Data files for ab initio calculations of the lattice parameter and elastic stiffness coefficients of bcc Fe with solutes
Not Available
36 MATERIALS SCIENCE↗
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Results for “ab initio data”
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Data for "Integrated ab initio modelling of atomic order and magnetic anisotropy for rare-earth-free magnet design: effects of alloying additions in L1 0 FeNi."
We describe an integrated modelling approach to accelerate the search for novel, single-phase, multicomponent materials with high magnetocrystalline anisotropy (MCA). For a given system we predict the nature of atomic ordering, its dependence on the magnetic state, and then proceed to describe the consequent MCA, magnetisation, and magnetic critical temperature (Curie temperature). Crucially, within our modelling framework, the same ab initio description of a material’s electronic structure determines all aspects. We demonstrate this holistic method by studying the effects of alloying additions in FeNi, examining systems with the general stoichiometries Fe 4 Ni 3 X and Fe 3 Ni 4 X, for additives including X = Pt, Pd, Al, and Co. The atomic ordering behaviour predicted on adding these elements, fundamental for determining a material’s MCA, is rich and varied. Equiatomic FeNi has been reported to require ferromagnetic order to establish the tetragonal L1 0 order suited for significant MCA. Our results show that when alloying additions are included in this material, annealing in an applied magnetic field and/or below a material’s Curie temperature may also promote tetragonal order, along with an appreciable effect on the predicted hard magnetic properties.
36 MATERIALS SCIENCE↗
Development of Multicomponent EAM Potential for Ni-Based Superalloy
We initiated the development of multi-component EAM potentials for Aluminides and Carbides, key phases in Ni-based Superalloys. The goal is to utilize the MD simulation to understand the deformation dynamics that contribute to the formation of voids and creep initiation. For this purpose, we constructed the raw data from ab-initio (molecular dynamics) MD simulations fed into the potential development code and used Nickel as the base metal with the addition of a number of various elements including Aluminum, Chromium, Tungsten. We then developed the EAM potentials for the aluminide and carbide phases using the force-fitting code MEAMfit. Our generated potential reproduces the fundamental properties of the Ni3Al and Mo23C6 phases. We verified further the EAM potential through the thermal stability test at different temperatures and by reproducing the elastic constants consistent with the experimental values.
36 MATERIALS SCIENCE↗
Application of an ab initio S matrix to data analysis of transfer reactions to the continuum populating Be 11
Recently, the bound and continuum spectrum of 11 Be has been calculated within the ab initio no-core shell model with continuum (NCSMC) method, with the parity inversion in the ground state successfully reproduced. Here, the continuum spectrum obtained is in agreement with known experimental levels. The S matrix contained in the NCSMC continuum wave functions of the n + 10 Be system is used in this work for the first time in a transfer-to-the-continuum (TC) reaction calculation. The TC approach is applied to study the excitation energy spectrum of 11 Be measured in the 9 Be( 18 O, 16 O) 11 Be reaction at 84 MeV. Previously known levels are confirmed and theoretical and experimental evidence for a 9/2 + state at E x = 5.8 MeV is given, whose configuration is thought to be 10 Be(2 + )+n( d 5/2 ).
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
BEAST DB: Grand-Canonical Database of Electrocatalyst Properties
We present BEAST DB, an open-source database comprised of ab initio electrochemical data computed using grand-canonical density functional theory in implicit solvent at consistent calculation parameters. The database contains over 20,000 surface calculations and covers a broad set of heterogeneous catalyst materials and electrochemical reactions. Calculations were performed at self-consistent fixed potential as well as constant charge to facilitate comparisons to the computational hydrogen electrode. This article presents common use cases of the database to rationalize trends in catalyst activity, screen catalyst material spaces, understand elementary mechanistic steps, analyze the electronic structure, and train machine learning models to predict higher fidelity properties. Users can interact graphically with the database by querying for individual calculations to gain a granular understanding of reaction steps or by querying for an entire reaction pathway on a given material using an interactive reaction pathway tool. BEAST DB will be periodically updated, with planned future updates to include advanced electronic structure data, surface speciation studies, and greater reaction coverage.
