov 08, 2022

Locating guest molecules inside metal-organic framework pores with a multiscale computational approach


Michelle Ernst, Tomasz Poręba, Lars Gnägi, Ganna Gryn'ova

  • Molecular docking has traditionally mostly been employed in the field of protein-ligand binding. In the publication associated with this data, we extend this method, in combination with DFT-level geometry optimizations, to locate guest molecules inside the pores of metal-organic frameworks. Additional information on the adsorption strength in the studied host-guest systems emerges from the computed interaction energies. This record contains inputs and outputs of the molecular docking and the DFT computations.

Latest version: v2
Publication date: Nov 07, 2022

Screw vs. edge dislocation strengthening in body-centered-cubic high entropy alloys and implications for guided alloy design


Carolina Baruffi, Francesco Maresca, William Curtin

  • Body-centered-cubic (BCC) high entropy alloys (HEAs) can show exceptionally high strength up to high temperatures. Mechanistic theories are needed to guide alloy discovery within the immense multicomponent HEA compositional space. Here, two new theories for strengthening as controlled by screw and edge dislocations, respectively, are applied to predict the yield stresses of a range of BCC alloys over a wide range of temperatures. Results show that the screw theory, with one fitting parameter, can capture experiments in many dilute and non-dilute alloys while the parameter-free edge theory agrees with experiments in non-dilute alloys having a sufficiently large misfit parameter. These results indicate a transition in single-phase alloy strengthening from traditional screw dominance to edge dominance with increasing misfit that is enabled in complex non-dilute alloys. These results point to the use of the edge theory to guide design of high-temperature alloys in the non-dilute range.

Latest version: v1
Publication date: Nov 04, 2022

First-principles calculation of electron-phonon coupling in doped KTaO₃


Tobias Esswein, Nicola A. Spaldin

  • Motivated by the recent experimental discovery of strongly surface-plane-dependent superconductivity at surfaces of KTaO₃ single crystals, we calculate the electron-phonon coupling strength, λ, of doped KTaO₃ along the reciprocal-space high-symmetry directions. Using the Wannier-function approach implemented in the EPW package, we calculate λ across the experimentally covered doping range and compare its mode-resolved distribution along the [001], [110] and [111] directions. We find that the electron-phonon coupling is strongest in the optical modes around the Γ point, with some distribution to higher k values in the [001] direction. The electron-phonon coupling strength as a function of doping has a dome-like shape in all three directions, and is largest in the [001] direction and weakest in the [111] direction. This is in contrast to the experimentally measured critical temperatures, which are highest for the (111) plane, pointing to a non-BCS character of the superconductivity. ...

Latest version: v1
Publication date: Nov 04, 2022

Onsite and intersite electronic correlations in the Hubbard model for halide perovskites


Jiyuan Yang, Tianyuan Zhu, Shi Liu

  • Halide perovskites (HPs) are widely viewed as promising photovoltaic and light-emitting materials for their suitable band gaps in the visible spectrum. Density functional theory (DFT) calculations employing (semi)local exchange-correlation functionals usually underestimate the band gaps for these systems. Accurate descriptions of the electronic structures of HPs often demand higher-order levels of theory such as the Heyd-Scuseria-Ernzerhof (HSE) hybrid density functional and GW approximations that are much more computationally expensive than standard DFT. Here, we investigate three representative types of HPs, ABX3 halide perovskites, vacancy-ordered double perovskites (VODPs), and bond disproportionated halide perovskites (BDHPs), using DFT+U+V with onsite U and intersite V Hubbard parameters computed self-consistently without a priori assumption. The inclusion of Hubbard corrections improves the band gap prediction accuracy for all three types of HPs to a similar level of ...

Latest version: v1
Publication date: Nov 04, 2022

Theory of spontaneous grain boundary roughening in high entropy alloys


Carolina Baruffi, William Curtin

  • High Entropy Alloys (HEAs) are a new broad class of near-random solid solution alloys that can possess some impressive mechanical and physical properties including high stability against grain growth (i.e. low grain boundary (GB) mobility). Here, it is shown that an initially flat GB in an HEA can become spontaneously rough, driven by natural local compositional fluctuations. Roughening lowers the total GB energy and thus can inhibit migration. A parameter-free theoretical framework is developed to demonstrate the energetics and size scales of the roughening in terms of solute/GB interaction energies and GB disconnection energies. Above a critical level of solute/GB interactions, a planar GB is predicted to roughen down to the scale of the GB periodic unit. A similar theory for 1D GBs (minimum periodic length in one direction) is also developed since such geometries are common in atomistic simulations. Specific predictions are made for the symmetric tilt boundaries Σ17 [100] (530) ...

Latest version: v1
Publication date: Nov 03, 2022

Rich nature of Van Hove singularities in Kagome superconductor CsV₃Sb₅


Yong Hu, Xianxin Wu, Brenden R. Ortiz, Sailong Ju, Xinloong Han, Junzhang Ma, Nicholas C. Plumb, Milan Radovic, Ronny Thomale, Stephen D. Wilson, Andreas P. Schnyder

  • The recently discovered layered kagome metals AV₃Sb₅ (A=K, Rb, Cs) exhibit diverse correlated phenomena, which are intertwined with a topological electronic structure with multiple van Hove singularities (VHSs) in the vicinity of the Fermi level. As the VHSs with their large density of states enhance correlation effects, it is of crucial importance to determine their nature and properties. Here, we combine polarization-dependent angle- resolved photoemission spectroscopy with density functional theory to directly reveal the sublattice properties of 3d-orbital VHSs in CsV₃Sb₅. Four VHSs are identified around the M point and three of them are close to the Fermi level, with two having sublattice-pure and one sublattice-mixed nature. Remarkably, the VHS just below the Fermi level displays an extre- mely flat dispersion along MK, establishing the experimental discovery of higher-order VHS. The characteristic intensity modulation of Dirac cones around K further demonstrates the ...

Latest version: v1
Publication date: Nov 03, 2022

Complex magnetic structure and spin waves of the noncollinear antiferromagnet Mn₅Si₃


N. Biniskos, F. J. dos Santos, K. Schmalzl, S. Raymond, M. dos Santos Dias, J. Persson, N. Marzari, S. Blügel, S. Lounis, T. Brückel

  • Mn₅Si₃ displays an unusual and complex magnetic ground state, which is considered to be the origin of the anomalous transport and thermodynamic properties that it exhibits. We report the magnetic exchange couplings of the noncollinear antiferromagnetic phase of Mn₅Si₃ using inelastic neutron scattering measurements and density functional theory calculations. We determine the ground-state spin configuration and compute its magnon dispersion relations which are in good agreement with the ones obtained experimentally. Furthermore, we investigate the evolution of the spin texture under the application of an external magnetic field to demonstrate theoretically the multiple field-induced phase transitions that Mn₅Si₃ undergoes. Finally, we model the stability of some of the material’s magnetic moments under a magnetic field and we find that very susceptible magnetic moments in a frustrated arrangement can be tuned by the field. This data set contains the data relevant to perform the DFT ...

Latest version: v1
Publication date: Oct 26, 2022

Platinum nanoparticles under oxidizing conditions


Asfaw G. Yohannes, Karin Fink, Ivan Kondov

  • This data set includes the workflows (all steps including input parameters and output data) for the computation of the adsorption energies for atomic oxygen on different platinum nanoparticles using density functional theory. Different number of adsorbed oxygen atoms, starting from single adsorbed oxygen atoms, and different adsorption configurations have been considered. The lowest-energy adsorption configurations have been used to compute the phase diagrams describing the thermodynamic equilibrium in the platinum-oxygen system at different temperatures and pressures. For the construction of the phase diagrams, additional calculations for platinum oxide nanoparticles and a correction to the O2 dissociation energy have been performed.

Latest version: v1
Publication date: Oct 26, 2022

A transferable force field for gallium nitride crystal growth from the melt using on-the-fly active learning


Xiangyu Chen, William Shao, Nam Le, Paulette Clancy

  • Atomic-scale simulations of reactive processes have been stymied by two factors: the general lack of a suitable semi-empirical force field on the one hand, and the impractically large computational burden of using ab initio molecular dynamics on the other. In this paper, we use an “on-the-fly” active learning technique to develop a non-parameterized force field that, in essence, exhibits the accuracy of density functional theory and the speed of a classical molecular dynamics simulation. We developed a force field suitable to capture the crystallization of gallium nitride (GaN) using a novel additive manufacturing route and a combination of liquid Ga and ammonia gas precursors to grow GaN thin films. We show that this machine learning model is capable of producing a transferable force field that can model all three phases, solid, liquid and gas, involved in this additive manufacturing process. We verified our computational results against a range of experimental measurements and ...

Latest version: v2
Publication date: Oct 25, 2022

Ranking the synthesizability of hypothetical zeolites with the sorting hat


Benjamin A. Helfrecht, Giovanni Pireddu, Rocio Semino, Scott M. Auerbach, Michele Ceriotti

  • Zeolites are nanoporous alumino-silicate frameworks widely used as catalysts and adsorbents. Even though millions of siliceous networks can be generated by computer-aided searches, no new hypothetical framework has yet been synthesized. The needle-in-a-haystack problem of finding promising candidates among large databases of predicted structures has intrigued materials scientists for decades; yet, most work to date on the zeolite problem has been limited to intuitive structural descriptors. Here, we tackle this problem through a rigorous data science scheme—the “zeolite sorting hat”—that exploits interatomic correlations to discriminate between real and hypothetical zeolites and to partition real zeolites into compositional classes that guide synthetic strategies for a given hypothetical framework. We find that, regardless of the structural descriptor used by the zeolite sorting hat, there remain hypothetical frameworks that are incorrectly classified as real ones, suggesting that ...

