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At least 73 records · Page 4

Relativistic and Correlation Effects in CuH, AgH and AuH: Comparison of Various Relativistic Methods

The effects of relativity on the bond lengths, dissociation energies, and harmonic vibrational frequencies of the 1Epsilon(+) electronic ground states of the group IB hydrides CuH, AgH and AuH have been evaluated with a variety of ab initio methods. These properties were investigated with moderately-sized basis sets at the self-consistent field Hartree Fock (SCF HF) level and with second-order Moller-Plesset (MP2) perturbation theory for electron correlation. Comparisons were made between all-electron results using the nonrelativistic Hamiltonian, perturbation theory (PT) at first-order with only the one-electron non-fine structure terms of the Breit-Pauli Hamiltonian, the spin-free Douglas-Kroll (DK) transformed Dirac Hamiltonian and the untransformed Dirac Hamiltonian, and results using two sets of relativistic effective core potentials (RECPs). The expected trends of bond length decrease, dissociation energy increase and harmonic frequency increase with both relativity and correlation are found. Both sets of RECPs are shown to give good results, if accompanied by a reasonable basis set. The DK method is demonstrated to be an inexpensive, reliable approximation to the DHF method.

Collins, Charlene L.↗

Ab initio studies of the double–Gamow-Teller transition and its correlation with neutrinoless double- β decay

Here, we use chiral interactions and several ab initio methods to compute the nuclear matrix elements (NMEs) for ground-state-to-ground-state double Gamow-Teller transitions in a range of isotopes and explore the correlation of these NMEs with those for neutrinoless double beta decay produced by the exchange of a light Majorana neutrino. When all the NMEs of both isospin-conserving and isospin-changing transitions from the ab initio calculations are considered, the correlation is strong. For the experimentally relevant isospin-changing transitions by themselves, however, the correlation is weaker and may not be helpful for reducing the uncertainty in the NMEs for neutrinoless double beta decay.

20 ≤ A ≤ 38↗

An Ab Initio Multiple Cloning Method for Non-Adiabatic Excited-State Molecular Dynamics in NWChem

The recently developed ab-initio multiple cloning (AIMC) approach based on the multicongurational Ehrenfest (MCE) method provides a powerful and accurate way of describing the excited-state dynamics of molecular systems. The AIMC method is a controlled approximation to non-adiabatic dynamics with a particular strength in the proper description of decoherence effects due to branching of vibrational wavepackets at a level crossing. In this work, we report a new implementation of the AIMC algorithm in the open source NWChem computational chemistry program. The framework combines linear-response time-dependent density functional theory with Ehrenfest mean-eld theory to determine the equations of motion for classical trajectories. The multi-dimensional wave function is decomposed into a superposition of Gaussian coherent states guided by Ehrenfest trajectories (i.e., MCE approach), which can clone with fully quantum mechanical amplitudes and phases. By using an efficient time-derivative based non-adiabatic coupling approach within the AIMC method, all observable are calculated on-the-y in the non-adiabatic molecular dynamics process. As a representative example, we apply our implementation to study the ultrafast photoinduced electronic and vibrational energy transfer in a pyridine molecule. The effects of the cloning procedure on electronic and vibrational coherence, relaxation and unidirectional energy transfer are discussed. This new AIMC implementation provides a high-level non-adiabatic molecular dynamics framework for simulating photoexcited dynamics in complex molecular systems and experimentally relevant ultrafast spectroscopic probes, such as nonlinear coherent optical and X-ray signals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Recent Developments in DFTB+, a Software Package for Efficient Atomistic Quantum Mechanical Simulations

DFTB+ is a flexible, open-source software package developed by its community, designed for fast and efficient atomistic quantum mechanical simulations. It employs various methods that approximate density functional theory (DFT), such as density functional-based tight binding (DFTB) and the extended tight binding (xTB) approach allowing simulations of large systems over extended time scales with reasonable accuracy, while being significantly faster than traditional ab initio methods. In recent years, several new extensions of the DFTB method have been developed and implemented in the DFTB+ program package in order to improve the accuracy and generality of the available simulation results. In this paper, we review those enhancements, show several use case examples and discuss the strengths and limitations of its features.

