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DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials

Journal of Physical Chemistry A 2022年第49期126卷 9154-9164页

作者： Li, Wenfei Ou, Qi Chen, Yixiao Cao, Yu Liu, Renxi Zhang, Chunyi Zheng, Daye Cai, Chun Wu, Xifan Wang, Han Chen, Mohan Zhang, Linfeng AI for Science Institute Beijing100080 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States HEDPS CAPT College of Engineering School of Physics Peking University Beijing100871 China Department of Physics Temple University PhiladelphiaPA19122 United States Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Huayuan Road 6 Beijing100088 China DP Technology Beijing100080 China

Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods, such as density functional theory (DFT) at the meta-GGA level and/or with exact exchange, quantum Monte Carlo, etc., generating a sufficient amount of data for training an ML potential has remained computationally challenging due to their high cost. In this work, we demonstrate that this issue can be largely alleviated with Deep Kohn-Sham (DeePKS), an ML-based DFT model. DeePKS employs a computationally efficient neural network-based functional model to construct a correction term added upon a cheap DFT model. Upon training, DeePKS offers closely matched energies and forces compared with high-level QM method, but the number of training data required is orders of magnitude less than that required for training a reliable ML potential. As such, DeePKS can serve as a bridge between expensive QM models and ML potentials: one can generate a decent amount of high-accuracy QM data to train a DeePKS model and then use the DeePKS model to label a much larger amount of configurations to train an ML potential. This scheme for periodic systems is implemented in a DFT package ABACUS, which is open source and ready for use in various applications. © 2022 The Journal of Physical Chemistry A. All right reserved.

关键词： Density functional theory

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Autonomous Electron Tomography Reconstruction Using Bayesian Optimization

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Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada 2023年第1期29卷 1915-1916页

作者： Millsaps, William Schwartz, Jonathan Di, Zichao Wendy Jiang, Yi Hovden, Robert Department of Nuclear Engineering Radiological Sciences University of Michigan Ann Arbor MI United States Department of Materials Science and Engineering University of Michigan Ann Arbor MI United States Mathematics and Computer Science Division Argonne National Laboratory Lemont IL United States Advanced Photon Source Facility Argonne National Laboratory Lemont IL United States Applied Physics Program University of Michigan Ann Arbor MI United States

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Imaging atomic-scale chemistry from fused multi-modal electron microscopy

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npj Computational Materials 2022年第1期8卷 164-171页

作者： Jonathan Schwartz Zichao Wendy Di Yi Jiang Alyssa J.Fielitz Don-Hyung Ha Sanjaya D.Perera Ismail El Baggari Richard D.Robinson Jeffrey A.Fessler Colin Ophus Steve Rozeveld Robert Hovden Department of Materials Science and Engineering University of MichiganAnn ArborMIUSA Mathematics and Computer Science Division Argonne National LaboratoryLemontILUSA Advanced Photon Source Facility Argonne National LaboratoryLemontILUSA Dow Chemical Co. MidlandMIUSA Department of Material Science and Engineering Cornell UniversityIthacaNew YorkUSA School of Integrative Engineering Chung-Ang UniversitySeoulRepublic of Korea Department of Physics Cornell UniversityIthacaNYUSA The Rowland Institute at Harvard CambridgeMAUSA Department of Electrical Engineering and Computer Science University of MichiganAnn ArborMIUSA National Center for Electron Microscopy Lawrence Berkeley National LaboratoryMolecular FoundryBerkeleyCAUSA Applied Physics Program University of MIchiganAnn ArborMIUnited States

Efforts to map atomic-scale chemistry at low doses with minimal noise using electron microscopes are fundamentally limited by inelastic ***,fused multi-modal electron microscopy offers high signal-to-noise ratio(SNR)recovery of material chemistry at nano-and atomic-resolution by coupling correlated information encoded within both elastic scattering(high-angle annular dark-field(HAADF))and inelastic spectroscopic signals(electron energy loss(EELS)or energy-dispersive x-ray(EDX)).By linking these simultaneously acquired signals,or modalities,the chemical distribution within nanomaterials can be imaged at significantly lower doses with existing detector *** many cases,the dose requirements can be reduced by over one order of *** high SNR recovery of chemistry is tested against simulated and experimental atomic resolution data of heterogeneous nanomaterials.