Latest version: v2
Publication date: Oct 25, 2022

Learning local equivariant representations for large-scale atomistic dynamics


Albert Musaelian, Simon Batzner, Anders Johansson, Lixin Sun, Cameron J. Owen, Mordechai Kornbluth, Boris Kozinsky

  • A simultaneously accurate and computationally efficient parametrization of the energy and atomic forces of molecules and materials is a long-standing goal in the natural sciences. In pursuit of this goal, neural message passing has lead to a paradigm shift by describing many-body correlations of atoms through iteratively passing messages along an atomistic graph. This propagation of information, however, makes parallel computation difficult and limits the length scales that can be studied. Strictly local descriptor-based methods, on the other hand, can scale to large systems but do not currently match the high accuracy observed with message passing approaches. This work introduces Allegro, a strictly local equivariant deep learning interatomic potential that simultaneously exhibits excellent accuracy and scalability of parallel computation. Allegro learns many-body functions of atomic coordinates using a series of tensor products of learned equivariant representations, but without ...

Latest version: v1
Publication date: Oct 17, 2022

Structural, electronic, elastic, power, and transport properties of β-Ga2O3 from first principles


Samuel Poncé, Feliciano Giustino

  • We investigate the structural, electronic, vibrational, power, and transport properties of the β allotrope of Ga2O3 from first principles. We find phonon frequencies and elastic constants that reproduce the correct band ordering, in agreement with experiment. We use the Boltzmann transport equation to compute the intrinsic electron and hole drift mobility and obtain room-temperature values of 258 and 1.2 cm2/Vs, respectively, as well as 6300 and 13 cm2/Vs at 100 K. Through a spectral decomposition of the scattering contribution to the inverse mobility, we find that multiple longitudinal-optical modes of Bu symmetry are responsible for the electron mobility of β-Ga2O3 but that many acoustic modes also contribute, making it essential to include all scattering processes in the calculations. Using the von Hippel low-energy criterion, we computed the breakdown field to be 5.8 MV/cm at room temperature, yielding a Baliga ...

Latest version: v1
Publication date: Oct 04, 2022

Large-scale machine-learning-assisted exploration of the whole materials space


Jonathan Schmidt, Noah Hoffmann, Hai-Chen Wang, Pedro Borlido, Pedro J. M.A. Carriço, Tiago F. T. Cerqueira, Silvana Botti, Miguel A. L. Marques

  • Crystal-graph attention networks have emerged recently as remarkable tools for the prediction of thermodynamic stability and materials properties from unrelaxed crystal structures. Previous networks trained on two million materials exhibited, however, strong biases originating from underrepresented chemical elements and structural prototypes in the available data. We tackled this issue computing additional data to provide better balance across both chemical and crystal-symmetry space. Crystal-graph networks trained with this new data show unprecedented generalization accuracy, and allow for reliable, accelerated exploration of the whole space of inorganic compounds. We applied this universal network to performed machine-learning assisted high-throughput materials searches including 2500 binary and ternary prototypes and spanning about 1 billion compounds. After validation using density-functional theory, we uncover in total 19512 additional materials on the convex hull of ...

Latest version: v1
Publication date: Oct 04, 2022

Predicting hot-electron free energies from ground-state data


Chiheb Ben Mahmoud, Federico Grasselli, Michele Ceriotti

  • Machine-learning potentials are usually trained on the ground-state, Born-Oppenheimer energy surface, which depends exclusively on the atomic positions and not on the simulation temperature. This disregards the effect of thermally excited electrons, that is important in metals, and essential to the description of warm dense matter. An accurate physical description of these effects requires that the nuclei move on a temperature-dependent electronic free energy. We propose a method to obtain machine-learning predictions of this free energy at an arbitrary electron temperature using exclusively training data from ground-state calculations, avoiding the need to train temperature-dependent potentials, and benchmark it on metallic liquid hydrogen at the conditions of the core of gas giants and brown dwarfs. This Letter demonstrates the advantages of hybrid schemes that use physical consideration to combine machine-learning predictions, providing a blueprint for the development of ...

Latest version: v1
Publication date: Oct 03, 2022

Dataset of proximity induced superconductivity in a topological insulator


Philipp Rüßmann, Stefan Blügel

  • Interfacing a topological insulator (TI) with an s-wave superconductor (SC) is a promising material platform that offers the possibility to realize a topological superconductor through which Majorana-based topologically protected qubits can be engineered. In our computational study of the prototypical SC/TI interface between Nb and Bi₂Te₃, we identify the benefits and possible bottlenecks of this potential Majorana material platform. Bringing Nb in contact with the TI film induces charge doping from the SC to the TI, which shifts the Fermi level into the TI conduction band. For thick TI films, this results in band bending leading to the population of trivial TI quantum-well states at the interface. In the superconducting state, we uncover that the topological surface state experiences a sizable superconducting gap-opening at the SC/TI interface, which is furthermore robust against fluctuations of the Fermi energy. We also show that the trivial interface state is only marginally ...

Latest version: v1
Publication date: Sep 27, 2022

Tunable topological Dirac surface states and van Hove singularities in kagome metal GdV6Sn6


Yong Hu, Xianxin Wu, Yongqi Yang, Shunye Gao, Nicholas C. Plumb, Andreas P. Schnyder, Weiwei Xie, Junzhang Ma, Ming Shi

  • Transition-metal-based kagome materials at van Hove filling are a rich frontier for the investigation of novel topological electronic states and correlated phenomena. To date, in the idealized two-dimensional kagome lattice, topologically Dirac surface states (TDSSs) have not been unambiguously observed, and the manipulation of TDSSs and van Hove singularities (VHSs) remains largely unexplored. Here, we reveal TDSSs originating from a Z2 bulk topology and identify multiple VHSs near the Fermi level (EF) in magnetic kagome material GdV6Sn6. Using in situ surface potassium deposition, we successfully realize manipulation of the TDSSs and VHSs. The Dirac point of the TDSSs can be tuned from above to below EF, which reverses the chirality of the spin texture at the Fermi surface. These results establish GdV6Sn6 as a fascinating platform for studying the nontrivial topology, magnetism, and correlation effects ...

Latest version: v1
Publication date: Sep 26, 2022

What do we talk about, when we talk about single-crystal termination-dependent selectivity of Cu electrocatalysts for CO2 reduction? A data-driven retrospective


Kevin Rossi

  • We mine from the literature experimental data on the CO2 electrochemical reduction selectivity of Cu single crystal surfaces. We then probe the accuracy of a machine learning model trained to predict Faradaic Efficiencies for 11 CO2RR products, as a function of the applied voltage at which the reaction takes place, and the relative amounts of non equivalent surface sites, distinguished according to their nominal coordination. A satisfactory model accuracy is found only when discriminating data according to their provenance. On one hand, this result points at a qualitative agreement across reported experimental CO2RR trends for single-crystal surfaces with well-defined terminations. On the other, this finding hints at the presence of differences in nominally identical catalysts and/or CO2RR measurements, which result in quantitative disagreement between experiments.

Latest version: v1
Publication date: Sep 26, 2022

Mechanism of C-N bonds formation in electrocatalytic urea production revealed by ab initio molecular dynamics simulation


Xin Liu, Yan Jiao, Yao Zheng, Mietek Jaroniec, Shi-Zhang Qiao

  • Electrosynthesis of urea from CO2 and NOX provides an exceptional opportunity for human society, given the increasingly available renewable energy. To raise the overall electrosynthesis efficiency, the most critical reaction step for such electrosynthesis, C-N coupling, needs to be significantly improved. The C-N coupling can only happen at a narrow potential window, generally in the low overpotential region, and a fundamental understanding of the C-N coupling is needed for further development of this strategy. In this regard, we performed ab initio Molecular Dynamics (AIMD) simulations to reveal the origin of C-N coupling under a small electrode potential window with both the dynamic nature of water as a solvent, and the electrode potentials considered. We explored the key reaction networks for urea formation on Cu(100) surface in neutral electrolytes. Our work shows excellent agreement with experimentally observed selectivity under different potentials on ...

Latest version: v1
Publication date: Sep 26, 2022

Thermal conductivity of glasses above the plateau: first-principles theory and applications


Michele Simoncelli, Francesco Mauri, Nicola Marzari

  • Predicting the thermal conductivity of glasses from first principles has hitherto been a prohibitively complex problem. In fact, past works have highlighted challenges in achieving computational convergence with respect to length and/or time scales using either the established Allen-Feldman or Green-Kubo formulations, endorsing the concept that atomistic models containing thousands of atoms — thus beyond the capabilities of first-principles calculations — are needed to describe the thermal conductivity of glasses. In addition, these established formulations either neglect anharmonicity (Allen-Feldman) or miss the Bose-Einstein statistics of atomic vibrations (Green Kubo), thus leaving open the question on the relevance of these effects. Here, we present a first-principles formulation to address the thermal conductivity of glasses above the plateau, which can account comprehensively for the effects of structural disorder, anharmonicity, and quantum Bose-Einstein statistics. The ...

Latest version: v1
Publication date: Sep 22, 2022

Accurate electronic properties and intercalation voltages of olivine-type Li-ion cathode materials from extended Hubbard functionals


Iurii Timrov, Francesco Aquilante, Matteo Cococcioni, Nicola Marzari

  • The design of novel cathode materials for Li-ion batteries requires accurate first-principles predictions of structural, electronic, and magnetic properties as well as intercalation voltages in compounds containing transition-metal (TM) elements. For such systems, density-functional theory (DFT) with standard (semi-)local exchange-correlation functionals is of limited use as it often fails due to strong self-interaction (delocalization) errors that are especially large for the partially filled d shells of the TMs. Here, we perform the first comparative study of the phospho-olivine cathode materials LixMnPO4, LixFePO4, and mixed-TM LixMn1/2Fe1/2PO4 (x=0, 1/4, 1/2, 3/4, 1) using four electronic structure methods: DFT, DFT+U, DFT+U+V, and HSE06. We show that DFT+U+V outperforms the other three methods, provided that the onsite U and intersite V Hubbard parameters are determined from ...

