1044 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 paper presents a machine-learning-accelerated computational approach that uses surface-specific vibrational spectroscopy to demonstrate how graphene oxidation alters interfacial water structure, providing a quantitative spectroscopic fingerprint to reconcile conflicting experimental data.
This paper demonstrates that while atomic forces remain consistent between canonical and grand-canonical ensembles, vibrational frequencies and Stark tuning rates differ when simulating electrochemical interfaces using grand-canonical density functional theory and continuum electro-chemical models.
Using discontinuous molecular dynamics simulations, this study demonstrates that the rotational dynamics of dumbbell probes in 2D colloids transition from Brownian to non-Gaussian behavior across the liquid-hexatic phase transition, revealing a close link between probe motion, hexagonal bond-orientational order, and the emergence of "swing motion" as a decoupling mechanism between translation and rotation.
This study demonstrates that the Global Natural Orbital Functional (GNOF) and its modified version (GNOFm) provide accurate and robust descriptions of dynamic correlation in 5- and 6-membered molecular rings, performing comparably to the CCSD(T) benchmark.
The researchers demonstrate an experimental method to engineer tunable thermal reservoirs in a trapped-ion system, enabling the study of open-system quantum dynamics and temperature-dependent energy transfer processes.
This paper demonstrates that the seeding method in NVT molecular dynamics simulations effectively tests classical nucleation theory (CNT) for Lennard-Jones condensation in small systems, finding that CNT accurately predicts stable cluster radii and aligns well with the critical cluster properties of infinite systems when using robust equations of state.
Using molecular dynamics simulations, this study demonstrates that increasing salt concentration triggers structural and dynamical crossovers driven by the transition from charge-dominated to density-dominated regimes, a process that is significantly influenced by ion-solvent coupling and can be unified through a diffusion-corrected ion-pair lifetime descriptor.
This study demonstrates that incorporating mesoporous silica nanoparticles (MSNs) into alginate/chitosan scaffolds significantly enhances their mechanical strength, degradation resistance, and biomineralization potential, making the MSN30 composite a highly promising candidate for bone tissue engineering.
The paper proposes HEDMoL, a method that enhances molecular representation learning by transferring electron-level information from small molecules to large ones, enabling state-of-the-art prediction of molecular physics without the high computational cost of direct electron-level modeling.
This paper introduces tmQM-RDF, a knowledge graph dataset containing detailed qualitative and quantitative descriptions of approximately 50,000 transition metal complexes designed to facilitate machine learning and computational research in the field.