Toward Routing River Water in Land Surface Models with Recurrent Neural NetworksMachine learning is playing an increasing role in hydrology, supplementing or replacing physics-based models. One notable example is the use of recurrent neural networks (RNNs) for forecasting…Mauricio Lima, Katherine Deck, Oliver R. A. Dunbar et al.·Apr 22, 2024SaveLearn
Basis Function Dependence of Estimation Precision for Synchrotron-Radiation-Based M\"ossbauer SpectroscopyM\"ossbauer spectroscopy is a technique employed to investigate the microscopic properties of materials using transitions between energy levels in the nuclei. Conventionally, in…Binsheu Shieh, Ryo Masuda, Satoshi Tsutsui et al.·Apr 22, 2024SaveLearn
Quantum Transport Simulation of Sub-1-nm Gate Length Monolayer MoS2 TransistorsSub-1-nm gate length MoS2 transistors have been experimentally fabricated, but their device performance limit remains elusive. Herein, we explore the performance limits of the sub-1-nm gate length…Ying Li, Yang Shen, Linqiang Xu et al.·Apr 21, 2024SaveLearn
Scale-bridging within a complex model hierarchy for investigation of a metal-fueled circular energy economy by use of Bayesian model calibration with model error quantificationMetal energy carriers recently gained growing interest in research as a promising storage and transport material for renewable electricity. Within the development of a metal-fueled circular energy…Lisanne Gossel, Elisa Corbean, Sören Dübal et al.·Apr 18, 2024SaveLearn
Exploring the Premelting Transition through Molecular Simulations Powered by Neural Network PotentialsThe system has addressed the error of "Bad character(s) in field Abstract" for no reason. Please refer to manuscript for the full abstract.Limin Zeng, Ang Gao·Apr 18, 2024SaveLearn
Mean field initialization of the Annealed Importance Sampling algorithm for an efficient evaluation of the Partition Function of Restricted Boltzmann MachinesProbabilistic models in physics often require from the evaluation of normalized Boltzmann factors, which in turn implies the computation of the partition function Z. Getting the exact value of Z,…A. Prat Pou, E. Romero, J. Martí et al.·Apr 17, 2024SaveLearn
AI-equipped scanning probe microscopy for autonomous site-specific atomic-level characterization at room temperatureWe present an advanced scanning probe microscopy system enhanced with artificial intelligence (AI-SPM) designed for self-driving atomic-scale measurements. This system expertly identifies and…Zhuo Diao, Keiichi Ueda, Linfeng Hou et al.·Apr 17, 2024SaveLearn
Deep Learning Methods for Colloidal Silver Nanoparticle Concentration and Size Distribution Determination from UV-Vis Extinction SpectraElectron microscopy, while reliable, is an expensive, slow, and inefficient technique for thorough size distribution characterization of both mono- and polydisperse colloidal nanoparticles. If rapid…Tomas Klinavičius, Nadzeya Khinevich, Asta Tamulevičienė et al.·Apr 16, 2024SaveLearn
Numerical methods and improvements for simulating quasi-static elastoplastic materialsHypo-elastoplasticity is a framework suitable for modeling the mechanics of many hard materials that have small elastic deformation and large plastic deformation. In most laboratory tests for these…Jiayin Lu, Chris H. Rycroft·Apr 16, 2024SaveLearn
Enhancing GPU-acceleration in the Python-based Simulations of Chemistry FrameworkWe describe our contribution as industrial stakeholders to the existing open-source GPU4PySCF project (https: //github.com/pyscf/gpu4pyscf), a GPU-accelerated Python quantum chemistry package. We…Xiaojie Wu, Qiming Sun, Zhichen Pu et al.·Apr 15, 2024SaveLearn
Deuteration removes quantum dipolar defects from KDP crystalsThe structural, dielectric, and thermodynamic properties of the hydrogen-bonded ferroelectric crystal potassium dihydrogen phosphate (KH2PO4), KDP for short, differ significantly from…Bingjia Yang, Pinchen Xie, Roberto Car·Apr 11, 2024SaveLearn
Overcoming the chemical complexity bottleneck in on-the-fly machine learned molecular dynamics simulationsWe develop a framework for on-the-fly machine learned force field molecular dynamics simulations based on the multipole featurization scheme that overcomes the bottleneck with the number of chemical…Lucas R. Timmerman, Shashikant Kumar, Phanish Suryanarayana et al.·Apr 11, 2024SaveLearn
