Stochastic Representation of Time-Evolving Neural Network-based WavefunctionsSolving the time-dependent Schr\"odinger equation (TDSE) is pivotal for modeling non-adiabatic electron dynamics, a key process in ultrafast spectroscopy and laser-matter interactions. However, exact…Bizi Huang, Weizhong Fu, Ji Chen·Oct 1, 2025SaveLearn
Learning from the electronic structure of molecules across the periodic tableMachine-Learned Interatomic Potentials (MLIPs) require vast amounts of atomic structure data to learn forces and energies, and their performance continues to improve with training set size.…Manasa Kaniselvan, Benjamin Kurt Miller, Meng Gao et al.·Sep 30, 2025SaveLearn
Are neural scaling laws leading quantum chemistry astray?Neural scaling laws are driving the machine learning community toward training ever-larger foundation models across domains, assuring high accuracy and transferable representations for extrapolative…Siwoo Lee, Adji Bousso Dieng·Sep 30, 2025SaveLearn
Decoding Shake-up Satellites in XPS through Large-Scale ab initio Simulations: Spectral Signatures of Ring Fusion in PorphyrinsIn X-ray photoelectron spectroscopy (XPS), shake-up satellites arise when core ionization is accompanied by simultaneous charge-neutral valence excitations. Although these satellites can contain…Jannis Kockläuner, Majid Shaker, Maximilian Muth et al.·Sep 30, 2025SaveLearn
A Multimode Classical Hierarchical Fokker-Planck Equations Approach to Molecular Vibrations: Simulating Two-Dimensional SpectraThe multimode Brownian model with nonlinear system-bath coupling offers a flexible framework for studying both intra- and intermolecular vibrational modes in condensed-phase molecular systems. This…Ryotaro Hoshino, Yoshitaka Tanimura·Sep 30, 2025SaveLearn
Scalable Reactive Atomistic Dynamics with GAIAGroundbreaking advances in materials and chemical research have been driven by the development of atomistic simulations. However, the broader applicability of atomistic simulations remains limited,…Suhwan Song, Heejae Kim, Jaehee Jang et al.·Sep 30, 2025SaveLearn
Towards A Transferable Acceleration Method for Density Functional TheoryRecently, sophisticated deep learning-based approaches have been developed for generating efficient initial guesses to accelerate the convergence of density functional theory (DFT) calculations.…Zhe Liu, Yuyan Ni, Zhichen Pu et al.·Sep 30, 2025SaveLearn
Chiral Pt(Me-BPCH): Synthesis and theoretical investigation of parity violation sensitivityA complex of platinum and the tetra-coordinate chelating ligand, R,R'-6,6'-dimethyl-N,N'-bis(2'-pyridine-carboxamide)-1-cyclohexane (Me-BPCH) is investigated as a potential candidate…Eduardus, J. Wietze J. van Boven, Charles Silva et al.·Sep 30, 2025SaveLearn
n-alkanoate + n-alkane mixtures: folding of hydrocarbon chains of n-alkanoatesThe mixtures CH3(CH2)u-1COO(CH2)v-1CH3 (u=5-13, v=1,2; u=1,2,3, v=3,4; u=1,2,4, v=5) + n-alkane have been investigated using experimental data (viscosity and excess…Juan Antonio González, Fernando Hevia, Luis Felipe Sanz et al.·Sep 29, 2025SaveLearn
Sinc basis set for molecular orbitals calculation of cavity in 1DWe develop a numerical approach based on the sinc basis set for first-principles electronic structure calculations in one-dimensional systems. The method exploits the inherent accuracy and non-local…Xueyuan Yan·Sep 29, 2025SaveLearn
Observation of Iron Oxide to Nitride Conversion via Liquid Liquid Phase Separation in High pressure Borate MeltHigh pressure chemistry provides a powerful route to materials that are inaccessible or difficult to synthesize under ambient conditions. However, high pressure chemical reaction processes and…Yu Tao, Depu Liu, Chunyin Zhou et al.·Sep 29, 2025SaveLearn
Excitonic Energy Transfer in Red Algal Photosystem I Reveals an Evolutionary Bridge between Cyanobacteria and PlantsPhotosystem I converts light into chemical energy with near-unity quantum efficiency,yet its energy-transfer and charge-separation mechanisms remain debated. Evolution has diversified PSI…Mengyuan Cui, Zihui Liu, Miriam Izzo et al.·Sep 29, 2025SaveLearn
Enhancing Molecular Dipole Moment Prediction with Multitask Machine LearningWe present a multitask machine learning strategy for improving the prediction of molecular dipole moments by simultaneously training on quantum dipole magnitudes and inexpensive Mulliken atomic…William Colglazier, Nicholas Lubbers, Sergei Tretiak et al.·Sep 26, 2025SaveLearn
