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Spin fluctuation induced Weyl semimetal state in the paramagnetic phase of EuCd2As2
[materialscloud:2019.0080] Last version: 11 November 2019
This record mainly upload all the raw experimental data related to the manuscript. Fig1 include the transport data, magnetotransport data, AHE data, ESR data, uSR data. These data related to the conclusion that spin fluctuation established in the paramagnetic phase. Fig2 contains in-plane and out-of-plane 3D photoemission spectra, and high resolution cuts on top and side surface. Fig3 contains band electronic structure along high symmetry lines with spin along all kinds of typical directions. Fig4 contains 3-D in-plane and out-of-plane Fermi surfaces on the 101 cleavage, high resolution cuts, STM/STS data. The proved the observation of Weyl points.
A New Kind of Atlas of Zeolite Building Blocks
[materialscloud:2019.0079] Last version: 06 November 2019
We have analyzed structural motifs in the Deem database of hypothetical zeolites to investigate whether the structural diversity found in this database can be well-represented by classical descriptors, such as distances, angles, and ring sizes, or whether a more general representation of the atomic structure, furnished by the smooth overlap of atomic position (SOAP) method, is required to capture accurately structure–property relations. We assessed the quality of each descriptor by machine-learning the molar energy and volume for each hypothetical framework in the dataset. We have found that a SOAP representation with a cutoff length of 6 Å, which goes beyond near-neighbor tetrahedra, best describes the structural diversity in the Deem database by capturing relevant interatomic correlations. Kernel principal component analysis shows that SOAP maintains its superior performance even when reducing its dimensionality to those of the classical descriptors and that the first three ...
Valley-Engineering Mobilities in Two-Dimensional Materials
[materialscloud:2019.0075] Last version: 04 November 2019
Two-dimensional materials are emerging as a promising platform for ultrathin channels in field-effect transistors. To this aim, novel high-mobility semiconductors need to be found or engineered. Although extrinsic mechanisms can in general be minimized by improving fabrication processes, the suppression of intrinsic scattering (driven, for example, by electron–phonon interactions) requires modification of the electronic or vibrational properties of the material. Because intervalley scattering critically affects mobilities, a powerful approach to enhance transport performance relies on engineering the valley structure. We show here the power of this strategy using uniaxial strain to lift degeneracies and suppress scattering into entire valleys, dramatically improving performance. This is shown in detail for arsenene, where a 2% strain stops scattering into four of the six valleys and leads to a 600% increase in mobility. The mechanism is general and can be applied to many other ...
Highly anisotropic interlayer magnetoresitance in ZrSiS nodal-line Dirac semimetal
[materialscloud:2019.0074] Last version: 29 October 2019
In this work, we investigate the angle-dependent magnetoresistance (AMR) of the layered nodal-line Dirac semimetal ZrSiS for the in-plane and out-of-plane current directions. Combining the Fermi surfaces calculated from first principles with the Boltzmann’s semiclassical transport theory, we reproduce all the prominent features of the unusual behavior of the in-plane and out-of-plane AMR.We can conclude that the dominant contribution the cusplike AMR lies in open orbits of the hole pocket and, in general, AMR is strongly influenced by charge compensation effect and the off-diagonal conductivity tensor elements, which give rise to peculiar butterfly-shaped AMR.
Magnetoresistance from Fermi surface topology
[materialscloud:2019.0073] Last version: 29 October 2019
In this work, we investigate the transverse magnetoresistance of materials by combining the Fermi surfaces calculated from first principles with the Boltzmann transport theory approach relying on the semiclassical model and the relaxation time approximation. We first consider a series of simple model Fermi surfaces to provide a didactic introduction into the charge-carrier compensation and open-orbit mechanisms leading to nonsaturating magnetoresistance. We then address in detail magnetotransport in three representative materials: (i) copper, (ii) bismuth, and (iii) tungsten diphosphide. Furthermore, the calculations allow for a full interpretation of the observed features in terms of the Fermi surface topology. Our study thus establishes guidelines to clarifying the physical mechanisms underlying the magnetotransport properties in a broad range of materials.
Graphene Nanoribbons Derived From Zigzag Edge-Encased Poly(para-2,9-dibenzo[bc,kl]coronenylene) Polymer Chains
[materialscloud:2019.0078] Last version: 29 October 2019
In a recent work, we demonstrated the bottom-up on-surface synthesis of poly(para-dibenzo[bc,kl]-coronenylene) , a zigzag edge-encased analog of poly(para-phenylene), and its lateral fusion into zigzag edge-extended graphene nanoribbons. The record contains data to reproduce the calculations that were performed at Empa to support the findings discussed in the manuscript.
Electron density learning of non-covalent systems
[materialscloud:2019.0071] Last version: 28 October 2019
Chemists continuously harvest the power of non-covalent interactions to control phenomena in both the micro- and macroscopic worlds. From the quantum chemical perspective, the strategies essentially rely upon an in-depth understanding of the physical origin of these interactions, the quantification of their magnitude and their visualization in real-space. The total electron density ρ(r) represents the simplest yet most comprehensive piece of information available for fully characterizing bonding patterns and non-covalent interactions. The charge density of a molecule can be computed by solving the Schrödinger equation, but this approach becomes rapidly demanding if the electron density has to be evaluated for thousands of different molecules or very large chemical systems, such as peptides and proteins. Here we present a transferable and scalable machine-learning model capable of predicting the total electron density directly from the atomic coordinates. The regression model is ...
High-throughput computational screening for solid-state Li-ion conductors
[materialscloud:2019.0077] Last version: 28 October 2019
We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as solid-state electrolytes in next-generation batteries. We start from ~1400 unique Li-containing materials, of which ~900 are insulators at the level of density-functional theory. For those, we calculate the diffusion coefficient in a highly automated fashion, using extensive molecular dynamics simulations on a potential energy surface (the recently published pinball model) fitted on first-principles forces. The ~130 most promising candidates are studied with full first-principles molecular dynamics, first at high temperature and then more extensively for the 78 most promising candidates. The results of the first-principles simulations of the candidate solid-state electrolytes found are discussed in detail.
Band gap of atomically precise graphene nanoribbons as a function of ribbon length and termination
[materialscloud:2019.0069] Last version: 28 October 2019
The record contains the theoretical data supporting a recent publication where we discuss the band gap of finite armchair graphene nanoribbons with a width of seven rows of carbon atoms (7‐AGNRs) on Au(111) through scanning tunneling microscopy/spectroscopy combined with density functional theory calculations.
Transferable Machine-Learning Model of the Electron Density
[materialscloud:2019.0076] Last version: 28 October 2019
The electronic charge density plays a central role in determining the behavior of matter at the atomic scale, but its computational evaluation requires demanding electronic-structure calculations. We introduce an atom-centered, symmetry-adapted framework to machine-learn the valence charge density based on a small number of reference calculations. The model is highly transferable, meaning it can be trained on electronic-structure data of small molecules and used to predict the charge density of larger compounds with low, linear-scaling cost. Applications are shown for various hydrocarbon molecules of increasing complexity and flexibility, and demonstrate the accuracy of the model when predicting the density on octane and octatetraene after training exclusively on butane and butadiene. This transferable, data-driven model can be used to interpret experiments, accelerate electronic structure calculations, and compute electrostatic interactions in molecules and condensed-phase systems.
Open-shell Non-benzenoid Nanographenes Containing Two Pairs of Pentagonal and Heptagonal Rings
[materialscloud:2019.0072] Last version: 25 October 2019
Nonbenzenoid carbocyclic rings are postulated to serve as important structural elements toward tuning the chemical and electronic properties of extended polycyclic aromatic hydrocarbons (PAHs, or namely nanographenes), necessitating a rational and atomically precise synthetic approach toward their fabrication. This record contains data supporting a recent work where, using a combined bottom-up in-solution and on-surface synthetic approach, we report the synthesis of nonbenzenoid open-shell nanographenes containing two pairs of embedded pentagonal and heptagonal rings.
Simulating diffusion properties of solid-state electrolytes via a neural network potential: Performance and training scheme
[materialscloud:2019.0067] Last version: 25 October 2019
The recently published DeePMD model, based on a deep neural network architecture, brings the hope of solving the time-scale issue which often prevents the application of first principle molecular dynamics to physical systems. With this contribution we assess the performance of the DeePMD potential on a real-life application and model diffusion of ions in solid-state electrolytes. We consider as test cases the well known Li10GeP2S12, Li7La3Zr2O12 and Na3Zr2Si2PO12. We develop and test a training protocol suitable for the computation of diffusion coefficients, which is one of the key properties to be optimized for battery applications, and we find good agreement with previous computations. Our results show that the DeePMD model may be a successful component of a framework to identify novel solid-state electrolytes.
Comparison of computational methods for the electrochemical stability window of solid-state electrolyte materials
[materialscloud:2019.0070] Last version: 25 October 2019
Superior stability and safety are key promises attributed to all-solid-state batteries (ASSBs) containing solid-state electrolyte (SSE) in comparison to their conventional counterparts utilizing liquid electrolyte. To unfold the full potential of ASSBs, SSE materials are desirable that are stable in contact with both the low and the high potential electrode. The electrochemical stability window is conveniently used to assess the SSE--electrode interface stability. In the present work, we review the most important methods to compute the SSE stability window. We find that the stoichiometry stability method represents a bridge between HOMO--LUMO method and phase stability method (grand canonical phase diagram). We further provide implementations of these methods for SSE material screening and we compare their results for the relevant Li- and Na-SSE materials LGPS, LIPON, LLZO, LLTO, LATP, LISICON, and NASICON.
