Gibbs-Duhem-Informed Neural Networks for Binary Activity Coefficient PredictionWe propose Gibbs-Duhem-informed neural networks for the prediction of binary activity coefficients at varying compositions. That is, we include the Gibbs-Duhem equation explicitly in the loss…Jan G. Rittig, Kobi C. Felton, Alexei A. Lapkin et al.·May 31, 2023SaveLearn
Catalysis distillation neural network for the few shot open catalyst challengeThe integration of artificial intelligence and science has resulted in substantial progress in computational chemistry methods for the design and discovery of novel catalysts. Nonetheless, the…Bowen Deng·May 31, 2023SaveLearn
MAGNet: Motif-Agnostic Generation of Molecules from ShapesRecent advances in machine learning for molecules exhibit great potential for facilitating drug discovery from in silico predictions. Most models for molecule generation rely on the decomposition of…Leon Hetzel, Johanna Sommer, Bastian Rieck et al.·May 30, 2023SaveLearn
VO2 Phase Change Electrodes in Li-ion BatteriesUse of electrode materials that show phase change behavior and hence drastic changes in electrochemical activity during operation, have not been explored for Li-ion batteries. Here we demonstrate the…Samuel Castro-Pardo, Anand B. Puthirath, Shaoxun Fan et al.·May 30, 2023SaveLearn
Reduced-order electrochemical models with shape functions for fast, accurate prediction of lithium-ion batteries under high C ratesThis paper proposes physical-based, reduced-order electrochemical models that are much faster than the electrochemical pseudo 2D (P2D) model, while providing high accuracy even under the challenging…Tianhan Gao, Wei Lu·May 29, 2023SaveLearn
Density-Functional Theory (DFT) and Time-Dependent DFT Study of the Chemical and Physical Origins of Key Photoproperties of End-Group Derivatives of the Nonfullerene Bulk Heterojunction Organic Solar Cell Acceptor Molecule IDICAs emphasized in a recent review article [Chem. Rev. 122, 14180 (2022)], organic solar cell (OSC) photoconversion efficiency has been rapidly evolving with results increasingly comparable to those of…Taouali W, Alimi K, Nangraj A. S. et al.·May 29, 2023SaveLearn
Implicit Transfer Operator Learning: Multiple Time-Resolution Surrogates for Molecular DynamicsComputing properties of molecular systems rely on estimating expectations of the (unnormalized) Boltzmann distribution. Molecular dynamics (MD) is a broadly adopted technique to approximate such…Mathias Schreiner, Ole Winther, Simon Olsson·May 29, 2023SaveLearn
Deep Electron Cloud-activity and Field-activity RelationshipsChemists have been pursuing the general mathematical laws to explain and predict molecular properties for a long time. However, most of the traditional quantitative structure-activity relationship…Lu Xu, Qin Yang·May 29, 2023SaveLearn
Assessing mixed quantum-classical molecular dynamics methods for nonadiabatic dynamics of molecules on metal surfacesMixed-quantum classical (MQC) methods for simulating the dynamics of molecules at metal surfaces have the potential to accurately and efficiently provide mechanistic insight into reactive processes.…James Gardner, Scott Habershon, Reinhard J. Maurer·May 29, 2023SaveLearn
PubChemQC B3LYP/6-31G*//PM6 dataset: the Electronic Structures of 86 Million Molecules using B3LYP/6-31G* calculationsThis article presents the "PubChemQC B3LYP/6-31G*//PM6" dataset, containing electronic properties of 85,938,443 molecules. It includes orbitals, orbital energies, total energies, dipole moments, and…Maho Nakata, Toshiyuki Maeda·May 29, 2023SaveLearn
Effect of neighbouring molecules on ground-state properties of many-body polar linear rotor systemsA path integral ground state approach has been used to estimate the ground-state energy and structural properties of hydrogen fluoride molecules pinned to a one-dimensional lattice. In the…Tapas Sahoo, Gautam Gangopadhyay·May 28, 2023SaveLearn
Voltage Hysteresis of Silicon Nanoparticles: Chemo-Mechanical Particle-SEI ModelSilicon is a promising anode material for next-generation lithium-ion batteries. However, the volume change and the voltage hysteresis during lithiation and delithiation are two substantial drawbacks…Lukas Köbbing, Arnulf Latz, Birger Horstmann·May 27, 2023SaveLearn
Probing reaction channels via reinforcement learningWe propose a reinforcement learning based method to identify important configurations that connect reactant and product states along chemical reaction paths. By shooting multiple trajectories from…Senwei Liang, Aditya N. Singh, Yuanran Zhu et al.·May 27, 2023SaveLearn
