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Chemical Physics
The newest papers in Chemical Physics that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
160 papers, from 4 September 2026 to 5 November 2026: 160 arXiv preprints.
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Spectral symmetry fingerprints in equivariant representations
Symmetry governs the organization of physical structures, while symmetry breaking reveals their transformations.OPRD-Imp: a dataset of experimentally observed impurities and side products in multi-step pharmaceutical syntheses
Predicting reaction impurities is a critical yet persistently data-limited challenge in pharmaceutical process chemistry.Towards Multiscale Molecular Representation Learning through Geometry-Based Fragmentation for Polymer Property Prediction
It is well established that molecular substructures can contribute unequally to chemical and physical properties, with specific motifs or side chains often playing dominant roles.Machine learning quantum data to accelerate quantum Monte Carlo
Simulating strongly correlated electrons in molecules and materials remains a central goal for quantum computing.Colloidal 2D WS2 nanosheets exhibiting high-purity single photon emission
The search for quantum emitters, delivering single photons "on demand" at cryogenic and elevated temperatures for photonic technologies is ever progressing.Discrete Backbone Elasticity and Curvature-Dependent Torsion Statistics in Proteins
Coarse-grained models of protein conformational dynamics use $\mathrm{C}_α$ geometry to describe the probabilities of regular helices, ordered turns and disordered conformations.Thermodynamics-Informed Learning Captures Hierarchical Hydrogen-Bond Networks in Deep Eutectic Solvents
Deep eutectic solvents (DESs) offer a tunable platform for lignocellulose refining, but their solvation behavior depends on multicomponent hydrogen-bond networks rather than individual constituent…Context-Aware Automated NMR Structure Elucidation
Machine learning approaches are rapidly revolutionizing the ability to analyze and extract structural insights from chemical data, enabling high-throughput chemical discovery.Formamide formation on forsterite and Mg(OH)$_2\cdot$H$_2$O
Formamide formation in the Universe has been the subject of debate due to its importance as a precursor to amino acids and RNA.Broken-Symmetry Reference States for Sample-Based Quantum Diagonalization with Near-DMRG Accuracy
Sample-based quantum diagonalization (SQD) accuracy remains limited for strongly correlated systems like iron-sulfur clusters.Efficient simulations of spectra and transport for multiorbital quantum impurities
Quantum impurity calculations become challenging when multiple correlated orbitals are treated explicitly, particularly in nonequilibrium steady states.FlowBatt: Flow Matching for Probabilistic Battery Degradation Prediction
Battery degradation remains a central challenge in the development and broad application of sustainable energy technologies.Restrained Diffusion Bridges: Targeted Denoiser Training and Refinement
Diffusion models are often inaccurate in critical, data-sparse regions of the target distribution.Complete Donor-Set Guidance for Frozen Diffusion Docking Models
Metalloprotein docking requires a ligand pose to satisfy both global pocket fit and the identity and geometry of metal-coordinating atoms.PeptSol: A Translational Benchmark for Protected-Peptide Solubility in Drug Manufacturing
Liquid-phase peptide synthesis (LPPS) offers a scalable route to peptide manufacturing, but route development still depends on empirical solvent screens because each protected intermediate must be…Quantum algorithm for weakly correlated molecular electronic ground states with sub-quintic scaling in the system size
Weakly correlated electronic structures are predominant among molecules, and are routinely solved with heuristic classical methods such as the ``gold standard'' CCSD(T) coupled cluster model…ROSE: Deep Learning exchange-correlation functional from reduced density-matrix representations
We introduce ROSE, a deep-learning exchange--correlation energy functional built from the occupied-state density matrix.Optimally Weighted Constrained Shadow Tomography for Reduced Density Matrices
Accurate measurement of reduced density matrices (RDMs) is central to quantum simulations of many-fermion systems, but the required measurement resources remain a significant challenge.Density functionals for the Pauli-Fierz Hamiltonian
We develop a density-functional theory for the Pauli-Fierz Hamiltonian of nonrelativistic quantum electrodynamics in the spirit of the convex-analytic formulation of Lieb.Graph-Covariant Bottom-Up Scale-Bridging Reconstruction of Ground and Excited States of Extended Systems
We propose a hierarchical scale-bridging construction for building first principles electronic structure models of extended molecular aggregates with disorder, and its practical realization in…
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