关键词： materials chemistry fused

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Evolution mechanism of Ni 3 Si precipitate and anisotropic Frank loop variation in Ni-based alloy revealed by proton irradiation and MD simulations

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Journal of Materials science & Technology 2026年 244卷 34-45页

作者： Zhenbo Zhu Ping Yu Wenqing Liu Chengpeng Liu Weichi Ji Hefei Huang State Key Laboratory of Thorium Energy Shanghai Institute of Applied Physics Chinese Academy of Science Shanghai 201800 China Institute of Materials School of Materials Science and Engineering Shanghai University Shanghai 200444 China School of Nuclear Science and Technology University of Chinese Academy of Sciences Beijing 100049 China

Proton irradiation with a low damage rate was conducted on the Ni-based alloy GH3535 to investigate the evolution behavior of dislocation loops and irradiation-induced segregation (RIS), both of which are known to degrade mechanical properties. This study identified that RIS induced the nucleation of Ni 3 Si precipitates from Ni-Si clusters in the irradiated Ni-based alloys, which is considered a significant contributor to irradiation hardening in stainless steel. Atomic probe tomography (APT) analysis revealed Ni enrichment on both sides of the dislocation loop edges, forming a "W-shaped" profile. Meanwhile, Si accumulated along the edge, inhibiting loop growth and leading to the formation of shadows. Molecular dynamics (MD) simulations confirmed the mechanism of this enrichment distribution. With increasing irradiation dose, Ni 3 Si nucleates at loop edges and coarsens by absorbing nearby Si atoms, ultimately resulting in the dissolution of the loop. This RIS at dislocation loops results in a Si-depleted matrix, stabilizing the nucleation of CrMo-enriched M 2 C carbides and newly formed Frank loops. Meanwhile, four Frank loop (FL) variants were found to have anisotropic behavior. Scanning transmission electron microscopy (STEM) characterization across several crystal orientations revealed that the highest density of Frank loops occurred in the variant perpendicular to the crystal orientation. MD simulations indicated a distinct increase in the formation energy of the four variants under compressive stress, highlighting the influence of stress from ion penetration on Frank loop nucleation. These findings provide valuable insights into the evolution of precipitates and quantitative analysis of dislocation loops in Ni-based alloys.

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Surface Roughness and Optical Characterization of Nanoporous Silver Films Synthesized by One-Step Dealloying 23

Surface Roughness and Optical Characterization of Nanoporous...

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23rd International Conference on Transparent Optical Networks, ICTON 2023

作者： Anton, Stefan R. Fu, Engang Tranca, Denis E. Stanciu, Stefan G. Toma, Antonela Sammut, Charles V. Hu, Zhaoyi Stanciu, George A. University Politehnica of Bucharest Center for Microscopy-Microanalysis and Information Processing Romania Peking University State Key Laboratory of Nuclear Physics and Technology Department of Technical Physics School of Physics China University Politehnica of Bucharest Ctr. for Res. and Train. in Innov. Techniques of Applied Mathematics in Engineering Traian Lalescu Romania University of Malta Faculty of Science Department of Physics Msida Malta

ISBN: (纸本)9798350303032

The nano-topography, surface roughness and optical properties of nanoporous silver (NPS) films are investigated as a function of the dealloying agent using atomic force microscopy and near-field optical microscopy. Detailed metrological analysis is performed to measure the effect of the dealloying agent at the nano scale. It was found that the nano-roughness formed on the surface of the films greatly affects the optical properties of the NPS film. © 2023 IEEE.

关键词： Topography

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Gossypol derivate as a green anti-corrosion agent in the aqueous phase of crude oil

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Environmental science and Pollution Research 2024年第45期31卷 56499-56522页

作者： Berdimuradov, Khasan Berdimurodov, Elyor Haldhar, Rajesh Lal, Basant Kim, Seong-Cheol Guo, Lei Ziyayeva, Gulnar K. Katin, Konstantin P. Aliev, Nizomiddin Hosseini-Bandegharaei, Ahmad Physics and Chemistry Western Caspian University BakuAZ-1001 Azerbaijan University of Tashkent for Applied Sciences Str. Gavhar 1 Tashkent100149 Uzbekistan Chemical amp Materials Engineering New Uzbekistan University 54 Mustaqillik Ave Tashkent100007 Uzbekistan Faculty of Chemistry National University of Uzbekistan Tashkent100034 Uzbekistan Physics and Chemistry Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University Tashkent100000 Uzbekistan School of Chemical Engineering Yeungnam University Gyeongsan38541 Korea Republic of Department of Chemistry Institute of Applied Science and Humanities GLA University Mathura281406 India School of Materials and Chemical Engineering Tongren University Tongren554300 China Department of Applied Biology Named After M. Dulaty Taraz Regional University Taraz Kazakhstan National Research Nuclear University "MEPhI" Kashirskoe Shosse 31 Moscow115409 Russia Tashkent State University of Economics Tashkent100066 Uzbekistan Faculty of Chemistry Semnan University Semnan Iran Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India Department of Sustainable Engineering Saveetha School of Engineering SIMATS Tamil Nadu Chennai602105 India University Centre for Research amp Development Chandigarh University Punjab Mohali140413 India

