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 study demonstrates that integrating continuum transport modeling with adjoint-based design optimization significantly enhances CO reduction flow reactor performance by strategically patterning Ag and Cu catalysts to maximize ethylene current density, particularly at high voltages and with increased patterning sections.
This paper establishes a quantum mechanical framework based on molecular optomechanics to demonstrate that pump-and-probe surface-enhanced vibrational spectroscopy can detect intramolecular vibrational redistribution (IVR) signatures in single molecules through anti-Stokes SERS spectra, regardless of whether the vibrational pumping is driven by infrared lasers or Stokes scattering.
This paper introduces OmniMol, a state-of-the-art machine-learned interatomic potential for small molecules that leverages a Point-Edge Transformer architecture and knowledge transfer from high-energy physics to achieve excellent performance with minimal fine-tuning and uniquely fast inference.
This paper investigates intermediate-current transitions in asymmetric-valence binary electrolytes using a steady one-dimensional Poisson-Nernst-Planck model, revealing a smooth transition between near-equilibrium and strongly non-equilibrium regimes characterized by the vanishing of the Debye-scale boundary layer and providing explicit analytic solutions and a collapsed phase diagram to predict system behavior based on ion valences and fluxes.
This paper demonstrates that the Quantum Flow (QFlow) algorithm, particularly when employing a cost-effective single and double excitation ansatz (QFlow-SD) or a composite downfolding strategy, achieves accurate chemical energy simulations with significantly reduced qubit requirements and constant-depth circuits compared to canonical unitary coupled-cluster methods.
This paper extends the stochastic cluster expansion framework to excited states, enabling accurate calculation of excitation gaps in strongly correlated systems by expressing energy differences as a hierarchy of orbital-space cluster contributions that eliminate the need for large preselected active spaces.
This paper establishes a controlled theoretical framework mapping collective intermolecular electronic correlations in optical cavities to the solvable spherical Sherrington-Kirkpatrick model, revealing two novel entropy-driven phases (paracorrelated and spin-glass) that emerge from cavity-mediated electron correlations.
This feature article surveys the architectures and materials enabling strong light-matter coupling to form polaritons, discusses key phenomena and research tools, and highlights how these hybrid excitations can be used to control optical, electronic, and chemical properties.
This paper develops a nonequilibrium Green's function theory demonstrating that applied bias voltage can significantly enhance attractive dispersion interactions between nanostructures or even induce repulsion through population inversion, thereby generalizing the equilibrium London picture to open quantum systems.
This article establishes a unified framework for thermodynamic speed limits based on generalized means of various activities, derives an infinite variety of bounds for Markov jump processes and chemical reaction networks, and analyzes the tightness of their corresponding entropy production bounds.