Latest version: v1
Publication date: Sep 20, 2022

Comparative density functional theory study for predicting oxygen reduction activity of single-atom catalyst


Azim Fitri Zainul Abidin, Ikutaro Hamada

  • It has been well established that nitrogen coordinated transition metal, TM-N4-C (TM=Fe and Co) moieties, are responsible for the higher catalytic activity for the electrochemical oxygen reduction reaction. However, the results obtained using density functional theory calculations vary from one to another, which can lead to controversy. Herein, we assess the accuracy of the theoretical approach using different class of exchange-correlation functionals, i.e., Perdew-Burke-Ernzerhof (PBE) and revised PBE (RPBE), those with the Grimme's semiempirical dispersion correction (PBE+D3 and RPBE+D3), and the Bayesian error estimate functional with the nonlocal correlation (BEEF-vdW) on the reaction energies of oxygen reduction reaction on TM-N4 moieties in graphene and those with OH-termination. We found that the predicted overpotentials using RPBE+D3 are comparable and consistent with those using BEEF-vdW. Our finding indicates that a proper choice of the ...

Latest version: v1
Publication date: Sep 20, 2022

Oxygen evolution at the BiVO₄-water interface: mechanism of the water dehydrogenation reaction


Sai Lyu, Julia Wiktor, Alfredo Pasquarello

  • We study the water dehydrogenation reaction at the BiVO₄(010)-water interface by combining nudged-elastic-band calculations and electronic structure calculations at the hybrid functional level. We investigate the pathway and the kinetic barrier for the adiabatic reaction going from the hole polaron localized in BiVO₄ to the dehydrogenation of the adsorbed water molecule at the interface. The reaction is found to involve the H2O•⁺ radical cation as intermediate, to have a kinetic barrier of 0.7 eV, and to be initiated by the electron transfer. The calculated kinetic barrier is in good agreement with experiment and is consistent with the slow hole transfer kinetics observed at the surface of BiVO₄. To characterize the structural changes occurring during this process, we analyze the O-H distances for three relevant water molecules. We also examine the Wannier functions around the O atom of the adsorbate involved in the reaction to reveal the changes in the electronic structure during ...

Latest version: v1
Publication date: Sep 16, 2022

Many-body self-interaction and polarons


Stefano Falletta, Alfredo Pasquarello

  • We address the many-body self-interaction in relation to polarons in density functional theory. Our study provides (i) a unified theoretical framework encompassing many-body and one-body forms of self-interaction and (ii) an efficient semilocal scheme for charge localization. Our theoretical formulation establishes a quantitative connection between the many-body and one-body forms of self-interaction in terms of electron screening, thereby conferring superiority to the concept of many-body self-interaction. Our semilocal methodology involves the use of a weak localized potential and applies equally to electron and hole polarons. We find that polarons free from many-body self-interaction have formation energies that are robust with respect to the functional adopted.

Latest version: v1
Publication date: Sep 16, 2022

Anharmonic exciton-phonon coupling in metal-organic chalcogenides hybrid quantum wells


Christoph Kastl, Pietro Bonfà, Lorenzo Maserati

  • In stark contrast to inorganic quantum wells, hybrid quantum wells based on metal-organic semiconductors are characterized by relatively soft lattices. In the latter, excitonic states are deeply affected by coupling with optical phonons. A detailed understanding of the lattice role in exciton dynamics is therefore essential to improve the optoelectronic performance of these materials. Beyond 2D metal halide perovskites, layered metal-organic chalcogenides (MOCs) are an air-stable, underexplored material class hosting complex excitonic phenomena that could be exploited as photodetectors, light emitting devices and ultrafast photoswitches. Here, we elucidate the role of lattice phonons in the optical transitions at different temperatures in the prototypical MOC [AgSePh]∞. We detect coherent exciton-phonon coupling by pump-probe transient absorption spectroscopy, dominated by a Fröhlich interaction with optical phonons at 7 and 12 meV. Through a concerted use of ab initio ...

Latest version: v1
Publication date: Sep 14, 2022

Switching p-type to high-performance n-type organic electrochemical transistors via doped state engineering


Peiyun Li, Junwei Shi, Zhen Huang, Yuqiu Lei, Ting Lei

  • High-performance n-type organic electrochemical transistors (OECTs) are essential for logic circuits and sensors. However, the performances of n-type OECTs lag far behind that of p-type ones. Conventional wisdom posits that the LUMO energy level dictates the n-type performance. Herein, we show that engineering the doped state is more critical for n-type OECT polymers. By balancing more charges to the donor moiety, we could effectively switch a p-type polymer to high-performance n-type material. Based on this concept, the polymer, P(gTDPP2FT), exhibits a record high n-type OECT performance with μC* of 54.8 F cm⁻¹ V⁻¹ s⁻¹, mobility of 0.35 cm² V⁻¹ s⁻¹, and response speed of τon/τoff = 1.75/0.15 ms. Calculations and comparison studies show that the conversion is primarily due to the more uniform charges, stabilized negative polaron, enhanced conformation, and backbone planarity at negatively charged states. Our work highlights the critical role of understanding and engineering polymers’ doped states.

Latest version: v1
Publication date: Sep 14, 2022

Carbon dioxide adsorption and conversion to methane and ethane on hydrogen boride sheets


Taiga Goto, Shin-ichi Ito, Satish Laxman Shinde, Ryota Ishibiki, Yasuyuki Hikita, Iwao Matsuda, Ikutaro Hamada, Hideo Hosono, Takahiro Kondo

  • Hydrogen boride (HB) sheets are metal-free two-dimensional materials comprising boron and hydrogen in a 1:1 stoichiometric ratio. In spite of the several advancements, the fundamental interactions between HB sheets and discrete molecules remain unclear. Here, we report the adsorption of CO2 and its conversion to CH4 and C2H6 using hydrogen-deficient HB sheets. Although fresh HB sheets did not adsorb CO2, hydrogen-deficient HB sheets reproducibly physisorbed CO2 at 297 K. The adsorption followed the Langmuir model with a saturation coverage of 2.4 × 10−4 mol g−1 and a heat of adsorption of approximately 20 kJ mol−1, which was supported by density functional theory calculations. When heated in a CO2 atmosphere, hydrogen-deficient HB began reacting with CO2 at 423 K. The detection of CH4 and C2H6 as CO2 reaction products ...

Latest version: v1
Publication date: Sep 12, 2022

General invariance and equilibrium conditions for lattice dynamics in 1D, 2D, and 3D materials


Changpeng Lin, Samuel Poncé, Nicola Marzari

  • The long-wavelength behavior of vibrational modes plays a central role in carrier transport, phonon-assisted optical properties, superconductivity, and thermomechanical and thermoelectric properties of materials. Here, we present general invariance and equilibrium conditions of the lattice potential; these allow to recover the quadratic dispersions of flexural phonons in low-dimensional materials, in agreement with the phenomenological model for long-wavelength bending modes. We prove that for any low-dimensional material, the bending modes can have a purely out-of-plane polarization in the vacuum direction and a quadratic dispersion in the long-wavelength limit. In addition, we propose an effective approach to treat the invariance conditions in crystals with non-vanishing Born effective charges where the long-range dipole-dipole interactions induce a contribution to the stress tensor. Our approach has been successfully applied to the phonon dispersions of 158 two-dimensional ...

Latest version: v1
Publication date: Sep 12, 2022

Evolving wave networks for stealthy hyperuniform shielding and preferential attachment


Sunkyu Yu

  • The design of stealthy hyperuniform (SHU) materials has been a critical topic in realizing bandgap materials without crystalline order. Most previous approaches to constructing SHU materials, such as the collective coordinate method, have assumed the closed system, maintaining the number of particles inside a system during the design process. Here, I develop the concept of evolving wave networks, allowing for the open-system design of disordered materials based on the evolution process. The programs are applied to generate the datasets for the SHU shielding of existing materials (Code_Set_Fig_4) and the realization of preferential attachment in evolving wave networks (Code_Set_Fig_5).

Latest version: v1
Publication date: Sep 09, 2022

In silico study on probing atomistic insight into structural stability and tensile properties of Fe-doped hydroxyapatite single crystals


Subhadip Basu, Shubhadeep Nag, Nihal B Kottan, Bikramjit Basu

  • Hydroxyapatite (HA, Ca10PO4(OH)2) is a widely explored material in the experimental domain of biomaterials science, because of its resemblance with natural bone minerals. Specifically, in the bioceramic community, HA doped with multivalent cations (e.g., Mg+2, Fe+2, Sr+2, etc.) has been extensively investigated in the last few decades. Experimental research largely established the critical role of dopant content on the changes in mechanical and biocompatibility properties. The plethora of experimental measurements of mechanical response on doped HA is based on compression or indentation testing of polycrystalline materials. Such measurements, as well as computational predictions of me, on single crystalline (doped) HA are scarce. On that premise, the present study aims to build atomistic models of Fe2+-doped HA, a model system, with varying Fe content (10, 20, 30, and 40 mol%) and to explore their uniaxial tensile response by means of molecular dynamics (MD) simulation, together ...

Latest version: v1
Publication date: Aug 31, 2022

Machine learning guided high-throughput search of non-oxide garnets


Jonathan Schmidt, Hai-Chen Wang, Georg Schmidt, Miguel A. L. Marques

  • Garnets, known since the early stages of human civilization, have found important applications in modern technologies including magnetorestriction, spintronics, lithium batteries, etc. The overwhelming majority of experimentally known garnets are oxides, while explorations (experimental or theoretical) for the rest of the chemical space have been limited in scope. A key issue is that the garnet structure has a large primitive unit cell, requiring an enormous amount of computational resources. To perform a comprehensive search of the complete chemical space for new garnets, we combine recent progress in graph neural networks with high-throughput calculations. We apply the machine learning model to identify the potential (meta-)stable garnet systems before systematic density-functional calculations to validate the predictions. In this way, we discover more than 600 ternary garnets with distances to the convex hull below 100~meV/atom with a variety of physical and chemical ...