The solid-state Li-ion conductor Li7TaO6: A combined computational and experimental study
[materialscloud:2019.0068] Last version: 25 October 2019
We study the oxo-hexametallate Li7TaO6 with first-principles and classical molecular dynamics simulations, obtaining a low activation barrier for diffusion of ∼0.29 eV and a high ionic conductivity of 5.7×10−4 S cm−1 at room temperature (300 K). We find evidence for a wide electrochemical stability window from both calculations and experiments, suggesting its viable use as a solid-state electrolyte in next-generation solid-state Li-ion batteries. To assess its applicability in an electrochemical energy storage system, we performed electrochemical impedance spectroscopy measurements on multicrystalline pellets, finding substantial ionic conductivity, if below the values predicted from simulation. We further elucidate the relationship between synthesis conditions and the observed ionic conductivity using X-ray diffraction, inductively coupled plasma optical emission spectrometry, and X-ray photoelectron spectroscopy, and study the effects of Zr and Mo doping.
DFT+DMFT study of oxygen vacancies in a Mott insulator
[materialscloud:2019.0066] Last version: 24 October 2019
Oxygen vacancies are a common source of excess electrons in complex oxides. In Mott insulators, these additional electrons can induce a metal-insulator transition (MIT), fundamentally altering the electronic properties of the system. Here we study the effect of oxygen vacancies in LaTiO3, a prototypical Mott insulator close to the MIT. We show that the introduction of oxygen vacancies creates a vacancy-related band immediately below the partially filled Ti-t 2g bands. We study the effect of this additional band on the Mott MIT using a combination of density functional theory and dynamical mean-field theory (DFT+DMFT), employing a minimal correlated subspace consisting of effective Ti-t 2g orbitals plus an additional Wannier function centered on the vacancy site. We find that the Mott insulating state in LaTiO3 is robust to the presence of the vacancy band, which remains fully occupied even in the presence of a local Coulomb repulsion, and therefore does not cause a doping of the Mott insulator
On-Surface Synthesis of a Non-Planar Porous Nanographene
[materialscloud:2019.0064] Last version: 23 October 2019
In a recent publication we demonstrated the on surface synthesis of a porous nanographene and we characterized its electronic properties combining spectroscopy experiments to ab-initio simulations. In this record we provide experimental and computational data that support the results discussed in the manuscript.
Neural networks-based variationally enhanced sampling
[materialscloud:2019.0065] Last version: 22 October 2019
Sampling complex free-energy surfaces is one of the main challenges of modern atomistic simulation methods. The presence of kinetic bottlenecks in such surfaces often renders a direct approach useless. A popular strategy is to identify a small number of key collective variables and to introduce a bias potential that is able to favor their fluctuations in order to accelerate sampling. Here, we propose to use machine-learning techniques in conjunction with the recent variationally enhanced sampling method [O. Valsson, M. Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] in order to determine such potential. This is achieved by expressing the bias as a neural network. The parameters are determined in a variational learning scheme aimed at minimizing an appropriate functional. This required the development of a more efficient minimization technique. The expressivity of neural networks allows representing rapidly varying free-energy surfaces, removes boundary effects artifacts, and allows several collective variables to be handled.
Chemical Shifts in Molecular Solids by Machine Learning Datasets
[materialscloud:2019.0023] Last version: 22 October 2019
We present a database of energy and NMR chemical shifts DFT calculations of 4150 crystal organic solids. The structures contain only H/C/N/O/S atoms and were subject to all-atoms geometry optimisation. Calculations were carried out using Quantum Espresso and GIPAW.
Rethinking Metadynamics
[materialscloud:2019.0063] Last version: 22 October 2019
Metadynamics is an enhanced sampling method of great popularity, based on the on-the-fly construction of a bias potential that is function of a selected number of collective variables. In order to improve its usability and convergence speed, we propose here a change in perspective that shifts the focus form the bias to the probability distribution reconstruction. The result is an enhanced sampling method that combine metadynamics and adaptive umbrella sampling approaches, taking the best from the two worlds. This new method has a straightforward reweighting scheme and allows for efficient importance sampling, avoiding uninteresting high free energy regions. Thanks to a compressed kernel density estimation it can handle a higher dimensional collective variable space, and does not require the prior knowledge of the boundaries of such space. The new method comes in two variants. The first aims at a quick convergence, avoiding oscillations and maximizing the quasi-static bias regime, ...
Mechanism and control parameters of the coupled structural and metal-insulator transition in nickelates
[materialscloud:2019.0061] Last version: 22 October 2019
Rare-earth nickelates exhibit a remarkable metal-insulator transition accompanied by a symmetry-lowering structural distortion. Using model considerations and first-principles calculations, we present a theory of this phase transition which reveals the key role of the coupling between electronic and lattice instabilities. We show that the transition is driven by the proximity to an instability towards electronic disproportionation which couples to a specific structural distortion mode, cooperatively driving the system into the insulating state. This allows us to identify two key control parameters of the transition: the susceptibility to electronic disproportionation and the stiffness of the lattice mode. We show that our findings can be rationalized in terms of a Landau theory involving two coupled order parameters, with general implications for transition-metal oxides.
Atomistic simulation of carbohydrate-protein complex formation: Hevein-32 domain
[materialscloud:2019.0042] Last version: 21 October 2019
Unbiased molecular dynamics simulation was used to simulate systems containing hevein (HEV32) domain and mono-, di- or trisaccharide of GlcNAc. Carbohydrate molecules were placed outside the binding site. Three of six simulations led to formation of a carbohydrate-protein complex. Trajectories are available without water and are sampled every 100 ps. This study is one of the first application of docking by dynamics concept on carbohydrate-protein interactions.
Synthesis and Characterization of π-Extended Triangulene
[materialscloud:2019.0062] Last version: 21 October 2019
In a recent work, we reported a combined in-solution and on-surface synthesis of π-extended triangulene, a non-Kekulé nanographene with the structural formula C33H15, consisting of ten benzene rings fused in a triangular fashion. The distinctive topology of the molecule entails the presence of three unpaired electrons that couple to form a spin quartet ground state. In this record we include experimental and computational data that support the findings of the manuscript.
Charge transfer in LaVO3/LaTiO3 multilayers: Strain-controlled dimensionality of interface metallicity between two Mott insulators
[materialscloud:2019.0059] Last version: 17 October 2019
We use density-functional theory plus dynamical mean-field theory to demonstrate the emergence of a metallic layer at the interface between the two Mott insulators LaTiO3 and LaVO3. The metallic layer is due to charge transfer across the interface, which alters the valence state of the transition-metal cations close to the interface. Somewhat counterintuitively, the charge is transferred from the Ti cations with formal d1 electron configuration to the the V cations with formal d2 configuration, thereby increasing the occupation difference of the t2g states. This can be understood as a result of a gradual transition of the charge-transfer energy, or electronegativity, across the interface. The spatial extension of the metallic layer, in particular toward the LaTiO3 side, can be controlled by epitaxial strain, with tensile strain leading to a localization within a thickness of only two unit cells. Our results open up a route for creating a tunable quasi-two-dimensional electron gas in materials with strong electronic correlations.
Electron transport through metal/MoS2 interfaces: edge- or area-dependent process?
[materialscloud:2019.0060] Last version: 14 October 2019
In ultra-thin two-dimensional (2-D) materials, the formation of ohmic contacts with top metallic layers is a challenging task that involves different processes than in bulk-like structures. Besides the Schottky barrier height, the transfer length of electrons between metals and 2-D monolayers is a highly relevant parameter. For MoS2, both short (≤30 nm) and long (≥0.5 μm) values have been reported, corresponding to either an abrupt carrier injection at the contact edge or a more gradual transfer of electrons over a large contact area. Here we use ab initio quantum transport simulations to demonstrate that the presence of an oxide layer between a metallic contact and a MoS2 monolayer, for example TiO2 in case of titanium electrodes, favors an area-dependent process with a long transfer length, while a perfectly clean metal-semiconductor interface would lead to an edge process. These findings reconcile several theories that have been postulated about the physics of metal/MoS2 ...
Ab initio simulation of band-to-band tunneling FETs with single- and few-layer 2-D materials as channels
[materialscloud:2019.0058] Last version: 11 October 2019
Full-band atomistic quantum transport simulations based on first principles are employed to assess the potential of band-to-band tunneling field-effect-transistors (TFETs) with a 2-D channel material as future electronic circuit components. We demonstrate that single layer transition metal dichalcogenides (TMDs) are not well-suited for TFET applications. There might, however, exist a great variety of 2-D semiconductors that have not even been exfoliated yet: this work pinpoints some of the most promising candidates among them to realize highly efficient TFETs. Single-layer SnTe, As, TiNBr, and Bi are all found to ideally deliver ON-currents larger than 100 μA/μm at 0.5 V supply voltage and 0.1 nA/μm OFF current value. We show that going from single to multiple layers can boost the TFET performance as long as the gain from a narrowing band gap exceeds the loss from the deteriorating gate control. Finally, a 2-D van der Waals heterojunction TFET is revealed to perform almost as well ...
Overcoming steric hindrance in aryl-aryl homocoupling via on-surface copolymerization
[materialscloud:2019.0056] Last version: 10 October 2019
On‐surface synthesis is a unique tool for growing low‐dimensional carbon nanomaterials with precise structural control down to the atomic level. One of the most applied reactions to covalently interlink molecular precursors is dehalogenative aryl‐aryl coupling. Failures in this process are often related to the steric hindrance between reactants, which may arise due to their coplanarity upon adsorption on a surface. In a recent work we proposed a copolymerization approach to overcome the limitations that prevent intermolecular homocoupling. We used suitable linkers as additional reactants to demonstrate formation of fully conjugated polycyclic nanowires incorporating non‐benzenoid rings. This record contains data to support the experimental and theoretical evidences discussed in the manuscript.
The reaction mechanism of the azide–alkyne Huisgen cycloaddition
[materialscloud:2019.0057] Last version: 09 October 2019
In a recent publication we inspected the mechanism of the azide–alkyne Huisgen cycloaddition. We studied the dynamical aspects of the process using metadynamics computer simulations. We focused on the conformational aspects that determine the course of the reaction and characterize its free energy landscape. This record contains data related to the calculations discussed in the publication.
