785 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.
Using coupled-channel calculations on a Rb+KRb prototype model, the study reveals that near-threshold bound states with strong long-range character and weak short-range coupling can persist deep below thresholds, exhibiting long lifetimes and the potential to induce narrow Feshbach resonances while remaining largely immune to chaotic short-range dynamics and laser-induced destruction.
By combining machine learning classifiers with metadynamics simulations, this study reveals that the selection of specific polymorphs in Zn(imidazolate) metal-organic frameworks is determined as early as the pre-nucleation cluster stage, challenging the assumption that polymorph selection occurs later in the synthesis process.
This paper introduces a novel parallel athermal quasistatic deformation scheme that utilizes a two-level stepping approach to significantly accelerate the computation of molecular system trajectories, achieving speed-ups between 2.02 and 6.33 times while maintaining simulation accuracy.
This paper presents the development and initial validation of a new glow-discharge ion-trap instrument designed to directly measure slow radiative-association rate coefficients, successfully demonstrating its capability by determining a lower limit for the Ag + O reaction rate.
This paper presents a unified formalism for calculating the spin expectation value in two-component time-dependent density functional theory (TDDFT), deriving specialized equations for collinear references to demonstrate that excited-state spin contamination arises from both the reference state and the excitation process itself.
This contribution presents a physics-guided Bayesian active learning framework that integrates a Langmuir adsorption model with a two-stage parameter estimation strategy to autonomously and efficiently optimize pulse durations in atomic layer deposition, thereby achieving faster convergence, higher prediction accuracy, and significantly reduced precursor consumption compared to conventional data-driven approaches.
This paper demonstrates a breakthrough in natural-abundance 13C zero-field NMR spectroscopy by combining a compact optical magnetometer with vibrationally corrected DFT predictions to achieve high-sensitivity, isotopomer-resolved molecular identification and the extraction of transient solution-state structural information without requiring hyperpolarization or large magnetic fields.
This paper demonstrates that Slater-type orbitals can be efficiently encoded on quantum computers using matrix product states with constant or bounded bond dimensions, enabling accurate analytical state preparation and integral evaluation that has been experimentally validated on IBM hardware.
This master's thesis utilizes a dual-methodological quantum chemical approach to reveal that ethylbenzene dehydrogenation on rutile TiO(110) proceeds via proton-coupled electron transfer on stoichiometric surfaces but shifts to a more efficient direct hydrogen atom transfer mechanism on oxidized surfaces, with photon energy determining whether the reaction bypasses ground-state kinetic barriers through excited-state persistence.
This paper presents a physics-based model that disentangles and analyzes the distinct degradation mechanisms of silicon-graphite composite anodes in lithium-ion batteries, specifically addressing the interplay between SEI growth, particle cracking, and active material loss under various cycling, storage, and check-up conditions to inform future battery optimization.