Keeping recruitment of green and cost-effective solutions for environmental challenges in view, the current work was designed to solve the problems related to metal corrosion in the aqueous phases of crude oil in chemical industries. Green materials can play an important role in protecting metals from this corrosion. Hence, the green anti-corrosion material based upon gossypol derivate is suggested to solve the above problems. The electrochemical characteristics were appraised by cyclic voltammetry, electrochemical impedance spectroscopy, potentiodynamic polarization, and electrochemical noise methods. The thermodynamics were studied by gravimetric analyses. The surface morphology was scrutinized using scanning electron microscopy and energy-dispersive X-ray spectroscopy. Density functional theory and molecular dynamic simulations were exploited in theoretical analyses. The gossypol derivate is green, non-toxic, more efficient, non-volatile, and chemically stable anti-corrosion material for gas and oil industries. Carbon steel corrosion simulated in aqueous phases of crude oil (NaCl solutions (1.0 M) saturated with H2S and CO2) was maximally prohibited by forming a protective layer of binaphthalene. Its protection degree is 96.71% (at 100.0 mg/L/0.107 mM). The gossypol ring is a suitable core for preparing the next modification materials to protect against corrosion. The rigid adsorption progressed mainly via hydroxyl functional moieties. Compared to the inhibition behavior of the neutral form of gossypol, the optimized protonated form causes a greater inhibition. Graphical Abstract: A gossypol derivate showed excellent anti-corrosive efficiency as a green inhibitor. (Figure presented.) © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Cyclic voltammetry

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Evolution of cavities in BCC-Fe with coexisting H and He under fusion environments

arXiv

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arXiv 2025年

作者： Wang, Jin Luo, Fengping Zheng, Tao Zhang, Bowen Liu, Yuxin Chen, Denghuang Xie, Xinyue Chen, Mohan Zhou, Hong-Bo Gao, Fei Xue, Jianming Wang, Yugang Wang, Chenxu State Key Laboratory of Nuclear Physics and Technology Center for Applied Physics and Technology Peking University Beijing100871 China HEDPS College of Engineering School of Physics Peking University Beijing100871 China Department of Physics Beihang University Beijing100191 China Department of Nuclear Engineering and Radiological Science University of Michigan Ann ArborMI48109 United States

In the fusion environment, understanding the synergistic effects of transmutation-produced hydrogen (H), helium (He), and irradiation-induced displacement damage in iron-based alloys is crucial for the development of structural materials for fusion reactors. When H and He atoms are simultaneously introduced into the matrix, the interaction between irradiation-induced cavity defects (voids and bubbles) with H and He, along with their evolutionary behavior remains poorly understood. In this study, the evolutionary behavior of cavities in body-centered cubic (BCC) iron (Fe) with H and He atoms is systematically investigated through a combination of molecular dynamics (MD) calculations and statistical thermodynamics. First, an efficient and suitable set of Fe-H-He ternary potential functions for describing interatomic interactions is established. Based on the newly developed MD model, the evolutionary behavior of H/He atoms and cavities is systematically investigated under various temperature and cavity structure conditions. Specifically, the kinetic process of H/He capture by cavities is elucidated for different scenarios. Additionally, thermodynamic analyses are employed to assess the feasibility of cavity trapping of H under varying conditions. The results exhibit strong consistency with experimental results and provide significant evidence supporting the formation of the core-shell structure (where He is confined at the cavity center while H accumulates at the surface) from both kinetic and thermodynamic perspectives. This work provides mechanistic insights into the nucleation and growth of cavities over extended temporal and spatial scales in the presence of H-He synergies. © 2025, CC BY.