Termini effects on the optical properties of graphene nanoribbons
[materialscloud:2019.0055] Last version: 03 October 2019
First principles the optical response of finite-length armchair-edged graphene nanoribbons (AGNRs) within the framework of many-body perturbation theory. As a result of the explicit inclusion of zigzag extremities, we identify low-energy and low-intensity excitations that are expected to be almost independent of the GNR length. These excitations coexist with bulk-like excitations, which have the same origin as the ones characterizing infinite AGNRs. Our results are used to rationalize termini effects on the optical response of GNRs and to shed light on recent photoluminescence data.
Self-consistent site-dependent DFT+U study of stoichiometric and defective SrMnO3
[materialscloud:2019.0054] Last version: 25 September 2019
We propose a self-consistent site-dependent Hubbard U approach for density functional theory (DFT)+U calculations of defects in complex transition metal oxides, using Hubbard parameters computed via linear response theory. The formation of a defect locally perturbs the chemical environment of Hubbard sites in its vicinity, resulting in different Hubbard U parameters for different sites. Using oxygen vacancies in SrMnO3 as a model system, we investigate the dependence of U on the chemical environment and study its influence on the structural, electronic, and magnetic properties of defective bulk and strained thin-film structures. Our results show that a self-consistent U improves the description of stoichiometric bulk SrMnO3 with respect to generalized gradient approximation (GGA) or GGA+U calculations using an empirical U. For defective systems, U changes as a function of the distance of the Hubbard site from the defect, its oxidation state, and the magnetic phase of the bulk ...
On-surface synthesis of antiaromatic and open-shell indeno[2,1-b]fluorene polymers and their lateral fusion into porous ribbons
[materialscloud:2019.0053] Last version: 23 September 2019
This record contains the experimental and computational data needed to support the work done on on-surface synthesis of conjugated polymers consisting of indeno[2,1-b]fluorene units, which are antiaromatic and open-shell biradicaloids. The observed reaction products have been characterized via low-temperature scanning tunneling microscopy/spectroscopy and noncontact atomic force microscopy, complemented by density-functional theory calculations. These polymers present a low band gap when adsorbed on Au(111). Moreover, their pronounced antiaromaticity and radical character, elucidated by ab initio calculations, make them promising candidates for applications in electronics and spintronics. Further, they provide a rich playground to explore magnetism in low-dimensional organic nanomaterials.
Making the best of a bad situation: a multiscale approach to free energy calculation
[materialscloud:2019.0004] Last version: 17 September 2019
Many enhanced sampling techniques rely on the identification of a number of collective variables that describe all the slow modes of the system. By constructing a bias potential in this reduced space one is then able to sample efficiently and reconstruct the free energy landscape. In methods like metadynamics, the quality of these collective variables plays a key role in convergence efficiency. Unfortunately in many systems of interest it is not possible to identify an optimal collective variable, and one must deal with the non-ideal situation of a system in which some slow modes are not accelerated. We propose a two-step approach in which, by taking into account the residual multiscale nature of the problem, one is able to significantly speed up convergence. To do so, we combine an exploratory metadynamics run with an optimization of the free energy difference between metastable states, based on the recently proposed variationally enhanced sampling method. This new method is ...
EAM potential for Hf-Nb-Ta-Zr high-entropy alloy
[materialscloud:2019.0052] Last version: 14 September 2019
This is a LAMMPS readable EAM type potential file for Hf-Nb-Ta-Zr based high-entropy alloys (HEAs). In this potential file the elements are sequenced as Hf, Nb, Ta and Zr, respectively. This potential was previously used to model the HEA for the local lattice distortions due to short-range order clustering found in the alloy after long-term annealing at high-temperature. The input to build this potential is based on the physical properties of pure elements such as the lattice parameter, cohesive energy, elastic constants etc and the details are discussed in the associated reference. Units used are in eV/atom for energy and Angstrom for distance.
Dopant discovery in cuprous iodide
[materialscloud:2019.0051] Last version: 11 September 2019
Computational data to support an extensive study of prospective dopants in the zinc blende (gamma) phase of cuprous iodide. This phase of CuI holds the current record hole conductivity for intrinsic transparent p-type semiconductors. In the corresponding scientific article, a high-throughput approach was employed to systematically explore strategies for enhancing CuI further by impurity incorporation. Our objectives were to identify a practical approach for increasing hole conductivity in CuI thin films and to explore the possibility for ambivalent doping. A total of 64 chemical elements was investigated. This materials cloud record contains all optimized defective structures for Cu and I substitutional sites, calculation settings and some of the output (LOCPOT files, required for electrostatic correction calculations are not included due to their large size). Chalcogen elements were found to display acceptor character when substituting iodine. Further eight impurities suitable ...
Exploring chemical space in the search for improved Azoheteroarene-based photoswitches
[materialscloud:2019.0050] Last version: 10 September 2019
In the quest for improved photo switches, azoheteroarenes have emerged as a potential alternative to azobenzene. However, to date the number and types of these species that have subjected to study is insufficient to provide an in-depth understanding of the photochemical effects brought about by different substituents. Here, we computationally screen the optical properties and thermal stabilities of 512 azoheteroarenes that consist of eight different N-containing heteroarenes combined with 64 substitution patterns. The most promising compounds are identified and their properties rationalized based on the nature of the azoheteroarene core and the location and type of substitution patterns.
Lattice thermal conductivity of MgSiO3 post-perovskite under the lowermost mantle conditions from ab initio anharmonic lattice dynamics
[materialscloud:2019.0049] Last version: 10 September 2019
This database includes Isotropic lattice thermal conductivities of MgSiO3 post-perovskite under the lowermost mantle conditions. The conductivity was calculated based on the ab initio anharmonic lattice dynamics with solving the linearized phonon Boltzmann transport equation.
Defect Formation Energies of Interstitial C, Si, and Ge Impurities in β-Ga2O3
[materialscloud:2019.0048] Last version: 09 September 2019
We investigate formation energies of C, Si, and Ge defects in β-Ga2O3 through hybrid functional calculations. We find that the interstitial defects of these elements generally occur at higher energies than their substitutional counterparts, while they are more stable at low Fermi energies in Ga-rich conditions. In n-type and Ga-rich conditions, interstitials of Si and Ge show significantly higher formation energies than their substitutional form, but this difference is less pronounced for C. Charge transition levels of interstitial defects lie in the upper part of the band-gap, and account for several measured levels in unintentionally doped and Ge-doped samples of β-Ga2O3.
Local electronic descriptors for solute-defect interactions in bcc refractory metals
[materialscloud:2019.0047] Last version: 02 September 2019
The interactions between solute atoms and crystalline defects such as vacancies, dislocations, and grain boundaries are essential in determining alloy properties. Here we present a general linear correlation between two descriptors of local electronic structures and the solute-defect interaction energies in binary alloys of body-centered-cubic (bcc) refractory metals (such as W and Ta) with transition-metal substitutional solutes. One electronic descriptor is the bimodality of the d-orbital local density of states for a matrix atom at the substitutional site, and the other is related to the hybridization strength between the valance sp- and d-bands for the same matrix atom. For a particular pair of solute-matrix elements, this linear correlation is valid independent of types of defects and the locations of substitutional sites. These results provide the possibility to apply local electronic descriptors for quantitative and efficient predictions on the solute-defect interactions and defect properties in alloys.
Can metal–organic frameworks be used for cannabis breathalyzers?
[materialscloud:2019.0046] Last version: 02 September 2019
∆9-tetrahydrocannabinol (THC) is the principal psychoactive component of cannabis, and there is an urgent need to build low-cost and portable devices that can detect its presence from breath. Similarly to alcohol detectors, these tools can be used by law enforcement to determine driver intoxication and enforce safer and more regulated use of cannabis. In this work, we propose to use a class of microporous crystals, metal–organic frameworks (MOFs), to selectively adsorb THC that can be later detected using optical, electrochemical, or fluorescence-based sensing methods. We screened computationally more than 5000 MOFs, highlighting the materials that have the largest affinity with THC, as well as the highest selectivity against water, showing that it is thermodynamically feasible for MOFs to adsorb THC from humid breath. We propose and compare different models for THC and different computational protocols to rank the promising materials, also presenting a novel approach to assess ...
Automated high-throughput Wannierisation
[materialscloud:2019.0044] Last version: 30 August 2019
Maximally-localised Wannier functions (MLWFs) are routinely used to compute from first- principles advanced materials properties that require very dense Brillouin zone integration and to build accurate tight-binding models for scale-bridging simulations. At the same time, high- thoughput (HT) computational materials design is an emergent field that promises to accelerate the reliable and cost-effective design and optimisation of new materials with target properties. The use of MLWFs in HT workflows has been hampered by the fact that generating MLWFs automatically and robustly without any user intervention and for arbitrary materials is, in general, very challenging. We address this problem directly by proposing a procedure for automatically generating MLWFs for HT frameworks. Our approach is based on the selected columns of the density matrix method (SCDM) and we present the details of its implementation in an AiiDA workflow. We apply our approach to a dataset of 200 bulk ...
Negatively-curved warped nanographene self-assembled on metal surfaces
[materialscloud:2019.0045] Last version: 27 August 2019
In this work we characterize a conjugated polycyclic hydrocarbon containing multiple nonbenzenoid rings and exhibiting negative curvature—the warped nanographene C80H30. The record contains input files to reproduce the calculations discussed in the manuscript and the raw data of the experimental images discussed.