database↗
Quasi-Classical Trajectory Calculation of Rate Constants Using an Ab Initio Trained Machine Learning Model (aML-MD) with Multifidelity Data
Machine learning (ML) provides a great opportunity for the construction of models with improved accuracy in classical molecular dynamics (MD). However, the accuracy of a ML trained model is limited by the quality and quantity of the training data. Generating large sets of accurate ab initio training data can require significant computational resources. Furthermore, inconsistent or incompatible data with different accuracies obtained using different methods may lead to biased or unreliable ML models that do not accurately represent the underlying physics. Recently, transfer learning showed its potential for avoiding these problems as well as for improving the accuracy, efficiency, and generalization of ML models using multifidelity data. In this work, ab initio trained ML-based MD (aML-MD) models are developed through transfer learning using DFT and multireference data from multiple sources with varying accuracy within the Deep Potential MD framework. Further, the accuracy of the force field is demonstrated by calculating rate constants for the H + HO 2 → H 2 + 3 O 2 reaction using quasi-classical trajectories. We show that the aML-MD model with transfer learning can accurately predict the rate constants while reducing the computational cost by more than five times compared to the use of more expensive quantum chemistry training data sets. Hence, the aML-MD model with transfer learning shows great potential in using multifidelity data to reduce the computational cost involved in generating the training set for these potentials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Mechanical and optical response of [100] lithium fluoride to multi-megabar dynamic pressures
An understanding of the mechanical and optical properties of lithium fluoride (LiF) is essential to its use as a transparent tamper and window for dynamic materials experiments. In order to improve models for this material, we applied iterative Lagrangian analysis to ten independent sets of data from magnetically driven planar shockless compression experiments on single crystal [100] LiF to pressures as high as 350 GPa. We found that the compression response disagreed with a prevalent tabular equation of state for LiF that is commonly used to interpret shockless compression experiments. We also present complementary data from ab initio calculations performed using the diffusion quantum Monte Carlo method. The agreement between these two data sets lends confidence to our interpretation. In order to aid in future experimental analysis, we have modified the tabular equation of state to match the new data. We have also extended knowledge of the optical properties of LiF via shock-compression and shockless compression experiments, refining the transmissibility limit, measuring the refractive index to ~300 GPa, and confirming the nonlinear dependence of the refractive index on density. Lastly, we present a new model for the refractive index of LiF that includes temperature dependence and describe a procedure for correcting apparent velocity to true velocity for dynamic compression experiments.
36 MATERIALS SCIENCE↗
Simple and efficient algorithms for training machine learning potentials to force data
Machine learning models, trained on data from ab initio quantum simulations, are yielding molecular dynamics potentials with unprecedented accuracy. One limiting factor is the quantity of available training data, which can be expensive to obtain. A quantum simulation often provides all atomic forces, in addition to the total energy of the system. These forces provide much more information than the energy alone. It may appear that training a model to this large quantity of force data would introduce significant computational costs. Actually, training to all available force data should only be a few times more expensive than training to energies alone. Here, we present a new algorithm for efficient force training, and benchmark its accuracy by training to forces from real-world datasets for organic chemistry and bulk aluminum.
