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.
This paper presents a kinetic model, validated by molecular dynamics simulations, that explains the wide variation in experimentally observed water cavitation pressures by demonstrating how the competition between bulk, surface, and surface-defect nucleation pathways—particularly the dominance of nanoscopic hydrophobic defects—determines the metastability of water under negative pressure.
This paper introduces a fast, flexible, and modular framework (implemented in PyTorch and JAX) that integrates established long-range interaction algorithms like Ewald summation and particle-mesh Ewald into atomistic machine learning, enabling the seamless combination of physical long-range forces with local models to overcome limitations in describing electrostatics and other long-range effects.
This paper introduces a numerically exact, trajectory-based twin-space classical mapping model (TS-CMM) approach for simulating open quantum systems in the constraint phase space, which avoids environmental discretization errors and demonstrates high accuracy in reproducing population dynamics and nonlinear spectra for condensed-phase system-bath models.
This paper presents a general molecular-scale dynamic memristor model that integrates non-equilibrium charge transport kinetics with slow chemical processes to reproduce synaptic behaviors and optimize reservoir computing performance, thereby establishing a theoretical foundation for chemistry-driven neuromorphic information processing.
This paper introduces a parametric, temperature-dependent autoencoder framework that integrates non-negativity constraints and simultaneous optimization of kinetics and energetics to generate physically interpretable, high-accuracy reduced-order chemical kinetics models for energetic materials across a wide range of thermodynamic conditions.
This paper establishes a necessary and sufficient cusp criterion in the parameter space of an asymmetric two-degree-of-freedom adiabatic Marcus Hamiltonian to determine when the lower adiabatic surface possesses a genuine index-one saddle, thereby defining the existence of a phase-space transition state characterized by a normally hyperbolic invariant manifold and a no-recrossing dividing surface.
This paper introduces a chemical interpretation framework for time-dependent coupled-cluster theory by expanding wavefunctions into Slater-determinant bases to define time-dependent configuration weights, thereby enabling the straightforward assignment of absorption peaks to specific orbital transitions in both valence and core-level excitations across various molecular systems.
This paper introduces a stochastic framework utilizing complex absorbing potentials to simulate exciton transport in large molecular aggregates, revealing how structural disorder and aggregate topology influence energy dynamics and offering a classification scheme for optimizing material design.
This study presents absolute electron attachment cross sections for derived from total scattering measurements, revealing resonance features that contradict existing recommended databases and highlight the need for updated electron scattering cross section data.
Inspired by "shortcut to adiabaticity" techniques, this paper derives time-dependent voltage protocols within the Poisson-Nernst-Planck framework that eliminate relaxation modes to accelerate the charging and discharging of electric double-layer capacitors to equilibrium in times significantly shorter than their intrinsic natural timescales.