Canonical-Polyadic-Decomposition of the Potential Energy Surface Fitted by Warm-Started Support Vector RegressionIn this work, we propose a decoupled support vector regression (SVR) approach for direct canonical polyadic decomposition (CPD) of a potential energy surface (PES) through a set of discrete training…Zekai Miao, Xingyu Zhang, Qingfei Song et al.·Oct 31, 2024SaveLearn
Machine Learning Nonadiabatic Dynamics: Eliminating Phase Freedom of Nonadiabatic Couplings with the State-Intraction State-Averaged Spin-Restricted Ensemble-Referenced Kohn-Sham ApproachExcited-state molecular dynamics (ESMD) simulations near conical intersections (CIs) pose significant challenges when using machine learning potentials (MLPs). Although MLPs have gained recognition…Sung Wook Moon, Soohaeng Yoo Willow, Tae Hyeon Park et al.·Oct 30, 2024SaveLearn
Coupled-cluster theory for the ground state and for excitationsIn the molecular quantum chemistry community, coupled-cluster (CC) methods are well-recognized for their systematic convergence and reliability. The extension of the theory to extended systems has…Andreas Grüneis, Evgeny Moerman, Matthias Scheffler et al.·Oct 30, 2024SaveLearn
Transferability of the chemical bond-based machine learning model for dipole moment: the GHz to THz dielectric properties of liquid propylene glycol and polypropylene glycolWe conducted a first-principles study of the dielectric properties of liquid propylene glycol (PG) and polypropylene glycol (PPG) using a recently developed chemical bond-based machine learning (ML)…Tomohito Amano, Tamio Yamazaki, Naoki Matsumura et al.·Oct 30, 2024SaveLearn
Memory and Friction: From the Nanoscale to the MacroscaleFriction is a phenomenon that manifests across all spatial and temporal scales, from the molecular to the macroscopic scale. It describes the dissipation of energy from the motion of particles or…Benjamin A. Dalton, Anton Klimek, Henrik Kiefer et al.·Oct 29, 2024SaveLearn
Capturing the elusive curve-crossing in low-lying states of butadiene with dressed TDDFTA striking example of the need to accurately capture states of double-excitation character in molecules is seen in predicting photo-induced dynamics in small polyenes. Due to the coupling of…Davood B. Dar, Neepa T. Maitra·Oct 29, 2024SaveLearn
Fast and Scalable GPU-Accelerated Quantum Chemistry for Periodic Systems with Gaussian Orbitals: Implementation and Hybrid Density Functional Theory CalculationsEfficient hybrid DFT simulations of solid state materials would be extremely beneficial for computational chemistry and materials science, but is presently bottlenecked by difficulties in computing…Yuanheng Wang, Diptarka Hait, Pablo A. Unzueta et al.·Oct 29, 2024SaveLearn
CdTe0.25Se0.75 Quantum Dots as Efficient Room Temperature Single Photon Source for Quantum TechnologyRoom temperature single photon sources (SPS) are crucial for developing the next generation quantum technologies. Quantum dots (QDs), recently, have been reported as promising materials as SPS at…Kush Kaushik, Jiban Mondal, Ritesh Kumar Bag et al.·Oct 29, 2024SaveLearn
Realistic ab initio predictions of excimer behavior under collective light-matter strong couplingExperiments show that light-matter strong coupling affects chemical properties, though the underlying mechanism remains unclear. We present an ab initio quantum electrodynamics coupled cluster method…Matteo Castagnola, Marcus T. Lexander, Henrik Koch·Oct 29, 2024SaveLearn
Breaking the Million-Electron and 1 EFLOP/s Barriers: Biomolecular-Scale Ab Initio Molecular Dynamics Using MP2 PotentialsThe accurate simulation of complex biochemical phenomena has historically been hampered by the computational requirements of high-fidelity molecular-modeling techniques. Quantum mechanical methods,…Ryan Stocks, Jorge L. Galvez Vallejo, Fiona C. Y. Yu et al.·Oct 29, 2024SaveLearn
Mixed Atomistic-Implicit Quantum/Classical Approach to Molecular NanoplasmonicsA multiscale QM/classical approach is presented, that is able to model the optical properties of complex nanostructures composed of a molecular system adsorbed on metal nanoparticles. The latter are…Pablo Grobas Illobre, Piero Lafiosca, Luca Bonatti et al.·Oct 28, 2024SaveLearn
Excitation Energy Transfer between Porphyrin Dyes on a Clay Surface: A study employing Multifidelity Machine LearningNatural light-harvesting antenna complexes efficiently capture solar energy using chlorophyll, i.e., magnesium porphyrin pigments, embedded in a protein matrix. Inspired by this natural…Dongyu Lyu, Matthias Holzenkamp, Vivin Vinod et al.·Oct 27, 2024SaveLearn