Latest version: v1
Publication date: Aug 30, 2022

OSCAR: An extensive repository of chemically and functionally diverse organocatalysts


Simone Gallarati, Puck van Gerwen, Ruben Laplaza, Sergi Vela, Alberto Fabrizio, Clemence Corminboeuf

  • We introduce OSCAR, a repository of thousands of experimentally derived (OSCAR seed and CSD-extracted) and combinatorially enriched organocatalysts (OSCAR!(NHC) and OSCAR!(DHBD) for N-heterocyclic carbenes and hydrogen bond donors, respectively). The structures and corresponding stereoelectronic properties are publicly available and constitute the starting point to build generative and predictive models for organocatalyst performance.

Latest version: v2
Publication date: Aug 30, 2022

Ferroelectric, quantum paraelectric, or paraelectric? Calculating the evolution from BaTiO3 to SrTiO3 to KTaO3 using a single-particle quantum mechanical description of the ions


Tobias Esswein, Nicola A. Spaldin

  • We present an inexpensive first-principles approach for describing quantum paraelectricity that combines density functional theory (DFT) treatment of the electronic subsystem with quantum mechanical treatment of the ions through solution of the single-particle Schrödinger equation with the DFT-calculated potential. Using BaTiO3, SrTiO3, and KTaO3 as model systems, we show that the approach can straightforwardly distinguish between ferroelectric, paraelectric, and quantum paraelectric materials, based on simple quantities extracted from standard density functional and density functional perturbation theories. We calculate the influence of isotope substitution and strain on quantum paraelectric behavior and find that, while complete replacement of oxygen-16 by oxygen-18 has a surprisingly small effect, experimentally accessible strains can induce large changes. Finally, we collect the various choices for the phonon mass that have been introduced in the literature. We ide tify those ...

Latest version: v1
Publication date: Aug 21, 2022

High-throughput computation of Raman spectra from first principles


Mohammad Bagheri, Hannu-Pekka Komsa

  • Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its atomic structure and chemical composition. Raman spectra can be simulated using atomistic first-principles methods but these are computationally demanding and thus the existing databases of computational Raman spectra are fairly small. We developed an optimized workflow to efficiently calculate the Raman tensors, from which the Raman spectra can be straightforwardly simulated. The workflow was benchmarked and validated by comparison to experiments and previous computational methods for select technologically relevant material systems. Using the workflow, we performed high-throughput calculations for a large set of materials (5099) belonging to many different material classes, and collected the results to a database.

Latest version: v1
Publication date: Aug 21, 2022

Atomistic fracture in bcc iron revealed by active learning of Gaussian approximation potential


Lei Zhang, Gábor Csányi, Erik van der Giessen, Francesco Maresca

  • Existing, classical interatomic potentials for bcc iron predict contradicting crack-tip mechanisms (i.e. cleavage, dislocation emission, phase transition) for the same crack systems, thus leaving the crack propagation mechanism in bcc iron unclear. In this work, we develop a Gaussian approximation potential (GAP) by extending a DFT database for ferromagnetic bcc iron to include highly distorted primitive bcc cells and surface separation, along with small crack-tip configurations that are identified by means of a fully automated active learning workflow. Our GAP (referred to as Fe-GAP22) predicts crack propagation within 8 meV/atom accuracy. The fully automated, active learning workflow is made publicly available on GitHub. With the newly developed Fe-GAP22, we find that in absence of other defects around the crack tip (e.g. nanovoids, dislocations), the static (T=0K) crack-tip mechanism is cleavage, thus settling the contradictions in the literature. Our work also highlights the ...

Latest version: v1
Publication date: Aug 11, 2022

Gas adsorption and process performance data for MOFs


Kevin Maik Jablonka, Andrew S. Rosen, Berend Smit

  • Reticular chemistry provides materials designers with a practically infinite playground on different length scales. However, the space of all plausible materials for a given application is so large that it cannot be explored using a brute-force approach. One promising approach to guide the design and discovery of materials is machine learning, which typically involves learning a mapping of structures onto properties from data. To advance the data-driven materials discovery of metal-organic frameworks (MOFs) for gas storage and separation applications we provide a dataset of diverse gas separation properties (CO2, CH4, H2, N2, O2 isotherms); H2S, H2O, Kr, Xe Henry coefficients (computed using grand canonical Monte-Carlo with classical force fields) as well as parasitic energy for carbon capture from natural gas and a coal-fired power plant (computed using a simple process model) for the relaxed structures in the QMOF dataset with their DDEC charges.

Latest version: v1
Publication date: Aug 11, 2022

Experimental and theoretical study of stable and metastable phases in sputtered CuInS2


Jes Larsen, Kostiantyn Sopiha, Clas Persson, Charlotte Platzer-Björkman, Marika Edoff

  • The chalcopyrite Cu(In,Ga)S2 has gained renewed interest in recent years due to its potential application in tandem solar cells. In this contribution, a combined theoretical and experimental approach is applied to investigate stable and metastable phases forming in sputtered CuInS2 (CIS) thin films. Ab initio calculations are performed to obtain formation energies, X-ray diffraction patterns, and Raman spectra of various CIS polytypes and related compounds. Multiple low-energy CIS structures with zinc-blende and wurtzite-derived lattices are identified and their XRD/Raman patterns are shown to contain many overlapping features, which could lead to misidentification unless the techniques are duly combined and analyzed. The results are verified against experimental XRD/Raman spectra measured on a series of CIS films with different compositions and treated at different temperatures, revealing the formation of several CIS polymorphs and secondary phases. The characteristic features ...

Latest version: v2
Publication date: Aug 11, 2022

AI powered, automated discovery of polymer membranes for carbon capture


Ronaldo Giro, Hsianghan Hsu, Akihiro Kishimoto, Toshiyuki Hama, Rodrigo F. Neumann, Binquan Luan, Seiji Takeda, Lisa Hamada, Mathias B. Steiner

  • Data sets and scripts for computational discovery of polymer membranes for carbon dioxide separation. The training data set with 1,169 homo-polymers provides carbon dioxide permeability, glass transition temperature and half decomposition temperature for each listed material. The output data set contains 784 optimized homo-polymer candidates generated by Inverse Design and Machine Learning techniques. The Jupyter notebook enables the use of the Polymer Property Prediction Engine as a service for generating the properties provided in the training data set.

Latest version: v5
Publication date: Jul 27, 2022

Koopmans spectral functionals: an open-source periodic-boundary implementation


Nicola Colonna, Riccardo De Gennaro, Edward Linscott, Nicola Marzari

  • Koopmans' spectral functionals aim to describe simultaneously ground state properties and charged excitations of atoms, molecules, nanostructures and periodic crystals. This is achieved augmenting standard density functionals with simple but physically motivated orbital-density-dependent corrections. These corrections act on a set of localized orbitals that, in periodic systems, resembles maximally localized Wannier function. At variance with a direct supercell implementation, we discuss here i) the complex but efficient formalism required for a periodic-boundary code using explicit Brillouin zone sampling, and ii) the calculation of the screened Koopmans' corrections with density-functional perturbation theory. In addition to delivering improved scaling with system size, the present development makes the calculation of band structures with Koopmans functionals straightforward. The implementation in the Quantum ESPRESSO distribution and the application to prototypical insulating and semiconducting systems are presented and discussed.

Latest version: v2
Publication date: Jul 22, 2022

Temperature dependent properties of the aqueous electron


Jinggang Lan, Vladimir Rybkin, Alfredo Pasquarello

  • The temperature-dependent properties of the aqueous electron have been extensively studied using mixed quantum-classical simulations in a wide range of thermodynamic conditions based on one-electron pseudopotentials. While the cavity model appears to explain most of the physical properties of the aqueous electron, only a non-cavity model has so far been successful in accounting for the temperature dependence of the absorption spectrum. Here, we present an accurate and efficient description of the aqueous electron under various thermodynamic conditions by combining hybrid functional-based molecular dynamics, machine learning techniques, and multiple time-step methods. Our advanced simulations accurately describe the temperature dependence of the absorption maximum in the presence of cavity formation. Specifically, our work reveals that the red shift of the absorption maximum results from an increasing gyration radius with temperature, rather than from global density variations as previously suggested.

Latest version: v1
Publication date: Jul 20, 2022

Shape-controlled pathways in the hydrogen production from ethanol steam reforming over ceria nanoparticles


Julia Vecchietti, Patricia Pérez-Bailac, Pablo G. Lustemberg, Esteban L. Fornero, Laura Pascual, Marta Bosco, Arturo Martínez-Arias, M. Veronica Ganduglia-Pirovano, Adrian L. Bonivardi

  • The ethanol surface reaction over CeO₂ nanooctahedra (NO) and nanocubes (NC), which mainly expose (111) and (100) surfaces, respectively, was studied by means of infrared spectroscopy (TPSR-IR), mass spectrometry (TPSR-MS) and density functional theory (DFT) calculations. TPSR-MS results show that the production of H₂ is 2.4 times higher on CeO₂ -NC than on -NO, which is rationalized starting from the different types of adsorbed ethoxy species controlled by the shape of the ceria particles. Over the CeO₂(111) surface, monodentate type I and II ethoxy species with the alkyl chain perpendicular or parallel to the surface, respectively, were identified. Whereas on the CeO₂(100) surface, bidentate and monodentate type III ethoxy species on the checkerboard O-terminated and on a pyramid of the reconstructed (100) surface, respectively, are found. The more labile surface ethoxy species on each ceria nanoshape, which are the monodentate type I or III ethoxy on CeO₂ -NO and -NC, ...