74 ATOMIC AND MOLECULAR PHYSICS↗
Fast event-based electron counting for small-molecule structure determination by MicroED
Electron counting helped realize the resolution revolution in single-particle cryoEM and is now accelerating the determination of MicroED structures. Its advantages are best demonstrated by new direct electron detectors capable of fast (kilohertz) event-based electron counting (EBEC). This strategy minimizes the inaccuracies introduced by coincidence loss (CL) and promises rapid determination of accurate structures. We used the Direct Electron Apollo camera to leverage EBEC technology for MicroED data collection. Given its ability to count single electrons, the Apollo collects high-quality MicroED data from organic small-molecule crystals illuminated with incident electron beam flux densities as low as 0.01–0.045 e − /Å 2 /s. Under even the lowest flux density (0.01 e − /Å 2 /s) condition, fast EBEC data produced ab initio structures of a salen ligand (268 Da) and biotin (244 Da). Each structure was determined from a 100° wedge of data collected from a single crystal in as few as 50 s, with a delivered fluence of only ∼0.5 e − /Å 2 . Fast EBEC data collected with a fluence of 2.25 or 3.33 e − /Å 2 also facilitated a 1.5 Å structure of thiostrepton (1665 Da). While refinement of these structures appeared unaffected by CL, a CL adjustment applied to EBEC data further improved the distribution of intensities measured from the salen ligand and biotin crystals. However, CL adjustment only marginally improved the refinement of their corresponding structures, signaling the already high counting accuracy of detectors with counting rates in the kilohertz range. Overall, by delivering low-dose structure-worthy data, fast EBEC collection strategies open new possibilities for high-throughput MicroED.
EBEC↗
Development of an interatomic potential for the W–Ta system
A physics-inspired, data-driven interatomic potential framework for multi-element system is presented. This potential is based on the generalization of the embedded atom method potential and systematically incorporates two-, three- and many-body effects. Different atomic environments are described by atom-centered Gaussian basis sets which provides sufficient flexibility to capture diverse atomic environments and allows for easy optimization of the free parameters. An interatomic potential model for the tungsten–tantalum (W–Ta) system is developed using this framework by training on data from ab initio density functional theory (DFT) calculations. The potential is thoroughly tested at various compositions by comparing bulk and defect properties from experimental and DFT data. It is shown that the potential predicts the elastic constants, defect properties, such as vacancy and interstitial formation energies, core structures of dislocations, and melting points for both pure and tantalum and tungsten with an accuracy comparable to other single element machine learning based potentials. In conclusion, the potential model is used to investigate the formation energies of ordered alloys and vacancy formation energies for chemically random W–Ta alloys.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Ab Initio and Monte Carlo Approaches for the Magnetocaloric Effect in BaMnO{sub 3} Oxide Perovskite
The self-consistent ab initio calculations, based on density functional theory approach (DFT) and using full potential linearised augmented plane wave (FLAPW) method, have been used to investigate both electronic and magnetic properties of the BaMnO{sub 3} perovskite. Spin-polarised calculations, including the spin-orbit interaction, are used to determine the energy of the ferromagnetic (FM) and antiferromagnetic (AFM) states of BaMnO{sub 3} perovskite. Obtained data from ab initio calculations are used as input for the Monte Carlo simulations to compute other magnetic parameters. Magnetisation, specific heat and magnetic entropy change have been given using the Monte Carlo simulations. The adiabatic temperature change, transition temperature and relative cooling power have been established.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
The first potential energy surfaces for the C{sub 6}H{sup −}–H{sub 2} and C{sub 6}H{sup −}–He collisional systems and their corresponding inelastic cross sections
