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CO2Photoreduction: Heterostructure engineering of a Reverse Water Gas Shift Photocatalyst (Adv. Sci. 22/2019)

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Advanced Science 2019年第22期6卷 1970134-1970134页

作者： Hong Wang Jia Jia Lu Wang Keith Butler Rui Song Gilberto Casillas Le He Nazir P. Kherani Doug D. Perovic Liqiang Jing Aron Walsh Roland Dittmeyer Geoffrey A. Ozin Key Laboratory of Functional Polymer Materials of the Ministry of Education Institute of Polymer Chemistry College of Chemistry Nankai University Tianjin 300071 P. R. China Materials Chemistry and Nanochemistry Research Group Solar Fuels Cluster Departments of Chemistry University of Toronto 80 St. George Street Toronto ON M5S3H6 Canada Department of Materials Science and Engineering University of Toronto 184 College Street Toronto ON M5S3E4 Canada Institute of Functional Nano & Soft Materials (FUNSOM) Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices Soochow University 199 Ren'ai Road Suzhou Jiangsu P. R. China SciML Scientific Computing Department Rutherford Appleton Laboratory Didcot OX110QX UK UOW Electron Microscopy Centre University of Wollongong Wollongong New South Wales 2500 Australia Key Laboratory of Functional Inorganic Material Chemistry Ministry of Education School of Chemistry and Materials Science International Joint Research Center for Catalytic Technology Heilongjiang University Harbin 150080 P. R. China Department of Materials Imperial College London Exhibition Road London SW7 2AZ UK Department of Materials Science and Engineering Yonsei University Seoul 03722 Korea Institute for Micro Process Engineering Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 76344 Eggenstein-Leopoldshafen Germany

In article number https://***/10.1002/advs.201902170 , Hong Wang, Geoffrey A. Ozin, and co‐workers present a hetero‐nanostructure, oxygen vacancy, electronic band alignment and carrier lifetime engineering strategy of In 2 O 3− x (OH) y @Nb 2 O 5 , enabling the solar‐powered, reverse water gas shift reaction to operate at a 44‐fold higher conversion rate than pristine In 2 O 3− x (OH) y , with high selectivity and long‐term operational stability, an advance that augers well for the metal oxide hetero‐nanostructure engineering approach to the industrialization of gas‐phase CO 2 photocatalysis. Image credit: Chenxi Qian.

关键词： charge transfer CO2 conversion heterostructures photocatalysts semiconductors