Latest version: v1
Publication date: Jul 19, 2022

Reactivity of layered manganese oxide toward water oxidation under alkaline conditions in presence and in absence of iron


Ivan Kondov, Matthias Vandichel

  • This dataset includes the computational workflows of a density functional theory based study of the oxygen evolution reaction (OER) on a manganese oxide catalyst in presence and absence of iron dopant. The thermodynamic OER overpotential has been computed by using a surface slab model based on a layered birnessite bulk structure of MnO₂ considering supercells with two and four MnO₂ units and by varying the intercalation with KOH, the amount of Fe dopant and the dopant positions. In addition, the dependence of the oxidation state of the active site atoms (either Mn or Fe) on the directly bound OER intermediate species, has been investigated. The results suggest a decrease of up to 310 mV in the thermodynamic OER overpotential upon doping the considered model structures with Fe that is consistent with the experimentally measured total overpotential decrease of 190 mV.

Latest version: v1
Publication date: Jul 19, 2022

Oxygen evolution reaction by a palladium foil in the presence of iron


Ivan Kondov, Matthias Vandichel

  • This dataset includes the full computational workflows of a density functional theory based thermodynamics model for the overpotential of the oxygen evolution reaction (OER) on an oxidized palladium surface. The model assumes an oxygen bridge vacancy as an active site on the 110 surface of the tetragonal PdO2 (rutile type structure). The critical OER potential has been computed with variation of the Fe modifyer type, either dopant or adsorbate, and modifyer position. Furthermore, an alternative bifunctional pathway of OER has been considered by adding an H atom to an auxiliary O-bridge site from which the proton−electron pair for second OER reaction step is released rather than from the hydroxylated active site. The computed OER overpotential on the Fe-free surface via this bifunctional route is 0.42 V. A substitution of Pd with Fe directly at this active site further reduces the calculated OER overpotential, over the same route, to 0.35 V. This 70 mV decrease in overpotential is ...

Latest version: v1
Publication date: Jul 19, 2022

Oxygen evolution and reduction on Fe‑doped NiOOH


Matthias Vandichel, Kari Laasonen, Ivan Kondov

  • This dataset includes the full computational workflows of a proof-of-concept study of various possible mechanisms (standard and bifunctional ones) for oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) on exfoliated NiOOH as electrocatalyst, including active edge sites (M5) and hydrogen acceptor sites in the same model system. Furthermore, explicit water is included in the model to describe the equilibration of the M-OOH species to M-OOH/eq, a crucial step that enables a bifunctional route to be operative. Additionally, different single Fe-dopant positions (M1, M2, M3, M4, M5, M6 and M7) are considered and four different reaction schemes (S1, S2, S3 and S4) are studied for the OER and the reverse ORR process. The results are relevant in alkaline conditions, where the studied model systems are stable. Certain Fe-dopant positions result in active Ni-edge sites with very low overpotentials provided that water is present within the model system.

Latest version: v1
Publication date: Jul 18, 2022

Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt


Jonathan Vandermause, Yu Xie, Jin Soo Lim, Cameron Owen, Boris Kozinsky

  • Atomistic modeling of chemically reactive systems has so far relied on either expensive ab initio methods or bond-order force fields requiring arduous parametrization. Here, we describe a Bayesian active learning framework for autonomous ``on-the-fly'' training of fast and accurate reactive many-body force fields during molecular dynamics simulations. At each time step, predictive uncertainties of a sparse Gaussian process are evaluated to automatically determine whether additional ab initio training data are needed. We introduce a general method for mapping trained kernel models onto equivalent polynomial models whose prediction cost is much lower and independent of the training set size. As a demonstration, we perform direct two-phase simulations of heterogeneous H2 turnover on the Pt(111) catalyst surface at chemical accuracy. The model trains itself in three days and performs at twice the speed of a ReaxFF model, while maintaining much higher fidelity to DFT and excellent agreement with experiment.

Latest version: v1
Publication date: Jul 18, 2022

Artificial intelligence enables mobile soil analysis for sustainable agriculture


Ademir Ferreira da Silva, Ricardo Luis Ohta, Jaione Tirapu Azpiroz, Matheus Esteves Fereira, Daniel Vitor Marçal, André Botelho, Tulio Coppola, Allysson Flavio Melo de Oliveira, Murilo Bettarello, Lauren Schneider, Rodrigo Vilaça, Noorunisha Abdool, Pedro Augusto Malanga, Vanderlei Junior, Wellington Furlaneti, Mathias Steiner

  • For optimizing production yield while limiting negative environmental impact, sustainable agriculture benefits greatly from real-time, on-the-spot analysis of soil at low cost. Colorimetric paper sensors are ideal candidates for cheap and rapid chemical spot testing. However, their field application requires previously unattained paper sensor reliability and automated readout and analysis by means of integrated mobile communication, artificial intelligence, and cloud computing technologies. Here, we report such a mobile chemical analysis system based on colorimetric paper sensors that operates under tropical field conditions. By mapping topsoil pH in a field with an area of 9 hectares, we have benchmarked the mobile system against precision agriculture standards following a protocol with reference analysis of compound soil samples. As compared with routine lab analysis, our mobile soil analysis system has correctly classified soil pH in 97% of cases while reducing the analysis ...

Latest version: v4
Publication date: Jul 18, 2022

Bloch's theorem in orbital-density-dependent functionals: Band structures from Koopmans spectral functionals


Riccardo De Gennaro, Nicola Colonna, Edward Linscott, Nicola Marzari

  • Koopmans-compliant functionals provide an orbital-density-dependent framework for an accurate evaluation of spectral properties; they are obtained by imposing a generalized piecewise-linearity condition on the total energy of the system with respect to the occupation of any orbital. In crystalline materials, due to the orbital-density-dependent nature of the functionals, minimization of the total energy to a ground state provides a set of minimizing variational orbitals that are localized and thus break the periodicity of the underlying lattice. Despite this, we show that Bloch symmetry can be preserved and it is possible to describe the electronic states with a band-structure picture, thanks to the Wannier-like character of the variational orbitals. We also present a method to unfold and interpolate the electronic bands from supercell (Γ-point) calculations, which enables us to calculate full band structures with Koopmans-compliant functionals. The results obtained for a set of ...

Latest version: v2
Publication date: Jul 08, 2022

turboMagnon - A code for the simulation of spin-wave spectra using Liouville-Lanczos approach to time-dependent density-functional perturbation theory


Tommaso Gorni, Oscar Baseggio, Pietro Delugas, Stefano Baroni, Iurii Timrov

  • We introduce turboMagnon, an implementation of the Liouville-Lanczos approach to linearized time-dependent density-functional theory, designed to simulate spin-wave spectra in solid-state materials. The code is based on the noncollinear spin-polarized framework and the self-consistent inclusion of spin-orbit coupling that allow to model complex magnetic excitations. The spin susceptibility matrix is computed using the Lanczos recursion algorithm that is implemented in two flavors - the non-Hermitian and the pseudo-Hermitian one. turboMagnon is open-source software distributed under the terms of the GPL as a component of QE. As with other components, turboMagnon is optimized to run on massively parallel architectures using native mathematical libraries (LAPACK and FFTW) and a hierarchy of custom parallelization layers built on top of MPI. The effectiveness of the code is showcased by computing magnon dispersions for the CrI₃ monolayer, and the importance of the spin-orbit coupling is discussed.

Latest version: v1
Publication date: Jun 29, 2022

Thermodynamics and dielectric response of BaTiO₃ by data-driven modeling


Lorenzo Gigli, Max Veit, Michele Kotiuga, Giovanni Pizzi, Nicola Marzari, Michele Ceriotti

  • Modeling ferroelectric materials from first principles is one of the successes of density-functional theory, and the driver of much development effort, requiring an accurate description of the electronic processes and the thermodynamic equilibrium that drive the spontaneous symmetry breaking and the emergence of macroscopic polarization. We demonstrate the development and application of an integrated machine learning (ML) model that describes on the same footing structural, energetic and functional properties of barium titanate (BaTiO₃), a prototypical ferroelectric. The model uses ab initio calculations as reference and achieves accurate yet inexpensive predictions of energy and polarization on time and length scales that are not accessible to direct ab initio modeling. The ML model allows us to thoroughly probe the static and dynamical behavior of BaTiO₃ across its phase diagram, without the need to introduce a coarse-grained description of the ferroelectric transition. ...

Latest version: v1
Publication date: Jun 29, 2022

In situ spectroelectrochemical probing of CO redox landscape on copper single-crystal surfaces


Feng Shao, Jun Kit Wong, Qi Hang Low, Marcella Iannuzzi, Jingguo Li, Jinggang Lan

  • Electrochemical reduction of CO(2) to value-added chemicals and fuels is a promising strategy to sustain pressing renewable energy demands and address climate change issues. Direct observation of reaction intermediates during the CO(2) reduction reaction will contribute to mechanistic understandings and thus promote the design of catalysts with the desired activity, selectivity, and stability. Herein, we combined in situ electrochemical shell-isolated nanoparticle-enhanced Raman spectroscopy and ab initio molecular dynamics calculations to investigate the CORR process on Cu single-crystal surfaces in various electrolytes. Competing redox pathways and coexistent intermediates of CO adsorption dimerization, oxidation, and hydrogenation, as well as Cu-Oad/Cu-OHad species at Cu-electrolyte interfaces, were simultaneously identified using in situ spectroscopy and further confirmed with isotope-labeling experiments. With AIMD simulations, we report accurate vibrational frequency ...

Latest version: v1
Publication date: Jun 28, 2022

Machine-learning accelerated identification of exfoliable two-dimensional materials


Mohammad Tohidi Vahdat, Kumar Agrawal Varoon, Giovanni Pizzi

  • Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify accurately and efficiently if bulk three-dimensional (3D) materials are formed by layers held together by weak binding energy and, thus, can be potentially exfoliated into 2D materials. In this work, we develop a machine-learning (ML) approach that, combined with a fast preliminary geometrical screening, is able to efficiently identify potentially exfoliable materials. Starting from a combination of descriptors for crystal structures, we work out a subset of them that are crucial for accurate predictions. Our final ML model, based on a random forest classifier, has a very high recall of 98%. Using a SHapely Additive exPlanations (SHAP) analysis, we also provide an intuitive explanation of the five most important variables of the model. Finally, we ...