36 MATERIALS SCIENCE↗

The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems

The effective fragment molecular orbital (EFMO) method has been developed to predict the total energy of a very large molecular system accurately (with respect to the underlying quantum mechanical method) and efficiently by taking advantage of the locality of strong chemical interactions and employing a two-level hierarchical parallelism. The accuracy of the EFMO method is partly attributed to the accurate and robust intermolecular interaction prediction between distant fragments, in particular, the many-body polarization and dispersion effects, which require the generation of static and dynamic polarizability tensors by solving the coupled perturbed Hartree–Fock (CPHF) and time-dependent HF (TDHF) equations, respectively. Solving the CPHF and TDHF equations is the main EFMO computational bottleneck due to the inefficient (serial) and I/O-intensive implementation of the CPHF and TDHF solvers. In this work, the efficiency and scalability of the EFMO method are significantly improved with a new CPU memory-based implementation for solving the CPHF and TDHF equations that are parallelized by either message passing interface (MPI) or hybrid MPI/OpenMP. Here, the accuracy of the EFMO method is demonstrated for both covalently bonded systems and noncovalently bound molecular clusters by systematically examining the effects of basis sets and a key distance-related cutoff parameter, R cut . R cut determines whether a fragment pair (dimer) is treated by the chosen ab initio method or calculated using the effective fragment potential (EFP) method (separated dimers). Decreasing the value of Rcut increases the number of separated (EFP) dimers, thereby decreasing the computational effort. It is demonstrated that excellent accuracy (<1 kcal/mol error per fragment) can be achieved when using a sufficiently large basis set with diffuse functions coupled with a small R cut value. With the new parallel implementation, the total EFMO wall time is substantially reduced, especially with a high number of MPI ranks. Given a sufficient workload, nearly ideal strong scaling is achieved for the CPHF and TDHF parts of the calculation. For the first time, EFMO calculations with the inclusion of long-range polarization and dispersion interactions on a hydrated mesoporous silica nanoparticle with explicit water solvent molecules (more than 15k atoms) are achieved on a massively parallel supercomputer using nearly 1000 physical nodes. In addition, EFMO calculations on the carbinolamine formation step of an amine-catalyzed aldol reaction at the nanoscale with explicit solvent effects are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Throughput Screening of Li Solid-State Electrolytes With Bond Valence Methods and Graph Neural Networks

Li-based solid-state electrolyte (Li-SSE) materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. We present a high-throughput screening approach for Li-SSE materials using a combination of bond-valence methods and graph neural networks. We demonstrate the screening approach with a dataset containing tens of thousands of Li-containing compounds. Furthermore, we combine the machine-learning screening procedure with an isovalent substitution scheme to generate and screen additional Li SSE candidates beyond existing databases. Finally, we discuss relative importances of geometric and bond-valence quantities in the training of graph neural networks, providing insight for future modeling of ionic conductivity in Li-SSE materials.

Materials discovery↗

Screening of Li-Based Solid Electrolytes Using Bond-Valence Methods and Graph Neural Networks

Li-based solid-state electrolyte (Li-SSE) materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. We present a high-throughput screening approach for Li-SSE materials using a combination of bond-valence methods and graph neural networks. We demonstrate the screening approach with a dataset containing tens of thousands of Li-containing compounds. Furthermore, we combine the machine-learning screening procedure with an isovalent substitution scheme to generate and screen additional Li SSE candidates beyond existing databases. Finally, we discuss relative importances of geometric and bond-valence quantities in the training of graph neural networks, providing insight for future modeling of ionic conductivity in Li-SSE materials.