Detection of Nanopores with the Scanning Ion Conductance Microscopy: A Simulation StudyDuring the dielectric breakdown process of thin solid-state nanopores, the application of high voltages may cause the formation of multi-nanopores on one chip, which number and sizes are important…Yinghua Qiu, Long Ma, Zhe Liu et al.·Oct 27, 2024SaveLearn
Modulation of ionic current rectification in short bipolar nanoporesBipolar nanopores, with asymmetric charge distributions, can induce significant ionic current rectification (ICR) at ultra-short lengths, finding potential applications in nanofluidic devices, energy…Hongwen Zhang, Long Ma, Chao Zhang et al.·Oct 27, 2024SaveLearn
Molecular Fingerprints of Ice Surfaces in Sum Frequency Generation Spectra: a First Principles Machine Learning StudyUnderstanding the molecular-level structure and dynamics of ice surfaces is crucial for deciphering several chemical, physical, and atmospheric processes. Vibrational sum-frequency generation (SFG)…Margaret L. Berrens, Marcos F. Calegari Andrade, John T. Fourkas et al.·Oct 25, 2024SaveLearn
Hyperfine rovibrational states of H3+ in a weak external magnetic fieldRovibrational energies, wave functions, and Raman transition moments are reported for the lowest-energy states of the H3+ molecular ion including the magnetic couplings of the proton spins and…Gustavo Avila, Ayaki Sunaga, Stanislav Komorovsky et al.·Oct 25, 2024SaveLearn
Binding memory of liquid moleculesUnderstanding the binding dynamics of liquid molecules is of fundamental importance in physical and life sciences. However, nanoscale fast dynamics pose great challenges for experimental…Shiyi Qin, Zhi Yang, Huimin Liu et al.·Oct 25, 2024SaveLearn
Physics-based inverse modeling of battery degradation with Bayesian methodsTo further improve Lithium-ion batteries (LiBs), a profound understanding of complex battery processes is crucial. Physical models offer understanding but are difficult to validate and parameterize.…Micha C. J. Philipp, Yannick Kuhn, Arnulf Latz et al.·Oct 25, 2024SaveLearn
Polarizable Water Model with Ab Initio Neural Network Dynamic Charges and Spontaneous Charge TransferSimulating water accurately has been a challenge due to the complexity of describing polarization and intermolecular charge transfer. Quantum mechanical (QM) electronic structures provide an accurate…Qiujiang Liang, Jun Yang·Oct 25, 2024SaveLearn
Electronic structure of norbornadiene and quadricyclaneThe ground and excited state electronic structure of the molecular photoswitches quadricyclane and norbornadiene is examined qualitatively and quantitatively. A new custom basis set is introduced,…Joseph C. Cooper, Adam Kirrander·Oct 25, 2024SaveLearn
An Open Quantum Chemistry Property Database of 120 Kilo Molecules with 20 Million ConformersArtificial intelligence is revolutionizing computational chemistry, bringing unprecedented innovation and efficiency to the field. To further advance research and expedite progress, we introduce the…Weiqi Liu, Xi Ai, Zhijian Zhou et al.·Oct 25, 2024SaveLearn
Phaseless auxiliary-field quantum Monte Carlo method for cavity-QED matter systemsWe present a generalization of the phaseless auxiliary-field quantum Monte Carlo (AFQMC) method to cavity quantum-electrodynamical (QED) matter systems. The method can be formulated in both the…Lukas Weber, Leonardo dos Anjos Cunha, Miguel A. Morales et al.·Oct 24, 2024SaveLearn
Enhancing Accuracy and Feature Insights in Hydration Free Energy Predictions for Small Molecules with Machine LearningThe accurate prediction of solvation free energy is of significant importance as it governs the behavior of solutes in solution. In this work, we apply a variety of machine learning techniques to…Mingjun Han, Yukai Zhang, Taotao Yu et al.·Oct 24, 2024SaveLearn
Eigenvalue crossings in equivariant families of matricesAccording to a result of Wigner and von Neumann [1], real symmetric matrices with a doubly degenerate lowest eigenvalue form a submanifold of codimension 2 within the space of all real symmetric…Jonathan Rawlinson·Oct 23, 2024SaveLearn
Liquid-Vapor Phase Equilibrium in Molten Aluminum Chloride (AlCl3) Enabled by Machine Learning Interatomic PotentialsMolten salts are promising candidates in numerous clean energy applications, where challenges in experimental methods limit knowledge of their safety-critical temperature-properties correlations.…Rajni Chahal, Luke D Gibson, Santanu Roy et al.·Oct 23, 2024SaveLearn