Latest version: v1
Publication date: Jun 24, 2022

The Materials Cloud 2D database (MC2D)


Davide Campi, Nicolas Mounet, Marco Gibertini, Giovanni Pizzi, Nicola Marzari

  • Two-dimensional (2D) materials are among the most promising candidates for beyond silicon electronic and optoelectronic applications. Recently, their recognized importance, sparked a race to discover and characterize new 2D materials. Within few years the number of experimentally exfoliated or synthesized 2D materials went from a couple of dozens to few hundreds while the number theoretically predicted compounds reached a few thousands. In 2018 we first contributed to this effort with the identification of 1825 compounds that are either easily (1036) or potentially (789) exfoliable from experimentally known 3D compounds. In the present work we report on the new materials recently added to the 2D-portfolio thanks to the extension of the screening to an additional experimental database (MPDS) as well as the most up-to-date versions of the two databases (ICSD and COD) used in our previous work. This expansion led to the discovery of an additional 1252 unique monolayers bringing the ...

Latest version: v1
Publication date: Jun 24, 2022

Pivotal role of intersite Hubbard interactions in Fe-doped α-MnO₂


Ruchika Mahajan, Arti Kashyap, Iurii Timrov

  • We present a first-principles investigation of the structural, electronic, and magnetic properties of the pristine and Fe-doped α-MnO₂ using density-functional theory with extended Hubbard functionals. The onsite U and intersite V Hubbard parameters are determined from first principles and self-consistently using density-functional perturbation theory in the basis of Löwdin-orthogonalized atomic orbitals. First, we analyze the pristine α-MnO₂ and show that the C2-AFM spin configuration is the most energetically favorable, in agreement with the experimentally observed antiferromagnetic state. For the Fe-doped α-MnO₂ two types of doping are considered: Fe insertion in the 2 × 2 tunnels and partial substitution of Fe for Mn. The calculated formation energies show that the experimentally observed Fe insertion is energetically favorable only when intersite Hubbard interactions are taken into account. Moreover, we find that both types of doping preserve the C2-AFM spin configuration of ...

Latest version: v2
Publication date: Jun 23, 2022

Towards a robust evaluation of nanoporous materials for carbon capture applications


Elias Moubarak, Seyed Mohamad Moosavi, Charithea Charalambous, Susana Garcia, Berend Smit

  • In this paper, we present a workflow that is designed to work without manual intervention to efficiently predict, by using molecular simulations, the thermodynamic data that is needed to design a carbon capture process. We developed a procedure that does not rely on fitting of the adsorption isotherms. From molecular simulations, we can obtain accurate data for both, the pure component isotherms as well as the mixture isotherms. This allowed us to make a detailed comparison of the different methods to predict the mixture isotherms. All approaches rely on an accurate description of the pure component isotherms and a model to predict the mixture isotherms. As we are interested in low CO₂ concentrations, it is essential that these models correctly predict the low pressure limit, i.e., give a correct description of the Henry regime. Among the equations that describe this limit correctly, the dual-site Langmuir (DSL) model is often used for the pure components and the extended DSL ...

Latest version: v1
Publication date: Jun 20, 2022

Excited-state properties for extended systems: efficient hybrid density functional methods


Anna-Sophia Hehn, Beliz Sertcan, Fabian Belleflamme, Sergey K. Chulkov, Matthew B. Watkins, Jürg Hutter

  • Time-dependent density functional theory has become state-of-the-art for describing photophysical and photochemical processes in extended materials due to its affordable cost. The inclusion of exact exchange was shown to be essential for the correct description of the long-range asymptotics of electronic interactions and thus a well-balanced description of valence, Rydberg and charge-transfer excitations. Several approaches for an efficient treatment of exact exchange have been established for the ground state, while implementations for excited-state properties are rare. Furthermore, the high computational costs required for excited-state properties in comparison to ground-state computations often hinder large-scale applications on periodic systems with hybrid functional accuracy. We therefore propose two approximate schemes for improving computational efficiency for the treatment of exact exchange. Within the auxiliary density matrix method (ADMM), exact exchange is estimated ...

Latest version: v1
Publication date: Jun 17, 2022

Enhancement of exchange bias and perpendicular magnetic anisotropy in CoO/Co multilayer thin films by tuning the alumina template nanohole size


Mohamed Salaheldeen, Ayman Nafady, Ahmed M. Abu-Dief, Rosario Díaz Crespo, María Paz Fernández -García, Juan Pedro Andrés, Ricardo López Antón, Jesús A. Blanco, Pablo Álvarez-Alonso

  • The interest in magnetic nanostructures exhibiting perpendicular magnetic anisotropy and ex-change bias effect has increased in recent years owing to their applications in a new generation of spintronic devices that combine several functionalities. We present a nanofabrication process used to induce perpendicular magnetic anisotropy and exchange bias. 30-nm-thick CoO/Co multilayers were deposited on nanostructured alumina templates with a broad range of pore diameters, 34 nm ≤ Dp ≤ 96 nm, while maintaining the hexagonal lattice parameter at 107 nm. Increase of both the exchange bias field (HEB) and the coercivity (HC) (12 times and 27 times, respectively) was ob-served in the nanostructured films compared to the non-patterned film. The marked dependence of HEB and HC with antidot hole diameters pinpoints to an in-plane to out-of-plane changeover of the magnetic anisotropy at a nanohole diameter of ∼ 75 nm. Micromagnetic simulation shows the existence of antiferromagnetic layers ...

Latest version: v1
Publication date: Jun 16, 2022

The mapped gaussian process (MGP) force-field of Cu-Zn surface alloy


Harry Handoko Halim, Yoshitada Morikawa

  • The mapped gaussian process (MGP) force-field used to elucidate the surface alloying of Cu-Zn. The force-field is made based on first-principles data by using machine-learning technique called Gaussian Process as implemented in FLARE package (https://github.com/mir-group/flare). Active and on-the-fly learning were employed to build the database efficiently. The simulation reveals atomistic details of the alloying process, i.e., the incorporation of deposited Zn adatoms to the Cu substrate. The surface alloying is found to start at upper and lower terraces near the step edge, which emphasize the role of steps and kinks in the alloying. The incorporation of Zn at the middle terrace was found at the later stage of the simulation.

Latest version: v1
Publication date: Jun 15, 2022

Force-based method to determine the potential dependence in electrochemical barriers


Sudarshan Vijay, Georg Kastlunger, Joseph Gauthier, Anjli Patel, Karen Chan

  • Determining ab-initio potential dependent energetics are critical to investigating mechanisms for electrochemical reactions. While methodology for evaluating reaction thermodynamics is established, simulation techniques for the corresponding kinetics is still a major challenge owing to a lack of potential control, finite cell size effects or computational expense. In this work, we develop a model which allows for computing electrochemical activation energies from just a handful of Density Functional Theory (DFT) calculations. The sole input into the model are the atom centered forces obtained from DFT calculations performed on a homogeneous grid composed of varying field-strengths. We show that the activation energies as a function of the potential obtained from our model are consistent for different super-cell sizes and proton concentrations for a range of electrochemical reactions. This record contains output files from all the DFT calculations needed to reproduce the figures in the manuscript.

Latest version: v1
Publication date: Jun 15, 2022

HP - A code for the calculation of Hubbard parameters using density-functional perturbation theory


Iurii Timrov, Nicola Marzari, Matteo Cococcioni

  • We introduce HP, an implementation of density-functional perturbation theory, designed to compute Hubbard parameters (on-site U and inter-site V) in the framework of DFT+U and DFT+U+V. The code does not require the use of computationally expensive supercells of the traditional linear-response approach; instead, unit cells are used with monochromatic perturbations that significantly reduce the computational cost of determining Hubbard parameters. HP is an open-source software distributed under the terms of the GPL as a component of Quantum ESPRESSO. As with other components, HP is optimized to run on a variety of different platforms, from laptops to massively parallel architectures, using native mathematical libraries (LAPACK and FFTW) and a hierarchy of custom parallelization layers built on top of MPI. The effectiveness of the code is showcased by computing Hubbard parameters self-consistently for the phospho-olivine LixMn0.5Fe0.5PO4 (x=0, 0.5, 1) and by highlighting the accuracy ...

Latest version: v1
Publication date: Jun 13, 2022

Viscosity in water from first-principles and deep-neural-network simulations


Cesare Malosso, Linfeng Zhang, Roberto Car, Stefano Baroni, Davide Tisi

  • We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio molecular dynamics (AIMD), based on density-functional theory (DFT). In order to cope with the long simulation times necessary to achieve an acceptable statistical accuracy, our ab initio approach is enhanced with deep-neural-network potentials (NNP). This approach is first validated against AIMD results, obtained by using the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional and paying careful attention to crucial, yet often overlooked, aspects of the statistical data analysis. Then, we train a second NNP to a dataset generated from the Strongly Constrained and Appropriately Normed (SCAN) functional. Once the error resulting from the imperfect prediction of the melting line is offset by referring the simulated temperature to the theoretical melting one, our SCAN predictions of the shear viscosity of water are in very good agreement with experiments.

Latest version: v2
Publication date: Jun 10, 2022

Tuning selectivity in the direct conversion of methane to methanol: bimetallic synergistic effects on the cleavage of C-H and O-H bonds over NiCu/CeO₂ catalysts


Pablo G. Lustemberg, Sanjaya D. Senanayake, Jose A. Rodriguez, M. Verónica Ganduglia-Pirovano

  • The efficient activation of methane and simultaneous water dissociation are crucial in many catalytic reactions on oxide-supported transition metal catalysts. On very low-loaded Ni/CeO₂ surfaces, methane easily fully decomposes, CH₄ -> C + 4H, and water dissociates, H₂O -> OH + H. However, in important reactions such as the direct oxidation of methane to methanol (MTM), where complex interplay exists between reactants (CH₄, O₂), it is desirable to avoid the complete dehydrogenation of methane to carbon. Remarkably, the barrier for the activation of C-H bonds in CHx (x= 1-3) species on Ni/CeO₂ surfaces can be manipulated by adding Cu, forming bimetallic NiCu clusters, whereas the ease for cleavage of O-H bonds in water, is not affected by ensemble effects, as obtained from density functional theory-based calculations. CH4 activation occurs only on Ni sites and H₂O activation on both Ni and Cu sites. The MTM reaction pathway for the example of the Ni₃Cu₁/CeO₂ model catalyst ...

