Comprehensive Study of L-Menthol and Octanoic Acid as a Hydrophobic Eutectic SolventHydrophobic eutectic solvents (HES) based on natural compounds represent promising green alternatives to conventional solvents. In this work, we investigate the physicochemical, structural, and…Bernarda Lovrinčević, Martina Požar, Romana Cerc Korošec et al.·Sep 9, 2026SaveLearn
Quantum-accurate atomistic modeling of enzyme catalysis using a machine learned potentialElectronic rearrangements associated with bond forming/breaking in catalytic enzymes require quantum mechanical (QM) treatment beyond classical molecular mechanics (MM). Hybrid QM/MM methods enable…Meng Gao, Armin Shayesteh Zadeh, Aniruddha Seal et al.·Sep 8, 2026SaveLearn
Multipole splats for optimized and inverted effective potentialsIn modern density functional theory, effective Hamiltonians are constructed to reproduce densities and forces of electrons at equilibrium. However, their nonlocal potentials leave systematic errors…Matija Medvidović, Angel Rubio, Juan Carrasquilla·Sep 8, 2026SaveLearn
Balanced and broadly-normed meta-generalized gradient approximationConventional semi-local density functional approximations for the exchange-correlation energy systematically underestimate fundamental band gaps. Advanced meta-generalized gradient approximations…Yanyong Wang, Chandra Shahi, John P. Perdew et al.·Sep 8, 2026SaveLearn
Orbital choice in constructing model HamiltoniansModel Hamiltonians (e.g., the Hubbard or Heisenberg models) provide a simple yet physically meaningful description of complex electronic phenomena through a small number of parameters, such as…David W. O. Sousa, Elvira R. Sayfutyarova·Sep 8, 2026SaveLearn
Examination of Cluster Based Methods to Fermionic SystemsWe present the cluster mean field(cMF) and its extensions into perturbation theory(cPT) and coupled cluster(cCC) methods for fermionic systems. We discuss how the commutation rules for fermionic…Jeffrey Keyes, Carlos Jimenez-Hoyos·Sep 8, 2026SaveLearn
TSBench: A physics-grounded benchmark for evaluating LLM understanding of chemical reaction mechanismsUnderstanding a chemical reaction requires mapping a symbolic reactant-product description onto the three-dimensional pathway through which atoms rearrange, yet chemistry benchmarks for large…Xiaohu Xu, Tong Zhu·Sep 8, 2026SaveLearn
Fixed-Dimensional Latent Flow for Generating Variable-Size 3D MoleculesMolecular size is coupled to composition, structure, and function, yet most 3D molecular generators require a predefined atom count. We introduce Equivariant-Free Transformer-Autoencoded Latent Flow…Weichi Yao, Cameron Gruich, Bryan R. Goldsmith et al.·Sep 8, 2026SaveLearn
Construction of downfolded Hamiltonians from projective transcorrelationProjective transcorrelation recovers the short-range electron correlation by a similarity transformation with a geminal function f(r12), at the cost of an effective Hamiltonian containing a…Seiichiro Ten-no·Sep 8, 2026SaveLearn
Hemoglycin as a Candidate for Permanent MemoryThe Hemoglycin polymer of glycine derived from space is terminated by iron and silicon to form a three-dimensional regular lattice with a high density of silicon tetrahedral vertices. Divalent cation…Julie E. M. McGeoch, Malcolm W. McGeoch·Sep 7, 2026SaveLearn
Simulation-Supervised Foundation Models for Retention Time Prediction in High-Performance Liquid Chromatography beyond Experimental Data CoverageAccurate prediction of high-performance liquid chromatography (HPLC) retention times (RTs) across diverse molecules and chromatographic methods remains challenging because experimental training data…Stephen Wu, Yufeng Han, Yasuhiro Mito et al.·Sep 7, 2026SaveLearn
Low-rank approximation of Moment Tensor Potential enables reducing training set size without loss of accuracyIn this study, we implement a low-rank approximation of Moment Tensor Potential (MTP) based on the tensor train (TT) decomposition. The implemented tensor-factorized MTP (TFMTP) and the original MTP…Anna Bondarenko, Nikita Rybin, Maxim Rakhuba et al.·Sep 7, 2026SaveLearn
Strong Evidence for Formation of Hydroxyl Anion via 2-Particle-1-Hole Feshbach ResonancesThis study investigates the formation of the hydroxyl anion (OH-) via dissociative electron attachment in 2-propanol as a model system for studying both organic and inorganic molecules. Using…Siddique Ali, Meenakshi Rana, Soumya Ghosh et al.·Sep 7, 2026SaveLearn