Materials discovery↗

Hyperfine and quadrupole interactions for Dy isotopes in DyPc 2 molecules

Nuclear spin levels play a vital role in understanding magnetization dynamics and implementation and control of quantum bits in lanthanide-based single-molecule magnets. We investigate the hyperfine and nuclear quadrupole interactions for 161 Dy and 163 Dy nuclei in anionic DyPc 2 (Pc=phthalocyanine) single-molecule magnets, using multiconfigurational ab initio methods (beyond density-functional theory) including spin–orbit interaction. The two isotopes of Dy are chosen because the others have zero nuclear spin. Both isotopes have the nuclear spin I =5/2, although the magnitude and sign of the nuclear magnetic moment differ from each other. The large energy gap between the electronic ground and first-excited Kramers doublets, allows us to map the microscopic hyperfine and quadrupole interaction Hamiltonian onto an effective Hamiltonian with an electronic pseudo-spin that corresponds to the ground Kramers doublet. Our ab initio calculations illustrate that the coupling between the nuclear spin and electronic orbital angular momentum contributes the most to the hyperfine interaction and that both the hyperfine and nuclear quadrupole interactions for 161 Dy and 163 Dy nuclei are much smaller than those for the 159 Tb nucleus in TbPc 2 single-molecule magnets. The calculated separations of the electronic-nuclear levels are comparable to experimental data reported for 163 DyPc 2 . We demonstrate that hyperfine interaction for the Dy Kramers ion leads to tunnel splitting (or quantum tunneling of magnetization) at zero field. This effect does not occur for TbPc 2 single-molecule magnets. The magnetic field values of the avoided level crossings for 161 DyPc 2 and 163 DyPc 2 are found to be noticeably different, which can be observed from the experiment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Charge-mediated cation deposition on metallic surfaces

This work reveals the general mechanisms of Li + cation partial reduction and further deposition under specific electrolyte conditions, and in the proximity of an electrified metal surface. The factors affecting the ion complexation and transport and resultant adsorbed structures are identified for various external electric fields and for several applied voltages. Using ab initio methods, we investigate the relation between solvent–salt structures and dynamics, cation reductive stability, and the existing electric field between electrodes, or under the applied potential if the system is designed as an electrochemical cell. In absence of an applied field, it is found that not only cation but also non-solvated salt deposition on a metallic surface is an endothermic process. However, localized surface polarization orbitals created by an external electric field affect both the thermodynamics and kinetics of the adsorption, leading to a drastic change on the energetic profile; ab initio molecular dynamics simulations describe in detail the underlying mechanisms. Externally applied bias to an electrochemical cell also changes the deposition dynamics: by examining various solvent/salt combinations, we unravel the cation deposition mechanisms at both low and moderately high voltages, determining the relative time scale of each separate process. In this work, different polyhedra formed by the metal cation and its surrounding oxygen atoms appear to be the key indicator driving deposition dynamics at different voltages. Our findings disclose the importance of selecting appropriate voltage windows for stable and uniform growth of metal anode layers, showing the mechanisms leading to impurity formation and non-uniform cation deposition, as well as the role of charged interfacial phenomena in designing stable electrode–electrolyte interfaces.

25 ENERGY STORAGE↗

De novo atomic protein structure modeling for cryoEM density maps using 3D transformer and HMM

Accurately building 3D atomic structures from cryo-EM density maps is a crucial step in cryo-EM-based protein structure determination. Converting density maps into 3D atomic structures for proteins lacking accurate homologous or predicted structures as templates remains a significant challenge. Here, we introduce Cryo2Struct, a fully automated de novo cryo-EM structure modeling method. Cryo2Struct utilizes a 3D transformer to identify atoms and amino acid types in cryo-EM density maps, followed by an innovative Hidden Markov Model (HMM) to connect predicted atoms and build protein backbone structures. Cryo2Struct produces substantially more accurate and complete protein structural models than the widely used ab initio method Phenix. Additionally, its performance in building atomic structural models is robust against changes in the resolution of density maps and the size of protein structures.

59 BASIC BIOLOGICAL SCIENCES↗

Non-orthogonal configuration interaction with single substitutions for the calculation of core-excited states

In this paper, we present the non-orthogonal configuration interaction singles (NOCIS) method for calculating core-excited states of closed-shell molecules. NOCIS is a black-box variant of NOCI, which uses A different core-ionized determinants for a molecule with A atoms of a given element to form single substitutions. NOCIS is a variational, spin-pure, size-consistent ab initio method that dramatically improves on standard CIS by capturing essential orbital relaxation effects, in addition to essential configuration interaction. We apply it to the calculation of core-excitations for several smaller molecules and demonstrate that it performs competitively with other Hartree-Fock and DFT-based methods. We also benchmark it in several basis sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ab initio prediction of FeCr sigma (001)/FCC Fe(111) interfacial energy: Effect of interfacial doping of C, B, and N

