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Fermi energy determination for advanced smearing techniques


Flaviano José dos Santos, Nicola Marzari

  • Smearing techniques are widely used in first-principles calculations of metallic and magnetic materials, where they improve the accuracy of Brillouin zone sampling and lessen the impact of level-crossing instabilities. Smearing introduces a fictitious electronic temperature that smooths the discontinuities of the integrands; consequently, a corresponding fictitious entropic term arises and needs to be considered in the total free energy functional. Advanced smearing techniques – such as Methfessel-Paxton and cold smearing – have been introduced to guarantee that the system’s total free energy remains independent of the smearing temperature at least up to the second order. In doing so, they give rise to non-monotonic occupation functions (and, for Methfessel-Paxton, non-positive definite), which can result in the chemical potential not being uniquely defined. We explore this shortcoming in detail and introduce a numerical protocol utilizing Newton’s minimization method that is able ...

Latest version: v1
Publication date: Mar 20, 2023

Testing Koopmans spectral functionals on the analytically-solvable Hooke's atom


Yannick Schubert, Nicola Marzari, Edward Linscott

  • Koopmans spectral functionals are a class of orbital-density-dependent functionals designed to accurately predict spectroscopic properties. They do so markedly better than their Kohn-Sham density-functional theory counterparts, as demonstrated in earlier works on benchmarks of molecules and bulk systems. This work is a complementary study where --- instead of comparing against real, many-electron systems --- we test Koopmans spectral functionals on Hooke's atom, a toy two-electron system that has analytical solutions for particular strengths of its harmonic confining potential. As these calculations clearly illustrate, Koopmans spectral functionals do an excellent job of describing Hooke's atom across a range of confining potential strengths. This work also provides broader insight into the features and capabilities of Koopmans spectral functionals more generally.

Latest version: v3
Publication date: Mar 17, 2023

Projectability disentanglement for accurate and automated electronic-structure Hamiltonians


Junfeng Qiao, Giovanni Pizzi, Nicola Marzari

  • Maximally-localized Wannier functions (MLWFs) are a powerful and broadly used tool to characterize the electronic structure of materials, from chemical bonding to dielectric response to topological properties. Most generally, one can construct MLWFs that describe isolated band manifolds, e.g. for the valence bands of insulators, or entangled band manifolds, e.g. in metals or describing both the valence and the conduction manifolds in insulators. Obtaining MLWFs that describe a target manifold accurately and with the most compact representation often requires chemical intuition and trial and error, a challenging step even for experienced researchers and a roadblock for automated high-throughput calculations. Here, we present a very natural and powerful approach that provides automatically MLWFs spanning the occupied bands and their natural complement for the empty states, resulting in WÎannier Hamiltonian models that provide a tight-binding picture of optimized atomic orbitals in ...

Latest version: v1
Publication date: Mar 17, 2023

Machine learning of twin/matrix interfaces from local stress field


Javier Fernandez Troncoso, Yang Hu, Nicolo Maria della Ventura, Amit Sharma, Xavier Maeder, Vladyslav Turlo

  • Twinning is an important deformation mode in plastically deformed hexagonal close-packed materials. The extremely high twin growth rates at the nanoscale make atomistic simulations an attractive method for investigating the role of individual twin/matrix interfaces such as twin boundaries and basal-prismatic interfaces in twin growth kinetics. Unfortunately, there is no single framework that allows researchers to differentiate such interfaces automatically, neither in experimental in-situ transmission electron microscopy analysis images nor in atomistic simulations. Moreover, the presence of alloying elements introduces substantial noise to local atomic environments, making it nearly impossible to identify which atoms belong to which interface. Here, with the help of advanced machine learning methods, we provide a proof-of-concept way of using the local stress field distribution as an indicator for the presence of interfaces and for determining their types. We apply such an ...

Latest version: v1
Publication date: Mar 15, 2023

Topological data analysis of superionic conductor silver iodide


Ryuhei Sato, Kazuto Akagi, Shigeyuki Takagi, Kartik Sau, Kazuaki Kisu, Hao Li, Shin-ichi Orimo

  • Topological data analysis based on persistent homology has been applied to the molecular dynamics simulation for the fast ion-conducting phase (α-phase) of AgI, to show its effectiveness on the ion-migration mechanism analysis. Time-averaged persistence diagrams of α-AgI, which quantitatively records the shape and size of the ring structures in the given atomic configurations, clearly showed the emergence of the four-membered rings formed by two Ag and two I ions at high temperatures. They were identified as common structures during the Ag ion migration. The averaged potential energy change due to the deformation of four-membered ring agrees well with the activation energy calculated from the conductivity Arrhenius plot. The concerted motion of two Ag ions via the four-membered ring was also successfully extracted from molecular dynamics simulations by our approach, providing the new insight into the specific mechanism of the concerted motion.

Latest version: v1
Publication date: Mar 14, 2023

Two-dimensional pure isotropic proton solid state NMR


Pinelopi Moutzouri, Manuel Cordova, Bruno Simões de Almeida, Daria Torodii, Lyndon Emsley

  • One key bottleneck of solid-state NMR spectroscopy is that ¹H NMR spectra of organic solids are often very broad due to the presence of a strong network of dipolar couplings. We have recently suggested a new approach to tackle this problem. More specifically, we parametrically mapped errors leading to residual dipolar broadening into a second dimension and removed them in a correlation experiment. In this way pure isotropic proton (PIP) spectra were obtained that contain only isotropic shifts and provide the highest ¹H NMR resolution available today in rigid solids. Here, using a deep-learning method, we extend the PIP approach to a second dimension, and for samples of L-tyrosine hydrochloride and ampicillin we obtain high resolution ¹H-¹H double-quantum/single-quantum dipolar correlation and spin-diffusion spectra with significantly higher resolution than the corresponding spectra at 100 kHz MAS, allowing the identification of previously overlapped isotropic correlation peaks.

Latest version: v1
Publication date: Mar 10, 2023

Dielectric response and excitations of hydrogenated free-standing graphene


Miki Bonacci, Elisa Molinari, Deborah Prezzi

  • The conversion of semimetallic suspended graphene (Gr) to a large-gap semiconducting phase is realized by controlled adsorption of atomic hydrogen (deuterium) on free-standing Gr veils in nanoporous graphene. The effects of local rehybridization from sp² to sp³ chemical bonding are investigated by combining X-ray photoelectron spectroscopy and high-resolution electron energy-loss spectroscopy (HREELS) with ab-initio based modelling. The hydrogen adatoms on the C sites induce a stretching frequency, clearly identified in vibrational spectra thanks to the use of the D isotope, which is compatible with the predicted fingerprints of adsorption on both sides of Gr corresponding to the graphane configuration. HREELS of the deuterated samples shows a wide opening of the optical band gap, consistent with the modified spectral density observed in the valence band photoemission. The results are in agreement with ab-initio calculations by GW and Bethe-Salpeter equation approaches, showing a ...

