1002 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 proposes a path-integral hybrid Monte Carlo method with enveloping bridging potentials (PIHMC-EBP) that enables numerically exact, efficient, and automated calculation of tunneling splittings in molecular systems, achieving unprecedented precision and reduced computational costs for molecules like malonaldehyde, the HCl dimer, and the water dimer.
This paper introduces X-MACE, a transferable machine-learning potential combined with curvature-driven surface hopping, to efficiently screen fluorescent protein chromophores and reveal how steric crowding and conjugation extension govern their excited-state dynamics and fluorescence properties.
This Perspective reviews a 2023 community challenge where over 70 researchers used diverse computational methods to predict the photochemistry of cyclobutanone and its time-resolved MeV-UED signal, ultimately demonstrating the qualitative predictive power of nonadiabatic molecular dynamics while highlighting the critical impact of electronic-structure theory choices on simulation outcomes.
This study utilizes DFT simulations with various exchange-correlation functionals to analyze the pressure-enthalpy landscape, mechanical stability, and guest-dependent structural dynamics of methane and carbon dioxide structure I hydrates, revealing how CO₂'s rotational freedom and alignment within large cages differ from methane's behavior under hydrostatic loads.
This study quantitatively assesses the fidelity of two distinct machine-learned potential energy surfaces (PIP and PhysNet) for protonated oxalate by subjecting them to rigorous stress tests, including VSCF/VCI vibrational calculations and tunneling splitting evaluations requiring billions of energy evaluations, ultimately demonstrating that both methods yield excellent agreement in predicting key physical properties.
This paper presents an efficient, scalable implementation of relativistic linear-response coupled-cluster singles and doubles (LR-CCSD) theory that combines X2C-based Hamiltonians, Cholesky decomposition, and perturbation-sensitive natural spinor truncation to accurately compute polarizabilities for large molecular systems, such as Uranium Hexafluoride, while significantly reducing memory and computational costs.
This paper introduces EOM-fpCCSD, a computationally efficient equation-of-motion coupled-cluster method based on a pair coupled-cluster doubles reference that significantly improves the accuracy and convergence of doubly excited and charge-transfer state descriptions compared to standard EOM-CCSD and its pair-tailored variant.
This paper introduces SmileyLlama, a large language model transformed via supervised fine-tuning and direct preference optimization to function as a chemical language model that reliably generates novel drug-like molecules with user-specified properties and optimized 3D conformations.
This paper introduces the Seniority-zero Linear Canonical Transformation (SZ-LCT) method, which employs a specialized unitary transformation to map the electronic Hamiltonian into the computationally efficient seniority-zero space, achieving highly accurate results for strongly correlated systems with submilliHartree errors and favorable computational scaling.
This paper introduces a Seniority-Zero Canonical Transformation Theory that achieves high accuracy ( Hartree) for small- to medium-sized systems by exactly evaluating the first three commutators of a unitary transformation applied to a seniority-zero reference wavefunction, while approximating higher-order terms to reduce truncation errors.