Interfacial energy plays a crucial role for high-temperature material systems in determining their microstructure evolution and mechanical properties. Optimizing the interfacial energy through doping can improve the stability, performance, and overall functionality of these materials. Here, the present study delivers theoretical investigation on the sigma FeCr (001)//FCC Fe (111) interfacial energy using ab initio methods, focusing on the implications of interfacial doping with important interstitial elements carbon (C), boron (B), and nitrogen (N). The calculated interfacial energy without doping is 0.183J/m 2 . Upon doping, notable reductions in interfacial energy were observed. Doping with B decreased the interfacial energy to 0.046J/m 2 , with single C doping to 0.126J/m 2 , with two C doping to 0.098J/m 2 , and with a single N doping to 0.071J/m 2 . These findings not only shed light on the atomistic origin for the effect of stabilizing the microstructure of stainless steel at elevated temperatures by interstitial doping, but also present a systematic, thorough ab initio approach to predict interfacial doping properties and guide alloy design to enhance the performance and stability.

FeCr sigma phase↗

Ab initio single-neutron spectroscopic overlaps in lithium isotopes

We calculate single-neutron spectroscopic overlaps for lithium isotopes in the framework of the ab initio symmetry-adapted no-core shell model. We report the associated neutron-nucleus asymptotic normalization coefficients (ANCs) and spectroscopic factors (SFs) that are important ingredients in many reaction cross-section calculations. While spectroscopic factors have been traditionally extracted from experimental cross sections, their sensitivity on the type of reactions, the energy, and the underlying models point to the need for determining SFs from first-principle structure considerations. As illustrative examples, we present 6 Li + n, 7 Li ⁢+ n, and 8 Li ⁢+ n, and we show that the results are in a good agreement with those of other ab initio methods, where available, including the quantum Monte Carlo approach. Here, we compare ANCs and SFs to available experimentally deduced values, with a view toward expanding this study to heavier nuclei and to extracting intercluster effective interactions for input into analyses of existing and future experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Robust training of machine learning interatomic potentials with dimensionality reduction and stratified sampling

Abstract Machine learning interatomic potentials (MLIPs) enable accurate simulations of materials at scales beyond that accessible by ab initio methods and play an increasingly important role in the study and design of materials. However, MLIPs are only as accurate and robust as the data on which they are trained. Here, we present DImensionality-Reduced Encoded Clusters with sTratified (DIRECT) sampling as an approach to select a robust training set of structures from a large and complex configuration space. By applying DIRECT sampling on the Materials Project relaxation trajectories dataset with over one million structures and 89 elements, we develop an improved materials 3-body graph network (M3GNet) universal potential that extrapolates more reliably to unseen structures. We further show that molecular dynamics (MD) simulations with the M3GNet universal potential can be used instead of expensive ab initio MD to rapidly create a large configuration space for target systems. We combined this scheme with DIRECT sampling to develop a reliable moment tensor potential for titanium hydrides without the need for iterative augmentation of training structures. This work paves the way for robust high-throughput development of MLIPs across any compositional complexity.

Qi, Ji (ORCID:0000000158089931)↗

The behavior of methane–water mixtures under elevated pressures from simulations using many-body potentials

Non-polarizable empirical potentials have been proven to be incapable of capturing the mixing of methane–water mixtures at elevated pressures. Although density functional theory-based ab initio simulations may circumvent this discrepancy, they are limited in terms of the relevant time and length scales associated with mixing phenomena. Here, we show that the many-body MB-nrg potential, designed to reproduce methane–water interactions with coupled cluster accuracy, successfully captures this phenomenon up to 3 GPa and 500 K with varying methane concentrations. Two-phase simulations and long time scales that are required to fully capture the mixing, affordable due to the speed and accuracy of the MBX software, are assessed. Constructing the methane–water equation of state across the phase diagram shows that the stable mixtures are denser than the sum of their parts at a given pressure and temperature. As a result, we find that many-body polarization plays a central role, enhancing the induced dipole moments of methane by 0.20 D during mixing under pressure. Overall, the mixed system adopts a denser state, which involves a significant enthalpic driving force as elucidated by a systematic many-body energy decomposition analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate Free Energies for Complex Condensed-Phase Reactions Using an Artificial Neural Network Corrected DFTB/MM Methodology