Latest version: v2
Publication date: Mar 10, 2023

Phonon self-energy corrections: To screen, or not to screen


Jan Berges, Nina Girotto, Tim Wehling, Nicola Marzari, Samuel Poncé

  • First-principles calculations of phonons are often based on the adiabatic approximation, and Brillouin-zone samplings that might not always be sufficient to capture the subtleties of Kohn anomalies. These shortcomings can be addressed through corrections to the phonon self-energy arising from the low-energy electrons. A well-founded correction method exists [Phys. Rev. B 82, 165111 (2010)], which only relies on adiabatically screened quantities. However, many-body theory suggests to use one bare electron-phonon vertex in the phonon self-energy [Rev. Mod. Phys. 89, 015003 (2017)] to avoid double counting. We assess the accuracy of both approaches in estimating the low-temperature phonons of monolayer TaS₂ and doped MoS₂. We find that the former yields excellent results at low computational cost due to its designed error cancellation to first order, while the latter becomes exact in the many-body limit but is not accurate in approximate contexts. We offer a third strategy based on ...

Latest version: v1
Publication date: Mar 08, 2023

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: v9
Publication date: Mar 08, 2023

Learning the electronic density of states in condensed matter


Chiheb Ben Mahmoud, Andrea Anelli, Gábor Csányi, Michele Ceriotti

  • The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation of experimentally observable material properties such as optical absorption and electrical conductivity. We discuss the challenges inherent in the construction of a machine-learning (ML) framework aimed at predicting the DOS as a combination of local contributions that depend in turn on the geometric configuration of neighbors around each atom, using quasiparticle energy levels from density functional theory as training data. We present a challenging case study that includes configurations of silicon spanning a broad set of thermodynamic conditions, ranging from bulk structures to clusters and from semiconducting to metallic behavior. We compare different approaches to represent the DOS, and the accuracy of predicting quantities ...

Latest version: v2
Publication date: Mar 08, 2023

Principles of isomer stability in small clusters


Giuseppe Fisicaro, Bastian Schaefer, Jonas A. Finkler, Stefan Goedecker

  • In this work we study isomers of several representative small clusters to find principles for their stability. Our conclusions about the principles underlying the structure of clusters are based on a huge database of 44'000 isomers generated for 59 different clusters on the density functional theory level by Minima Hopping. We explore the potential energy surface of small neutral, anionic and cationic isomers, moving left to right across the third period of the periodic table and varying the number of atoms n and the cluster charge state q (X^q_n, with X={Na, Mg, Al, Si, Ge}, q=-1,0,1,2). We use structural descriptors such as bond lengths and atomic coordination numbers, the surface to volume ratios and the shape factor as well as electronic descriptors such as shell filling and hardness to detect correlations with the stability of clusters. The isomers of metallic clusters are found to be structure seekers with a strong tendency to adopt compact shapes. However certain numbers ...

Latest version: v1
Publication date: Mar 06, 2023

Multi-technique approach to unravel the (dis)order in amorphous materials


Francesco Tavanti, Arrigo Calzolari

  • The concept of order in disordered materials is the key to controlling the mechanical, electrical, and chemical properties of amorphous compounds widely exploited in industrial applications and daily life. Rather, it is far from being understood. Here, we propose a multi-technique numerical approach to study the order/disorder of amorphous materials on both the short- and the medium-range scale. We combine the analysis of the disorder level based on chemical and physical features with their geometrical and topological properties, defining a previously unexplored interplay between the different techniques and the different order scales. We applied this scheme to amorphous GeSe and GeSeTe chalcogenides, showing a modulation of the internal disorder as a function of the stoichiometry and composition: Se-rich systems are less ordered than Ge-rich systems at the short- and medium-range length scales. The present approach can be easily applied to more complex systems containing three or ...

Latest version: v1
Publication date: Mar 05, 2023

Hybridization driving distortions and multiferroicity in rare-earth nickelates


Luca Binci, Michele Kotiuga, Iurii Timrov, Nicola Marzari

  • For decades transition-metal oxides have generated a huge interest due to the multitude of physical phenomena they exhibit. In this class of materials, the rare-earth nickelates, RNiO₃, stand out for their rich phase diagram stemming from complex couplings between the lattice, electronic and magnetic degrees of freedom. Here, we present a first-principles study of the low-temperature phase for two members of the RNiO₃ series, with R = Pr, Y. We employ density-functional theory with Hubbard corrections accounting not only for the on-site localizing interactions among the Ni-3d electrons (U), but also the inter-site hybridization effects between the transition-metals and the ligands (V). All the U and V parameters are calculated from first-principles using density-functional perturbation theory, resulting in a fully ab initio methodology. Our simulations show that the inclusion of the inter-site interaction parameters V is necessary to simultaneously capture the features ...

Latest version: v1
Publication date: Mar 02, 2023

Device-to-materials pathway for electron traps detection in amorphous GeSe-based selectors


Amine Slassi, Linda-Sheila Medondjio, Andrea Padovani, Francesco Tavanti, Xu He, Sergiu Clima, Daniele Garbin, Ben Kaczer, Luca Larcher, Pablo Ordejón, Arrigo Calzolari

  • The choice of the ideal material employed in selector devices is a tough task both from the theoretical and experimental side, especially due to the lack of a synergistic approach between techniques able to correlate specific material properties with device characteristics. Using a material-to-device multiscale technique, a reliable protocol for an efficient characterization of the active traps in amorphous GeSe chalcogenide is proposed. The resulting trap maps trace back the specific features of materials responsible for the measured findings, and connect them to an atomistic description of the sample. The metrological approach can be straightforwardly extended to other materials and devices, which is very beneficial for an efficient material-device codesign and the optimization of novel technologies.

