1002 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 introduces a novel simulation technique combining isobaric Lattice Switch Monte Carlo and thermodynamic integration to accurately calculate free energy differences and coexistence pressures between clathrate hydrate structures II and H, yielding results that align well with experimental data for argon and methane systems.
This paper introduces the qumode-based variational quantum deflation (QumVQD) framework, which leverages bosonic quantum processors and symmetry-constrained Fock basis filtering to efficiently compute electronic and vibrational excited states with high accuracy and significantly reduced circuit depth compared to qubit-based algorithms.
This study employs a many-body machine-learned force field (MACE) trained on density functional theory data to successfully reproduce and mechanistically explain the ion-specific anomalous water diffusion in NaCl and CsI electrolytes, revealing that Na⁺ retards water via strong hydration shell interactions while I⁻ accelerates it through a diffuse, weakly structured shell.
This paper introduces an efficient partitioning scheme that overcomes the scalability limitations of the variational polaron framework, enabling the accurate simulation of quantum energy transport dynamics in large, complex networks comprising hundreds to thousands of sites.
This paper extends the Kähler manifold formalism to CASSCF theory to derive linear response equations and develop a robust state-specific method for computing electronic excitation energies, demonstrating its effectiveness on molecular systems while highlighting challenges arising from the theory's inherent nonlinearity.
This paper introduces the antisymmetrized geminal power configuration interaction (AGP-CI) method, which extends the AGP framework to capture inter-geminal correlations via a computationally efficient linear combination of AGPs, demonstrating superior accuracy over standard LC-AGP in strongly correlated systems like the Hubbard model and small molecules.
This paper employs stochastic density functional theory to extend the classical Debye-Falkenhagen prediction of frequency-dependent conductivity from dilute to concentrated electrolytes by incorporating hard-core repulsion effects, while also addressing the challenges in experimentally observing this phenomenon.
Using a novel combination of electron-microscopy-based vibrational and core-level spectroscopy, researchers mapped the nanoscale distribution and chemical composition of uncommon, nitrogen-containing organic matter in asteroid Ryugu, revealing soluble, aliphatic components and NHx functional groups that likely formed in the outer solar nebula or via fluid reactions on the parent body.
By combining machine-learning molecular dynamics with vibrational sum-frequency generation simulations, this study reveals that the apparent hydrophilicity of monolayer graphene on hydrophilic substrates stems from thermodynamically favorable intercalated water molecules causing signal cancellation, rather than wetting transparency, while multilayer graphene lacks this intercalation.
This paper demonstrates that a diffusion-based Transformer neural network can successfully solve the challenging inverse problem of retrieving molecular structures from ion-momentum distributions generated by Coulomb explosion imaging, achieving reconstruction accuracy within half the length of a typical chemical bond.