关键词： Diffusion

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Consistent wide-range equation of state of silicon by a unified first-principles method

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Physical Review B 2023年第16期107卷 165150-165150页

作者： Chang Gao Xing Liu Shen Zhang Wei Kang Ping Zhang X. T. He School of Science Wuhan University of Technology Wuhan Hubei 430070 China HEDPS Center for Applied Physics and Technology and School of Physics Peking University Beijing 100871 China China Institute of Nuclear Industry Strategy Beijing 100048 China Department of Nuclear Science and Technology National University of Defense Technology Changsha Hunan 410073 China HEDPS Center for Applied Physics and Technology and College of Engineering Peking University Beijing 100871 China Institute of Applied Physics and Computational Mathematics Beijing 100088 China

Using a unified method of the extended first-principles molecular dynamics, we report a wide-range (density ρ=2.329–18.632 g/cm3, temperature T=1.00×104–1.29×108 K) equation of state (EOS) and principal Hugoniot of silicon, which agree well with experimental results, and then evaluate the precision of the results of first-principles calculations and a universal database. Moreover, we investigate the effects of finite-temperature exchange-correlation functionals and emphasize their importance and necessity in the warm dense matter regime, although it vanishes in the nondegenerate and fully degenerate limits. Finally, we show the ionic radial distribution function and density of electronic states to study the evolution of warm dense Si towards the classic plasma limit along its principal Hugoniot. The established standard theoretical EOS table of Si provides a benchmark for the development of high-precision first-principles methods and may improve radiation-hydrodynamics simulations of inertial confinement fusion and deepen the understanding of high-energy-density physics.

关键词： Equations of state Warm-dense matter Ab initio molecular dynamics Density functional theory

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Novel Circuit Design for a 3D Position Sensitive Scintillation TOF-PET Detector that Achieves ~100 ps CTR

Novel Circuit Design for a 3D Position Sensitive Scintillati...

引用

2022 IEEE nuclear science Symposium, Medical Imaging Conference, and Room Temperature Semiconductor Detector Conference, IEEE NSS MIC RTSD 2022

作者： Pourashraf, Shirin Zhao, Zhixiang Innes, Derek Gonzalez-Montoro, Andrea Cates, Joshua W. Levin, Craig S. Stanford University Department of Radiology StanfordCA94305 United States Lawrence Berkeley National Laboratory Applied Nuclear Physics Program BerkeleyCA94720 United States Stanford University Molecular Imaging Program Departments of Radiology Bioengineering Physics and Electrical Engineering StanfordCA94305 United States The School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665488723

We have built a scalable mixed-signal readout circuit for a 3D position sensitive PET detector that achieves ~100 ps FWHM CTR. For this work we used individual 3×3×3 mm3 and 3×3×10 mm3 LGSO crystals, as well as 2×4 arrays of 3×3×10 mm3 crystals side-coupled to arrays of 3.16×3.16 mm2 SiPMs. The preliminary results verify that the CPLD is able to resolve 3D interaction positions along the array with © 2022 IEEE.

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Projecting Assumptions: The Duality Between Sparse Autoencoders and Concept Geometry

arXiv

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arXiv 2025年

作者： Hindupur, Sai Sumedh R. Lubana, Ekdeep Singh Fel, Thomas Ba, Demba School of Engineering and Applied Science Harvard University United States CBS-NTT Program in Physics of Intelligence Harvard University United States Kempner Institute Harvard University United States

Sparse Autoencoders (SAEs) are widely used to interpret neural networks by identifying meaningful concepts from their representations. However, do SAEs truly uncover all concepts a model relies on, or are they inherently biased toward certain kinds of concepts? We introduce a unified framework that recasts SAEs as solutions to a bilevel optimization problem, revealing a fundamental challenge: each SAE imposes structural assumptions about how concepts are encoded in model representations, which in turn shapes what it can and cannot detect. This means different SAEs are not interchangeable—switching architectures can expose entirely new concepts or obscure existing ones. To systematically probe this effect, we evaluate SAEs across a spectrum of settings: from controlled toy models that isolate key variables, to semi-synthetic experiments on real model activations and finally to large-scale, naturalistic datasets. Across this progression, we examine two fundamental properties that real-world concepts often exhibit: heterogeneity in intrinsic dimensionality (some concepts are inherently low-dimensional, others are not) and nonlinear separability. We show that SAEs fail to recover concepts when these properties are ignored, and we design a new SAE that explicitly incorporates both, enabling the discovery of previously hidden concepts and reinforcing our theoretical insights. Our findings challenge the idea of a universal SAE and underscores the need for architecture-specific choices in model interpretability. Overall, we argue an SAE does not just reveal concepts—it determines what can be seen at all. Copyright © 2025, The Authors. All rights reserved.

关键词： Neural networks

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