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.
This study utilizes a deep-learning potential validated by experiments to reveal that polyacrylonitrile facilitates concerted electron-ion transport through a rapid, Li+-coupled sequential ring-formation mechanism triggered by a nucleophile-initiated cyclization rate-limiting step.
This study demonstrates that while quantum effects significantly influence hydrogen permeation through graphdiyne membranes, classical molecular dynamics simulations combined with Feynman-Hibbs corrections can reliably bound these results, provided that the crucial thermal motion of the membrane is included to accurately capture the reduction in permeation barriers.
This paper presents a GPU-accelerated multigrid Gaussian-Plane-Wave density fitting algorithm implemented in PySCF's GPU4PySCF module, which achieves up to 25x speedup over CPU implementations for large-scale Kohn-Sham DFT calculations while maintaining high efficiency for high angular momentum functions.
This study demonstrates a sustainable photocatalytic strategy using microalgae as a sacrificial agent with brookite TiO2 to simultaneously maximize green hydrogen production and convert microalgae into valuable chemicals like methane and carbon monoxide, while also facilitating CO2 capture.
This paper reviews a framework that combines deep learning to predict the committor with explainable artificial intelligence (XAI) techniques to identify and quantify the contributions of key collective variables as reaction coordinates for understanding complex molecular transition mechanisms.
Using ab initio molecular dynamics, this study proposes a complementary Eigen-Zundel interpretation that reconciles the apparent contradiction between the distinct thermodynamic behaviors and similar vibrational spectra of excess protons in aqueous HF and HCl solutions by revealing a dynamically shared proton structure and nearly identical proton transfer free-energy profiles.
This paper presents a framework that combines transferable deep-learning variational Monte Carlo with Gaussian process regression to enable accurate and efficient *ab initio* geometry optimization and potential energy surface exploration for strongly correlated systems, achieving zero-shot chemical accuracy across diverse molecular configurations.
This paper introduces a decoupled agent-skill framework using OpenClaw that automates multistep computational chemistry workflows by separating centralized planning, domain-specific procedures, and heterogeneous HPC execution, successfully demonstrated through a methane oxidation molecular dynamics case study.
This paper proposes a diffusion-oscillatory model of liquid water, derived from broadband dielectric spectroscopy data, which links dc conductivity and various relaxation processes to the lifetimes of neutral molecules and ions while challenging the conventional view of water molecule stability.
Using spectral-weight analysis, researchers experimentally identified short-lived hydronium and deuterated hydronium ions in liquid water, revealing that these fluctuation-born species constitute approximately 2% of the water content on the picosecond timescale and effectively render liquid water an ionic liquid in femtochemistry.