On the interpretation of molecular photoexcitation with long and ultrashort laser pulsesPhotoexcitation is an inherent part of any photochemical or spectroscopic experiment, yet its impact on the excited-state dynamics is often overlooked. However, it is the excited molecular state,…Jiří Janoš, Federica Agostini, Petr Slavíček et al.·Mar 6, 2026SaveLearn
Parity violation effects in helical osmocene: theoretical analysis and experimental prospectsWe present a computational investigation of the parity-violating (PV) contributions to the vibrational transitions and nuclear magnetic resonance shieldings of helical osmocene. A number of promising…Eduardus, Agathe Bonifacio, Mathieu Manceau et al.·Mar 6, 2026SaveLearn
MQED-QD: An Open-Source Package for Quantum Dynamics Simulation in Complex Dielectric EnvironmentsSimulating the dynamics of molecular excitons in complex nanophotonic environments requires integrating rigorous electromagnetic simulations with accurate treatments of open quantum system dynamics.…Guangming Liu, Siwei Wang, Hsing-Ta Chen·Mar 6, 2026SaveLearn
Real-Time Electron-Electron Scattering Dynamics in Plasmonic NanostructuresElectron-electron scattering is one of the most important hot carrier relaxation pathways in plasmonic nanoparticles. Understanding the dynamics of this scattering process and the effects of this on…Yanze Wu, George C. Schatz·Mar 5, 2026SaveLearn
Partial Information Decomposition of Electronic Observables Along a Reaction CoordinateA reaction-coordinate--resolved information-theoretic analysis of chemical reactivity is developed using mutual information and partial information decomposition (PID). Along an intrinsic reaction…Kyunghoon Han, Miguel Gallegos·Mar 5, 2026SaveLearn
Latent space design of interatomic potentialsThe advent of neural-network-based deep learning techniques has led to the emergence of increasingly sophisticated numerical interatomic potentials, including graph neural networks and large…Susan R. Atlas·Mar 5, 2026SaveLearn
Neural Wavefunction Calculations of μSR Spectra with Quantum Muons and ProtonsAccurate prediction of muon hyperfine constants is useful for interpreting muon spin spectroscopy data, yet standard methods such as density functional theory (DFT) compute muon-electron pair density…Jamie Carr, Mathias Volkai, W. M. C. Foulkes et al.·Mar 5, 2026SaveLearn
Benchmarking mixed quantum-classical dynamics for collective electronic strong couplingExperiments indicate that collective coupling of molecular ensembles to confined optical modes can modify excited-state dynamics and photochemical reactivity. To describe such cavity-induced effects…Arun Kumar Kanakati, Oriol Vendrell, Gerrit Groenhof·Mar 5, 2026SaveLearn
The Angular Localization Function (ALF): a practical tool to measure solvent angular order with Molecular Density Functional TheoryMolecular density functional theory is a powerful technique for efficiently computing the spatially and orientationally dependent equilibrium density of a molecular solvent around an arbitrary…Maïwenn Souetre, Benjamin Rotenberg, Guillaume Jeanmairet·Mar 5, 2026SaveLearn
Why Projection-Based DMRG-in-DFT Cannot Be Exact, Even with the Exact Exchange-Correlation FunctionalWe establish the theoretical foundations for embedding a correlated wave function in an environment formed by Kohn-Sham orbitals. We show that introducing an approximation which equates two, in…Enzo Monino, Daria Drwal, Michał Hapka et al.·Mar 5, 2026SaveLearn
Escaping the Hydrolysis Trap: An Agentic Workflow for Inverse Design of Durable Photocatalytic Covalent Organic FrameworksCovalent organic frameworks (COFs) are promising photocatalysts for solar hydrogen production, yet the most electronically favorable linkages, imines, hydrolyze rapidly in water, creating a…Iman Peivaste, Nicolas D. Boscher, Ahmed Makradi et al.·Mar 5, 2026SaveLearn
Particle-Guided Diffusion for Gas-Phase Reaction KineticsPhysics-guided sampling with diffusion model priors has shown promise for solving partial differential equation (PDE) governed problems, but applications to chemically meaningful reaction-transport…Andrew Millard, Henrik Pedersen·Mar 5, 2026SaveLearn
Viscosity as a Smoking Gun for Complex Formation in Solution: Fe2+ and Mg2+ Chlorides as ExamplesElectrolyte solutions at high concentration are indispensable and yet poorly understood. In particular, the extent of speciation -- the formation of complexes composed of multiple species -- in…Amrita Goswami, Samuel Blazquez, Lucía Fernández-Sedano et al.·Mar 5, 2026SaveLearn