Latest version: v1
Publication date: Mar 02, 2023

Dynamic crystal rocking of nickel-based single crystal superalloy during the epitaxial growth of the additive manufacturing process


Dongsheng Zhang, Wei Liu, Yuxiao Li, Darui Sun, Yu Wu, Shengnian Luo, Sen Chen, Ye Tao, Bingbing Zhang

  • The understanding of dynamic process of epitaxial microstructure forming in laser additive manufacturing is of vital importance for achieving products with single crystalline texture. Here, we perform in-situ, real-time synchrotron Laue diffraction experiments to capture the microstructural evolution of nickel-based single-crystal superalloys during rapid laser remelting process. In-situ synchrotron radiation Laue diffraction characterizes the crystal rotation behavior and stray grains formation process. With complementary thermo-mechanical coupled finite element simulation and molecular dynamics simulation, we identify that the crystal rotation is governed by the localized heating/cooling heterogeneity induced deformation gradient, and that the subgrains rotation caused by rapid dislocation movement and complex stress field could be the major mechanism in the generation of granular stray grains at the bottom of the melt pool.

Latest version: v1
Publication date: Mar 02, 2023

Pruning photonic circuits for realizing artificial materials with efficient universal unitary operators


Sunkyu Yu, Namkyoo Park

  • Achieving high-fidelity photonic circuits for universal unitaries has been a critical issue for classical and quantum computing applications. The basic strategy for realizing U(n) in photonic systems is to find the algorithm to decompose U(n) into a set of SU(2) operations. While various methods have been implemented for such decomposition, the resulting U(n) may not be optimized for high fidelity, especially when we assume noises in the constituent elements. The programs of this archive describe the analysis of achieving the artificial photonic materials having universal unitary operations, quantifying heavy-tailed distributions in photonic circuits and platforms, examining pruning performance in unitary operations, and applying the pruning to deep neural network applications in order to achieve high-fidelity operations.

Latest version: v1
Publication date: Feb 28, 2023

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: v2
Publication date: Feb 23, 2023

koopmans: an open-source package for accurately and efficiently predicting spectral properties with Koopmans functionals


Edward Linscott, Nicola Colonna, Riccardo De Gennaro, Ngoc Linh Nguyen, Giovanni Borghi, Andrea Ferretti, Ismaila Dabo, Nicola Marzari

  • Over the past decade we have developed Koopmans functionals, a computationally efficient approach for predicting spectral properties with an orbital-density-dependent functional formulation. These functionals address two fundamental issues with density functional theory (DFT). First, while Kohn-Sham eigenvalues can loosely mirror experimental quasiparticle energies, they are not meant to reproduce excitation energies and there is formally no connection between the two (except for the HOMO for the exact functional). Second, (semi-)local DFT deviates from the expected piecewise linear behavior of the energy as a function of the total number of electrons. This can make eigenvalues an even poorer proxy for quasiparticle energies and, together with the absence of the exchange-correlation derivative discontinuity, contributes to DFT's underestimation of band gaps. By enforcing a generalized piecewise linearity condition to the entire electronic manifold, Koopmans functionals yield ...

Latest version: v1
Publication date: Feb 17, 2023

The role of phosphate functionalization on the oxygen evolution reaction activity of cobalt-based oxides at different pH values


Wataru Yoshimune, Juliana B. Falqueto, Adam H. Clark, Nur Sena Yüzbasi, Thomas Graule, Dominika Baster, Mario El Kazzi, Thomas J. Schmidt, Emiliana Fabbri

  • Cobalt-based oxides are active electrocatalysts for the oxygen evolution reaction (OER) in alkaline electrolytes. However, their OER activity at near-neutral pHs is generally low and more active OER catalysts at neutral pHs are desired for practical applications. Herein, La0.2Sr0.8CoO3–δ, La0.2Sr0.8Co0.8Fe0.2O3–δ, La0.5Sr1.5CoO4–δ and CoOx catalysts were prepared by the flame spray synthesis method and their surface was functionalized by a dry phosphate incorporation process. Small amount of P was incorporated on the surface of the catalyst (in the range of ppm). All the samples were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and soft and hard X-ray absorption spectroscopy (XAS) before and after the functionalization process. The electrocatalytic activity towards OER of the different nanoparticle catalysts was ...

Latest version: v1
Publication date: Feb 13, 2023

Unraveling the effects of inter-site Hubbard interactions in spinel Li-ion cathode materials


Iurii Timrov, Michele Kotiuga, Nicola Marzari

  • Accurate first-principles predictions of the structural, electronic, magnetic, and electrochemical properties of cathode materials can be key in the design of novel efficient Li-ion batteries. Spinel-type cathode materials LixMn2O4 and LixMn1.5Ni0.5O4 are promising candidates for Li-ion battery technologies, but they present serious challenges when it comes to their first-principles modeling. Here, we use density-functional theory with extended Hubbard functionals - DFT+U+V with on-site U and inter-site V Hubbard interactions - to study the properties of these transition-metal oxides. The Hubbard parameters are computed from first-principles using density-functional perturbation theory. We show that while U is crucial to obtain the right trends in properties of these materials, V is essential for a quantitative description of the structural and electronic properties, as well as the Li-intercalation ...

Latest version: v1
Publication date: Feb 13, 2023

Probing temperature responsivity of microgels and its interplay with a solid surface by super-resolution microscopy and numerical simulations


Xhorxhina Shaulli, Rodrigo Rivas-Barbosa, Maxime J. Bergman, Chi Zhang, Nicoletta Gnan, Frank Scheffold, Emanuela Zaccarelli

  • Super-resolution microscopy has become a powerful tool to investigate the internal structure of complex colloidal and polymeric systems, such as microgels, at the nanometer scale. An interesting feature of this method is the possibility of monitoring microgel response to temperature changes in situ. However, when performing advanced microscopy experiments, interactions between the particle and the environment can be important. Often microgels are deposited on a substrate, since they have to remain still for several minutes during the experiment. In the publication associated with this data, we use direct stochastic optical reconstruction microscopy (dSTORM) and advanced coarse-grained molecular dynamics simulations to investigate how individual microgels anchored on hydrophilic and hydrophobic surfaces undergo their volume phase transition with temperature. We find that, in the presence of a hydrophilic substrate, the structure of the microgel is unperturbed and the resulting ...

Latest version: v1
Publication date: Feb 10, 2023

Engineering host-guest interactions in organic framework materials for drug delivery


Michelle Ernst, Ganna Gryn'ova

  • Metal-organic frameworks (MOF) and covalent organic frameworks (COFs) are promising nanocarriers for targeted drug delivery. For their uptake and release, non-covalent interactions between the framework and the drugs play a fundamental role. However, an in-depth understanding of how different functional groups affect these interactions is still lacking. Using a multilevel approach combining molecular docking and density functional theory, we show in the publication associated with this data how computational modeling can be exploited to gain information on the interplay between functionalization and drug delivery features. We find that functional groups significantly impact the strength of the host-guest interactions. Moreover, the interaction strength qualitatively correlates with drug release data from experimental literature, providing a link between framework structure and release properties. The results of our study facilitate the customization of non-covalent interactions ...