Mixed quantum-classical evolution in open molecular systemsWe consider a mixed quantum-classical formulation for open nonequilibrium molecular systems. We employ the pseudoparticle nonequilibrium Green's function (PP-NEGF) method as a fully quantum…Michael Galperin, Abraham Nitzan·Sep 7, 2026SaveLearn
First-order Degenerate Symmetry-Adapted Perturbation TheoryDegenerate electronic states govern the photophysics of excimers and the molecular dynamics near conical intersections. In regions where potential energy surfaces are degenerate or nearly degenerate,…Dominik Cieśliński, Tijs Karman, Anthony Scemama et al.·Sep 7, 2026SaveLearn
Out-of-Distribution Inverse Design of Elastic Networks with Differentiable Graph Neural Network Molecular DynamicsMachine-learning-based inverse design can accelerate the discovery of materials with targeted properties, but conventional structure--property models often require large training datasets and…Sergey A. Shteingolts, Salman N. Salman, Ron Levie et al.·Sep 6, 2026SaveLearn
Tensor-based Approximation of Molecular Kinetics: Generator Learning, Reaction Coordinates and Incremental UpdatingWe present an approach to analyze long-timescale kinetics of molecular dynamics simulations - meta-stable states and transition timescales - by a tensor-based approximation of the infinitesimal…Minakshi Verma, Peter Benner, Feliks Nüske·Sep 6, 2026SaveLearn
Performance of a minimally empirical local-hybrid density functional for molecular chemistryDelocalisation error has been argued to be the greatest outstanding challenge in density-functional theory (DFT). One of the most promising routes to minimise this error is development of local…Erin R. Johnson, Kyle R. Bryenton·Sep 5, 2026SaveLearn
cuSOAP: a GPU-accelerated Generator of Smooth Overlap of Atomic Positions DescriptorThe Smooth Overlap of Atomic Positions (SOAP) descriptor is one of the most widely adopted representations of atomic environments in molecular machine learning, but the cost of evaluating it and its…Hongyu Yan, Yuqing Xia, Yong Wei et al.·Sep 4, 2026SaveLearn
Differentiable Solvation Shell Model for Rational Electrolyte DesignTailoring Li+ solvation structures has emerged as a promising design principle across multiple Li metal battery (LMB) electrolytes, with localized high concentration electrolytes (LHCE) emerging as a…Hancheng Zhao, Hongyi Lin, Celia Kelly et al.·Sep 4, 2026SaveLearn
Polarizable Embedding for Photoelectron Spectroscopy and Photoelectron Circular Dichroism in Solution: Core-Level Ionization of Aqueous AlanineWe present a polarizable quantum-mechanics/molecular-mechanics formulation for the calculation of molecular photoionization observables in solution. The approach couples the static-exchange…Giovanni Nottoli, Piero Decleva. Chiara Cappelli·Sep 4, 2026SaveLearn
Measurements of Diffusion Coefficients of CO2 in 1-Butanol with a New Laminar Jet Apparatus and PFG-NMR, Pointing to Interfacial Mass Transfer EffectsA novel laminar jet apparatus (LJA) was constructed for precise gas-liquid mass transfer measurements up to 12 bar, significantly extending the technique's operating window. It was applied to…Oliver Großmann, Sarah Mross, Jens Wagner et al.·Sep 4, 2026SaveLearn
Operando imaging of intercalation memory in MXenesIon intercalation enables reversible control of charge, structure and function in layered solids. Yet layered materials contain nanosheets with different thicknesses and stacking, whose intercalation…Franz Groebmeyer, Mohsen Beladi, Christoph G. Gruber et al.·Sep 4, 2026SaveLearn
Derivation of the Sample-Size Scaling of TWO-NN Intrinsic-Dimension Estimates from Molecular Dynamics TrajectoriesThe intrinsic dimension of a dataset is the number of independent directions needed to describe the space occupied by its data. Estimators based on nearest neighbors infer this number from how the…Riccardo Capelli·Sep 4, 2026SaveLearn
Voltage-embedded equivariant machine learning potential for open system simulationsModeling electrochemical interfaces under operational non-equilibrium conditions is vital for energy technologies but remains bottlenecked by the expensive cost of ab initio methods. Current machine…Yiming Guan, Rongzhi Gao, ChiYung Yam et al.·Sep 4, 2026SaveLearn