From Free-Energy Profiles to Activation Free EnergiesGiven a chemical reaction going from reactant (R) to the product (P) on a potential energy surface (PES) and a collective variable (CV) that discriminates between R and P, one can define a…Johannes C. B. Dietschreit, Dennis J. Diestler, Andreas Hulm et al.·Jun 6, 2022SaveLearn
Benefits of Range-separated Hybrid and Double-Hybrid Functionals for a Large and Diverse Dataset of Reaction Energies and Barrier HeightsTo better understand the thermochemical kinetics and mechanism of a specific chemical reaction, an accurate estimation of barrier heights (forward and reverse) and reaction energy are vital. Due to…Golokesh Santra, Rivka Calinsky, Jan M. L. Martin·Jun 6, 2022SaveLearn
Quantum calculations on a new CCSD(T) machine-learned PES reveal the leaky nature of gas-phase trans and gauche ethanol conformersEthanol is a molecule of fundamental interest in combustion, astrochemistry, and condensed phase as a solvent. It is characterized by two methyl rotors and trans (anti) and gauche conformers,…Apurba Nandi, Riccardo Conte, Chen Qu et al.·Jun 6, 2022SaveLearn
Coupled electron pair-type approximations for tensor product state wavefunctionsSize extensivity, defined as the correct scaling of energy with system size, is a desirable property for any many-body method. Traditional CI methods are not size extensive hence the error increases…Vibin Abraham, Nicholas J. Mayhall·Jun 6, 2022SaveLearn
Open Challenges in Developing Generalizable Large Scale Machine Learning Models for Catalyst DiscoveryThe development of machine learned potentials for catalyst discovery has predominantly been focused on very specific chemistries and material compositions. While effective in interpolating between…Adeesh Kolluru, Muhammed Shuaibi, Aini Palizhati et al.·Jun 4, 2022SaveLearn
Computation of NMR shieldings at the CASSCF level using gauge-including atomic orbitals and Cholesky decompositionWe present an implementation of coupled-perturbed complete active space self-consistent field (CP-CASSCF) theory for the computation of nuclear magnetic resonance chemical shifts using…Tommaso Nottoli, Sophia Burger, Stella Stopkowicz et al.·Jun 4, 2022SaveLearn
Doped Graphene Quantum Dots UV-Vis Absorption Spectrum: A high-throughput TDDFT studyWe report on time-dependent density functional theory (TDDFT) calculations of the excited states of 63 different graphene quantum dots (GQDs) in square shape with side lengths 1 nm, 1.5 nm and 2 nm.…Şener Özönder, Caner Ünlü, Cihat Güleryüz et al.·Jun 4, 2022SaveLearn
Integral-direct Hartree-Fock and Møller-Plesset Perturbation Theory for Periodic Systems with Density Fitting: Application to the Benzene CrystalWe present an algorithm and implementation of integral-direct, density-fitted Hartree-Fock (HF) and second-order Møller-Plesset perturbation theory (MP2) for periodic systems. The new code eliminates…Sylvia J. Bintrim, Timothy C. Berkelbach, Hong-Zhou Ye·Jun 3, 2022SaveLearn
GPU-Accelerated Approximate Kernel Method for Quantum Machine LearningConventional kernel-based machine learning models for ab initio potential energy surfaces, while accurate and convenient in small data regimes, suffer immense computational cost as training set sizes…Nicholas J. Browning, Felix A. Faber, O. Anatole von Lilienfeld·Jun 3, 2022SaveLearn
Towards reliable calculations of thermal rate constants: ring polymer molecular dynamics for the OH + HBr Br + H2O reactionWe combined Moment Tensor Potential (MTP) and Ring Polymer Molecular Dynamics (RPMD) for calculating the thermal rate constants of the OH + HBr system. We used the active learning (AL) algorithm for…Ivan S. Novikov, Edgar M. Makarov, Alexander V. Shapeev et al.·Jun 3, 2022SaveLearn
Can vibrational sum frequency scattering spectra be measured from the surface of 40-100 nm aerosols in a cloud containing 106 particles/mL?Understanding the interfacial properties of aerosol particles is important for science and medicine, crucial for air quality, human health, and environmental chemistry. Qian et al. presented…Arianna Marchioro, Thaddeus W. Golbek, Adam S. Chatterley et al.·Jun 3, 2022SaveLearn
Machine learning the quantum flux-flux correlation function for catalytic surface reactionsA dataset of fully quantum flux-flux correlation functions and reaction rate constants was constructed for organic heterogeneous catalytic surface reactions. Gaussian process regressors were…Brenden G. Pelkie, Stephanie Valleau·Jun 3, 2022SaveLearn