Latest version: v1
Publication date: Feb 06, 2023

Single-point spin Chern number in a supercell framework


Roberta Favata, Antimo Marrazzo

  • We present an approach for the calculation of the Z2 topological invariant in non-crystalline two-dimensional quantum spin Hall insulators. While topological invariants were originally mathematically introduced for crystalline periodic systems, and crucially hinge on tracking the evolution of occupied states through the Brillouin zone, the introduction of disorder or dynamical effects can break the translational symmetry and imply the use of larger simulation cells, where the k-point sampling is typically reduced to the single Γ-point. Here, we introduce a single-point formula for the spin Chern number that enables to adopt the supercell framework, where a single Hamiltonian diagonalisation is performed. Our single-point approach allows to calculate the spin Chern number even when the spin operator does not commute with the Hamiltonian, as in the presence of Rashba spin-orbit coupling. This archive entry contains the results of the single-point calculations of the ...

Latest version: v1
Publication date: Jan 30, 2023

Machine learning for metallurgy V: A neural-network potential for zirconium data of published plots


Manura Liyanage, David Reith, Volker Eyert, W. A. Curtin

  • The mechanical performance—including deformation, fracture, and radiation damage—of zirconium is determined at the atomic scale. With Zr and its alloys extensively used in the nuclear industry, understanding that atomic-scale behavior is crucial. The defects controlling that performance are at size scales far larger than accessible by first-principles methods, necessitating the use of semi-empirical interatomic potentials. Existing potentials for Zr are not sufficiently quantitative, nor easily extendable to alloys, oxides, or hydrides. To overcome these issues, a neural network machine learning potential (NNP) is developed here within the Behler-Parrinello framework for Zr. With a careful choice of descriptors of the atomic environments and the creation of a first-principles training dataset that includes a wide spectrum of configurations of metallurgical relevance, a very accurate NNP is demonstrated. Specifically, the Zr NNP yields a good description of dislocation structures ...

Latest version: v1
Publication date: Jan 30, 2023

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: v7
Publication date: Jan 30, 2023

Phase formation capability and compositional design of β-phase multiple rare-earth principal component disilicates


Yixiu Luo, Luchao Sun, Jiemin Wang, Tiefeng Du, Cui Zhou, Jie Zhang, Jingyang Wang

  • A key strategy to design environmental barrier coatings focuses on doping multiple rare-earth principal components into β-type rare-earth disilicates (RE2Si2O7) to achieve versatile property optimization. However, controlling the phase formation capability of (nRExi)2Si2O7 remains a crucial challenge, due to the complex polymorphic phase competitions and evolutions led by different RE3+ combination. Herein, by fabricating twenty-one model (REI0.25REII0.25REIII0.25REIV0.25)2Si2O7 compounds, we find that their formation capability can be evaluated by the ability to accommodate configurational randomness of multiple RE3+ cations in β-type lattice while preventing the β-to-γ polymorphic transformation. The phase formation and stabilization are controlled by the average RE3+ radius and the deviations of different RE3+ combinations. Subsequently, based on high-throughput density-functional-theory calculations, we propose that the configurational entropy of mixing is a reliable ...

Latest version: v2
Publication date: Jan 30, 2023

Modeling of precipitate strengthening with near-chemical accuracy: case study of Al-6xxx alloys


Yi Hu, William Curtin

  • Many metal alloys are strengthened by controlling precipitation to achieve an optimal peak-aged condition where the strength-limiting processes of precipitate shearing and Orowan looping are thought to be comparable. Qualitative models have long captured the basic mechanisms but realistic predictions have been challenging due to both the lack of accurate material parameters and an inability to quantitatively validate the models. Here, dislocation/precipitate interaction mechanisms are studied in Al-6xxx Al–Mg–Si alloys using atomistic simulations in tandem with a near-chemically-accurate Al–Mg–Si neural network interatomic potentials. Results show that a given precipitate can exhibit shearing or looping depending on the relative orientation of the precipitate and dislocation, as influenced by the matrix and precipitate coherency stresses, direction-dependence of precipitate shearing energies, and dislocation line tension. Analytic models for shearing and calibrated discrete ...

Latest version: v1
Publication date: Jan 30, 2023

Steering on-surface reactions through molecular steric hindrance and molecule-substrate van der Waals interactions


Shiyong Wang, Tomohiko Nishiuchi, Carlo A. Pignedoli, Xuelin Yao, Marco Di Giovannantonio, Yan Zhao, Akimitsu Narita, Xinliang Feng, Klaus Müllen, Pascal Ruffieux, Roman Fasel

  • On-surface synthesis is a rapidly developing field involving chemical reactions on well-defined solid surfaces to access the synthesis of low-dimensional organic nanostructures which cannot be achieved via traditional solution chemistry. On-surface reactions critically depend on a high degree of chemoselectivity in order to achieve an optimum balance between the target structure and possible side products. In this record we provide data for the calculations that support a work that we recently published. In the published manuscript, we demonstrate the synthesis of graphene nanoribbons with a large unit cell based on steric hindrance-induced complete chemoselectivity as revealed by scanning probe microscopy measurements and density functional theory calculations. Our results disclose that combined molecule-substrate van der Waals interactions and intermolecular steric hindrance promote a selective aryl-aryl coupling, giving rise to high-quality uniform graphene nanostructures. The ...

Latest version: v1
Publication date: Jan 30, 2023

Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes


Haoyue Guo, Matthew R. Carbone, Chuntian Cao, Jianzhou Qu, Feng Wang, Shinjae Yoo, Nongnuch Artrith, Alexander Urban, Deyu Lu

  • We present a sulfur K-edge X-ray absorption near-edge structure (XANES) database of 18 crystalline and 48 amorphous Lithium-Phosphorous-Sulfur (LPS) compounds. The database contains a total of 2681 XANES spectra of symmetrically inequivalent absorbing S sites. Structures were taken from Materials Cloud entry 2022.17 (archive.materialscloud.org/record/2022.17) and were originally generated by systematically removing Li, P and S atoms from known crystal structures using an evolutionary algorithm and an artificial neural network based interatomic potential. The details of this procedure can be found in Guo et al. (see references below). From this data set, low-energy structures were selected for spectral simulations. The excited electron and core hole method as implemented in VASP 6.2.1 was used to compute the XANES spectra for each symmetrically inequivalent Sulfur atom. The details of the VASP simulations can be found in the associated manuscript. Acknowledgements: We acknowledge ...

