1032 papers
This collection explores the fascinating intersection where the laws of physics meet the complex machinery of chemistry. Here, researchers investigate how quantum mechanics governs molecular bonds, how light interacts with matter at the atomic scale, and how fundamental forces shape chemical reactions. It is a realm where abstract mathematical models collide with tangible substances to reveal the hidden mechanisms driving our material world.
On Gist.Science, we process every new preprint in this category directly from arXiv to make these discoveries accessible to everyone. Whether you are a seasoned expert or a curious reader, you will find both plain-language explanations and detailed technical summaries for each paper. Below are the latest contributions from the community pushing the boundaries of physical chemistry.
The paper introduces **sbml4md**, a machine learning-powered software package that extracts parameters from molecular dynamics trajectories to enable numerically exact, empirically minimal simulations of nonlinear vibrational spectra for molecular liquids using the Hierarchical Equations of Motion framework.
This study utilizes a hierarchical equations of motion (HEOM) framework applied to molecular dynamics-based machine learning models to simulate and analyze the non-Markovian, nonlinear vibrational dynamics and isotope effects in the 2D infrared correlation spectra of liquid H2O and D2O.
This paper presents a visualization-based educational approach that combines analytic derivations and numerical simulations of time-dependent Hückel Hamiltonians to intuitively demonstrate how environmental stochastic fluctuations disrupt coherent electronic motion in polyene chains, thereby explaining the physical origins of condensed-phase spectral line broadening for undergraduate students.
By combining ultrafast oxygen K-edge TR-NEXAFS spectroscopy with ab initio multiple spawning simulations, this study elucidates the complete photoexcited population flow in gas-phase acetophenone, revealing a sequential pathway from the initially excited state to the reactive state via intermediate and states that drives Norrish type I chemistry.
The paper introduces EquiEwald, a unified SO(3)-equivariant neural interatomic potential that embeds an Ewald-inspired reciprocal-space formulation to accurately model anisotropic long-range electrostatic and polarization interactions while maintaining physical consistency and improving accuracy across periodic and aperiodic systems.
This paper presents a data-driven workflow combining SOAP descriptors, principal component analysis, and active learning to construct a highly accurate and efficient machine-learning interatomic potential for simulating NO scattering on graphite, successfully reproducing experimental trends while overcoming the computational limitations of traditional ab initio methods.
This paper proposes a maximum entropy principle for quantum wavefunction ensembles at thermal equilibrium, termed the Scrooge ensemble, which demonstrates that valid equilibrium states require constraining measurement entropy to equal the Rényi divergence with respect to the Gibbs state, in addition to standard energy constraints.
This paper argues that for quantum computational chemistry to achieve utility-scale impact, algorithm development must evolve beyond solving isolated, strongly correlated problems to enable the practical integration of quantum-accelerated methods into high-throughput pipelines for routine calculations on arbitrary molecules.
This paper derives analytical expressions for chemical potentials within the Random Phase Approximation (RPA) and demonstrates that the GW correlation self-energy exhibits a derivative discontinuity at integer particle numbers, thereby resolving the apparent inconsistency between accurate quasiparticle energies and large delocalization errors in RPA total energies.
This study predicts that phosphorus carbide nanotubes (NTs) are a stable, chemically realistic quasi-one-dimensional material that uniquely hosts coexisting Dirac fermions and robust flat bands at the Fermi level, while exhibiting strain-induced structural and quantum phase transitions, localized edge states, and tunable magnetism for potential applications in quantum hardware and spintronics.