Enhanced Third-Order Optical Nonlinearity in a Dipolar Carbene-Metal-Amide Material with Two-Photon Excited Delayed FluorescenceAdvanced photonic materials showing two-photon absorption (2PA) have been widely explored to develop three-dimensional imaging, micro and nanofabrication, all-optical switching, lithography on a…Ikechukwu D Nwosu, Lujo Matasović, Tárcius N Ramos et al.·Mar 5, 2026SaveLearn
Projected Hessian Learning: Fast Curvature Supervision for Accurate Machine-Learning Interatomic PotentialsThe Hessian matrix (second derivatives) encodes far richer local curvature of the potential energy surface than energies and forces alone. However, training machine-learning interatomic potentials…Austin Rodriguez, Justin S. Smith, Sakib Matin et al.·Mar 4, 2026SaveLearn
False Metallization in Short-Ranged Machine Learned Interatomic PotentialsMachine learned interatomic potentials (MLIPs) have enabled atomistic simulations with ab initio accuracy for a fraction of the computational cost. However, many widely used MLIPs are short-ranged…Isaac J. Parker, Mandy J. Hoffmann, William J. Baldwin et al.·Mar 4, 2026SaveLearn
Optimally Tuned Multiconfigurational Short-Range DFT for Linear Response PropertiesMulticonfigurational short-range density functional theory (MC-srDFT) rigorously combines ground state wavefunction theory with DFT. Unlike single-reference range-separated hybrid functionals,…Michał Hapka, Katarzyna Pernal, Ewa Pastorczak·Mar 4, 2026SaveLearn
Structure-resolved free energy estimation of the 38-atom Lennard Jones cluster via population annealingWe systematically investigate the thermodynamic landscape of the 38-atom Lennard--Jones cluster LJ38 using Population Annealing (PA), a method suited for systems with challenging double-funnel…Akie Kowaguchi, Koji Hukushima·Mar 4, 2026SaveLearn
Absolute Primary Nanothermometry Using Individual Stark Sublevels of Rare-Earth-doped CrystalsWe present two independent optical methods for absolute primary thermometry using rare-earth-doped nanoparticles. Both approaches rely exclusively on the internal energy levels and population…Allison R. Pessoa, Thomas Possmayer, Jefferson A. O. Galindo et al.·Mar 3, 2026SaveLearn
Expanding Universal Machine Learning Interatomic Potentials to 97 Elements Towards Nuclear ApplicationsMachine learning interatomic potentials (MLIPs) evaluate potential energy surfaces orders of magnitude faster while maintaining accuracy comparable to first-principles calculations, and universal…Naoya Kuroda, Kenji Ishihara, Tomoya Shiota et al.·Mar 3, 2026SaveLearn
A Perturbative Super-CI Approach for orbital optimization in Two-Component relativistic CASSCFIn this work, we develop a new orbital optimization approach, perturbative Super-CI (Super-CIPT), for the two-component complete active space self-consistent field (2C-CASSCF) method. By…Yang Guo, Achintya Kumar Dutta·Mar 3, 2026SaveLearn
ChemFlow:A Hierarchical Neural Network for Multiscale Representation Learning in Chemical MixturesAccurate prediction of the physicochemical properties of molecular mixtures using graph neural networks remains a significant challenge, as it requires simultaneous embedding of intramolecular…Jinming Fan, Chao Qian, Wilhelm T. S. Huck et al.·Mar 3, 2026SaveLearn
Hybrid Machine Learning for Enhanced Prediction of Diffusion Coefficients in LiquidsDiffusion coefficients are key thermophysical properties for modeling mass transport in liquids, but experimental data are scarce, making reliable prediction methods indispensable. In the present…Jens Wagner, Zeno Romero, Kerstin Münnemann et al.·Mar 3, 2026SaveLearn
Bayesian Optimization in Chemical Compound Sub-Spaces using Low-Dimensional Molecular DescriptorsEfficient optimization of molecules with targeted properties remains a significant challenge due to the vast size and discrete nature of chemical compound space. Conventional machine-learning-based…Yun-Wen Mao, Roman V. Krems·Mar 3, 2026SaveLearn
On the Reliability of AI Methods in Drug Discovery: Evaluation of Boltz-2 for Structure and Binding Affinity PredictionDespite continuing hype about the role of AI in drug discovery, no "AI-discovered drugs" have so far received regulatory approval. Here we assess one of the latest AI based tools in this domain. The…Shunzhou Wan, Xibei Zhang, Xiao Xue et al.·Mar 2, 2026SaveLearn