Predicting elastic and plastic properties of small iron polycrystals by machine learningDeformation of crystalline materials is an interesting example of complex system behaviour. Small samples typically exhibit a stochastic-like, irregular response to externally applied stresses,…Marcin Mińkowski, Lasse Laurson·Feb 27, 2023SaveLearn
Hybrid functionals for periodic systems in the density functional tight-binding methodScreened range-separated hybrid (SRSH) functionals within generalized Kohn-Sham density functional theory (GKS-DFT) have been shown to restore a general 1/(r) asymptotic decay of the…Tammo van der Heide, Bálint Aradi, Ben Hourahine et al.·Feb 24, 2023SaveLearn
Adaptive weighting of Bayesian physics informed neural networks for multitask and multiscale forward and inverse problemsIn this paper, we present a novel methodology for automatic adaptive weighting of Bayesian Physics-Informed Neural Networks (BPINNs), and we demonstrate that this makes it possible to robustly…Sarah Perez, Suryanarayana Maddu, Ivo F. Sbalzarini et al.·Feb 24, 2023SaveLearn
Comparative study of the physical properties for the A2TiX6 (A= Cs or NH4 and X= Cl or Br) vacancy-ordered double perovskitesThe vacancy-ordered double perovskites (VODP) are emerging materials for the renewable energy because of their extraordinary stability. In the present work, we have addressed the structural,…M. Talebi, A. Mokhtari·Feb 24, 2023SaveLearn
Strain-driven phonon topological phase transition impedes thermal transport in titanium monoxideTopological phonon states in crystalline materials have attracted significant research interests due to their importance for fundamental physical phenomena, yet their implication on phonon thermal…Xin Jin, Da-shuai Ma, Peng Yu et al.·Feb 24, 2023SaveLearn
Differentiable Rotamer Sampling with Molecular Force FieldsMolecular dynamics is the primary computational method by which modern structural biology explores macromolecule structure and function. Boltzmann generators have been proposed as an alternative to…Congzhou M. Sha, Jian Wang, Nikolay V. Dokholyan·Feb 22, 2023SaveLearn
Nevanlinna.jl: A Julia implementation of Nevanlinna analytic continuationWe introduce a Julia implementation of the recently proposed Nevanlinna analytic continuation method. The method is based on Nevanlinna interpolants and, by construction, preserves the causality of a…Kosuke Nogaki, Jiani Fei, Emanuel Gull et al.·Feb 21, 2023SaveLearn
Discretized hierarchical equations of motion in mixed Liouville--Wigner space for two-dimensional vibrational spectroscopies of liquid waterA model of a bulk water system describing the vibrational motion of intramolecular and intermolecular modes is constructed, enabling analysis of its linear and nonlinear vibrational spectra, as well…Hideaki Takahashi, Yoshitaka Tanimura·Feb 20, 2023SaveLearn
A Simple and Fast Approach for Computing the Fusion Reactivities with Arbitrary Ion Velocity DistributionsCalculating fusion reactivity involves a complex six-dimensional integral of the fusion cross section and ion velocity distributions of two reactants. We demonstrate a simple Monte Carlo approach…Huasheng Xie·Feb 20, 2023SaveLearn
GPU acceleration of local and semilocal density functional calculations in the SPARC electronic structure codeWe present a GPU-accelerated version of the real-space SPARC electronic structure code for performing Kohn-Sham density functional theory calculations within the local density and generalized…Abhiraj Sharma, Alfredo Metere, Phanish Suryanarayana et al.·Feb 20, 2023SaveLearn
On the accuracy of a recent regularized nuclear potentialF. Gygi recently suggested an analytic, norm-conserving, regularized nuclear potential to enable all-electron plane-wave calculations [J. Chem. Theory Comput. 2023, 19, 1300--1309]. This potential…Susi Lehtola·Feb 19, 2023SaveLearn
Predicting structure-dependent Hubbard U parameters for assessing hybrid functional-level exchange via machine learningDFT+U is a widely used treatment in the density functional theory (DFT) to deal with correlated materials that contain open-shell elements, whereby the quantitative and sometimes even qualitative…Zhendong Cao, Guanghui Cai, Fankai Xie et al.·Feb 19, 2023SaveLearn
Accurate prediction of heat conductivity of water by a neuroevolution potentialWe propose an approach that can accurately predict the heat conductivity of liquid water. On the one hand, we develop an accurate machine-learned potential based on the neuroevolution-potential…Ke Xu, Yongchao Hao, Ting Liang et al.·Feb 18, 2023SaveLearn
