Converging High-Level Coupled-Cluster Energetics via Adaptive Selection of Excitation Manifolds Driven by Moment ExpansionsA novel approach to rapidly converging high-level coupled-cluster (CC) energetics in an automated fashion is proposed. The key idea is an adaptive selection of the excitation manifolds defining…Karthik Gururangan, Piotr Piecuch·Jun 16, 2023SaveLearn
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 MoleculesSupervised machine learning approaches have been increasingly used in accelerating electronic structure prediction as surrogates of first-principle computational methods, such as density functional…Haiyang Yu, Meng Liu, Youzhi Luo et al.·Jun 15, 2023SaveLearn
Water-assisted electron capture exceeds photorecombination in biological conditionsA decade ago, an electron-attachment process called interatomic Coulombic electron capture has been predicted to be possible through energy transfer to a nearby neighbor. It has been estimated to be…Axel Molle, Oleg Zatsarinny, Thomas Jagau et al.·Jun 15, 2023SaveLearn
Pressure-Induced Detour of Li+ Transport during Large-Scale Electroplating of Lithium in High-Energy Lithium Metal Pouch CellsExternally applied pressure impacts the performance of batteries particularly in those undergoing large volume changes, such as lithium metal batteries. In particular, the Li+ electroplating…Dianying Liu, Bingbin Wu, Yaobin Xu et al.·Jun 15, 2023SaveLearn
Automated, Consistent, and Even-handed Selection of Active Orbital Spaces for Quantum EmbeddingA widely used strategy to reduce the computational cost in quantum-chemical calculations is to partition the system into an active subsystem, which is the focus of the computational efforts and an…Elena Kolodzeiski, Christopher J. Stein·Jun 15, 2023SaveLearn
The Design of New Practical Constraints in Auxiliary-Field Quantum Monte CarloWe formulate and characterize a new constraint for Auxiliary Field Quantum Monte Carlo (AFQMC) applicable for general fermionic systems, which allows for the accumulation of phase in the random walk…John L. Weber, Hung Vuong, Richard A. Friesner et al.·Jun 15, 2023SaveLearn
On the Interplay of Subset Selection and Informed Graph Neural NetworksMachine learning techniques paired with the availability of massive datasets dramatically enhance our ability to explore the chemical compound space by providing fast and accurate predictions of…Niklas Breustedt, Paolo Climaco, Jochen Garcke et al.·Jun 15, 2023SaveLearn
Multiscale simulation of three-dimensional thin-film lubricationFor three-dimensional mono-layer molecularly thin-film lubrication, it is found that elasticity of the substrate affects tribological behaviors of a thin fluid film confined by two solid…Zuo-Bing Wu·Jun 15, 2023SaveLearn
Quantum Control of Radical Pair Dynamics beyond Time-Local OptimizationWe realize arbitrary waveform-based control of spin-selective recombination reactions of radical pairs in the low magnetic field regime. To this end, we extend the Gradient Ascent Pulse Engineering…Farhan T. Chowdhury, Matt C. J. Denton, Daniel C. Bonser et al.·Jun 14, 2023SaveLearn
Mapping Electronic Decoherence Pathways in MoleculesEstablishing the fundamental chemical principles that govern molecular electronic quantum decoherence has remained an outstanding challenge. Fundamental questions such as how solvent and…Ignacio Gustin, Chang Woo Kim, David W. McCamant et al.·Jun 14, 2023SaveLearn
Exploring the parameter space of an endohedral atom in a cylindrical cavityEndohedral fullerenes, or endofullerenes, are chemical systems of fullerene cages encapsulating single atoms or small molecules. These species provide an interesting challenge of Potential Energy…K. Panchagnula, A. J. W. Thom·Jun 14, 2023SaveLearn
MUBen: Benchmarking the Uncertainty of Molecular Representation ModelsLarge molecular representation models pre-trained on massive unlabeled data have shown great success in predicting molecular properties. However, these models may tend to overfit the fine-tuning…Yinghao Li, Lingkai Kong, Yuanqi Du et al.·Jun 14, 2023SaveLearn
Probing the unfolded configurations of a β-hairpin using sketch-mapThis work examines the conformational ensemble involved in β-hairpin folding by means of advanced molecular dynamics simulations and dimensionality reduction. A fully atomistic description of…Albert Ardevol, Gareth A. Tribello, Michele Ceriotti et al.·Jun 14, 2023SaveLearn