Unraveling the Mechanism of Tip-Enhanced Molecular Energy TransferElectronic Energy Transfer (EET) between chromophores is fundamental in many natural light-harvesting complexes, serving as a critical step for solar energy funneling in photosynthetic plants and…Colin Coane, Marco Romanelli, Giulia Dall'Osto et al.·May 26, 2023SaveLearn
Basis-set correction based on density-functional theory: Linear-response formalism for excited-state energiesThe basis-set correction method based on density-functional theory consists in correcting the energy calculated by a wave-function method with a given basis set by a density functional. This…Diata Traore, Emmanuel Giner, Julien Toulouse·May 26, 2023SaveLearn
Production of positronium chloride: A study of the charge exchange reaction between Ps and Cl-We present cross sections for the formation of positronium chloride (PsCl) in its ground state from the charge exchange between positronium (Ps) and chloride (Cl-) in the range of 10 meV - 100 eV…K. Lévêque-Simon, A. Camper, R. Taïeb et al.·May 26, 2023SaveLearn
Elucidating the role of hydrogen bonding in the optical spectroscopy of the solvated green fluorescent protein chromophore: using machine learning to establish the importance of high-level electronic structureHydrogen bonding interactions with chromophores in chemical and biological environments play a key role in determining their electronic absorption and relaxation processes, which are manifested in…Michael S. Chen, Yuezhi Mao, Andrew Snider et al.·May 26, 2023SaveLearn
Connections and performances of Green's function methods for charged and neutral excitationsIn recent years, Green's function methods have garnered considerable interest due to their ability to target both charged and neutral excitations. Among them, the well-established GW approximation…Enzo Monino, Pierre-François Loos·May 26, 2023SaveLearn
Low and High Frequency Vibrations Synergistically Enhance Singlet Exciton Fission Through Robust Vibronic ResonancesSinglet exciton fission (SEF) is initiated by ultrafast internal conversion of a singlet exciton into a correlated triplet pair (TT)1. The `reaction coordinates' for ultrafast SEF even in archetypal…Atandrita Bhattacharyya, Amitav Sahu, Sanjoy Patra et al.·May 26, 2023SaveLearn
DASH: Dynamic Attention-Based Substructure Hierarchy for Partial Charge AssignmentWe present a robust and computationally efficient approach for assigning partial charges of atoms in molecules. The method is based on a hierarchical tree constructed from attention values extracted…Marc T. Lehner, Paul Katzberger, Niels Maeder et al.·May 25, 2023SaveLearn
The Real Space Correlation Function of Gaussian Chain in Spin-echo Small Angle Neutron ScatteringThe utilization of spin-echo small angle neutron scattering (SESANS) for the analysis of structures in soft matter is becoming increasingly prevalent. In this context, the Gaussian chain model and…Tengfei Cui, Xiangqiang Chu·May 25, 2023SaveLearn
A machine learning potential for simulating infrared spectra of nanosilicate clustersThe use of machine learning (ML) in chemical physics has enabled the construction of interatomic potentials having the accuracy of ab initio methods and a computational cost comparable to that of…Zeyuan Tang, Stefan T. Bromley, Bjørk Hammer·May 25, 2023SaveLearn
Proton Collective Quantum Tunneling Induces Anomalous Thermal Conductivity of Ice under PressureProton tunneling is believed to be non-local in ice but has never been shown experimentally. Here we measured thermal conductivity of ice under pressure up to 50 GPa and found it to increase with…Yufeng Wang, Ripeng Luo, Jian Chen et al.·May 25, 2023SaveLearn
Exact and model exchange-correlation potentials for open-shell systemsThe conventional approaches to the inverse density functional theory problem typically assume non-degeneracy of the Kohn-Sham (KS) eigenvalues, greatly hindering their use in open-shell systems. We…Bikash Kanungo, Jeffrey Hatch, Paul M. Zimmerman et al.·May 24, 2023SaveLearn
Evaluation of the MACE Force Field Architecture: from Medicinal Chemistry to Materials ScienceThe MACE architecture represents the state of the art in the field of machine learning force fields for a variety of in-domain, extrapolation and low-data regime tasks. In this paper, we further…David Peter Kovacs, Ilyes Batatia, Eszter Sara Arany et al.·May 23, 2023SaveLearn