Molecular anions have recently been detected in the interstellar and circumstellar media. Accurate modeling of their abundance requires calculations of collisional data with the most abundant species that are usually He atoms and H{sub 2} molecules. In this paper, we focus on the collisional excitation of the first observed molecular anion, C{sub 6}H{sup −}, by He and H{sub 2}. Theoretical calculations of collisional cross sections rely generally on ab initio interaction potential energy surfaces (PESs). Hence, we present here the first PESs for the C{sub 6}H{sup −}–H{sub 2} and C{sub 6}H{sup −}–He van der Waals systems. The ab initio energy data for the surfaces were computed at the explicitly correlated coupled cluster with single, double, and scaled perturbative triple excitations level of theory. The method of interpolating moving least squares was used to construct 4D and 2D analytical PESs from these data. Both surfaces are characterized by deep wells and large anisotropies. Analytical models of the PESs were used in scattering calculations to obtain cross sections for low-lying rotational transitions. As could have been anticipated, important differences exist between the He and H{sub 2} cross sections. Conversely, no significant differences exist between the collisions of C{sub 6}H{sup −} with the two species of H{sub 2} (para- and ortho-H{sub 2}). We expect that these new data will help in accurately determining the abundance of the C{sub 6}H{sup −} anions in space.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Communication: Improved ab initio molecular dynamics by minimally biasing with experimental data
Accounting for electrons and nuclei simultaneously is a powerful capability of ab initio molecular dynamics (AIMD). However, AIMD is often unable to accurately reproduce properties of systems such as water due to inaccuracies in the underlying electronic density functionals. This shortcoming is often addressed by added empirical corrections and/or increasing the simulation temperature. We present here a maximum-entropy approach to directly incorporate limited experimental data via a minimal bias. Biased AIMD simulations of water and an excess proton in water are shown to give significantly improved properties both for observables which were biased to match experimental data and for unbiased observables. Here, this approach also yields new physical insight into inaccuracies in the underlying density functional theory as utilized in the unbiased AIMD.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Gas–Phase Synthesis of 3–Vinylcyclopropene via the Crossed Beam Reaction of the Methylidyne Radical (CH; X 2 Π) with 1,3–Butadiene (CH 2 CHCHCH 2 ; X 1 Ag)
The crossed molecular beam reactions of the methylidyne radical (CH; X 2 Π) with 1,3-butadiene (CH 2 CHCHCH 2 ; X 1 Ag) along with their (partially) deuterated counterparts were performed at collision energies of 20.8 kJ mol -1 under single collision conditions. Combining our laboratory data with ab initio calculations, we reveal that the methylidyne radical may add barrierlessly to the terminal carbon atom and/or carbon-carbon double bond of 1,3-butadiene, leading to doublet C 5 H 7 intermediates with life times longer than the rotation periods. Furthermore, these collision complexes undergo non-statistical unimolecular decomposition through hydrogen atom emission yielding the cyclic cis- and trans-3-vinyl-cyclopropene products with reaction exoergicities of 119±42 kJ mol -1 . Since this reaction is barrierless, exoergic, and all transition states are located below the energy of the separated reactants, these cyclic C 5 H 6 products are predicted to be accessed even in low-temperature environments, such as in hydrocarbon-rich atmospheres of planets and cold molecular clouds such as TMC-1.
3-vinylcyclopropene↗
First Full Structural Characterization of Chloro Formamidinium Salts
While the synthesis of chloro formamidinium chloride has been known for over one century, no solid‐state structure of a chlorine‐substituted formamidinium compound has been reported up to now. Herein, we describe syntheses, solid‐state structures, and vibrational properties of four chloro formamidinium compounds, namely [ClC(NH 2 ) 2 ]Cl ( 1 ), [ClC(NH 2 ) 2 ](AuCl 4 ) ( 2 ), [ClC(NH 2 ) 2 ] 2 (PdCl 4 ) ( 3 ), and [ClC(NH 2 ) 2 ] 2 (PtCl 6 ) ( 4 ), as determined by single‐crystal X‐ray diffraction (SCXRD). 1 and 3 crystallize in the monoclinic space group P 2 1 / c , 2 in the orthorhombic space group Pbcn , whereas 4 adopts the triclinic space group P 1 . By using a combination of high‐resolution time‐of‐flight neutron powder diffraction, state‐of‐the‐art DFT calculations as well as IR spectroscopy, the prior SCXRD result was fully confirmed and augmented by determining the hydrogen‐bonded molecular networks. First‐principles electronic‐structure calculations corroborate the ionic nature of these salts by showing very flat, molecular‐like bands next to the Fermi level, in addition to indirect bandgaps. This study underlines the upmost importance of complementing diffraction data by ab initio calculations, as theory‐derived anisotropic displacement parameters served as fixed numerical entries.