Propagators for molecular dynamics in a magnetic fieldAb initio molecular dynamics in a magnetic field requires solving equations of motion with velocity-dependent forces -- namely, the Lorentz force arising from the nuclear charges moving in a magnetic…Laurens D. M. Peters, Erik I. Tellgren, Trygve Helgaker·Jun 14, 2023SaveLearn
Beyond potential energy surface benchmarking: a complete application of machine learning to chemical reactivityWe train an equivariant machine learning model to predict energies and forces for a real-world study of hydrogen combustion under conditions of finite temperature and pressure. This challenging case…Xingyi Guan, Joseph Heindel, Taehee Ko et al.·Jun 14, 2023SaveLearn
Highly Accurate Prediction of NMR Chemical Shifts from Low-Level Quantum Mechanics Calculations Using Machine LearningTheoretical predictions of NMR chemical shifts from first-principles can greatly facilitate experimental interpretation and structure identification. However, accurate prediction of chemical shifts…Jie Li, Jiashu Liang, Zhe Wang et al.·Jun 14, 2023SaveLearn
Anisotropic Interfacial Force Field for Interfaces of Water with Hexagonal Boron NitrideThis study introduces an anisotropic interfacial potential that provides an accurate description of the van der Waals (vdW) interactions between water and hexagonal boron nitride (h-BN) at their…Zhicheng Feng, Zhangke Lei, Yuanpeng Yao et al.·Jun 13, 2023SaveLearn
Analysis of hydrogen diffusion in the three stage electro-permeation testThe presence of hydrogen traps within a metallic alloy influences the rate of hydrogen diffusion. The electro-permeation (EP) test can be used to assess this: the permeation of hydrogen through a…A. Raina, V. S. Deshpande, E. Martínez-Pañeda et al.·Jun 13, 2023SaveLearn
Von Mises Mixture Distributions for Molecular Conformation GenerationMolecules are frequently represented as graphs, but the underlying 3D molecular geometry (the locations of the atoms) ultimately determines most molecular properties. However, most molecules are not…Kirk Swanson, Jake Williams, Eric Jonas·Jun 13, 2023SaveLearn
Efficient Approximations of Complete Interatomic Potentials for Crystal Property PredictionWe study property prediction for crystal materials. A crystal structure consists of a minimal unit cell that is repeated infinitely in 3D space. How to accurately represent such repetitive structures…Yuchao Lin, Keqiang Yan, Youzhi Luo et al.·Jun 12, 2023SaveLearn
Thermalization of open quantum systems using the multiple-Davydov-D2 variational approachNumerical implementation of an explicit phonon bath requires a large number of oscillator modes in order to maintain oscillators at the initial temperature when modeling energy relaxation processes.…Mantas Jakucionis, Darius Abramavicius·Jun 9, 2023SaveLearn
Ultrafast internal conversion and photochromism in gas-phase salicylideneanilineSalicylidenaniline (SA) is an archetypal system for excited-state intramolecular proton transfer (ESIPT) in non-planar systems. Multiple channels for relaxation involving both the keto and enol forms…Myles C. Silfies, Arshad Mehmood, Grzegorz Kowzan et al.·Jun 9, 2023SaveLearn
MultiBinding Sites United in Covalent-Organic Frameworks (MSUCOF) for H2 Storage and Delivery at Room TemperatureThe storage of hydrogen gas (H2) has presented a significant challenge that has hindered its use as a fuel source for transportation. To meet the Department of Energy's ambitious goals of…Marcus Djokic, Jose L. Mendoza-Cortes·Jun 8, 2023SaveLearn
The fundamental drivers of electrochemical barriersWe find that ion creation/destruction dominates the behavior of electrochemical reaction barriers, through grand-canonical electronic structure calculations of proton-deposition on transition metal…Xi Chen, Georg Kastlunger, Andrew A. Peterson·Jun 8, 2023SaveLearn
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep LearningAdvances in deep learning have greatly improved structure prediction of molecules. However, many macroscopic observations that are important for real-world applications are not functions of a single…Shuxin Zheng, Jiyan He, Chang Liu et al.·Jun 8, 2023SaveLearn