Latest version: v2
Publication date: Jan 26, 2023

ReDD-COFFEE: A ready-to-use database of covalent organic framework structures and accurate force fields to enable high-throughput screenings


Juul S. De Vos, Sander Borgmans, Pascal Van Der Voort, Sven M. J. Rogge, Veronique Van Speybroeck

  • Covalent organic frameworks (COFs) are a versatile class of nanoporous materials that can be used for a broad range of applications. They possess strong covalent bonds and low densities. Owing to their building block nature, the number of hypothetical COFs envisioned by reticular synthesis is enormous. Since experimental screening is not possible, computational high-throughput screenings offer a valuable alternative to characterize the material space and speed-up materials discovery. These screening studies typically require a diverse materials database and accurate interatomic potentials to accurately predict the macroscopic behavior of each hypothetical COF. Here, we present ReDD-COFFEE, the Ready-to-use and Diverse Database of Covalent Organic Frameworks with Force field based Energy Evaluation. Our database contains 268 687 COFs and accompanying ab initio derived, system-specific force fields for each of them. We hope this database may inspire other researchers to further ...

Latest version: v1
Publication date: Jan 25, 2023

Topological magnons driven by the Dzyaloshinskii-Moriya interaction in the centrosymmetric ferromagnet Mn₅Ge₃


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

  • The phase of the quantum-mechanical wave function can encode a topological structure with wide-ranging physical consequences, such as anomalous transport effects and the existence of edge states robust against perturbations. While this has been exhaustively demonstrated for electrons, properties associated with the elementary quasiparticles in magnetic materials are still underexplored. Here, we show theoretically and via inelastic neutron scattering experiments that the bulk ferromagnet Mn₅Ge₃ hosts gapped topological Dirac magnons. Although inversion symmetry prohibits a net Dzyaloshinskii-Moriya interaction in the unit cell, it is locally allowed and is responsible for the gap opening in the magnon spectrum. This gap is predicted and experimentally verified to close by rotating the magnetization away from the c-axis. Hence, Mn₅Ge₃ is the first realization of a gapped Dirac magnon material in three dimensions. Its tunability by chemical doping or by thin film nanostructuring ...

Latest version: v1
Publication date: Jan 19, 2023

Influence of the triangular Mn-O breathing mode on magnetic ordering in multiferroic hexagonal manganites


Tara Niamh Tosic, Quintin Noël Meier, Nicola Ann Spaldin

  • We use a combination of symmetry analysis, phenomenological modeling, and first-principles density functional theory to explore the interplay between the magnetic ground state and the detailed atomic structure in the hexagonal rare-earth manganites. We find that the magnetic ordering is sensitive to a breathing mode distortion of the Mn and O ions in the ab plane, which is described by the K1 mode of the high-symmetry structure. Our density functional calculations of the magnetic interactions indicate that this mode particularly affects the single-ion anisotropy and the interplanar symmetric exchanges. By extracting the parameters of a magnetic model Hamiltonian from our first-principles results, we develop a phase diagram to describe the magnetic structure as a function of the anisotropy and exchange interactions. This in turn allows us to explain the dependence of the magnetic ground state on the identity of the rare-earth ion and on the K1 mode. The attached files contain VASP ...

Latest version: v1
Publication date: Jan 17, 2023

A low-temperature prismatic slip instability in Mg understood using machine learning potentials


Xin Liu, Masoud Rahbar Niazi, Tao Liu, Binglun Yin, William Curtin

  • Prismatic slip in magnesium at temperatures T ≲ 150 K occurs at ∼ 100 MPa independent of temperature, and jerky flow due to large prismatic dislocation glide distances is observed; this athermal regime is not understood. In contrast, the behavior at T ≳ 150 K is understood to be governed by a thermally-activated double-cross-slip of the stable basal screw dislocation through an unstable or weakly metastable prism screw configuration and back to the basal screw. Here, a range of neural network potentials (NNPs) that are very similar for many properties of Mg including the basal-prism-basal cross-slip path and pro- cess, are shown to have an instability in prism slip at a potential-dependent critical stress. One NNP, NNP-77, has a critical instability stress in good agreement with experiments and also has basal-prism-basal transition path energies in very good agreement with DFT results, making it an excellent potential for understanding Mg prism slip. Full 3d simulations of the ...

Latest version: v1
Publication date: Jan 17, 2023

A complementary screening for quantum spin Hall insulators in 2D exfoliable materials


Davide Grassano, Davide Campi, Antimo Marrazzo, Nicola Marzari

  • Quantum spin Hall insulators (QSHIs) are a class of topological materials that has been extensively studied during the past decade. One of their distinctive features is the presence of a finite band gap in the bulk and gapless, topologically protected edge states that are spin-momentum locked. These materials are characterized by a Z₂ topological order where, in the 2D case, a single topological invariant can be even or odd for a trivial or a topological material, respectively. Thanks to their interesting properties, such as the realization of dissipationless spin currents, spin pumping and spin filtering, they are of great interest in the field of electronics, spintronics and quantum computing. In this work we perform an high-throughput screening of QSHI starting from a set of 783 2D exfoliable materials (603 after removing materials with lanthanides), recently identified from a systematic screening of the ICSD, COD, and MPDS databases (MC2D). In this screening we identify 4 Z₂ ...

Latest version: v1
Publication date: Jan 13, 2023

Structure evolution of graphitic surface upon oxidation: insights by scanning tunneling microscopy


Shaoxian Li, Mohammad Tohidi Vahdat, Shiqi Huang, Kuang-Jung Hsu, Mojtaba Rezaei, Mounir Mensi, Nicola Marzari, Kumar Varoon Agrawal

  • Oxidation of graphitic materials has been studied for more than a century to synthesize materials such as graphene oxide, nanoporous graphene, and to cut or unzip carbon nanotubes. However, the understanding of the early stages of oxidation is limited to theoretical studies, and experimental validation has been elusive. This is due to (i) challenging sample preparation for characterization because of the presence of highly mobile and reactive epoxy groups formed during oxidation, and (ii) gasification of the functional groups during imaging with atomic resolution, e.g., by transmission electron microscopy. Herein, we utilize a low-temperature scanning tunneling microscope (LT-STM) operating at 4 K to solve the structure of epoxy clusters form upon oxidation. Three distinct nanostructures corresponding to three stages of evolution of vacancy defects are found by quantitatively verifying the experimental data by the van der Waals density functional theory. The smallest cluster is a ...