Amphiphilic Peptide Binding on Crystalline vs. Amorphous Silica from Molecular Dynamics Simulations
[materialscloud:2019.0043] Last version: 26 August 2019
The leucine-lysine amphiphilic peptide LKα14 has been used to study fundamental driving forces in processes such as peptide-surface binding and biomineralization. Here, we employ molecular dynamics (MD) simulations in tandem with replica exchange metadynamics to probe the binding mechanism and thermodynamics of LKα14 on silica. We also investigate the effect that the nature of the silica surface – crystalline vs. amorphous, has on the binding properties and peptide-surface conformations. We find that water adsorbs differently on both surfaces; it forms a denser interfacial layer on the crystalline surface, compared to the amorphous surface. This causes the peptide to bind more strongly on the amorphous surface than the crystalline surface. Cluster analysis shows that the peptide adopts a helical conformation at both surfaces, with a greater distribution of states on the crystalline surface. Peptide binding is primarily through lysine interactions, in line with prior experimental results.
Applicability of tail-corrections in the molecular simulations of porous materials
[materialscloud:2019.0024] Last version: 21 August 2019
Molecular simulations with periodic boundary conditions require to define a certain cutoff distance beyond which pairwise dispersion interactions are neglected. For the simulation of homogeneous phases it is well-established to use tail-corrections, that can remedy this truncation of the potential. These corrections are built under the assumption that beyond the cutoff the radial distribution function is equal to one. In this work we shed some light on the discussion whether or not tail corrections should be used in the modelling of heterogeneous systems. We show that for the adsorption of gasses in a diverse set nanoporous crystalline materials (zeolites, Covalent Organic Frameworks (COFs), and Metal Organic Frameworks (MOFs)), tail-corrections are an appropriate choice with which the results are much less sensitive to the details of the truncation.
Generalized stacking fault energy surfaces for eight face-centered cubic transition metals
[materialscloud:2019.0041] Last version: 13 August 2019
Density functional theory calculations were used to obtain the generalized stacking fault energy surfaces in eight FCC metals: Ag, Au, Cu, Ir, Ni, Pd, Pt, and Rh. Among them, ferromagnetism was considered only in Ni. Results based on non-magnetic Ni are denoted as Ni-NM.
Quantum Mechanical Static Dipole Polarizabilities in the QM7b and AlphaML Showcase Databases
[materialscloud:2019.0002] Last version: 13 August 2019
Dipole polarizabilities (and other molecular properties) computed using linear response coupled cluster theory (LR-CCSD/d-aug-cc-pVDZ) and hybrid density functional theory (B3LYP/d-aug-cc-pVDZ, SCAN0/d-aug-cc-pVDZ, and B3LYP/d-aug-cc-pVTZ) for the 7,211 molecules in the QM7b database and the 52 molecules in the AlphaML showcase database.
Supplementary Data for “Non-Abelian band topology in noninteracting metals”
[materialscloud:2019.0040] Last version: 09 August 2019
Electron energy bands, which are studied to explain electronic and optical properties of crystalline solids, often exhibit degeneracies called band-structure nodes. Here, we introduce non-Abelian topological charges that characterize line nodes inside the momentum space of -symmetric crystalline metals with weak spin-orbit coupling. We show that these are quaternion charges, similar to those describing disclinations in biaxial nematics. Starting from two-band considerations, we develop the complete many-band description of nodes in the presence of and mirror symmetries, which allows us to investigate the topological stability of nodal chains in metals. The non-Abelian charges put strict constraints on the possible nodal line configurations. Our analysis goes beyond the standard approach to band topology and implies the existence of 1D topological phases not present in existing classifications.
Adjustable potential probes for band-gap predictions of extended systems through nonempirical hybrid functionals
[materialscloud:2019.0039] Last version: 08 August 2019
We describe a nonempirical procedure for achieving accurate band gaps of extended systems through the insertion of suitably defined potential probes. By enforcing Koopmans' condition on the resulting localized electronic states, we determine the optimal fraction of Fock exchange to be used in the adopted hybrid functional. As potential probes, we consider point defects, the hydrogen interstitial, and various adjustable potentials that allow us to vary the energy level of the localized state in the band gap. By monitoring the delocalized screening charge, we achieve a measure of the degree of hybridization with the band states, which can be used to improve the band-gap estimate. Application of this methodology to AlP, C, and MgO yields band gaps differing by less than 0.2 eV from experiment.
Effect of the Solvent on the Oxygen Evolution Reaction at the TiO2-Water Interface
[materialscloud:2019.0038] Last version: 02 August 2019
We investigate the solvation effect of water on the overpotentials of the oxygen evolution reaction on rutile TiO2 by applying the thermodynamic integration method on atomistic model interfaces with and without the water molecules. We compare the results at the vacuum interface with the commonly used computational hydrogen electrode method, finding overall good agreement. The effect of the solvent is found to be twofold. First, the explicit treatment of the solvent can lead to equilibrium configurations differing from the relaxed structures without solvent. Second, the overpotentials can be affected by up to 0.5 eV. The energetics are subject to electrostatic effects at the interface rather than to modifications in the hydrogen bond network. These results provide a promising perspective for treating the solvent with implicit models.
On-surface light-induced generation of higher acenes and elucidation of their open-shell character
[materialscloud:2019.0037] Last version: 15 July 2019
In this work we demonstrate the on surface synthesis of nonacene and heptacene and we discuss their open shell character comparing experimental evidence to theoretical predictions. The record contains input files to reproduce the calculations discussed in the manuscript and the raw data of the experimental images discussed.
The complex non-collinear magnetic orderings in Ba2YOsO6: A new approach to tuning spin-lattice interactions and controlling magnetic orderings in frustrated complex oxides
[materialscloud:2019.0036] Last version: 02 July 2019
Project abstract: Frustrated magnets are one class of fascinating materials that host many intriguing phases such as spin ice, spin liquid and complex long-range magnetic orderings at low temperatures. In this work we use first-principles calculations to find that in a wide range of magnetically frustrated oxides, at zero temperature a number of non-collinear magnetic orderings are more stable than the type-I collinear ordering that is observed at finite temperatures. The emergence of non-collinear orderings in those complex oxides is due to higher-order exchange interactions that originate from second-row and third-row transition metal elements. This implies a collinear-to-noncollinear spin transition at sufficiently low temperatures in those frustrated complex oxides. Furthermore, we find that in a particular oxide Ba2YOsO6, experimentally feasible uniaxial strain can tune the material between two different non-collinear magnetic orderings. Our work predicts new non- collinear ...
Electron and Hole Polarons at the BiVO4–Water Interface
[materialscloud:2019.0035] Last version: 01 July 2019
We determine the transition levels of electron and hole polarons at the BiVO4–water interface through thermodynamic integration within a hybrid functional scheme, thereby accounting for the liquid nature of the water component. The electron polaron is found to be less stable at the interface than in the bulk by 0.18 eV, while for the hole polaron the binding energy increases by 0.20 eV when the charge localizes in the surface layer of BiVO4. These results indicate that interfacial effects on the polaron binding energy and charge distribution are sizeable and cannot trivially be inferred from bulk calculations.
Building a consistent and reproducible database for adsorption evaluation in Covalent-Organic Frameworks
[materialscloud:2019.0034] Last version: 25 June 2019
We present a workflow that traces the path from the bulk structure of a crystalline material to assessing its performance in carbon capture from coal's post-combustion flue gases. We apply the workflow to a database of 324 covalent-organic frameworks (COFs) reported in the literature to characterize their CO2 adsorption properties using the following steps: (1) optimization of the crystal structure (atomic positions and cell) using density functional theory, (2) fitting atomic point charges based on the electron density, (3) characterizing the (pore) geometry of the structures before and after optimization, (4) computing carbon dioxide and nitrogen isotherms using grand canonical Monte Carlo simulations (empirical interaction potential) and, finally, (5) assessing the CO2 parasitic energy via process modelling. The full workflow has been encoded in the Automated Interactive Infrastructure and Database for Computational Science (AiiDA). Both the workflow and the ...
Picture of Wet Electron: A Localized Transient State in Liquid Water
[materialscloud:2019.0033] Last version: 20 June 2019
A transient state of the excess electron in liquid water preceding the development of the solvation shell, the so-called wet electron, has been invoked to explain spectroscopic observations, but its binding energy and atomic structure have remained highly elusive. Here, we carry out hybrid functional molecular dynamics to unveil the ultrafast solvation mechanism leading to the hydrated electron. In the pre-hydrated regime, the electron is found to repeatedly switch between a quasi-free electron state in the conduction band and a localized state with a binding energy of 0.26 eV, which we assign to the wet electron. This transient state self-traps in a region of the liquid which extends up to ∼4.5 Å and involves a severe disruption of the hydrogen-bond network. Our picture provides an unprecedented view on the nature of the wet electron, which is instrumental to understand the properties of this fundamental species in liquid water.
Reaction pathway of oxygen evolution on Pt(1 1 1) revealed through constant Fermi level molecular dynamics
[materialscloud:2019.0031] Last version: 18 June 2019
The pathway of the oxygen evolution reaction at the Pt(1 1 1)/water interface is disclosed through constant Fermi level molecular dynamics. Upon the application of a positive bias potential H2O_ads and O_ads adsorbates are found to arrange in a hexagonal lattice with an irregular alternation. Increasing further the electrode potential then induces the oxygen evolution reaction, which is found to proceed through a hydrogen peroxide intermediate. Calculation of the associated overpotential shows a reduction of 0.2 eV compared to the associative mechanism. This result highlights the forcefullness of the applied scheme in exploring catalytic reactions in an unbiased way.
Free-Energy Surface Prediction by Flying Gaussian Method
[materialscloud:2019.0032] Last version: 18 June 2019
Molecular simulations are computationally expensive, especially in systems with multiple free energy minima. To address this problem many enhanced sampling techniques have been developed. Metadynamics uses a bias potential defined as a sum of Gaussian hills in space of few (one or two) collective variables. This bias potential disfavors states that have been visited since the beginning of the simulation. Multiple walker metadynamics simulates the system in multiple parallel replicas. The bias potential disfavors states that have been visited since the beginning of the simulation in any replica. Flying Gaussian method presented here also simulates the system in multiple parallel replicas. It disfavors states that are, at certain moment, similar in two or more replicas. It was demonstrated on Alanine Dipeptide in vacuum and water, cis/trans-isomerisation of Proline-containing peptides and Met-enkephalin.
