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.
The paper proposes a "compensated-SLIC" (cSLIC) method that uses a repetitive sequence with two different radiofrequency amplitudes to robustly correct for field amplitude deviations in strongly coupled NMR systems without increasing the total sequence duration.
This paper demonstrates that enzyme-coated colloids can be organized into chemical logic circuits that autonomously sense environmental signals and coordinate collective motion to perform specific tasks, such as identifying and suppressing invasive threats.
This paper establishes a comprehensive theoretical framework demonstrating that mirror symmetry in high-resolution NMR spectra arises from either the geometric bisymmetry of the Hamiltonian matrix or a more fundamental topological isospectrality, contingent upon the existence of a specific "palindromic" spin ordering that simultaneously balances resonance frequencies and J-coupling interactions.
The paper introduces ChemNavigator, an agentic AI system that autonomously integrates large language model reasoning with computational chemistry to discover six statistically significant, chemically grounded design rules for organic photocatalysts, outperforming previous machine learning approaches by independently deriving interpretable structure-property relationships through a hypothesis-driven scientific workflow.