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.

Scalable Preconditioners for the Pseudo-4D DFN Lithium-ion Battery Model

This paper proposes scalable, block-structured preconditioning strategies—combining multigrid techniques and localized solvers—to efficiently solve the large-scale, nonlinear systems generated by the high-fidelity pseudo-4D Doyle-Fuller-Newman lithium-ion battery model.

Thomas Roy, Nicholas W. Brady, Giovanna Bucci, Nicholas R. Cross, Victoria M. Ehlinger, Tiras Y. Lin, Hanyu Li, Marcus A. Worsley2026-02-10🔬 physics.app-ph

Analyzing Band Gaps in Ensemble Density Functional Theory using Thermodynamic Limits of Finite One-Dimensional Model Systems

This paper demonstrates that Ensemble Density Functional Theory (EDFT) is a promising approach for calculating band gaps in periodic systems by showing that, when applied to increasingly large one-dimensional Kronig-Penney models, it provides a reasonable correction to the Kohn-Sham gap in the thermodynamic limit.

Gregory G. V. Kenning, Remi J. Leano, David A. Strubbe2026-02-10🔬 cond-mat.mtrl-sci

Spinor Double-Quantum Excitation in the Solution NMR of Near-Equivalent Spin-1/2 Pairs

This paper describes new double-quantum excitation schemes for near-equivalent spin-1/2 pairs in solution NMR that utilize the spinor behavior of two-level systems to manipulate coherence phases through either symmetry-based pulse sequences or spin-lock-induced crossing (SLIC).

Urvashi D. Heramun, Mohamed Sabba, Dolnapa Yamano, Christian Bengs, Bonifac Legrady, Giuseppe Pileio, Sam Thompson, Malcolm H. Levitt2026-02-10⚛️ quant-ph

Cutting Through the Noise: On-the-fly Outlier Detection for Robust Training of Machine Learning Interatomic Potentials

This paper introduces an automated, unsupervised on-the-fly outlier detection method that uses an exponential moving average of the loss distribution to down-weight noisy training data, enabling the robust and efficient training of machine learning interatomic potentials without the need for manual filtering or additional expensive calculations.

Terry C. W. Lam, Niamh O'Neill, Christoph Schran, Lars L. Schaaf2026-02-10🔬 cond-mat.mtrl-sci