Tracking Microhydration of the NaCl Rocksalt Molecule in Helium Nanodroplets by Penning Ionization Electron SpectroscopyThe microhydration of rock salt (NaCl) molecules was investigated using high-resolution Penning ionization electron spectroscopy (PIES) in helium nanodroplets. Although model calculations predict…Ltaief Ben Ltaief, Keshav Sishodia, Robert Richter et al.·Oct 24, 2025SaveLearn
Efficient Exploration of Chemical KineticsEstimating reaction rates and chemical stability is fundamental, yet efficient methods for large-scale simulations remain out of reach despite advances in modeling and exascale computing. Direct…Rohit Goswami·Oct 24, 2025SaveLearn
A complex Gaussian representation of continuum wavefunctions respectful of their asymptotic behaviourComplex Gaussian basis sets are optimized to accurately represent continuum radial wavefunctions over the whole space. First, attention is put on the technical ability of the optimization method to…Stéphanie Laure Egome Nana, Arnaud Leclerc, Lorenzo Ugo Ancarani·Oct 24, 2025SaveLearn
Fully Analytic Nuclear Gradients for the Bethe--Salpeter EquationThe Bethe-Salpeter equation (BSE) formalism, combined with the GW approximation for ionization energies and electron affinities, is emerging as an efficient and accurate method for predicting…Johannes Tölle, Marios-Petros Kitsaras, Pierre-François Loos·Oct 24, 2025SaveLearn
Stoichiometrically-informed symbolic regression for extracting chemical reaction mechanisms from dataA data-driven computational method is introduced to extract chemical reaction mechanisms from time series chemical concentration data. It is realized through the use of dynamic symbolic regression in…Manuel Palma Banos, Joel D. Kress, Rigoberto Hernandez et al.·Oct 23, 2025SaveLearn
An interpretable molecular descriptor for machine learning predictions in atmospheric scienceThe study of aerosol formation and chemistry using machine learning is limited by the lack of molecular descriptors suited to atmospheric compounds. Interpretable models are particularly affected…Linus Lind, Hilda Sandström, Patrick Rinke·Oct 23, 2025SaveLearn
Extending machine learning model for implicit solvation to free energy calculationsThe implicit solvent approach offers a computationally efficient framework to model solvation effects in molecular simulations. However, its accuracy often falls short compared to explicit solvent…Rishabh Dey, Michael Brocidiacono, Kushal Koirala et al.·Oct 23, 2025SaveLearn
Latent Spaces for Langevin DynamicsIn the field of machine learning coarse-grained potentials in molecular dynamics, many propagators require that the effective Hamiltonian is quadratic in momentum, thus limiting the family of…Andy Bruce, Alexander Aghili, Razvan Marinescu et al.·Oct 23, 2025SaveLearn
Applying R-Matrix Theory to Atom-Molecule Inelastic Collisions: the case study of H2O + HThe present study presents a comprehensive theoretical investigation of atom and asymmetric top molecule inelastic scattering based on the R-matrix formalism. The proposed methodology establishes a…Ricardo Manuel García-Vázquez, Lisan David Cabrera-González, Otoniel Denis-Alpizar et al.·Oct 22, 2025SaveLearn
Fokker-Planck equation governing the distribution of walkers in AFQMCAuxiliary-field quantum Monte Carlo (AFQMC) is typically formulated as an open-ended random walk in an overcomplete space of Slater determinants, implemented through a Langevin equation. However, the…Alfred Li, Ankit Mahajan, Sandeep Sharma·Oct 22, 2025SaveLearn
How Accurate Are DFT Forces? Unexpectedly Large Uncertainties in Molecular DatasetsTraining of general-purpose machine learning interatomic potentials (MLIPs) relies on large datasets with properties usually computed with density functional theory (DFT). A pre-requisite for…Domantas Kuryla, Fabian Berger, Gábor Csányi et al.·Oct 22, 2025SaveLearn
Manning-type potential induced by kink scatterings with phonons in molecular chains with hyperbolic double-well substratesA rescaled Manning potential is obtained in the analysis of scatterings of small- amplitude excitations with a kink defect. The generic model is a nonlinear Klein- Gordon Hamiltonian describing a…Alain M. Dikande·Oct 22, 2025SaveLearn
Ab Initio Calculations of the Static and Dynamic Polarizability of BaOHWe present high-precision ab initio calculations of the static and dynamic polarizability of the barium monohydroxide (138BaOH) molecule, using relativistic coupled-cluster theory. By thoroughly…E. H. Prinsen, A. Borschevsky, S. Hoekstra et al.·Oct 22, 2025SaveLearn