Reducing the Number of Mean-Square Deviation Calculations with Floating Close Structure in Metadynamics
[materialscloud:2019.0021] Last version: 17 June 2019
Biomolecular simulations are computationally expensive. This limits their application in protein folding simulations, protein engineering, drug design and related fields. Enhanced sampling techniques such as metadynamics accelerates slow events in molecular simulation. This and other method apply artificial forces in directions of collective degrees of freedom (aka collective variables). Path collective variables and Property Map collective variables are defined using a series of reference structures of the studied molecular system. They require a huge number of mean square deviation calculations along the simulation. Close Structure algorithm reduces the number of these operations.
Multithermal-multibaric molecular simulations from a variational principle
[materialscloud:2019.0016] Last version: 12 June 2019
We present a method for performing multithermal-multibaric molecular dynamics simulations that sample entire regions of the temperature-pressure (TP) phase diagram. The method uses a variational principle [Valsson and Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] in order to construct a bias that leads to a uniform sampling in energy and volume. The intervals of temperature and pressure are taken as inputs and the relevant energy and volume regions are determined on the fly. In this way the method guarantees adequate statistics for the chosen TP region. We show that our multithermal-multibaric simulations can be used to calculate all static physical quantities for all temperatures and pressures in the targeted region of the TP plane. We illustrate our approach by studying the density anomaly of TIP4P/Ice water. This record includes input and output files, and Jupyter Notebooks describing the analysis of the simulations and the creation of the figures for the paper.
MD trajectories of semiconductor-water interfaces and relaxed atomic structures of semiconductor surfaces
[materialscloud:2019.0029] Last version: 02 June 2019
This entry includes the MD trajectories of several semiconductor-water interfaces generated with ab initio molecular dynamics using the rVV10 density functional at the temperature of 350 K. Eight semiconductor surfaces are considered, namely GaAs(110), GaP(110), GaN(10-10), CdS(10-10), ZnO(10-10), SnO2(110), rutile TiO2(110) and anatase TiO2(101). For GaAs, GaP and anatase TiO2, the trajectories for the interfaces with both the molecular and the dissociative adsorption mode of water are provided. In addition, the relaxed atomic structures of the semiconductor surfaces used to calculate the ionization potential (IP) reported in [Chem. Mater. 2018, 30, 94−111] are added.
MD trajectories of bulk water and of the water-vacuum interface
[materialscloud:2019.0030] Last version: 01 June 2019
This entry provides MD trajectories for bulk water and the water-vacuum interface generated with ab initio molecular dynamics using rVV10 density functional at the temperature of 350 K. In the rVV10 functional, the parameter b is set to 9.3.
Determining interface structures in vertically aligned nanocomposite films
[materialscloud:2019.0025] Last version: 31 May 2019
Vertically aligned nanocomposites (VANs) films have self-assembled pillar-matrix nanostructures. Owing to their large area-to-volume ratios, interfaces in VAN films are expected to play key roles in inducing functional properties, but our understanding is hindered by limited knowledge about their structures. Motivated by the lack of definitive explanation for the experimentally-found enhanced ionic conductivity in Sm-doped-CeO2/SrTiO3 VAN films, we determine the structure at vertical interfaces using random structure searching and explore how it can affect ionic conduction. This record contains the candidate structures and provenance of the DFT validation calculations. Previously unknown interface structures are found, with lower energy than that of an optimized hand-built model. We find a strongly distorted oxygen sub-lattice which gives a complex landscape of vacancy energies. The cation lattice remains similar to the bulk phase but has a localized strain field. The excess ...
Extrinsic Defects in Amorphous Oxides: Hydrogen, Carbon, and Nitrogen Impurities in Alumina
[materialscloud:2019.0027] Last version: 30 May 2019
This entry provides the most stable defect configurations of hydrogen, carbon, and nitrogen impurities in alumina, which are identified through ab initio molecular dynamics in various charge states and structural relaxations with the PBE functional. The structural configurations related to carbon and nitrogen impurities are found to depend on the total charge set in the simulation cell.
Oxygen defects in amorphous Al2O3
[materialscloud:2019.0026] Last version: 30 May 2019
The electronic properties of the oxygen vacancy and interstitial in amorphous Al2O3 are studied via ab initio molecular dynamics simulations and hybrid functional calculations. Our results indicate that these defects do not occur in amorphous Al2O3, due to structural rearrangements which assimilate the defect structure and cause a delocalization of the associated defect levels. The imbalance of oxygen leads to a nonstoichiometric compound in which the oxygen occurs in the form of O2– ions. Intrinsic oxygen defects are found to be unable to trap excess electrons. For low Fermi energies, the formation of peroxy linkages is found to be favored leading to the capture of holes. The relative +2/0 defect levels occur at 2.5 eV from the valence band.
Intrinsic defects in amorphous TiO2
[materialscloud:2019.0028] Last version: 30 May 2019
This entry provides the atomic structures of three bulk amorphous TiO2 models generated through the melt-and-quench method with different cooling rates and of ten O-O peroxy linkages obtained by adding two holes to the bulk model constructed with the lowest cooling rate.
Dynamics of the Bulk Hydrated Electron from Many‐Body Wave‐Function Theory
[materialscloud:2019.0022] Last version: 27 May 2019
Trajectories and spin densities for the bulk hydrated electron at the MP2 level of theory. The data represent the first ab initio molecular dynamics study of the hydrated electron in the bulk using many-body wave function theory.
TopoMat: a database of high-throughput first-principles calculations of topological materials
[materialscloud:2019.0019] Last version: 21 May 2019
We present a database of topological materials predicted from high-throughput first-principles calculations. The database contains electronic band structures and topological indices of 13628 materials calculated on experimental crystal structures taken from the Inorganic Crystal Structure Database (ICSD) and the Crystallography Open Database (COD). The calculations have been performed on non-magnetic phases taking into account the spin-orbit interactions using the Quantum ESPRESSO package. The Fu-Kane method and the Wannier charge center method implemented in the Z2pack code have been utilized to calculate the Z2 topological numbers of centrosymmetric and non-centrosymmetric materials, respectively. Over 4000 topologically non-trivial materials have been identified.
Data-driven studies of magnetic two-dimensional materials
[materialscloud:2019.0020] Last version: 20 May 2019
We use a data-driven approach to study the magnetic and thermodynamic properties of van der Waals (vdW) layered materials. We investigate monolayers of the form A2B2X6, based on the known material Cr2Ge2Te6, using density functional theory (DFT) calculations and determine their magnetic properties, such as magnetic order and magnetic moment. We also examine formation energies and use them as a proxy for chemical stability.
MgTa2N3: A reference Dirac semimetal
[materialscloud:2019.0018] Last version: 13 May 2019
MgTa2N3 is predicted to host the topological Dirac semimetal phase. This archive includes input data necessary for reproducing first-principles calculation described in the publication.
Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials
[materialscloud:2019.0017] Last version: 09 May 2019
Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and environmental challenges. Many of these processes involve the dynamics of individual atoms or small molecules in condensed phases, e.g. lithium ions in electrolytes, water molecules in membranes, molten atoms at interfaces, etc., which are difficult to understand due to the complexity of local environments. We develop graph dynamical networks, an unsupervised learning approach for understanding atomic scale dynamics in arbitrary phases and environments from molecular dynamics simulations. We show that important dynamical information can be learned for various multi-component amorphous material systems, which is difficult to obtain otherwise. We develop a software package "gdynet" at https://github.com/txie-93/gdynet which implements the graph dynamical networks algorithm. This record contains the MD ...
High-throughput calculations of catalytic properties of bimetallic alloy surfaces
[materialscloud:2019.0015] Last version: 01 May 2019
We present a large dataset of adsorption of H, C, N, O and S onto more than 2,000 metallic and bimetallic alloy surfaces, consisting of approximately 90,000 DFT calculations performed in Quantum Espresso. The alloys are constructed from all possible combinations of 37 metals into AB and A3B stoichiometries, in the L1_0 and L1_2 structures respectively, where the 37 metals in the A1 structure are included as well. Slabs are cleaved along the 111 facet for A1 and L1_2 and along the 101 facet for L1_0, and all possible adsorption sites are sampled. In addition to the monoatomic adsorbates, adsorption of CH, CH2, CH3, NH, NH2, OH, H2O and SH is sampled for a smaller subset of alloys.
Approximation of Collective Variables by anncolvar
[materialscloud:2019.0014] Last version: 23 April 2019
Biomolecular simulations are computationally expensive. This limits their application in drug or protein design and related fields. Several methods have been developed to address this problem. These methods often use an artificial force or potential acting on selected degrees of freedom known as collective variables. This requires explicit calculation of a collective variable (and its derivatives) from molecular structure. For collective variables that cannot be calculated explicitly or such calculations is slow we developed anncolvar package (https://github.com/spiwokv/anncolvar). This package approximates collective variables using artificial neural networks. It was tested on Isomap low dimensional representation of cyclooctane derivative or solvent-accessible surface area of Trp-cage miniprotein.
Free-Energy Surface Prediction by Flying Gaussian Method: Numerical Proof
[materialscloud:2019.0013] Last version: 17 April 2019
Biomolecular simulations have a great potential in protein engineering, drug discovery and many other fields. Unfortunately, this method is computationally expensive, so many interesting processes cannot be routinely studied. In order to address this problem we developed Flying Gaussian method [Journal of Chemical Theory and Computation 12, 4644-4650 (2016)]. This method simultaneously simulates multiple replicas of the studied system and disfavor replicas with similar structures by artificial bias potential. The question arises how to calculate an unbiased free energy surface from a biased simulation. This dataset demonstrates together with mathematical arguments supports application of Umbrella Sampling reweighing method, despite the fact that this method is designed for methods with a time-independent bias potential.