Latest version: v1
Publication date: Jan 12, 2023

Two-component density functional theory study of quantized muons in solids


Li Deng, Yue Yuan, Francis Pratt, Wenshuai Zhang, Ziwen Pan

  • The quantum effect of light nuclei in materials is usually considered as lattice vibration and zero-point motion (ZPM) from an ab initio perspective. Here we start from full-quantized particles and take the muon as an example, considering the two-body quantized system of the muon and the electrons within Two-Component Density Functional Theory, which can calculate the related two-body wave functions directly and automatically taking into account the quantum effect of the muon. This is an attempt to reveal the quantum effect of light nuclei in materials from a different respect. It is tested in some metallic systems (Fe-bcc, Co-fcc, Co-hcp) and some non-metallic systems (NaF, CaF₂, diamond), we finally find this fundamental method agrees better with experiments and shows good potential for further such study.

Latest version: v1
Publication date: Jan 11, 2023

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


Christoph Kastl, Pietro Bonfà, Lorenzo Maserati

  • In contrast to inorganic quantum wells, hybrid quantum wells (HQWs) based on metal-organic semiconductors are characterized by relatively soft lattices, in which excitonic states can strongly couple to lattice phonons. Therefore, understanding the lattice’s impact on exciton dynamics is essential for harnessing the optoelectronic potential of HQWs. Beyond 2D metal halide perovskites, layered metal-organic chalcogenides (MOCs) are an air-stable, underexplored material class hosting room-temperature excitons that could be exploited as photodetectors, light emitting devices, and ultrafast photoswitches. Here, we elucidate the role of phonons in the optical transitions of the prototypical MOC [AgSePh]∞. Impulsive stimulated Raman scattering (ISRS) allows us to detect coherent exciton oscillations driven by Fröhlich interaction with low-energy optical phonons. Steady state absorption and Raman spectroscopies reveal a strong exciton-phonon coupling (Huang-Rhys parameter ~1.7) and its ...

Latest version: v2
Publication date: Jan 09, 2023

Lattice energies and relaxed geometries for 2'707 organic molecular crystals and their 3'242 molecular components.


Rose Cersonsky, Maria Pakhnova, Edgar Engel, Michele Ceriotti

  • This data record contains the xyz-style files for 2'707 organic molecular crystals and their 3'202 molecular components. The crystals were initially taken directly from the Cambridge Structure Database, and the relaxations were computed and reported by [1]. This record contains an augmentation of a subset of this data, where we have identified the molecular constituents of each crystal, performed geometric relaxations using the same computational parameters, and identified the constituent functional groups. A full detail of methodology and provenance is included in the ESI of [2]. Each crystal and molecule has been relaxed using Quantum Espresso with the following parameters: the PBE exchange-correlation functional, the D2 dispersion correction, ultrasoft pseudopotentials with GIPAW reconstruction, and an equivalent plane-wave energy cutoff of 60 Ryd. We converged the energies within 1E-4 Ryd and forces below 1E-3 Ryd/Bohr, respectively, using MT-decoupling for the molecules to ...

Latest version: v1
Publication date: Jan 09, 2023

Hubbard U through polaronic defect states


Stefano Falletta, Alfredo Pasquarello

  • Since the preliminary work of Anisimov and co-workers, the Hubbard corrected DFT+U functional has been used for predicting properties of correlated materials by applying on-site effective Coulomb interactions to specific orbitals. However, the determination of the Hubbard U parameter has remained under intense discussion despite the multitude of approaches proposed. Here, we define a selection criterion based on the use of polaronic defect states for the enforcement of the piecewise linearity of the total energy upon electron occupation. A good agreement with results from piecewise-linear hybrid functionals is found for the electronic and structural properties of polarons, including the formation energies. The values of U determined in this way are found to give a robust description of the polaron energetics upon variation of the considered state. In particular, we also address a polaron hopping pathway, finding that the determined value of U leads to accurate energetics without ...

Latest version: v1
Publication date: Jan 06, 2023

Alloying as a strategy to boost the stability of Copper nanocatalysts during electrochemical CO₂ reduction reaction


Valery Okatenko, Anna Loiudice, Mark A. Newton, Dragos C. Stoian, Anastasia Blokhina, Alexander N. Chen, Kevin Rossi, Raffaella Buonsanti

  • Cu nano catalysts are among the most promising candidates to enable the up-conversion of CO₂ by means of electrochemical reduction. Yet, the lack of stability of Cu nano catalysts during electrochemical CO₂ reduction reaction represents a strong limiting factor in enabling their widespread use at the industrial level. The record gathers data related to the theoretical evaluation of the stability and activity of Cu-rich nano catalysts, in the presence of a second metal, namely Ga, whose amount varies between 5% and 30%.

Latest version: v1
Publication date: Jan 06, 2023

Influence of germanium substitution on the structural and electronic stability of the competing vanadium dioxide phases


Peter Mlkvik, Claude Ederer, Nicola A. Spaldin

  • We present a density-functional theory (DFT) study of the structural, electronic, and chemical bonding behavior in germanium (Ge)-doped vanadium dioxide (VO2). Our motivation is to explain the reported increase of the metal-insulator transition temperature under Ge doping and to understand how much of the fundamental physics and chemistry behind it can be captured at the conventional DFT level. We model doping using a supercell approach, with various concentrations and different spatial distributions of Ge atoms in VO2. Our results suggest that the addition of Ge atoms strongly perturbs the high-symmetry metallic rutile phase and induces structural distortions that partially resemble the dimerization of the experimental insulating structure. Our work, therefore, hints at a possible explanation of the observed increase in transition temperature under Ge doping, motivating further studies into understanding the interplay of structural and electronic transitions in VO2.

