1044 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 demonstrates that the ChemBFN model, enhanced by a semi-autoregressive strategy, reinforcement learning, and a controllable ODE solver, effectively overcomes the limitations of traditional distribution-learning methods to generate high-quality out-of-distribution molecules for de novo drug design.
This paper reviews the foundational theory of Brownian motion from Einstein and Langevin to modern stochastic thermodynamics and fluctuation theorems, while also analyzing non-Markovian dynamics through generalized Langevin equations to elucidate the fluctuation-dissipation relation and the effective-mass framework.
This paper introduces and experimentally validates a novel quantum J-oscillator that utilizes intrinsic nuclear spin-spin couplings in a zero magnetic field with digital feedback to achieve ultra-narrow linewidths, enabling high-precision spectroscopy and serving as a compact platform for exploring complex nonlinear spin dynamics.
This paper introduces DD-13M, a novel 4-D trajectory database containing over 26,000 complete ligand-protein dissociation processes, and utilizes it to train UnbindingFlow, a deep generative model capable of predicting dissociation dynamics and rate constants for new drug targets.
This paper introduces the Microsoft Research Accurate Chemistry Collection (MSR-ACC), specifically its initial release MSR-ACC/TAE25, which provides a comprehensive dataset of over 73,000 high-accuracy CCSD(T) atomization energies for closed-shell neutral molecules to enable the development of predictive data-driven computational chemistry methods across a broad chemical space.
This study demonstrates that the neural canonical transformation (NCT) approach, when applied to atomic coordinates, successfully calculates the ground and excited vibrational spectra of the highly fluxional CH5+ molecule by effectively capturing its anharmonic effects and nuclear quantum delocalization.
The paper introduces , a GPU-accelerated implementation of the stochastic Resolution of the Identity GW method that enables rapid, semi-linear scaling calculations of quasi-particle energies for massive molecular systems exceeding 10,000 atoms with high precision.
This paper introduces a stochastic cluster expansion framework that enables near-DMRG accuracy for total correlation energies in large condensed-phase systems by combining exactly treated subspaces with randomly sampled environment orbitals, thereby eliminating the need for prior active space selection and facilitating high-accuracy studies of chemical processes in complex environments.
This study introduces a novel numerical model demonstrating that aligning graphene sheets parallel to the substrate significantly reduces corrosive substance diffusion and delays corrosion initiation by up to 65 times compared to perpendicular alignment, a finding validated by experimental data.
This paper combines simulations and experiments to identify and quantify four distinct mechanisms, primarily involving break-in processes and high prelithiation, that cause anomalous early-life capacity gains in silicon-containing lithium-ion cells by altering electrode potentials and increasing the accessible lithium inventory.