physics.chem-ph papers | Gist.Science

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.

Microscopic Structure and Dynamics of Interfacial Water at Fluorinated vs Nonfluorinated Surfaces -- Insights from Ab-Initio Simulations and IR Spectroscopy

By combining large-scale ab-initio simulations with IR spectroscopy, this study reveals that while fluorinated surfaces exhibit macroscopic hydrophobicity, their interfacial water structure and slower reorientation dynamics are governed by dispersive rather than electrostatic interactions, resulting in unique spectroscopic signatures that defy simple classification as either hydrophobic or hydrophilic.

Maximilian R. Becker, Ruben Cruz, Kenichi Ataka, Joachim Heberle, Roland R. Netz2026-03-30🔬 cond-mat.mtrl-sci

Coupling Quantum Mechanical Modeling and Molecular Dynamics on Heterogeneous Supercomputers for Studying Distal Mutation Effects on Drug Binding in HIV-1

This study presents a scalable, heterogeneous supercomputing workflow that couples GPU-accelerated molecular dynamics with high-throughput quantum mechanical analysis to elucidate how distal mutations in HIV-1 protease induce Darunavir resistance through electronic structure changes, offering a pathway for designing more robust antiviral inhibitors.

William Dawson, Louis Beal, Marco Zaccaria, Luigi Genovese2026-03-30🔬 physics

Controlling isomer population using a dual-oscillator infrared free-electron laser

This paper demonstrates the control and characterization of isomer populations in singly deuterated proton-bound dimers of dihydrogen phosphate and formate within superfluid helium nanodroplets by utilizing a highly synchronized, tunable dual-oscillator infrared free-electron laser to record hidden infrared spectra of individual isomers.

América Y. Torres-Boy, Anoushka Ghosh, Myles B. T. Osenton, Akash C. Behera, Sandy Gewinner, Marco De Pas, Heinz Junkes, Wieland Schöllkopf, Alexander Paarmann, Gert von Helden, Gerard Meijer2026-03-30🔬 physics

Non-additive Ion Effects on the Coil-Globule Equilibrium of a Generic Uncharged Polymer

This study demonstrates through atomistic simulations that non-additive ion effects on the coil-globule equilibrium of thermoresponsive polymers can be reproduced using a generic uncharged polymer model with non-specific interactions, revealing that bulk ion-ion and ion-water interactions, rather than chemically specific polymer-anion binding, are the dominant drivers of these phenomena.

Kushagra Goel, Monika Choudhary, Swaminath Bharadwaj2026-03-30🔬 cond-mat

Coupled Lindblad pseudomode theory for simulating open quantum systems

This paper introduces a coupled Lindblad pseudomode theory that achieves efficient non-Markovian quantum dynamics simulation with polylogarithmic scaling in time and precision, featuring a robust numerical algorithm that eliminates non-convex optimization and demonstrates effectiveness across classical and quantum platforms.

Zhen Huang, Gunhee Park, Garnet Kin-Lic Chan, Lin Lin2026-03-27⚛️ quant-ph

Split-Flows: Measure Transport and Information Loss Across Molecular Resolutions

This paper introduces "split-flows," a novel flow-based framework that treats backmapping as a continuous-time measure transport to enable expressive conditional sampling of atomistic structures and, for the first time, provide a tractable method for computing mapping entropies to quantify information loss in coarse-grained molecular models.

Sander Hummerich, Tristan Bereau, Ullrich Köthe2026-03-27🔬 physics

On the Boroxol Ring Fraction in Melt-Quenched B $_2$ O $_3$ Glass

This study develops a DFT-accurate machine-learned potential and utilizes deep potential molecular dynamics with slow quench rates and extended geometry descriptors to successfully generate B $_2$ O $_3$ glass models containing over 30% boroxol rings, revealing that the energy-minimized boroxol fraction of 75% closely matches experimental estimates.

Debendra Meher, Nikhil V. S. Avula, Sundaram Balasubramanian2026-03-27🔬 cond-mat.mtrl-sci

Cyclic- and helical-symmetry-adapted phonon formalism within density functional perturbation theory

This paper presents a first-principles framework based on density functional perturbation theory that adapts phonon calculations for nanostructures with cyclic and helical symmetry, demonstrating high accuracy and physical consistency through applications to carbon nanotubes.

Abhiraj Sharma, Phanish Suryanarayana2026-03-27🔬 cond-mat.mtrl-sci

How unconstrained machine-learning models learn physical symmetries

This paper introduces rigorous metrics to analyze how unconstrained machine learning models learn physical symmetries, demonstrating that strategically injecting minimal inductive biases can achieve superior stability and accuracy while preserving the scalability of unconstrained architectures.

Michelangelo Domina, Joseph William Abbott, Paolo Pegolo, Filippo Bigi, Michele Ceriotti2026-03-27🤖 cs.LG

Autotuning T-PaiNN: Enabling Data-Efficient GNN Interatomic Potential Development via Classical-to-Quantum Transfer Learning

This paper introduces T-PaiNN, a transfer learning framework that pretrains graph neural network interatomic potentials on inexpensive classical force field data and fine-tunes them with limited quantum mechanical data, significantly improving accuracy and data efficiency for both gas-phase and condensed-phase systems compared to models trained solely on quantum data.

Vivienne Pelletier, Vedant Bhat, Daniel J. Rivera, Steven A. Wilson, Christopher L. Muhich2026-03-27🔬 physics

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