Unified theory of thermal transport in crystals and disordered solids
[materialscloud:2019.0001] Last version: 08 April 2019
Crystals and glasses exhibit fundamentally different heat conduction mechanisms: the periodicity of crystals allows for the excitation of propagating vibrational waves that carry heat, as first discussed by Peierls; in glasses, the lack of periodicity breaks Peierls' picture and heat is mainly carried by the coupling of vibrational modes, often described by a harmonic theory introduced by Allen and Feldman. Anharmonicity or disorder are thus the limiting factors for thermal conductivity in crystals or glasses; hitherto, no transport equation has been able to account for both. In the paper https://arxiv.org/abs/1901.01964, we derive such equation, resulting in a thermal conductivity that reduces to the Peierls and Allen-Feldman limits, respectively, in anharmonic-and-ordered or harmonic-and-disordered solids, while also covering the intermediate regimes where both effects are relevant. This approach also solves the long-standing problem of accurately predicting the thermal ...
Tailoring Bond Topologies in Open-Shell Graphene Nanostructures
[materialscloud:2019.0012] Last version: 07 April 2019
The data contained in this record, raw data of images and input files to reproduce calculations, support our recent report for the on-surface synthesis and characterization of two ultralow-gap open-shell molecules, namely peri-tetracene, a benzenoid graphene fragment with zigzag edge topology, and dibenzo[a,m]dicyclohepta[bcde,nopq]rubicene, a nonbenzenoid nonalternant structural isomer of peri-tetracene with two embedded azulene units. Our results provide an understanding of the ramifications of altered bond topologies at the single-molecule scale, with the prospect of designing functionalities in carbon-based nanostructures via engineering of bond topology
Two-dimensional materials from high-throughput computational exfoliation of experimentally known compounds
[materialscloud:2017.0008] Last version: 03 April 2019
Two-dimensional (2D) materials have emerged as promising candidates for next-generation electronic and optoelectronic applications. Yet, only a few dozens of 2D materials have been successfully synthesized or exfoliated. Here, we search for novel 2D materials that can be easily exfoliated from their parent compounds. Starting from 108423 unique, experimentally known three-dimensional compounds we identify a subset of 5619 that appear layered according to robust geometric and bonding criteria. High-throughput calculations using van-der-Waals density-functional theory, validated against experimental structural data and calculated random-phase-approximation binding energies, allow to identify 1825 compounds that are either easily or potentially exfoliable. In particular, the subset of 1036 easily exfoliable cases provides novel structural prototypes and simple ternary compounds as well as a large portfolio of materials to search from for optimal properties. For a subset of 258 ...
TuTraST data for methane diffusion in IZA structures
[materialscloud:2019.0011] Last version: 11 March 2019
Data for the case study of TuTraSt on methane diffusion in zeolites, using a standard kinetic Monte Carlo simulation based on the output of our grid analysis. We find that it is accurate, fast, and rigorous without limitations to the geometries of the diffusion tunnels or transition states.
Capturing chemical intuition in synthesis of metal-organic frameworks
[materialscloud:2018.0011] Last version: 03 March 2019
We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the highest surface area reported to date. We illustrate the importance of quantifying this chemical intuition for the synthesis of novel materials.
Enhanced sampling of transition states
[materialscloud:2019.0010] Last version: 28 February 2019
The free energy landscapes of several fundamental processes are characterized by high barriers separating long-lived metastable states. In order to explore these type of landscapes enhanced sampling methods are used. While many such methods are able to obtain sufficient sampling in order to draw the free energy, the transition states are often sparsely sampled. We propose an approach based on the Variationally Enhanced Sampling Method to enhance sampling in the transition region. To this effect, we introduce a dynamic target distribution which uses the derivative of the instantaneous free energy surface to locate the transition regions on the fly and modulate the probability of sampling different regions. Finally, we exemplify the effectiveness of this approach in enriching the number of configurations in the transition state region in the cases of a chemical reaction and of a nucleation process.
Mining the C-C Cross-Coupling Genome using Machine Learning
[materialscloud:2019.0007] Last version: 23 February 2019
Applications of machine-learning (ML) techniques to the study of catalytic processes have begun to appear in the literature with increasing frequency. The computational speed up provided by ML allows the properties and energetics of thousands of prospective catalysts to be rapidly assessed. These results, once compiled into a database containing different properties, can be mined with the goal of establishing relationships between the intrinsic chemical properties of different catalysts and their overall catalytic performance. Previously, we applied ML models to predict the performance of 18,000 prospective catalysts for a Suzuki coupling reaction using molecular volcano plots. Here, we expand on our earlier work by examining a larger section of the C-C cross-coupling genome by using a dimensionality-reducing data-clustering algorithms (i.e., sketch-map) to, first, identify the compatibility of each catalyst with different C-C cross-coupling variants (e.g., Suzuki, Kumada, ...
Energetics of the coupled electronic–structural transition in the rare-earth nickelates
[materialscloud:2019.0009] Last version: 21 February 2019
Rare-earth nickelates exhibit a metal–insulator transition accompanied by a structural distortion that breaks the symmetry between formerly equivalent Ni sites. The quantitative theoretical description of this coupled electronic–structural instability is extremely challenging. Here, we address this issue by simultaneously taking into account both structural and electronic degrees of freedom using a charge self-consistent combination of density functional theory and dynamical mean-field theory, together with screened interaction parameters obtained from the constrained random phase approximation. Our total energy calculations show that the coupling to an electronic instability toward a charge disproportionated insulating state is crucial to stabilize the structural distortion, leading to a clear first order character of the coupled transition. The decreasing octahedral rotations across the series suppress this electronic instability and simultaneously increase the screening of the ...
Unsupervised landmark analysis for jump detection in molecular dynamics simulations
[materialscloud:2019.0008] Last version: 12 February 2019
Molecular dynamics is a versatile and powerful method to study diffusion in solid-state ionic conductors, requiring minimal prior knowledge of equilibrium or transition states of the system's free energy surface. However, the analysis of trajectories for relevant but rare events, such as a jump of the diffusing mobile ion, is still rather cumbersome, requiring prior knowledge of the diffusive process in order to get meaningful results. In this work we present a novel approach to detect the relevant events in a diffusive system without assuming prior information regarding the underlying process. We start from a projection of the atomic coordinates into a landmark basis to identify the dominant features in a mobile ion's environment. Subsequent clustering in landmark space enables a discretization of any trajectory into a sequence of distinct states. As a final step, the use of the Smooth Overlap of Atomic Positions descriptor allows distinguishing between different ...
DORI reveals the influence of non-covalent interactions on covalent bonding patterns in molecular crystals under pressure
[materialscloud:2019.0006] Last version: 06 February 2019
The study of organic molecular crystals under high pressure provides fundamental insight into crystal packing distortions and reveals mechanisms of phase transitions and the crystallization of polymorphs. These solid state transformations can be monitored directly by analyzing electron charge densities that are experimentally obtained at high pressure. However, restricting the analysis to the featureless electron density does not reveal the chemical bonding nature and the existence of intermolecular interactions. This shortcoming can be resolved by the use of the DORI (Density Overlap Region Indicator) descriptor, which is capable of detecting simultaneously both covalent patterns and non-covalent interactions from electron density and its derivatives. Using the biscarbonyl[14]annulene crystal under pressure as an example, we demonstrate how DORI can be exploited on experimental electron densities to reveal and monitor changes in electronic structure patterns resulting from ...
Double helix PBDT polymer - Submitted manuscript, simulations and other source data
[materialscloud:2019.0005] Last version: 03 February 2019
We describe a double helical conformation in the densely charged aromatic polyamide poly(2,2’- disulfonyl-4,4’-benzidine terephthalamide) or PBDT. This double helix macromolecule represents one of the most rigid simple molecular structures known, exhibiting an extremely high axial persistence length (~ 1 micrometer).
Emergence of hidden phases of methylammonium lead-iodide (CH3NH3PbI) upon compression
[materialscloud:2019.0003] Last version: 23 January 2019
We perform a thorough structural search with the minima hopping method (MHM) to explore low-energy structures of methylammonium lead iodide. By combining the MHM with a forcefield, we efficiently screen vast portions of the configurational space with large simulation cells containing up to 96 atoms. Our search reveals two structures of methylammonium iodide perovskite (MAPI) that are substantially lower in energy than the well-studied experimentally observed low-temperature orthorhombic phase. The data set containing approximately ~180,000 crystal structures is provided.
Few layer 2D pnictogens catalyze the alkylation of soft nucleophiles with esters.
[materialscloud:2018.0021] Last version: 14 January 2019
Group 15 elements in zero oxidation state (P, As, Sb and Bi), also called pnictogens, are rarely used in catalysis due to the difficulties associated in preparing well–structured and stable materials. Here, we report on the synthesis of highly exfoliated, few layer 2D phosphorene and antimonene in zero oxidation state, suspended in an ionic liquid, with the native atoms ready to interact with external reagents while avoiding aerobic or aqueous decomposition pathways, and on their use as efficient catalysts for the alkylation of nucleophiles with esters. The few layer pnictogen material circumvents the extremely harsh reaction conditions associated to previous superacid–catalyzed alkylations, by enabling an alternative mechanism on surface, protected from the water and air by the ionic liquid. These 2D catalysts allow the alkylation of a variety of acid–sensitive organic molecules and giving synthetic relevancy to the use of simple esters as alkylating agents.