Extended Thermodynamic and Mechanical Evolution Criterion for FluidsThe Glansdorff and Prigogine General Evolution Criterion (GEC) is an inequality that holds for macroscopic physical systems obeying local equilibrium and that are constrained under timeindependent…David Hochberg, Isabel Herreros·Apr 11, 2024SaveLearn
On the conjugate interface conditions and Galilean invarianceIn the referred paper("H. Karani, C. Huber, Physical Review E, 91(2)(2015) 023304"), a total heat flux continuity condition for conjugate heat transfer problems with moving interfaces was proposed.…Yang Hu·Apr 10, 2024SaveLearn
Facilities and practices for linear response Hubbard parameters U and J in AbinitMembers of the DFT+U family of functionals are increasingly prevalent methods of addressing errors intrinsic to (semi-) local exchange-correlation functionals at minimum computational cost, but…Lórien MacEnulty, Matteo Giantomassi, Bernard Amadon et al.·Apr 9, 2024SaveLearn
Deep Learning Method for Computing Committor Functions with Adaptive SamplingThe committor function is a central object for quantifying the transitions between metastable states of dynamical systems. Recently, a number of computational methods based on deep neural networks…Bo Lin, Weiqing Ren·Apr 9, 2024SaveLearn
Computing Transition Pathways for the Study of Rare Events Using Deep Reinforcement LearningUnderstanding the transition events between metastable states in complex systems is an important subject in the fields of computational physics, chemistry and biology. The transition pathway plays an…Bo Lin, Yangzheng Zhong, Weiqing Ren·Apr 8, 2024SaveLearn
Enhanced Deep Potential Model for Fast and Accurate Molecular Dynamics; Application to the Hydrated ElectronIn molecular simulations, neural network force fields aim at achieving ab initio accuracy with reduced computational cost. This work introduces enhancements to the Deep Potential network…Ruiqi Gao, Yifan Li, Roberto Car·Apr 5, 2024SaveLearn
Proposal on the Calculation of the Ionisation-Cluster Size Distribution (I). The Model and Its Simulation MethodologyA statistical model for the calculation of the ionisation-cluster size distribution in nanodosimetry is proposed. It is based on a canonical ensemble and derives from the well-known nuclear droplet…Bernd Heide·Apr 5, 2024SaveLearn
Modeling of Zircaloy Oxidation Through Dynamic Mesh DeformationZircaloy cladding corrosion in Light Water Reactors (LWRs) results in the formation of an outer oxide layer and in the thinning of the metallic portion of the cladding. At the \'Ecole Polytechnique…A. Scolaro, E. Brunetto, C. Fiorina·Apr 4, 2024SaveLearn
An asynchronous discontinuous Galerkin method for massively parallel PDE solversThe discontinuous Galerkin (DG) method is widely being used to solve hyperbolic partial differential equations (PDEs) due to its ability to provide high-order accurate solutions in complex…Shubham Kumar Goswami, Konduri Aditya·Apr 4, 2024SaveLearn
DiffObs: Generative Diffusion for Global Forecasting of Satellite ObservationsThis work presents an autoregressive generative diffusion model (DiffObs) to predict the global evolution of daily precipitation, trained on a satellite observational product, and assessed with…Jason Stock, Jaideep Pathak, Yair Cohen et al.·Apr 4, 2024SaveLearn
Functionality Optimization for Singlet Fission Rate Screening in the Full-Dimensional Molecular and Intermolecular Coordinate SpaceIn computational chemistry, accurately predicting molecular configurations that exhibit specific properties remains a critical challenge. Its intricacies become especially evident in the study of…Johannes Greiner, Anurag Singh, Merle I. S. Röhr·Apr 3, 2024SaveLearn
GPU acceleration of ab initio simulations of large-scale identical particles based on path integral molecular dynamicsPath integral Monte Carlo (PIMC) and path integral molecular dynamics (PIMD) provide the golden standard for the ab initio simulations of identical particles. In this work, we achieved significant…Yunuo Xiong·Apr 3, 2024SaveLearn
Combining transition path sampling with data-driven collective variables through a reactivity-biased shooting algorithmRare event sampling is a central problem in modern computational chemistry research. Among the existing methods, transition path sampling (TPS) can generate unbiased representations of reaction…Jintu Zhang, Odin Zhang, Luigi Bonati et al.·Apr 3, 2024SaveLearn