Latest version: v1
Publication date: Jan 06, 2023

Gap opening in double-sided highly hydrogenated free-standing graphene


Miki Bonacci, Elisa Molinari, Deborah Prezzi

  • Conversion of graphene into pure free-standing graphane — where each C atom is sp³ bound to a hydrogen atom — has not been achieved so far, in spite of numerous experimental attempts. Here, we obtain an unprecedented level of hydrogenation (~90% of sp³ bonds) by exposing fully free-standing nano porous samples — constituted by single to few veils of smoothly rippled graphene — to atomic hydrogen in ultra-high-vacuum. Such a controlled hydrogenation of high-quality and high-specific-area samples converts the original conductive graphene into a wide gap semiconductor, with the valence band maximum (VBM) ~3.5 eV below the Fermi level, as monitored by photoemission spectro-microscopy and confirmed by theoretical predictions. In fact, the calculated band structure unequivocally identifies the achievement of a stable, double-side fully hydrogenated configuration, with no trace of pi states and a gap opening in excellent agreement with the experimental results.

Latest version: v2
Publication date: Jan 06, 2023

Pure isotropic proton NMR spectra in solids using deep learning


Manuel Cordova, Pinelopi Moutzouri, Bruno Simões de Almeida, Daria Torodii, Lyndon Emsley

  • The resolution of proton solid-state NMR spectra is usually limited by broadening arising from dipolar interactions between spins. Magic-angle spinning alleviates this broadening by inducing coherent averaging. However, even the highest spinning rates experimentally accessible today are not able to completely remove dipolar interactions. Here, we introduce a deep learning approach to determine pure isotropic proton spectra from a two-dimensional set of magic-angle spinning spectra acquired at different spinning rates. Applying the model to 8 organic solids yields high-resolution 1H solid-state NMR spectra with isotropic linewidths in the 50-400 Hz range.

Latest version: v1
Publication date: Dec 22, 2022

Evolving scattering networks for material classification, stealthy hyperuniform shielding, preferential attachment, and material phase diagram


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 introduce the concept of evolving wave networks (Code_Set_Fig_2), classify material states according to network parameters (Code_Set_Fig_3), generate the stealthy hyperuniformity (SHU) shielding of existing materials (Code_Set_Fig_4), realize preferential attachment in evolving wave networks (Code_Set_Fig_5), and obtain the following phase diagram of disordered materials (Code_Set_Fig_6).

Latest version: v3
Publication date: Dec 22, 2022

The impact of valley profile on the mobility and Kerr rotation of transition metal dichalcogenides


Thibault Sohier, Pedro M. M. C. de Melo, Zeila Zanolli, Matthieu Jean Verstraete

  • The transport and optical properties of semiconducting transition metal dichalcogenides around room temperature are dictated by electron-phonon scattering mechanisms within a complex, spin-textured and multi-valley electronic landscape. The relative positions of the valleys are critical, yet they are sensitive to external parameters and very difficult to determine directly. We propose a first-principles model as a function of valley positions to calculate carrier mobility and Kerr rotation angles, and apply it to MoS₂, WS₂, MoSe₂, and WSe₂. The model brings valuable insights, as well as quantitative predictions of macroscopic properties for a wide range of carrier density. The doping-dependant mobility displays a characteristic peak, the height depending on the position of the valleys. In parallel, the Kerr rotation signal is enhanced when same spin-valleys are aligned, and quenched when opposite spin-valleys are populated. We provide guidelines to optimize and correlate these ...

Latest version: v1
Publication date: Dec 22, 2022

Fixed node diffusion Monte Carlo energies for over one thousand small organic molecules


Bing Huang, Anatole von Lilienfeld, Jaron Krogel, Anouar Benali

  • In the past decade, quantum diffusion Monte Carlo (DMC) has been demonstrated to successfully predict the energetics and properties of a wide range of molecules and solids by numerically solving the electronic many-body Schrödinger equation. We show that when coupled with quantum machine learning (QML) based surrogate methods the computational burden can be alleviated such that QMC shows clear potential to undergird the formation of high quality descriptions across chemical space. We discuss three crucial approximations necessary to accomplish this: The fixed node approximation, universal and accurate references for chemical bond dissociation energies, and scalable minimal amons set based QML (AQML) models. Numerical evidence presented includes converged DMC results for over one thousand small organic molecules with up to 5 heavy atoms used as amons, and 50 medium sized organic molecules with 9 heavy atoms to validate the AQML predictions. Numerical evidence collected for 𝛥-AQML ...

Latest version: v1
Publication date: Dec 19, 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. For each model, we provide the .mph file (Comsol) and the .java file (Java+Comsol). We also provide examples of the resulting impedances and frequency responses of various parameters.

Latest version: v2
Publication date: Dec 19, 2022

ML-ready Curie temperatures and descriptors extracted from the JuHemd database


Robin Hilgers, Daniel Wortmann, Stefan Blügel

  • The uploaded archive provides a ML-ready data set extracted from the juHemd database (see references) augmented with supplemental data for atomic descriptors. Descriptors provided in this data set include structural, magnetic, atomic quantities as well as derived (summed) quantities. In total, 118 possible descriptors are included of which 12 are DFT generated. For each simulation type (LDA/GGA) there is also a data set cleaned from DFT data available. After data cleaning and preprocessing we extracted 387 LDA calculated magnetic Heusler structures as well as 408 GGA structures which have a full structural and magnetic data set. As we only aim at magnetic compounds, we chose to filter out compounds from the original JuHemd which have at least 0.1 Bohr magneton as total absolute magnetic moment. For each data file there is an existing descriptor file naming all the descriptors included in the data set.

Latest version: v1
Publication date: Dec 19, 2022

Antiferromagnetism-driven two-dimensional topological nodal-point superconductivity


Maciej Bazarnik, Roberto Lo Conte, Eric Mascot, Kirsten von Bergmann, Dirk K. Morr, Roland Wiesendanger

  • Magnet/superconductor hybrids (MSHs) hold the promise to host emergent topological superconducting phases. Both one-dimensional (1D) and two-dimensional (2D) magnetic systems in proximity to s-wave superconductors have shown evidence of gapped topological superconductivity with zero-energy end states and chiral edge modes. Recently, it was proposed that the bulk transition-metal dichalcogenide 4Hb-TaS2 is a gapless topological nodal-point superconductor (TNPSC). However, there has been no experimental realization of a TNPSC in a MSH system yet. In our work we present the discovery of TNPSC in antiferromagnetic (AFM) monolayers on top of an s-wave superconductor. Our calculations show that the topological phase is driven by the AFM order, resulting in the emergence of a gapless time-reversal invariant topological superconducting state. Using low-temperature scanning tunneling microscopy we observe a low-energy edge mode, which separates the topological phase from the trivial one, ...

