1032 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 two novel microfluidic platforms—one utilizing pillar arrays and the other employing a custom Pt-coated PMMA photomask—for the in situ micropatterning of PEGDA-PEG hydrogels to enable precise control and tracking of molecular diffusion for diverse applications ranging from biosensing to drug delivery.
This paper introduces a nonequilibrium instanton framework to demonstrate that path entropy, rather than thermodynamics, governs the stability of metastable spatial patterns in stochastic reaction-diffusion systems by modulating transition rates between competing phases.
This study resolves the long-standing puzzle of ice's slipperiness by demonstrating that while nanoscale simulations alone fail to predict the correct friction behavior, incorporating frictional heating—which raises contact temperatures to the melting point even at modest speeds—accurately reproduces experimental data and confirms the 1939 hypothesis by Bowden and Hughes that frictional heating is the primary driver of ice's low friction.
ChemFit is a flexible Python framework designed to streamline the parameterization of complex simulation-based models by enabling the definition, composition, and massively concurrent evaluation of heterogeneous objective functions in conjunction with gradient-free optimization algorithms.
This study demonstrates that the spin-opposite variant of one-body Møller-Plesset perturbation theory (O2BMP2) offers a computationally efficient and highly accurate method for predicting inverted singlet-triplet gaps in INVEST molecules, achieving benchmark-level precision comparable to high-cost methods like ADC(3) and EOM-CCSD while enabling high-throughput screening for OLED applications.
This paper demonstrates that the recently developed one-body Møller–Plesset perturbation theory (OBMP2), when applied within a SCF framework, provides a robust and highly accurate method for predicting K-edge excitation energies in both closed- and open-shell systems, outperforming established techniques like DFT and EOM-CCSD.
This paper introduces a physics-augmented machine learning framework that utilizes thermodynamic descriptors derived from molecular dynamics simulations to enable accurate and extrapolable prediction of normal boiling points for diverse chemical classes, including inorganic compounds and salts, where traditional structure-based models fail.
This paper presents a measurement-driven, ancilla-free quantum framework that evaluates overlap and Hamiltonian matrix elements for spin-coupled generalized valence bond wavefunctions using shallow local Pauli measurements, thereby enabling accurate, low-depth quantum assistance for nonorthogonal valence-bond electronic structure calculations on near-term hardware.
This paper presents a rigorous theoretical derivation of the one-body double-hybrid density functional (OBDHF) theory, which resolves the self-consistency issues of conventional double-hybrid functionals by embedding OBMP2 correlation directly into the generalized Kohn-Sham effective Hamiltonian to enable fully self-consistent calculations without requiring optimized effective potentials.
This study employs ab initio calculations to reveal that spin-phonon relaxation in Yb(III) molecular qubits is governed by non-trivial, delocalized phonon interactions that defy simple magneto-structural correlations, thereby advocating for predictive first-principles frameworks to guide future chemical design.