Development of an Optimized Parameter Set for Monovalent Ions in the Reference Interaction Site Model of SolvationAccurate modeling of aqueous monovalent ions is essential for understanding the function of biomolecules, such as nucleic acid stability and binding of charged drugs to protein targets. The 1D and 3D…Felipe Silva Carvalho, Alexander McMahon, David A. Case et al.·Sep 26, 2025SaveLearn
Noise-reduced stochastic resolution of identity to CC2 for large-scale calculations via tensor hypercontractionThe stochastic resolution of identity (sRI) approximation significantly reduces the computational scaling of CC2 from O(N5) to O(N3), where N is a measure of system size. However, the inherent…Chongxiao Zhao, Wenjie Dou·Sep 26, 2025SaveLearn
Automated Workflow for Absolute Binding Free Energy Calculations with Implicit Solvent and Double DecouplingAccurate absolute binding free energy (ABFE) calculations can reduce the time and cost of identifying drug candidates from a diverse pool of molecules that may have been overlooked experimentally.…Steven Ayoub, Michael Barton, David A. Case et al.·Sep 26, 2025SaveLearn
Multireference equation-of-motion driven similarity renormalization group for X-ray photoelectron spectraWe formulate and implement the core-valence separated multireference equation-of-motion driven similarity renormalization group method (CVS-IP-EOM-DSRG) for simulating X-ray photoelectron spectra…Shuhang Li, Zijun Zhao, Francesco A. Evangelista·Sep 25, 2025SaveLearn
PhenoMoler: Phenotype-Guided Molecular Optimization via Chemistry Large Language ModelCurrent molecular generative models primarily focus on improving drug-target binding affinity and specificity, often neglecting the system-level phenotypic effects elicited by compounds.…Ran Song, Hui Liu·Sep 25, 2025SaveLearn
MLIP Arena: Advancing Fairness and Transparency in Machine Learning Interatomic Potentials via an Open, Accessible Benchmark PlatformMachine learning interatomic potentials (MLIPs) have revolutionized molecular and materials modeling, but existing benchmarks suffer from data leakage, limited transferability, and an over-reliance…Yuan Chiang, Tobias Kreiman, Christine Zhang et al.·Sep 25, 2025SaveLearn
Numerically exact quantum dynamics with tensor networks: Predicting the decoherence of interacting spin systemsPredicting the quantum dynamics of promising solid-state and molecular quantum technology candidates remains a formidable challenge. Yet, accessing these dynamics is key to understanding and…Tianchu Li, Pranay Venkatesh, Nanako Shitara et al.·Sep 24, 2025SaveLearn
A relativistic coupled-cluster treatment of magnetic hyperfine structure of the X2 and A2+ states of OH isotopologuesAb initio calculations of the parallel component of the magnetic dipole hyperfine structure (HFS) constant have been carried out for hydroxyl radical isotopologues (16,17OH(D)) over…D. P. Usov, Y. S. Kozhedub, A. V. Stolyarov et al.·Sep 24, 2025SaveLearn
Scalable Machine Learning Model for Energy Decomposition Analysis in Aqueous SystemsEnergy decomposition analysis (EDA) based on absolutely localized molecular orbitals provides detailed insights into intermolecular bonding by decomposing the total molecular binding energy into…Hossein Tahmasbi, Michael Beerbaum, Bartosz Brzoza et al.·Sep 24, 2025SaveLearn
Colossal Effect of Nanopore Surface Ionic Charge on the Dynamics of Confined WaterInterfacial interactions significantly alter the fundamental properties of water confined in mesoporous structures, with crucial implications for geological, physicochemical, and biological…Armin Mozhdehei, Philip Lenz, Stella Gries et al.·Sep 24, 2025SaveLearn
Computation of the heat capacity of water from first principlesWater is a unique solvent with many remarkable properties. An example is its exceptionally high heat capacity, which plays an important role in storing and transporting thermal energy, with…Motoyuki Shiga, Jan Elsner, Jörg Behler et al.·Sep 24, 2025SaveLearn
SMILES-Inspired Transfer Learning for Quantum Operators in Generative Quantum EigensolverGiven the inherent limitations of traditional Variational Quantum Eigensolver(VQE) algorithms, the integration of deep generative models into hybrid quantum-classical frameworks, specifically the…Zhi Yin, Xiaoran Li, Shengyu Zhang et al.·Sep 24, 2025SaveLearn