Domain Decomposition Framework for Maxwell Finite Element Solvers and Application to PICThe most popular methods for self-consistent simulation of fields interacting with charged species is using finite difference time domain (FDTD) methods together with Newton's laws of motion to…Zane D. Crawford, O. H. Ramachandran, Scott O'Connor et al.·Apr 28, 2022SaveLearn
Mathematical formulae for neutron self-shielding properties of media in an isotropic neutron fieldThe complexity of the neutron transport phenomenon throws its shadows on every physical system wherever neutron is produced or used. In the current study, an ab initio derivation of the neutron…Ateia W. Mahmoud, Elsayed K. Elmaghraby, E. Salama et al.·Apr 28, 2022SaveLearn
Multi-scale membrane process optimization with high-fidelity ion transport models through machine learningInnovative membrane technologies optimally integrated into large separation process plants are essential for economical water treatment and disposal. However, the mass transport through membranes is…Deniz Rall, Artur M. Schweidtmann, Maximilian Krusea et al.·Apr 27, 2022SaveLearn
Micron-scale heterogeneous catalysis with Bayesian force fields from first principles and active learningQuantum-mechanically accurate reactive molecular dynamics (MD) at the scale of billions of atoms has been achieved for the heterogeneous catalytic system of H2/Pt(111) using the FLARE Bayesian…Anders Johansson, Yu Xie, Cameron J. Owen et al.·Apr 26, 2022SaveLearn
Studying First Passage Problems using Neural Networks: A Case Study in the Slit-Well Microfluidic DeviceThis study presents deep neural network solutions to a time-integrated Smoluchowski equation modeling the mean first passage time of nanoparticles traversing the slit-well microfluidic device. This…Andrew M. Nagel, Martin Magill, Hendrick W. de Haan·Apr 26, 2022SaveLearn
High-order Unified Gas-kinetic SchemeIn this paper, we present a high-order unified gas-kinetic scheme (UGKS) using the weighted essentially non-oscillatory with adaptive-order (WENO-AO) method for spatial reconstruction and the…Gyuha Lim, Yajun Zhu, Kun Xu·Apr 25, 2022SaveLearn
Improved random batch Ewald method in molecular dynamics simulationsThe random batch Ewald (RBE) is an efficient and accurate method for molecular dynamics (MD) simulations of physical systems at the nano-/micro- scale. The method shows great potential to solve the…Jiuyang Liang, Zhenli Xu, Yue Zhao·Apr 22, 2022SaveLearn
De-channeling in terms of instantaneous transition rates -- Computer simulations for 855 MeV electrons at (110) planes of diamondMonte-Carlo simulation calculation have been performed for 855 MeV electrons channeling in (110) planes of a diamond single crystal. The continuum potential picture has been utilized. Both, the…H. Backe·Apr 22, 2022SaveLearn
An effective introduction to the Markov Chain Monte Carlo methodWe present an intuitive, conceptual, but semi-rigorous introduction to the celebrated Markov Chain Monte Carlo method using a simple model of population dynamics as our motivation and focusing on a…Wenlong Wang·Apr 21, 2022SaveLearn
Temperature-dependent magnetism in Fe foams via spin-lattice dynamicsSpin-lattice dynamics is used to study the magnetic properties of Fe foams. The temperature dependence of the magnetization in foams is determined as a function of the fraction of surface atoms in…Robert Meyer, Felipe Valencia, Gonzalo dos Santos et al.·Apr 21, 2022SaveLearn
Thermodynamic modeling with uncertainty quantification using the modified quasichemical model in quadruplet approximation: Implementation into PyCalphad and ESPEIThe modified quasichemical model in the quadruplet approximation (MQMQA) considers the first- and the second-nearest-neighbor coordination and interactions, particularly useful in describing…Jorge Paz Soldan Palma, Rushi Gong, Brandon J. Bocklund et al.·Apr 19, 2022SaveLearn
Steering edge currents through a Floquet topological insulatorPeriodic driving may cause topologically protected, chiral transport along edges of a 2D lattice that, without driving, would be topologically trivial. We study what happens if one adds a different…Helena Drüeke, Marcus Meschede, Dieter Bauer·Apr 19, 2022SaveLearn