Pulsed laser ablation in liquid of sp-carbon chains: status and recent advancesThis review provides a discussion of the current state of research on sp-carbon chains synthesized by pulsed laser ablation in liquid. In recent years, pulsed laser ablation in liquid (PLAL) has been…Pietro Marabotti, Sonia Peggiani, Alessandro Vidale et al.·Jun 2, 2022SaveLearn
Geometry of Nonequilibrium Chemical Reaction Networks and Generalized Entropy Production DecompositionsWe derive the Hessian geometric structure of nonequilibrium chemical reaction networks (CRN) on the flux and force spaces induced by the Legendre duality of convex dissipation functions and…Tetsuya J. Kobayashi, Dimitri Loutchko, Atsushi Kamimura et al.·Jun 2, 2022SaveLearn
Chemical reactions in imperfect cavities: enhancement, suppression, and resonanceThe use of optical cavities to control chemical reactions has been of great interest recently, following demonstrations of enhancement, suppression, and negligible effects on chemical reaction rates…John P. Philbin, Yu Wang, Prineha Narang et al.·Jun 2, 2022SaveLearn
A perspective on the current state-of-the-art of quantum computing for drug discovery applicationsComputational chemistry is an essential tool in the pharmaceutical industry. Quantum computing is a fast evolving technology that promises to completely shift the computational capabilities in many…Nick S. Blunt, Joan Camps, Ophelia Crawford et al.·Jun 1, 2022SaveLearn
Torsional Diffusion for Molecular Conformer GenerationMolecular conformer generation is a fundamental task in computational chemistry. Several machine learning approaches have been developed, but none have outperformed state-of-the-art cheminformatics…Bowen Jing, Gabriele Corso, Jeffrey Chang et al.·Jun 1, 2022SaveLearn
Regularized by Physics: Graph Neural Network Parametrized Potentials for the Description of Intermolecular InteractionsSimulations with an explicit description of intermolecular forces using electronic structure methods are still not feasible for many systems of interest. As a result, empirical methods such as force…Moritz Thürlemann, Lennard Böselt, Sereina Riniker·Jun 1, 2022SaveLearn
Connecting Entropy Scaling and Density ScalingIt is shown that the residual entropy (entropy minus that of the ideal gas at the same temperature and density) is mostly synonymous with the independent variable of density scaling, identifying a…Ian Bell, Robin Fingerhut, Jadran Vrabec et al.·May 31, 2022SaveLearn
Radio-Frequency Sweeps at μT Fields for Parahydrogen-Induced Polarization of BiomoleculesMagnetic resonance imaging of 13C-labeled metabolites enhanced by parahydrogen-induced polarization (PHIP) can enable real-time monitoring of processes within the body. We introduce a robust,…Alastair Marshall, Alon Salhov, Martin Gierse et al.·May 31, 2022SaveLearn
Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine LearningThis study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of…Jiace Sun, Lixue Cheng, Thomas F. Miller·May 31, 2022SaveLearn
Laser-induced dynamic alignment of the HD molecule without the Born-Oppenheimer approximationLaser-induced molecular alignment is well understood within the framework of the Born-Oppenheimer (BO) approximation Without the BO approximation, however, the concept of molecular structure is lost,…Ludwik Adamowicz, Simen Kvaal, Caroline Lasser et al.·May 30, 2022SaveLearn
Zero-Cost Corrections to Influence Functional Coefficients from Bath Response FunctionsRecent work has shown that it is possible to circumvent the calculation of the spectral density and directly calculate the coefficients of the discretized influence functionals using data from…Amartya Bose·May 30, 2022SaveLearn
Incorporation of density scaling constraint in density functional design via contrastive representation learningIn a data-driven paradigm, machine learning (ML) is the central component for developing accurate and universal exchange-correlation (XC) functionals in density functional theory (DFT). It is well…Weiyi Gong, Tao Sun, Hexin Bai et al.·May 30, 2022SaveLearn
Efficient Bosonic and Fermionic Sinkhorn Algorithms for Non-Interacting Ensembles in One-body Reduced Density Matrix Functional Theory in the Canonical EnsembleWe introduce 1-RDMFT in the canonical ensemble and then proceed to approximate the interacting ensemble by a non-interacting ensemble that maximizes the entropy, independently of temperature. Bosonic…Derk P. Kooi·May 30, 2022SaveLearn