Latest version: v1
Publication date: Dec 13, 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: v3
Publication date: Dec 12, 2022

Solids that are also liquids: elastic tensors of superionic materials


Giuliana Materzanini, Tommaso Chiarotti, Nicola Marzari

  • This work presents an application of the strain-fluctuation method, exploiting the fluctuations of the strain from extensive first-principles molecular dynamics simulations in the isobaric-isothermal ensemble, to the study of the elastic tensors of superionic materials. As the superionic materials for solid-state electrolyte applications usually do not have well-defined ground-state configurations, it is challenging to apply the static methods to calculate the elastic tensors of these materials. Instead, the strain-fluctuation method captures the dynamical nature of the elastic response of these materials and is a promising approach to studying their elastic properties. In this work: a protocol is presented and documented to extract the elastic the elastic moduli and their statistical errors from the molecular dynamics trajectories (open-source code available at https://github.com/materzanini); results for two benchmark superionic materials (Li₁₀GeP₂S₁₂ and Li₁₀GeP₂O₁₂) are given; ...

Latest version: v1
Publication date: Dec 09, 2022

Growth optimization and device integration of narrow-bandgap graphene nanoribbons


Gabriela Borin Barin, Qiang Sun, Marco Di Giovannantonio, Cheng-Zhuo Du, Xiao-Ye Wang, Juan Pablo Llinas, Zafer Mutlu, Yuxuan Lin, Jan Wilhelm, Jan Overbeck, Colin Daniels, Michael Lamparski, Hafeesudeen Sahabudeen, Mickael L. Perrin, José I. Urgel, Shantanu Mishra, Amogh Kinikar, Roland Widmer, Samuel Stolz, Max Bommert, Carlo A. Pignedoli, Xinliang Feng, Michel Calame, Klaus Müllen, Akimitsu Narita, Vincent Meunier, Jeffrey Bokor, Roman Fasel, Pascal Ruffieux

  • The electronic, optical, and magnetic properties of graphene nanoribbons (GNRs) can be engineered by controlling their edge structure and width with atomic precision through bottom-up fabrication based on molecular precursors. This approach offers a unique platform for all-carbon electronic devices but requires careful optimization of the growth conditions to match structural requirements for successful device integration, with GNR length being the most critical parameter. In a recent work we study, the growth, characterization, and device integration of 5-atom wide armchair GNRs (5-AGNRs), which are expected to have an optimal bandgap as active material in switching devices. 5-AGNRs are obtained via on-surface synthesis under ultrahigh vacuum conditions from Br- and I-substituted precursors. It is shown that the use of I-substituted precursors and the optimization of the initial precursor coverage quintupled the average 5-AGNR length. This significant length increase allowed the ...

Latest version: v1
Publication date: Dec 08, 2022

Raman spectra of 2D titanium carbide MXene from machine-learning force field molecular dynamics


Ethan Berger, Zhong-Peng Lv, Hannu-Pekka Komsa

  • MXenes represent one of the largest class of 2D materials with promising applications in many fields and their properties tunable by the surface group composition. Raman spectroscopy is expected to yield rich information about the surface composition, but the interpretation of measured spectra has proven challenging. The interpretation is usually done via comparison to simulated spectra, but there are large discrepancies between the experimental and earlier simulated spectra. In this work, we develop a computational approach to simulate Raman spectra of complex materials that combines machine-learning force-field molecular dynamics and reconstruction of Raman tensors via projection to pristine system modes. The approach can account for the effects of finite temperature, mixed surfaces, and disorder. We apply our approach to simulate Raman spectra of titanium carbide MXene and show that all these effects must be included in order to properly reproduce the experimental spectra, in ...

Latest version: v1
Publication date: Dec 07, 2022

Engineering solvation in initiated Chemical Vapor Deposition (iCVD) for process-property control


Pengyu Chen, Zheyuan Zhang, Zach Rouse, Shefford Baker, Jingjie Yeo, Rong Yang

  • Organic solvents are widely used in polymer synthesis, despite their use lengthening purification steps and generating chemical waste. All-dry synthesis techniques, such as initiated Chemical Vapour Deposition (iCVD) polymerization, eliminate the use of solvents, however, only a narrow palette of material properties is accessible. Inspired by the principles of solvent engineering in solution synthesis, we report a strategy to broaden this palette by vapour-phase complexing (namely, vapour-phase solvation) mediated by hydrogen-bonding. Broad ranges of polymer chain length, as well as the mechanical strength and variety of film surface morphology are demonstrating using this strategy. We further achieve an unprecedented solvation modality; more specifically, interfacial solvation. The molecular interactions, locations of solvation, and kinetics of the coupled solvation-adsorption-polymerization process are investigated using molecular dynamic simulations and experimental validation ...

Latest version: v1
Publication date: Dec 06, 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: v2
Publication date: Dec 06, 2022

Data-driven discovery of organic electronic materials enabled by hybrid top-down/bottom-up design


J. Terence Blaskovits, R. Laplaza, S. Vela, C. Corminboeuf

  • The high-throughput molecular exploration and screening of organic electronic materials often starts with either a 'top-down' mining of existing repositories, or the 'bottom-up' assembly of fragments based on predetermined rules and known synthetic templates. In both instances, the datasets used are often produced on a case-by-case basis, and require the high-quality computation of electronic properties and extensive user input: curation in the top-down approach, and the construction of a fragment library and introduction of rules for linking them in the bottom-up approach. Both approaches are time-consuming and require significant computational resources. Here, we generate a top-down set named FORMED consisting of 117K synthesized molecules containing their optimized structures, associated electronic and topological properties and chemical composition, and use these structures as a vast library of molecular building blocks for bottom-up fragment-based materials design. A tool is ...

Latest version: v1
Publication date: Dec 05, 2022

Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows


Miki Bonacci, Junfeng Qiao, Nicola Spallanzani, Antimo Marrazzo, Giovanni Pizzi, Elisa Molinari, Daniele Varsano, Andrea Ferretti, Deborah Prezzi

  • The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations that are relevant to extend this approach beyond density functional theory (DFT), in order to automate many-body perturbation theory (MBPT) calculations. Notably, a novel algorithm pursuing the goal of an efficient and robust convergence procedure for GW and BSE simulations is provided, together with its implementation in a fully automated framework. This is accompanied by an automatic GW band interpolation scheme based on maximally-localized Wannier functions, aiming at a reduction of the computational burden of quasiparticle band structures while preserving high accuracy. The proposed developments are validated on a set of representative semiconductor and metallic systems.

Latest version: v1
Publication date: Dec 02, 2022

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

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

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

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

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

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

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