Unveiling chiral electron-photon correlation effects in circularly polarized optical devicesStrong coupling with circularly polarized vacuum fluctuations offers a viable route to manipulate molecular chirality. While experiments are advancing toward the realization of chiral cavities, a…Yassir El Moutaoukal, Rosario R. Riso, Andrea Bianchi et al.·Oct 22, 2025SaveLearn
Mechanism of the electrochemical hydrogenation of grapheneThe electrochemical hydrogenation of graphene induces a robust and reversible conductor-insulator transition, of strong interest in logic-and-memory applications. However, its mechanism remains…Y. -C. Soong, H. Li, Y. Fu et al.·Oct 22, 2025SaveLearn
Identifying the Catalytic Descriptor of Single-Atom Catalysts in Nitrate Reduction Reaction: An Interpretable Machine-Learning MethodElucidating the catalytic descriptor that accurately characterizes the structure-activity relationships of typical catalysts for various important heterogeneous catalytic reactions is pivotal for…Zhen Zhu, Shan Gao, Jing Zhang et al.·Oct 22, 2025SaveLearn
Learning Optimal Decoherence Time Formulas for Surface Hopping Simulation of High-Dimensional ScatteringIn our recent work (J. Phys. Chem. Lett. 2023, 14, 7680), we utilized the exact quantum dynamics results as references and proposed a general machine learning method to obtain the optimal decoherence…Cancan Shao, Rixin Xie, Zhecun Shi et al.·Oct 22, 2025SaveLearn
Predicting Spectroscopic Properties of Solvated Nile Red with Automated Workflows for Machine Learned Interatomic PotentialsMachine Learned Interatomic Potentials (MLIPs) offer a powerful combination of abilities for accelerating theoretical spectroscopy calculations utilising both ensemble sampling and trajectory…Jacob Eller, Nicholas D. M. Hine·Oct 21, 2025SaveLearn
Non-Resonant Raman Optical Activity From Phase-Space Electronic Structure TheoryIn order to model experimental non-resonant Raman optical activity, chemists must compute a host of second-order response tensors, (e.g. the electric-dipole magnetic-dipole polarizability) and their…Zhen Tao, Mansi Bhati, Joseph E. Subotnik·Oct 21, 2025SaveLearn
Relativistic unitary coupled cluster method for ground-state molecular propertiesWe propose a relativistic unitary coupled cluster (UCC) expectation value approach for computing first-order properties of heavy-element systems. Both perturbative (UCC3) and non-perturbative (qUCC)…Kamal Majee, Somesh Chamoli, Malaya K. Nayak et al.·Oct 21, 2025SaveLearn
Technomolecular Materials: 3D Printed 2D Nanosheets with Self Patterned ElectrodesBuilding on our prior work, where our team transcended self assembled molecular monolayers (SAMs) research from a 2D configuration to 3D structured materials and successfully introduced the molecular…Hicham Hamoudi, Sara Iyad Ahmad, Atef Zekri et al.·Oct 21, 2025SaveLearn
Prospects for Using Artificial Intelligence to Understand Intrinsic Kinetics of Heterogeneous Catalytic ReactionsArtificial intelligence (AI) is influencing heterogeneous catalysis research by accelerating simulations and materials discovery. A key frontier is integrating AI with multiscale models and…Andrew J. Medford, Todd N. Whittaker, Bjarne Kreitz et al.·Oct 21, 2025SaveLearn
Foundation Models for Discovery and Exploration in Chemical SpaceAccurate prediction of atomistic, thermodynamic, and kinetic properties from molecular structures underpins materials innovation. Existing computational and experimental approaches lack the…Alexius Wadell, Anoushka Bhutani, Victor Azumah et al.·Oct 20, 2025SaveLearn
Local Proton Disorder Induced Intermolecular H-H Coupling in Ionization of Dense AmmoniaUnder cold compression, hydrogen bonding was considered to dominate intermolecular interaction during the ionization of ammonia. Here, we provide experimental and theoretical evidence of…Yu Tao, Li Lei, Jingyi Liu et al.·Oct 20, 2025SaveLearn
Discovering How Ice Crystals Grow Using Neural ODE's and Symbolic RegressionDepositional ice growth is an important process for cirrus cloud evolution, but the physics of ice growth in atmospheric conditions is still poorly understood. One major challenge in constraining…Kara D. Lamb, Jerry Y. Harrington, Alfred M. Moyle et al.·Oct 20, 2025SaveLearn