Topology-based Phase Identification of Bulk, Interface, and Confined Water using Edge-Conditioned Convolutional Graph Neural NetworkWater plays a significant role in various physicochemical and biological processes. Understanding and identifying water phases in various systems such as bulk, interface, and confined water is…Alireza Moradzadeh, Hananeh Oliaei, Narayana R. Aluru·Apr 15, 2022SaveLearn
Helicity-conservative Physics-informed Neural Network Model for Navier-Stokes EquationsWe design the helicity-conservative physics-informed neural network model for the Navier-Stokes equation in the ideal case. The key is to provide an appropriate PDE model as loss function so that its…Jiwei Jia, Young Ju Lee, Ziqian Li et al.·Apr 15, 2022SaveLearn
Characterizing metastable states with the help of machine learningPresent-day atomistic simulations generate long trajectories of ever more complex systems. Analyzing these data, discovering metastable states, and uncovering their nature is becoming increasingly…Pietro Novelli, Luigi Bonati, Massimiliano Pontil et al.·Apr 15, 2022SaveLearn
Thermodynamically consistent concurrent material and structure optimization of elastoplastic multiphase hierarchical systemsThe concept of concurrent material and structure optimization aims at alleviating the computational discovery of optimum microstructure configurations in multiphase hierarchical systems, whose…Tarun Gangwar, Dominik Schillinger·Apr 14, 2022SaveLearn
Dendrite formation in rechargeable lithium-metal batteries: Phase-field modeling using open-source finite element libraryWe describe a phase-field model for the electrodeposition process that forms dendrites within metal-anode batteries. We derive the free energy functional model, arriving at a system of partial…Marcos E. Arguello, Nicolas A. Labanda, Victor M. Calo et al.·Apr 14, 2022SaveLearn
Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of nanoscale heat transportDeep neural operators can learn operators mapping between infinite-dimensional function spaces via deep neural networks and have become an emerging paradigm of scientific machine learning. However,…Lu Lu, Raphael Pestourie, Steven G. Johnson et al.·Apr 14, 2022SaveLearn
The Transferability Limits of Static BenchmarksEvery practical method to solve the Schr\"odinger equation for interacting many-particle systems introduces approximations. Such methods are therefore plagued by systematic errors. For computational…Thomas Weymuth, Markus Reiher·Apr 13, 2022SaveLearn
BeAGLE: Benchmark eA Generator for LEptoproduction in high energy lepton-nucleus collisionsThe upcoming Electron-Ion Collider (EIC) will address several outstanding puzzles in modern nuclear physics. Topics such as the partonic structure of nucleons and nuclei, the origin of their mass and…Wan Chang, Elke-Caroline Aschenauer, Mark D. Baker et al.·Apr 13, 2022SaveLearn
Dynamic grain models via fast heuristics for diagram representationsThe present paper introduces a mathematical model for studying dynamic grain growth. In particular, we show how characteristic measurements, grain volumes, centroids, and central second-order moments…Andreas Alpers, Maximilian Fiedler, Peter Gritzmann et al.·Apr 13, 2022SaveLearn
Utilizing variational autoencoders in the Bayesian inverse problem of photoacoustic tomographyThere has been an increasing interest in utilizing machine learning methods in inverse problems and imaging. Most of the work has, however, concentrated on image reconstruction problems, and the…Teemu Sahlström, Tanja Tarvainen·Apr 13, 2022SaveLearn
Extracting resonance poles from numerical scattering data: type-II Pad\`e reconstructionWe present a FORTRAN 77 code for evaluation of resonance pole positions and residues of a numerical scattering matrix element in the complex energy (CE) as well as in the complex angular momentum…D. Sokolovski, E. Akhmatskaya, S. K. Sen·Apr 12, 2022SaveLearn
Plane-Wave-Based Stochastic-Deterministic Density Functional Theory for Extended SystemsTraditional finite-temperature Kohn-Sham density functional theory (KSDFT) has an unfavorable scaling with respect to the electron number or at high temperatures. The evaluation of the ground-state…Qianrui Liu, Mohan Chen·Apr 12, 2022SaveLearn
Learning Local Equivariant Representations for Large-Scale Atomistic DynamicsA simultaneously accurate and computationally efficient parametrization of the energy and atomic forces of molecules and materials is a long-standing goal in the natural sciences. In pursuit of this…Albert Musaelian, Simon Batzner, Anders Johansson et al.·Apr 11, 2022SaveLearn