Latest version: v1
Publication date: Jun 10, 2022

Ab initio simulation of structure and properties in Ni-based superalloys Haynes282 and Inconel740


Wai-Yim Ching, Saro San, Caizhi Zhou, Ridwan Sakidja

  • The electronic structure, interatomic bonding, and mechanical properties of two supercell models of Ni-based super alloys are calculated by using ab initio density functional theory methods. The alloys are in the face centered cubic lattice having 864 atoms and eleven elements: Haynes282 (Ni₄₄₄Cr₂₀₂Co₇₉Al₅₆Ti₂₅Mo₂₅Fe₁₂Mn₃Si₅C₁₂B) and Inconel740 (Ni₃₇₃Cr₂₄₆Co₁₅₃Al₃₃Ti₂₁Nb₆MoFe₆ Mn₃Si₁₇C₅). These multi-component alloys have very complex electronic structure, bonding and partial charge distributions depending on the composition and strength of local bonding environment. We employ the novel concept of total bond order density (TBOD) and its partial components (PBOD) to ascertain the internal cohesion that controls the intricate balance between the propensity of metallic bonding between Ni, Cr and Co, and the strong bonds with C and Al. We find Inconel740 has slightly stronger mechanical properties than Haynes282. Comparison with more conventional high entropy alloys with equal components are discussed.

Latest version: v1
Publication date: Jun 10, 2022

Stability and magnetic behavior of exfoliable nanowire 1D materials


Joshua Paul, Janet Lu, Sohum Shah, Stephen Xie, Richard Hennig

  • Low-dimensional materials can display enhanced electronic, magnetic, and quantum properties. However, 1D exfoliable nanowires have not been explored as much as their 2D and 0D counterparts. To address this, we use the topological scaling algorithm to identify all sufficiently metastable materials in the Materials Project database which have bulk crystals with one-dimensional (1D) structural motifs. We narrow our search to 263 bulk precursors which exfoliate unique 1D nanowires and contain d-orbital valence electrons. After exfoliating nanowires from these bulk precursors and applying structural optimization, we determine thermodynamic stability in both exfoliation energy (per-atom) and line tension (per-Angstrom) units, the latter of which we argue is a better predictor of stability in 1D materials. We further calculate the ferromagnetic ordering of these isolated nanowire materials. This repository reports the final atomic structure, thermodynamic stability, magnetic moment ...

Latest version: v1
Publication date: Jun 10, 2022

Numerical simulation of an electrochemical system and semi-analytical method


Farid Taherkhani, Doriano Brogioli, Fabio La Mantia

  • Electrochemical systems are often simulated by using numerical methods based on finite element solution of differential equations. We developed a method to decrease the needed computational resources, based on the analytical solution of a part of the system: the obtained analytical equations are applied as boundary conditions to the finite element calculation. The part of the system that is analytically solved is the region of the diffuse double layer. We provide two COMSOL models: i) a 1d fully numerical calculation and ii) the same simulation performed with the semi-analytical method. We also provide examples of the resulting impedances and frequency responses of various parameters.

Latest version: v1
Publication date: Jun 03, 2022

Shadow-light images of simulated 25 classes of surface roughness for automatic classification


Janusz V. Kozubal, Ahmad Hassanat, Ahmad S. Tarawneh, Roman J. Wróblewski, Hubert Anysz, Jónatas Valença, Eduardo Júlio

  • Many relationships important to civil engineering depend on surface roughness (morphology). Examples are the bond strength between concrete layers, the adhesion of a wheel to the pavement, the angle of friction in the soil in contact with a wall surface, and many other cases when we deal with a material with a surface having the characteristics of a Gaussian field. Based on scans of the natural concrete surfaces subjected to different smoothing processes, theoretical models were made. The observed features of the models were grouped into 25 categories belonging to the spherical semivariogram model. Each category is described by two parameters: range (with discrete domain 0.01, 0.04, 0.08, 0.16, 0.32) and upper limits (also with discrete domain 1, 2, 4 , 8, 16) with zero trend. For all combinations of range-limit pairs, homogeneous Gaussian random fields satisfying the spatial dependence of the category were generated in R software by using the RandomFields library. In the final ...

Latest version: v1
Publication date: Jun 03, 2022

Dynamic response of oxygen vacancies on the Deacon reaction over reduced single crystalline CeO₂-x(111) surfaces


V. Koller, C. Sack, P. Lustemberg, M. V. Ganduglia-Pirovano, H. Over

  • The heterogeneously catalyzed HCl oxidation reaction (Deacon reaction) over ceria leads under typical reaction conditions to a reduction and surface chlorination of CeO2. The reduced single crystalline CeO2-x(111) model surface stabilizes various ordered surface structures, e.g. (√7 × √7)R19.1°, (3 × 3), or (4 × 4), depending on the concentration of oxygen vacancies (VO). Saturating these phases with HCl at room temperature, followed by annealing to the process temperature of 700 K, leads in all cases to a uniformly covering (√3 × √3)R30° overlayer structure with identical Cl coverage and identical adsorption geometry. Low energy electron diffraction (LEED) fingerprinting, density functional theory (DFT) calculations and X-ray photoelectron spectroscopy (XPS) evidence that Cl adsorbs into the O-vacancy at the surface (Clvac) with a high adsorption energy (>2 eV). From thermal desorption spectroscopy (TDS) and XPS of Cl 2p the adsorption energy of Clvac and the water formation is ...

Latest version: v1
Publication date: May 24, 2022

Efficient, interpretable graph neural network representation for angle-dependent properties and its application to optical spectroscopy


Tim Hsu, Tuan Anh Pham, Nathan Keilbart, Stephen Weitzner, James Chapman, Penghao Xiao, S. Roger Qiu, Xiao Chen, Brandon Wood

  • Graph neural networks are attractive for learning properties of atomic structures thanks to their intuitive graph encoding of atoms and bonds. However, conventional encoding does not include angular information, which is critical for describing atomic arrangements in disordered systems. In this work, we extend the recently proposed ALIGNN encoding, which incorporates bond angles, to also include dihedral angles (ALIGNN-d). This simple extension leads to a memory-efficient graph representation that captures the complete geometry of atomic structures. ALIGNN-d is applied to predict the infrared optical response of dynamically disordered Cu(II) aqua complexes, leveraging the intrinsic interpretability to elucidate the relative contributions of individual structural components. Bond and dihedral angles are found to be critical contributors to the fine structure of the absorption response, with distortions representing transitions between more common geometries exhibiting the strongest ...

Latest version: v1
Publication date: May 23, 2022

Donor-acceptor-donor “hot exciton” triads for high reverse intersystem crossing in OLEDs


Yanan Zhu, Sergi Vela, Hong Meng, Clémence Corminboeuf, Maria Fumanal

  • Hot exciton materials have the potential to improve the quantum efficiency of organic light-emitting diodes (OLEDs) by promoting high Reversed InterSystem Crossing (hRISC) between a high-lying triplet (Tn, n≥2) and a radiative singlet (Sm). In recent years, donor–acceptor-donor (D-A-D) molecular systems have shown great promise in its ability to enhance the hRISC process under certain conditions. However, strategies to find appropriate D-A-D combinations beyond trial-and-error are still elusive. This work exposes the limited applicability of the current fragment-based design rules and proposes high-throughput screening as the optimal route to find promising candidates that fulfill the energy criteria for hot exciton materials. The strategy consists of first establishing the thresholds for large triplet-triplet splitting and small singlet-triplet gap, then filtering combinations through rate comparison of competitive crossing pathways, and finally confirming hRISC with spin-orbital ...

Latest version: v1
Publication date: May 06, 2022

Impact of glutamate carboxylation in the adsorption of the alpha-1 domain of osteocalcin to hydroxyapatite and titania


Sarah Alamdari, Jim Pfaendtner

  • One proposed mechanism of implant fouling is attributed to the nonspecific adsorption of non-collagenous bone matrix proteins (NCPs) onto a newly implanted interface. With the goal of capturing the fundamental mechanistic and thermodynamic forces that govern changes in these NCP recognition domains as a function of γ-carboxyglutamic acid (Gla) post-translational modification and surface chemistry, we probe the adsorption process of the most commonly occurring NCP, osteocalcin, onto a mineral and metal oxide surface. Here, we apply two enhanced sampling methods to independently probe the effects of post-translational modification and peptide structure on adsorption. First, well-tempered metadynamics was used to capture the binding of acetyl and N-methylamide capped glutamic acid and Gla single amino acids onto crystalline hydroxyapatite and titania model surfaces at physiological pH. Following this, parallel tempering metadynamics in the well-tempered ensemble (PTMetaD-WTE) was ...

Latest version: v2
Publication date: Apr 27, 2022

cell2mol: encoding chemistry to interpret crystallographic data


Sergi Vela, Ruben Laplaza, Yuri Cho, Clemence Corminboeuf

  • The creation and maintenance of crystallographic data repositories is one of the greatest data-related achievements in chemistry. Platforms such as the Cambridge Structural Database host what is likely the most diverse collection of synthesizable molecules. If properly mined, they could be the basis for the large-scale exploration of new regions of the chemical space using quantum chemistry (QC). However, it is currently challenging to retrieve all the necessary information for QC based exclusively on the available structural data, especially for transition metal complexes. To solve this shortcoming, we present cell2mol, a software that interprets crystallographic data and retrieves the connectivity and total charge of molecules, including the oxidation state (OS) of metal atoms. We prove that cell2mol outperforms other popular methods at assigning the metal OS, while offering a much more comprehensive interpretation of the unit cell, and we make publicly available reliable ...