Semiempirical methods like density functional tight-binding (DFTB) allow extensive phase space sampling, making it possible to generate free energy surfaces of complex reactions in condensed-phase environments. Such a high efficiency often comes at the cost of reduced accuracy, which may be improved by developing a specific reaction parametrization (SRP) for the particular molecular system. Thiol–disulfide exchange is a nucleophilic substitution reaction that occurs in a large class of proteins. Its proper description requires a high-level ab initio method, while DFT-GAA and hybrid functionals were shown to be inadequate, and so is DFTB due to its DFT-GGA descent. We develop an SRP for thiol–disulfide exchange based on an artificial neural network (ANN) implementation in the DFTB+ software and compare its performance to that of a standard SRP approach applied to DFTB. Furthermore, as an application, we use both new DFTB-SRP as components of a QM/MM scheme to investigate thiol–disulfide exchange in two molecular complexes: a solvated model system and a blood protein. Demonstrating the strengths of the methodology, highly accurate free energy surfaces are generated at a low cost, as the augmentation of DFTB with an ANN only adds a small computational overhead.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Laying the Foundation for a Predictive Theory of Electroweak Nuclear Phenomena

Reliable model-independent predictions of nuclear processes such as beta-decay and neutrinonucleus scattering are important for many fundamental science and mission-related investigations; For example, accurate descriptions of as beta-decay are required for modeling the anti-neutrino spectrum of nuclear reactor, whether for trying to detect new physics such as sterile neutrinos, or remotely identifying the purpose of that reactor. For these activities, we need accurate calculations, as well as careful and thorough analyses of theoretical error and uncertainty in the underlying models and the many-body methods and codes used in solving that model. Unfortunately, modern theoretical calculations of these processes are inadequate for this task. At the heart of this inadequacy is the interaction between nucleons and other particles known as nuclear currents. Historically, descriptions of nuclear currents took into account only the simplest of particle interactions. Recently, the development of an effective field theory known as chiral EFT has been used to derive large corrections to these particle interactions. However, the complex nature of these corrections inhibited their use in ab initio methods of predicting nuclear processes. We developed a novel method to address these complexities and applied it in a series of benchmark and demonstrative calculations using state-of-the-art quantum few-nucleon solvers. Specifically, we studied the role of two-nucleon currents in electroweak processes using light nuclei (i.e., nuclei containing fewer than five nucleons) as a workbench to compute these processes and quantify their uncertainties using Bayesian extensions of the EFT.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Methods to accelerate high-throughput screening of atomic qubit candidates in van der Waals materials

The discovery of atom-like spin emitters associated with defects in two-dimensional (2D) wide-bandgap (WBG) semiconductors presents new opportunities for highly tunable and versatile qubits. So far, the study of such spin emitters has focused on defects in hexagonal boron nitride (hBN). However, hBN necessarily contains a high density of nuclear spins, which are expected to create a strong incoherent spin-bath that leads to poor coherence properties of spins hosted in the material. Therefore, identification of new qubit candidates in other 2DWBG materials is necessary. Given the time demands of ab initio methods, new approaches for rapid screening and calculations of identifying properties of suitable atom-like qubits are required. In this work, we present two new methods for rapid estimation of the zero-phonon line (ZPL), a key property of atomic qubits in WBG materials. First, the ZPL is calculated by exploiting Janak’s theorem. For finite changes in occupation, we provide the leading-order estimate of the correction to the ZPL obtained using Janak’s theorem, which is more rapid than the standard method (ΔSCF). Next, we demonstrate an approach to converging excited states that is faster for systems with small strain than the standard approach used in the ΔSCF method. We illustrate these methods using the case of the singly negatively charged calcium vacancy in SiS2, which we are the first to propose as a qubit candidate. This work has the potential to assist in accelerating the high-throughput search for quantum defects in materials, with applications in quantum sensing and quantum computing.

Kuate Defo, Rodrick (ORCID:0000000242788196)↗