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 establishes a finite-element weak formulation and a stable numerical scheme for solving the Bloch equations with distant dipolar fields on bounded domains, proving local well-posedness and energy stability while enabling accurate simulations of complex geometries through a matrix-free real-space evaluation and second-order IMEX time-stepping.
This paper proposes a Central-Peripheral Distillation (CPD) algorithm that significantly improves the training efficiency of machine learning force fields in phase transition regimes by distilling a highly diverse dataset of just 200 representative and critical configurations, enabling accurate simulation of liquid hydrogen's structural and dynamical properties.
This study demonstrates that while photodissociation of ammonia in cometary ice analogs can account for most observed molecular nitrogen, the substantial carbon monoxide abundances in many comets likely require low-temperature entrapment rather than in-situ chemical processing.
This paper presents a thermodynamically consistent entropy scaling framework that successfully predicts self- and mutual diffusion coefficients in fluid mixtures across a wide range of states, including non-ideal systems, by leveraging pure component self-diffusion data, infinite-dilution coefficients, and molecular-based equations of state.
This paper introduces a "freeze-and-release" direct optimization method that successfully achieves variational orbital optimization for excited electronic states, particularly charge transfer excitations, by preventing variational collapse and correctly describing energy dependencies without requiring long-range exact exchange, where conventional maximum overlap methods often fail.
This paper introduces Point Group Order Parameters (PGOPs) as a new set of metrics to directly quantify local point-group symmetry in complex particle systems, demonstrating their superior utility in detecting crystalline order compared to traditional bond-orientational parameters and providing their implementation in the open-source SPATULA software package.
The authors demonstrate that the intense chiral asymmetry typically observed in photoelectron angular distributions can be translated into a measurable total photoionization yield for submicron-sized chiral nanoparticles, enabling highly sensitive enantiopurity analysis without the need for high-vacuum electron spectrometers.
This paper presents a method combining variational orbital optimization with plane-wave basis sets and neural-network-assisted configuration interaction to accurately calculate Rydberg states of molecules, overcoming the limitations of traditional diffuse atomic basis sets and achieving results in close agreement with experimental data.
This study utilizes machine-learning-enabled simulations to demonstrate that while anisotropic electronic friction significantly influences the rate of energy transfer and reaction probabilities during laser-driven hydrogen recombination on copper, the final molecular energy distributions are primarily governed by the potential energy landscape rather than the friction anisotropy.
The paper introduces Hyperion, a high-performance, GPU-accelerated quantum emulator that combines exact sparse matrix-vector kernels with a novel partitioned SV-MPS strategy to enable accurate simulations of strongly correlated chemical systems ranging from 32 to 40 qubits, thereby bridging the gap between current quantum hardware limitations and the need for rigorous algorithm validation.