Möller, Andreas↗
Exploring structural transitions at grain boundaries in Nb using a generalized embedded atom interatomic potential
The advancement in experimental techniques, like the atom probe tomography and high resolution electron microscopy, is fueling interest in studying structural transformations of grain boundaries in metal and alloys to uncover correlations between mechanical properties and solute or impurity segregation to grain boundaries. Atomistic modeling is an important tool that can pinpoint the intricate dynamics of grain boundary phase transitions, but the lack of accurate interatomic potentials needed to simulate the complex dynamics of grain boundary structural transitions and identify different metastable phases has been the bottleneck. To this end, we use niobium as a model body centered cubic (BCC) metal and develop an interatomic potential to study grain boundary phase transitions. The potential for Nb is based on a generalization of the embedded atomic method potential and has sufficient flexibility to learn complex energy landscapes using a small set of training structures. We systematically test and validate the using data from ab initio density functional theory calculations and experiments. Using this potential, we calculate energies of multiple symmetric-tilt grain boundaries spanning a wide range of misorientation angles. Additionally, we explore different metastable structures of the Σ 27(552) [$1\overline{1}0$] grain boundary and use molecular dynamic simulations to study the coexistence of metastable phases and grain boundary transitions at finite temperature.
36 MATERIALS SCIENCE↗
Analysis of phase stability and chemical segregation in the Mo-V alloys using a generalized embedded atom method potential
A new interatomic potential for the Mo-V system is introduced to facilitate the study of phase stability and mechanical properties at lower temperatures. This potential is based on a generalization of the embedded atom method and includes contributions from embedding energy, explicit two- and three-body interactions and nonlocal many-body interaction terms. The parameters of the potential are optimized by using data from ab initio density functional theory (DFT) calculations. The potential is rigorously validated across a range of physical properties, such as elastic constants, equation of states, phonon dispersion curves, point defect properties and melting temperatures for different compositions. Even though our potential is trained on a small dataset, its accuracy is comparable to available machine learning potentials for Mo and V. Furthermore, our results show that an ordered B2 phase is stable at low temperatures in alloys containing 50% V, but the solid solution phase is stable above 800 K. However, such long-range ordering is not observed in V-rich or Mo-rich alloys. In addition, our results show that V segregates to dislocation cores and grain boundaries.
36 MATERIALS SCIENCE↗
Mechanisms and stability of Li dynamics in amorphous Li-Ti-P-S-based mixed ionic–electronic conductors: A machine learning molecular dynamics study
Mixed ionic–electronic conductors (MIECs) exhibit both high ionic and electronic conductivity to improve the battery performance. In this work, we investigate the mechanism and stability of transport channels in our recently developed MIEC material, amorphous Ti-doped lithium phosphorus sulfide (LPS), using molecular dynamics (MD) simulations with a 99% accurate machine-learning force field (MLFF) trained on ab initio MD data. The achieved MLFF helps efficient large-scale MD simulations on LPS with three Ti concentrations (10%, 20%, and 30%) and six temperatures (25°C to 225°C) to calculate ionic conductivity, activation energy, Li-ion transport mechanism, and configurational entropy. Results show that ionic conductivities and activation energies are consistent with our recent experimental values. Moreover, Li-ion transport occurs via free-volume diffusion facilitated by the formation of disordered Li-S polyhedra. The enhanced stability of transport channels at 10% and 20% Ti doping, compared to 0% and 30%, is observed by analyzing the vibrational and configurational entropy of these disordered Li-S polyhedra. Overall, this study highlights the utility of MLFF-based large-scale MD simulations in explaining the transport mechanism and the stability of Li-ion in Ti-doped LPS electrolyte with significant computational efficiency.
And configuration entropy↗