Atomic structures of semiconductor surfaces
[materialscloud:2018.0022] Last version: 10 December 2018
This entry includes the surface structures of some prototypical semiconductors obtained via structural optimizations using the PBE density functional. The structures were initially used for benchmarking ionization potentials calculated with hybrid density functionals and GW approximation. Seven semiconductor surfaces are provided in the form of Quantum ESPRESSO input: Si(111), C(111), GaAs(110), GaP(110), ZnSe(110), ZnO(10-10), and TiO2(110).
Ab initio electronic structure of liquid water: Molecular dynamics snapshots
[materialscloud:2018.0023] Last version: 10 December 2018
This entry provides the snapshots of liquid water generated with ab initio molecular dynamics using rVV10 density functional at room temperature. Nuclear quantum effects are taken into account through path-integral molecular dynamics simulations.
Ab initio thermodynamics of liquid and solid water: supplemental materials
[materialscloud:2018.0020] Last version: 04 December 2018
Thermodynamic properties of liquid water as well as hexagonal (Ih) and cubic (Ic) ice are predicted based on density functional theory at the hybrid-functional level, rigorously taking into account quantum nuclear motion, anharmonic fluctuations and proton disorder. This is made possible by combining advanced free energy methods and state-of-the-art machine learning techniques. The ab initio description leads to structural properties in excellent agreement with experiments, and reliable estimates of the melting points of light and heavy water. We observe that nuclear quantum effects contribute a crucial 0.2 meV/H2O to the stability of ice Ih, making it more stable than ice Ic. Our computational approach is general and transferable, providing a comprehensive framework for quantitative predictions of ab initio thermodynamic properties using machine learning potentials as an intermediate step. In this set of supplemental materials, we have included the neural network potential for ...
Special quasi-random structures for the 6-component high entropy alloys
[materialscloud:2018.0019] Last version: 03 December 2018
We propose a general method to calculate the average misfit volumes of atoms in any random alloy via DFT calculations. The method is validated with an example of a 6-component equi-composition high entropy alloy. The special quasi-random structures (SQSs) used in our work are reported here.
Evaluating charge equilibration methods to generate electrostatic fields in nanoporous materials
[materialscloud:2018.0017] Last version: 29 November 2018
Charge equilibration (Qeq) methods can estimate the electrostatic potential of molecules and periodic frameworks by assigning point charges to each atom, using only a small fraction of the resources needed to compute density functional (DFT)-derived charges. This makes possible, for example, the computational screening of thousands of microporous structures to assess their performance for the adsorption of polar molecules. Recently, different variants of the original Qeq scheme were proposed to improve the quality of the computed point charges. One focus of this research was to improve the gas adsorption predictions in Metal Organic Frameworks (MOFs), for which many different structures are available. In this work, we review the evolution of the method from the original Qeq scheme, understanding the role of the different modifications on the final output. We evaluated the result of combining different protocols and set of parameters, by comparing the Qeq charges with high quality ...
Data-driven design and synthesis of metal-organic frameworks for wet flue gas CO2 capture
[materialscloud:2018.0016] Last version: 25 November 2018
The data and metadata of this record was submitted for the review phase of the associated manuscript only and not intended for publication. The data intended for public use will be made available in version v3 of this record under doi: 10.24435/materialscloud:2018.0016/v3.
Hidden Beneath the Surface: Origin of the Observed Enantioselective Adsorption on PdGa(111)
[materialscloud:2018.0018] Last version: 23 November 2018
We provide the input files to reproduce the data presented in the work: Hidden Beneath the Surface: Origin of the Observed Enantioselective Adsorption on PdGa(111) The files are subdivided in directories named after the figures/table of the manuscript A. V. Yakutovich, J. Hoja, D. Passerone, Alexandre Tkatchenko, C. A. Pignedoli J. Am. Chem. Soc., 140, 1401-1408 (2018) DOI: 10.1021/jacs.7b10980 In the work, we unravel the origin of the recently observed striking enantioselectivity of the PdGa(111) surface with respect to the adsorption of a small organic molecule, 9-ethynylphenanthrene, using first-principles calculations. It turns out that the key ingredient to understand the experimental evidence is the appropriate description of van der Waals interactions beyond the widely employed atomic pairwise approximation. A recently developed van der Waals-inclusive density functional method, which encompasses dielectric screening effects, reveals the origin of the experimentally ...
Mail-order metal-organic frameworks (MOFs): designing isoreticular MOF-5 analogues comprising commercially available organic molecules
[materialscloud:2018.0007] Last version: 14 November 2018
Metal–organic frameworks (MOFs), a class of porous materials, are of particular interest in gas storage and separation applications due largely to their high internal surface areas and tunable structures. MOF-5 is perhaps the archetypal MOF; in particular, many isoreticular analogues of MOF-5 have been synthesized, comprising alternative dicarboxylic acid ligands. In this contribution we introduce a new set of hypothesized MOF-5 analogues, constructed from commercially available organic molecules. We describe our automated procedure for hypothetical MOF design, comprising selection of appropriate ligands, construction of 3D structure models, and structure relaxation methods. 116 MOF-5 analogues were designed and characterized in terms of geometric properties and simulated methane uptake at conditions relevant to vehicular storage applications. A strength of the presented approach is that all of the hypothesized MOFs are designed to be synthesizable utilizing ligands purchasable online. Version 2 includes the structures in CIF format.
High-throughput computational screening of nanoporous adsorbents for CO 2 capture from natural gas
[materialscloud:2018.0005] Last version: 14 November 2018
With the growth of natural gas as an energy source, upgrading CO2-contaminated supplies has become increasingly important. Here we develop a single metric that captures how well an adsorbent performs the separation of CH4 and CO2, and we then use this metric to computationally screen tens of thousands of all-silica zeolites. We show that the most important predictors of separation performance are the CO2 heat of adsorption (Qst, CO2) and the CO2 saturation loading capacity. We find that a higher-performing material results when the absolute value of the CH4 heat of adsorption (Qst, CH4) is decreased independently of Qst, CO2, but a correlation that exists between Qst, CH4 and Qst, CO2 in all-silica zeolites leads to incongruity between the objectives of optimizing Qst, CO2 and minimizing Qst, CH4, rendering Qst, CH4 nonpredictive of separation performance. We also conduct a large-scale analysis of ideal adsorbed solution theory (IAST) by comparing results obtained using ...
The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials (Data Download)
[materialscloud:2017.0003] Last version: 10 November 2018
Project Abstract: For applications of metal-organic frameworks (MOFs) such as gas storage and separation, flexibility is often seen as a parameter that can tune material performance. In this work we aim to determine the optimal flexibility for the shape selective separation of similarly sized molecules (e.g., Xe/Kr mixtures). To obtain systematic insight into how the flexibility impacts this type of separation we develop a simple analytical model that predicts a material's Henry regime adsorption and selectivity as a function of flexibility. We elucidate the complex dependence of selectivity on a framework's intrinsic flexibility whereby performance is either improved or reduced with increasing flexibility, depending on the material's pore size characteristics. However, the selectivity of a material with the pore size and chemistry that already maximizes selectivity in the rigid approximation is continuously diminished with increasing flexibility, demonstrating that ...
A Standard Solid State Pseudopotentials (SSSP) library optimized for precision and efficiency (Version 1.1, data download)
[materialscloud:2018.0001] Last version: 08 November 2018
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 provenance of all data and calculations as stored by AiiDA.
In Silico Design of 2D and 3D Covalent Organic Frameworks for Methane Storage Applications
[materialscloud:2018.0003] Last version: 05 October 2018
Here we present 69,840 covalent organic frameworks (COFs) assembled in silico from a set of 666 distinct organic linkers into 2D-layered and 3D configurations. We investigate the feasibility of using these frameworks for methane storage by using grand-canonical Monte Carlo (GCMC) simulations to calculate their deliverable capacities (DCs). From these calculations, we predict that the best structure in the database is linker91_C_linker91_C_tbd, a structure composed of carbon-carbon bonded triazine linkers in the tbd topology. This structure has a predicted 65-bar DC of 216 v STP/v, greater than that of the best current methane storage material. We also predict other top performing materials, with 305 structures having DCs of over 190 v STP/v, and 34 of these having DCs of over 200 v STP/v. This archive entry contains the database of assembled COF structures (in CIF file format) together with all of their properties, which can be explored using interactive figures. Among the ...
Toward GW Calculations on Thousands of Atoms
[materialscloud:2018.0015] Last version: 28 September 2018
We provide the input files needed to reproduce the results of the article Toward GW Calculations on Thousands of Atoms J. Wilhelm, D. Golze, L. Talirz, J. Hutter, C. A. Pignedoli J. Phys. Chem. Lett. 9, 306–312 (2018) DOI:10.1021/acs.jpclett.7b02740 The GW approximation of many-body perturbation theory is an accurate method for computing electron addition and removal energies of molecules and solids. In a canonical implementation, however, its computational cost is in the system size N, which prohibits its application to many systems of interest. We present a full-frequency GW algorithm in a Gaussian-type basis, whose computational cost scales with N2 to N3. The implementation is optimized for massively parallel execution on state-of-the-art supercomputers and is suitable for nanostructures and molecules in the gas, liquid or condensed phase, using either pseudopotentials or all electrons. We validate the accuracy of the algorithm on the GW100 molecular test ...
The geometric blueprint of perovskites
[materialscloud:2018.0012] Last version: 03 September 2018
Perovskite minerals form an essential component of the Earth’s mantle, and synthetic crystals are ubiquitous in electronics, photonics, and energy technology. The extraordinary chemical diversity of these crystals raises the question of how many and which perovskites are yet to be discovered. Here we show that the “no-rattling” principle postulated by Goldschmidt in 1926, describing the geometric conditions under which a perovskite can form, is much more effective than previously thought and allows us to predict perovskites with a fidelity of 80%. By supplementing this principle with inferential statistics and internet data mining we establish that currently known perovskites are only the tip of the iceberg, and we enumerate 90,000 hitherto-unknown compounds awaiting to be studied. Our results suggest that geometric blueprints may enable the systematic screening of millions of compounds and offer untapped opportunities in structure prediction and materials design.