Edge Dynamics in Iron-Cluster Catalyzed Growth of Single-Walled Carbon Nanotubes Revealed by Molecular Dynamics Simulations based on a Neural Network PotentialGiven the high potential for applications utilizing the unique properties of single-walled carbon nanotubes (SWCNTs), there is considerable enthusiasm for addressing the challenges associated with…Ikuma Kohata, Ryo Yoshikawa, Kaoru Hisama et al.·Feb 18, 2023SaveLearn
De novo structural ensemble determination from single-molecule X-ray scattering: A Bayesian approachSingle molecule X-ray scattering experiments with free electron lasers have opened a new route to the structure determination of biomolecules. Because typically only very few photons per scattering…Steffen Schultze, Helmut Grubmüller·Feb 17, 2023SaveLearn
Multi-body wave function of ground and low-lying excited states using unornamented deep neural networksWe propose a method to calculate wave functions and energies not only of the ground state but also of low-lying excited states using a deep neural network and the unsupervised machine learning…Tomoya Naito, Hisashi Naito, Koji Hashimoto·Feb 17, 2023SaveLearn
magnum.np -- A PyTorch based GPU enhanced Finite Difference Micromagnetic Simulation Framework for High Level Development and Inverse Designmagnum.np is a micromagnetic finite-difference library completely based on the tensor library PyTorch. The use of such a high level library leads to a highly maintainable and extensible code base…Florian Bruckner, Sabri Koraltan, Claas Abert et al.·Feb 17, 2023SaveLearn
Deep Ensembles vs. Committees for Uncertainty Estimation in Neural-Network Force Fields: Comparison and Application to Active LearningA reliable uncertainty estimator is a key ingredient in the successful use of machine-learning force fields for predictive calculations. Important considerations are correlation with error, overhead…Jesús Carrete, Hadrián Montes-Campos, Ralf Wanzenböck et al.·Feb 17, 2023SaveLearn
Symbiotic Dynamics in Living Liquid CrystalsAn amalgamate of nematic liquid crystals and active matter, referred to as living liquid crystals, is a promising self-healing material with futuristic applications for targeted delivery of…Aditya Vats, Pradeep Kumar Yadav, Varsha Banerjee et al.·Feb 17, 2023SaveLearn
Temperature effects on the point defects formation in [111] W by neutron induced collision cascadeTungsten is used as plasma-facing wall in ITER where it is subjected to extreme operating conditions. In this work, we study the damage formation in [111] crystalline W by neutron bombardment in the…F. J. Domínguez-Gutiérrez·Feb 17, 2023SaveLearn
Enhanced Sampling of Configuration and Path Space in a Generalized Ensemble by Shooting Point ExchangeThe computer simulation of many molecular processes is complicated by long time scales caused by rare transitions between long-lived states. Here, we propose a new approach to simulate such rare…Sebastian Falkner, Alessandro Coretti, Christoph Dellago·Feb 17, 2023SaveLearn
Solution of Volume Integral and Hydrodynamic Equations to Analyze Electromagnetic Scattering from Composite NanostructuresA coupled system of volume integral and hydrodynamic equations is solved to analyze electromagnetic scattering from nanostructures consisting of metallic and dielectric parts. In the metallic part,…Doolos Aibek Uulu, Rui Chen, Liang Chen et al.·Feb 16, 2023SaveLearn
Multimap targeted free energy estimationWe present a new method to compute free energies at a quantum mechanical (QM) level of theory from molecular simulations using cheap reference potential energy functions, such as force fields. To…Andrea Rizzi, Paolo Carloni, Michele Parrinello·Feb 15, 2023SaveLearn
A GPU-Parallelized Interpolation-Based Fast Multipole Method for the Relativistic Space-Charge Field CalculationThe fast multipole method (FMM) has received growing attention in the beam physics simulation. In this study, we formulate an interpolation-based FMM for the computation of the relativistic…Yi-Kai Kan, Franz X. Kärtner, Sabine Le Borne et al.·Feb 15, 2023SaveLearn
GRIDS-Net: Inverse shape design and identification of scatterers via geometric regularization and physics-embedded deep learningThis study presents a deep learning based methodology for both remote sensing and design of acoustic scatterers. The ability to determine the shape of a scatterer, either in the context of material…Siddharth Nair, Timothy F. Walsh, Greg Pickrell et al.·Feb 15, 2023SaveLearn