794 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.
PackFlow is a generative flow matching framework enhanced by reinforcement learning-based physics alignment that efficiently predicts organic molecular crystal structures by generating lattice-aware proposals which concentrate probability mass in low-energy basins, thereby outperforming heuristic methods in both structural similarity and energy minimization.
This paper demonstrates that the spectral complexity of the radiative transfer equation admits a finite effective rank via Young-measure homogenization, enabling highly accurate and efficient low-rank tensor train decompositions that significantly outperform traditional approximations like the correlated-k distribution across diverse molecular and atomic opacity sources.
This paper introduces HBAT 2, an updated Python package that automates the geometric analysis and visualization of hydrogen bonds and various non-covalent interactions in macromolecular structures through multiple user interfaces.
This paper demonstrates that machine learning models for materials discovery often achieve high benchmark performance by exploiting bibliographic confounding factors like author and publication year rather than learning genuine chemical principles, highlighting the urgent need for rigorous falsification tests and dataset redesign to ensure true scientific understanding.
This paper introduces El Agente Gráfico, a single-agent framework that enhances scientific automation by embedding LLM decision-making within a type-safe execution environment and dynamic knowledge graphs, thereby replacing fragile text-based coordination with structured, typed symbolic identifiers to ensure consistency, provenance tracking, and robust performance across complex computational tasks like quantum chemistry and materials design.
This paper benchmarks computational methods for predicting the UV-Vis absorption spectra of platinum-based DNA intercalators used in cancer detection, identifying range-separated hybrid functionals as essential for accuracy and establishing PBEh-3c as the most efficient protocol that balances speed with reliable results.
This paper introduces a thermodynamics-informed graph neural network that incorporates the Clapeyron equation as a regularization term to improve the accuracy of multi-task predictions for pure component vapor-liquid equilibrium properties, particularly in data-scarce scenarios.
This first-principles multiscale computational study demonstrates that a ferrocene-functionalized covalent organic framework (MSUCOF-4-FeCp) significantly exceeds U.S. Department of Energy hydrogen storage targets with 18.0 wt% gravimetric and 72.6 g H2/L volumetric capacities at 298 K and 700 bar, offering a cost-effective alternative to precious metal-based materials.
This paper introduces an efficient Brownian dynamics simulation method for electric double-layer capacitors that models electrodes with tunable Thomas-Fermi screening lengths under a Born-Oppenheimer approximation, enabling the study of larger systems and longer time scales while accurately capturing ionic density profiles and differential capacitance.
This paper investigates the algebro-geometric properties of the Coupled Cluster Doubles (CCD) truncation variety for four electrons, establishing that it is a complete intersection of a specific degree defined by Pfaffian quadratic relations, and connects these structural findings to the challenging bond formation process of beryllium insertion into molecular hydrogen.