Machine learning meets volcano plots: Computational discovery of cross-coupling catalysts
[materialscloud:2018.0014] Last version: 01 August 2018
The application of modern machine learning to challenges in atomistic simulation is gaining attraction. We present new machine learning models that can predict the energy of the oxidative addition process between a transition metal complex and a substrate for C-C cross-coupling reaction. In turn, this quantity can be used as a descriptor to estimate the activity of homogeneous catalysts using molecular volcano plots. The versatility of this approach is illustrated for vast libraries of organometallic catalysts based on Pt, Pd, Ni, Cu, Ag, and Au combined with 91 ligands. Out-of-sample machine learning predictions were made on a total of 18,062 compounds leading to 557 catalyst candidates falling into the ideal thermodynamic window. This number was further refined by searching for candidates with an estimated price lower than 10 US$/mmol. The 37 catalyst finalists are dominated by palladium phosphine ligand combinations but also include earth abundant (Cu) transition metal with ...
Generating carbon schwarzites via zeolite-templating
[materialscloud:2018.0013] Last version: 31 July 2018
Zeolite-templated carbons (ZTCs) comprise a relatively recent material class synthesized via the chemical vapor deposition of a carbon-containing precursor on a zeolite template, followed by the removal of the template. We have developed a theoretical framework to generate a ZTC model from any given zeolite structure, which we show can successfully predict the structure of known ZTCs. We use our method to generate a library of ZTCs from all known zeolites, to establish criteria for which zeolites can produce experimentally accessible ZTCs, and to identify over 10 ZTCs that have never before been synthesized. We show that ZTCs partition space into two disjoint labyrinths that can be described by a pair of interpenetrating nets. Since such a pair of nets also describes a triply periodic minimal surface (TPMS), our results establish the relationship between ZTCs and schwarzites—carbon materials with negative Gaussian curvature that resemble TPMSs—linking the research topics and ...
Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems
[materialscloud:2018.0009] Last version: 19 May 2018
Here we present 1,000 structures each of a water monomer, water dimer, Zundel cation and bulk water used to train tensorial machine-learning models in Phys. Rev. Lett. 120, 036002 (2018). The archive entry contains files in extended-XYZ format including the structures and several tensorial properties: for the monomer, dimer and Zundel cation, the dipole moment, polarizability and first hyperpolarizability are included, and for bulk water the dipole moment, polarizability and dielectric tensor are given.
Mapping uncharted territory in ice from zeolite networks to ice structures
[materialscloud:2018.0010] Last version: 19 May 2018
We report a large-scale density-functional-theory study of the configuration space of water ice. We geometry optimise 74,963 ice structures, which are selected and constructed from over five million tetrahedral networks listed in the databases of Treacy and Deem, and the International Zeolite Association database. All prior knowledge of ice is set aside and we introduce generalised convex hulls to identify configurations stabilised by appropriate thermodynamic constraints. We thereby rediscover all known phases (I to XVII, i, 0 and the quartz phase) except the metastable ice IV. Crucially, we also find promising candidates for ices XVIII through LI. Using the sketch-map dimensionality-reduction algorithm we construct an a priori, navigable map of configuration space, which reproduces similarity relations between structures and highlights the novel candidates. By relating the known phases to the tractably small, yet structurally diverse set of synthesisable candidate structures, we ...
In Silico Design of Porous Polymer Networks: High Throughput Screening for Methane Storage Materials
[materialscloud:2018.0008] Last version: 15 May 2018
Porous polymer networks (PPNs) are a class of advanced porous materials that combine the advantages of cheap and stable polymers with the high surface areas and tunable chemistry of metal–organic frameworks. They are of particular interest for gas separation or storage applications, for instance, as methane adsorbents for a vehicular natural gas tank or other portable applications. PPNs are self-assembled from distinct building units; here, we utilize commercially available chemical fragments and two experimentally known synthetic routes to design in silico a large database of synthetically realistic PPN materials. All structures from our database of 18,000 materials have been relaxed with semiempirical electronic structure methods and characterized with Grand-canonical Monte Carlo simulations for methane uptake and deliverable (working) capacity. A number of novel structure–property relationships that govern methane storage performance were identified. The relationships are ...
Improving the Mechanical Stability of Metal-Organic Frameworks Using Chemical Caryatids
[materialscloud:2018.0004] Last version: 17 April 2018
Metal-organic frameworks (MOFs) have emerged as versatile materials for applications ranging from gas separation and storage, catalysis, and sensing. The attractive feature of MOFs is that by changing the ligand and/or metal, they can be chemically tuned to perform optimally for a given application. In most, if not all, of these applications one also needs a material that has a sufficient mechanical stability, but our understanding of how changes in the chemical structure influence mechanical stability is limited. In this work, we rationalize how the mechanical properties of MOFs are related to framework bonding topology and ligand structure. We illustrate that the functional groups on the organic ligands can either enhance the mechanical stability through formation of a secondary network of non-bonded interactions, or soften the material by destabilizing the bonded network of a MOF. In addition, we show that synergistic effect of the bonding network of the material and the ...
Adatom-Induced Local Melting
[materialscloud:2018.0002] Last version: 11 February 2018
We introduce and discuss the phenomenon of adatom-induced surface local melting, using extensive first-principles molecular dynamics simulations of Al(100) taken as a paradigmatic case of a non-premelting surface that nevertheless displays facile adatom diffusion with single and multiple exchange pathways. Here, a single adatom deposited on the surface is sufficient to nucleate a localized and diffusing liquid-like region that remains confined to the surface layer, but with an area that increases with temperature; in the absence of the adatom, the surface instead remains crystalline until reaching the bulk melting temperature.
Isobaric-Isothermal Monte Carlo Simulations of Bulk Liquid Water from MP2 and RPA Theory (MC Trajectories Data Download)
[materialscloud:2017.0007] Last version: 28 November 2017
Methods based on the second order Møller–Plesset perturbation theory (MP2) and the Random Phase Approximation (RPA) have emerged as practicable and reliable approaches to improve the accuracy of density functional approximations for first principle atomistic simulations. Such approaches are in fact capable to account ab-initio for non-local dynamical electron correlation effects, which play a fundamental role, for example, in the description of non-bonded interactions. To assess the performance of MP2 and RPA for real applications, isobaric-isothermal Monte Carlo simulations have been performed to study the structural properties of bulk liquid water under ambient conditions. The choice of bulk liquid water as benchmark system is motivated by the complicated nature of the intermolecular interactions, where repulsion, polarization, hydrogen bonding and van der Waals forces play an important role and are particularly difficult to reproduce accurately in atomistic models. The results ...
Gaussian Approximation Potentials for iron from extended first-principles database (Data Download)
[materialscloud:2017.0006] Last version: 06 November 2017
Interatomic potentials are often necessary to describe complex realistic systems that would be too costly to study from first-principles. Commonly, interatomic potentials are designed using functional forms driven by physical intuition and fitted to experimental or computational data. The moderate flexibility of these functional forms limits their ability to be systematically improved by increasing the fitting datasets; on the other hand, their qualitative description of the essential physical interactions ensures a modicum degree of transferability. Recently, a novel trend has emerged where potential-energy surfaces are represented by neural networks fitted on large numbers of first-principles calculations, thus maximizing flexibility but requiring extensive datasets to ensure transferability. Gaussian Approximation Potentials in particular are a novel class of potentials based on non-linear, non-parametric Gaussian-process regression. Here we generate a Gaussian Approximation ...
Accurate Characterization of the Pore Volume in Microporous Crystalline Materials (Data Download)
[materialscloud:2017.0005] Last version: 18 May 2017
Project Abstract: Pore volume is one of the main properties for the characterization of microporous crystals. It is experimentally measurable and it can also be obtained from the refined unit cell by a number of computational techniques. In this work we assess the accuracy and the discrepancies between the different computational methods which are commonly used for this purpose, i.e, geometric, helium and probe center pore volume, by studying a database of more than 5000 frameworks. We developed a new technique to fully characterize the internal void of a microporous material and to compute the probe accessible and occupiable pore volume. We show that unlike the other definitions of pore volume, the occupiable pore volume can be directly related to the experimentally measured pore volumes from nitrogen isotherms.
Predicting Product Distribution of Propene Dimerization in Nanoporous Materials (Data Download)
[materialscloud:2017.0004] Last version: 05 May 2017
Project abstract: In this work, a theoretical framework is developed to explain and predict changes in the product distribution of the propene dimerization reaction, which yields a mixture of C6 olefin isomers, resulting from the use of different porous materials as catalysts. The MOF-74 class of materials has shown promise in catalyzing the dimerization of propene with high selectivity for valuable linear olefin products. We show that experimentally observed changes in the product distribution can be explained in terms of the contribution of the pores to the free energy of formation, which are directly computed using molecular simulation. Our model is used to screen a library of 118 existing and hypothetical MOF and zeolite structures to study how product distribution can be tuned by changing pore size, shape, and composition of porous materials. Using these molecular descriptors, catalyst properties are identified that increase the selective reaction of linear olefin ...
Barcodes for nanoporous materials
[materialscloud:2017.0001] Last version: 14 March 2017
In most applications of nanoporous materials the pore structure is as important as the chemical composition as a determinant of performance. For example, one can alter performance in applications like carbon capture or methane storage by orders of magnitude by only modifying the pore structure. For these applications it is therefore important to identify the optimal pore geometry and use this information to find similar materials. However, the mathematical language and tools to identify materials with similar pore structures, but different composition, has been lacking. Recently, we developed a pore recognition approach to quantify similarity of pore structures using topological data analysis. Barcodes generated with using this approach allow us to identify materials with similar pore geometries, and to screen for materials that are similar to given top-performing structures. This database has barcodes for zeolites, metal organic frameworks, and zeolitic imidazolate frameworks.