Latest version: v1
Publication date: Apr 25, 2022

Enhanced photodegradation of dimethoxybenzene isomers in/on ice compared to in aqueous solution


Ted Hullar, Theo Tran, Zekun Chen, Fernanda C. Bononi, Oliver Palmer, Davide Donadio, Cort Anastasio

  • Photochemical reactions of contaminants in snow and ice can be important sources and sinks for various organic and inorganic compounds. Snow contaminants can be found in the bulk ice matrix, in internal liquid-like regions (LLRs), or in quasi-liquid layers (QLLs) at the air-ice interface, where they can readily exchange with the firn air. Some studies have reported that direct photochemical reactions occur faster in LLRs and QLLs than in aqueous solution, while others have found similar rates. Here, we measure the photodegradation rate constants of the three dimethoxybenzene isomers under varying experimental conditions, including in aqueous solution, in LLRs, and at the air-ice interface of nature-identical snow. Relative to aqueous solution, we find modest photodegradation enhancements (3- and 6-fold) in LLRs for two of the isomers, and larger enhancements (15- to 30-fold) at the air-ice interface for all three isomers. We use computational modeling to assess the impact of light ...

Latest version: v1
Publication date: Apr 20, 2022

A data-science approach to predict the heat capacity of nanoporous materials


Seyed Mohamad Moosavi, Balázs Álmos Novotny, Daniele Ongari, Elias Moubarak, Mehrdad Asgari, Özge Kadioglu, Charithea Charalambous, Andres Ortega-Guerrero, Amir H. Farmahini, Lev Sarkisov, Susana Garcia, Frank Noé, Berend Smit

  • The heat capacity of a material is a fundamental property that is of significant practical importance. For example, in a carbon capture process, the heat required to regenerate a solid sorbent is directly related to the heat capacity of the material. However, for most materials suitable for carbon capture applications the heat capacity is not known, and thus the standard procedure is to assume the same value for all materials. In this work, we developed a machine-learning approach to accurately predict the heat capacity of these materials, i.e., zeolites, metal-organic frameworks, and covalent-organic frameworks. The accuracy of our prediction is confirmed with novel experimental data. Finally, for a temperature swing adsorption process that captures carbon from the flue gas of a coal-fired power plant, we show that for some materials the energy requirement is reduced by as much as a factor of two using the correct heat capacity.

Latest version: v1
Publication date: Apr 13, 2022

BELLO: A post-processing tool for the local-order analysis of disordered systems


Behnood Dianat, Francesco Tavanti, Andrea Padovani, Luca Larcher, Arrigo Calzolari

  • The characterization of the atomic structure of disordered systems, such as amorphous, glasses and (bio)molecule in solution, is a fundamental step for most theoretical investigations. The properties of short- and medium-range local order structures are responsible for the electronic, optical and transport properties of these systems. Here, we present the BELLO open source code, a post-processing script-tool created for the automatic analysis and extraction of structural characteristics of disordered and amorphous systems. BELLO is agnostic to the code that generated single configurations or trajectories, it provides an intuitive access through a graphical user interface (GUI), and it requires minimal computational resources. Its capabilities include the calculation of the order parameter , the folded structure identification, and statistical analysis tools such as atomic coordination number and pair/angle-distribution functions. The working principles of the code are described ...

Latest version: v1
Publication date: Apr 13, 2022

Is there a polaron signature in angle-resolved photoemission of CsPbBr₃?


Maryam Sajedi, Maxim Krivenkov, Dmitry Marchenko, Jaime Sánchez-Barriga, Anoop K. Chandran, Andrei Varykhalov, Emile D. L. Rienks, Irene Aguilera, Stefan Blügel, Oliver Rader

  • The formation of large polarons has been proposed as reason for the high defect tolerance, low mobility, low charge carrier trapping and low nonradiative recombination rates of lead halide perovskites. Recently, direct evidence for large-polaron formation has been reported from a 50% effective mass enhancement in angle-resolved photoemission of CsPbBr₃ over theory for the orthorhombic structure. We present in-depth band dispersion measurements of CsPbBr₃ and GW calculations which lead to almost identical effective masses at the valence band maximum of 0.203+/-0.016 m₀ in experiment and 0.217 m₀ in orthorhombic theory. We argue that the effective mass can be explained solely on the basis of electron-electron correlation and large polaron formation cannot be concluded from photoemission data.

Latest version: v1
Publication date: Apr 11, 2022

Adsorbate chemical environment-based machine learning framework for heterogeneous catalysis


Pushkar Ghanekar, Siddharth Deshpande, Jeffrey Greeley

  • Heterogeneous catalytic reactions are influenced by a subtle interplay of atomic-scale factors, ranging from the catalysts’ local morphology to the presence of high adsorbate coverages. Describing such phenomena via computational models requires generation and analysis of a large space of surface atomic configurations. To address this challenge, we present the Adsorbate Chemical Environment-based Graph Convolution Neural Network (ACE-GCN), a screening workflow that can account for atomistic configurations comprising diverse adsorbates, binding locations, coordination environments, and substrate morphologies. Using this workflow, we develop catalyst surface models for two illustrative systems: (i) NO adsorbed on a Pt3Sn(111) alloy surface, of interest for nitrate electroreduction processes, where high adsorbate coverages combine with the low symmetry of the alloy substrate to produce a large configurational space, and (ii) OH* adsorbed on a stepped Pt(221) facet, of relevance to ...

Latest version: v1
Publication date: Apr 11, 2022

Superconductivity in antiperovskites


Noah Hoffmann, Tiago F. T. Cerqueira, Jonathan Schmidt, Miguel A. L. Marques

  • We present a comprehensive theoretical study of conventional superconductivity in cubic antiperovskites materials with composition XYZ₃ where X and Z are metals and Y is H, B, C, N, O, and P. Our starting point are electron-phonon calculations for 384 materials performed with density-functional perturbation theory. While 40% of the materials were dynamically unstable as they exhibited imaginary frequencies, we discovered 16 compounds with Tc higher than 5 K including antiperovskites with Y=H, N, C and O. We used these results to train interpretable machine learning models to understand and further explore this family of compounds. This lead us to predict a further 44 materials with superconducting transition temperatures above 5 K, reaching a maximum of 17.8 K for PtHBe₃. Furthermore, the models give us an understanding of the mechanism of superconductivity in anti-perovskites and highlight the importance of the density of states at the Fermi level and of the mass of the Y-atom ...

Latest version: v1
Publication date: Apr 06, 2022

Accelerating the theoretical study of Li-polysulphide adsorption on single-atom catalysts via machine learning approaches


Eleftherios Andritsos, Kevin Rossi

  • Li–S batteries are a promising alternative to Li-ion batteries, offering large energy storage capacity and wide operating temperature range. However, their performance is heavily affected by the Li-polysulphide (LiPS) shuttling. Computational screening of LiPS adsorption on single-atom catalyst (SAC) substrates is of great aid to the design of Li–S batteries which are robust against the LiPS shuttling from the cathode to the anode and the electrolyte. To facilitate this process, we develop a machine learning (ML) protocol to accelerate the systematic mapping of dominant local energy minima found with calculations based on the density functional theory (DFT), and, in turn, fast screening of LiPS adsorption properties on SACs. We first validate the approach by probing the potential energy surface for LiPS adsorbed on graphene decorated with a Fe–N4–C SAC. We identify minima whose binding energies are better or on par with the one previously reported in the literature. We then move ...

Latest version: v2
Publication date: Apr 05, 2022

High-mobility semiconducting polymers with different spin ground states


Xiao-Xiang Chen, Jia-Tong Li, Yu-Hui Fang, Xin-Yu Deng, Xue-Qing Wang, Guangchao Liu, Yunfei Wang, Xiaodan Gu, Shang-Da Jiang, Ting Lei

  • Organic semiconductors with high-spin ground states are fascinating because they could enable fundamental understanding on the spin-related phenomenon in light element and provide opportunities for organic magnetic and quantum materials. Although high-spin ground states have been observed in some quinoidal type small molecules or doped organic semiconductors, semiconducting polymers with high-spin at their neutral ground state are rarely reported. Here we report three high-mobility semiconducting polymers with different spin ground states. We show that polymer building blocks with small singlet-triplet energy gap (ΔES-T) could enable small ΔES-T gap and increase the diradical character in copolymers. We demonstrate that the electronic structure, spin density, and solid-state interchain interactions in the high-spin polymers are crucial for their ground states. Polymers with a triplet ground state (S = 1) could exhibit doublet (S = 1/2) behavior due to different spin distributions ...

Latest version: v1
Publication date: Apr 01, 2022

E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials


Simon Batzner, Albert Musaelian, Lixin Sun, Mario Geiger, Jonathan P. Mailoa, Mordechai Kornbluth, Nicola Molinari, Tess E. Smidt, Boris Kozinsky

  • This work presents Neural Equivariant Interatomic Potentials (NequIP), an E(3)-equivariant neural network approach for learning interatomic potentials from ab-initio calculations for molecular dynamics simulations. While most contemporary symmetry-aware models use invariant convolutions and only act on scalars, NequIP employs E(3)-equivariant convolutions for interactions of geometric tensors, resulting in a more information-rich and faithful representation of atomic environments. The method achieves state-of-the-art accuracy on a challenging and diverse set of molecules and materials while exhibiting remarkable data efficiency. NequIP outperforms existing models with up to three orders of magnitude fewer training data, challenging the widely held belief that deep neural networks require massive training sets. The high data efficiency of the method allows for the construction of accurate potentials using high-order quantum chemical level of theory as reference and enables ...

Latest version: v1
Publication date: Mar 30, 2022

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