Recent developments in the PySCF program package

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arXiv 2020年

作者： Sun, Qiming Zhang, Xing Banerjee, Samragni Bao, Peng Barbry, Marc Blunt, Nick S. Bogdanov, Nikolay A. Booth, George H. Chen, Jia Cui, Zhi-Hao Eriksen, Janus Juul Gao, Yang Guo, Sheng Hermann, Jan Hermes, Matthew R. Koh, Kevin Koval, Peter Lehtola, Susi Li, Zhendong Liu, Junzi Mardirossian, Narbe McClain, James D. Motta, Mario Mussard, Bastien Pham, Hung Q. Pulkin, Artem Purwanto, Wirawan Robinson, Paul J. Ronca, Enrico Sayfutyarova, Elvira Scheurer, Maximilian Schurkus, Henry F. Smith, James E.T. Sun, Chong Sun, Shi-Ning Upadhyay, Shiv Wagner, Lucas K. Wang, Xiao White, Alec Whitfield, James Daniel Williamson, Mark J. Wouters, Sebastian Yang, Jun Yu, Jason M. Zhu, Tianyu Berkelbach, Timothy C. Sharma, Sandeep Sokolov, Alexander Yu. Chan, Garnet Kin-Lic AxiomQuant Investment Management LLC Shanghai200120 China Division of Chemistry and Chemical Engineering California Institute of Technology PasadenaCA91125 United States Department of Chemistry and Biochemistry The Ohio State University ColumbusOH43210 United States Beijing National Laboratory for Molecular Sciences State Key Laboratory for Structural Chemistry of Unstable and Stable Species Institute of Chemistry Chinese Academy of Sciences Beijing100190 China Simbeyond B.V. P.O. Box 513 EindhovenNL-5600 MB Netherlands Department of Chemistry Lensfield Road CambridgeCB2 1EW United Kingdom Max Planck Institute for Solid State Research Heisenbergstraße 1 Stuttgart70569 Germany Department of Physics King's College London Strand LondonWC2R 2LS United Kingdom Department of Physics University of Florida GainesvilleFL32611 United States Quantum Theory Project University of Florida GainesvilleFL32611 United States School of Chemistry University of Bristol Cantock's Close BristolBS8 1TS United Kingdom Division of Engineering and Applied Science California Institute of Technology PasadenaCA91125 United States Google Inc. Mountain ViewCA94043 United States FU Berlin Department of Mathematics and Computer Science Arnimallee 6 Berlin14195 Germany TU Berlin Machine Learning Group Marchstr. 23 Berlin10587 Germany Department of Chemistry Chemical Theory Center Supercomputing Institute University of Minnesota 207 Pleasant Street SE MinneapolisMN55455 United States Department of Chemistry and Biochemistry The University of Notre Dame du Lac 251 Nieuwland Science Hall Notre DameIN46556 United States Simune Atomistics S.L. Avenida Tolosa 76 Donostia-San Sebastian Spain HelsinkiFI-00014 Finland Key Laboratory of Theoretical and Computational Photochemistry Ministry of Education College of Chemistry Beijing Normal University Beijing100875 China Department of Chemistry The Johns Hopkins University BaltimoreMD21218 United States AMGEN

PYSCF is a Python-based general-purpose electronic structure platform that both supports first-principles simulations of molecules and solids, as well as accelerates the development of new methodology and complex computational workflows. The present paper explains the design and philosophy behind PYSCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PYSCF as a development environment. We then summarize the capabilities of PYSCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PYSCF across the domains of quantum chemistry, materials science, machine learning and quantum information science. Copyright © 2020, The Authors. All rights reserved.

关键词： Python

An approximate empirical Bayesian method for large-scale linear-Gaussian inverse problems

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arXiv 2017年

作者： Zhou, Qingping Liu, Wenqing Li, Jinglai Marzouk, Youssef M. Department of Mathematics Institute of Natural Sciences Shanghai Jiao Tong University Shanghai200240 China Department of Mathematics and Zhiyuan College Shanghai Jiao Tong University Shanghai200240 China Institute of Natural Sciences Department of Mathematics MOE Key Laboratory of Scientific and Engineering Computing Shanghai Jiao Tong University Shanghai200240 China Department of Aeronautics and Astronautics Massachusetts Institute of Technology CambridgeMA02139 United States

We study Bayesian inference methods for solving linear inverse problems, focusing on hierarchical formulations where the prior or the likelihood function depend on unspecified hyperparameters. In practice, these hyperparameters are often determined via an empirical Bayesian method that maximizes the marginal likelihood function, i.e., the probability density of the data conditional on the hyperparameters. Evaluating the marginal likelihood, however, is computationally challenging for largescale problems. In this work, we present a method to approximately evaluate marginal likelihood functions, based on a low-rank approximation of the update from the prior covariance to the posterior covariance. We show that this approximation is optimal in a minimax sense. Moreover, we provide an efficient algorithm to implement the proposed method, based on a combination of the randomized SVD and a spectral approximation method to compute square roots of the prior covariance matrix. Several numerical examples demonstrate good performance of the proposed method. Copyright © 2017, The Authors. All rights reserved.

关键词： Approximation theory

Correction to: Multivariate statistical and trend analyses of surface water quality in the central Indian River Lagoon area, Florida

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Environmental Earth Sciences 2018年第5期77卷 1-1页

作者： Sayem Zaman Ming Ye Fan Zhang Mingming Zhu Department of Scientific Computing Florida State University Tallahassee USA Draper Aden Associates Richmond USA School of Computer Science and Software Engineering Tianjin Polytechnic University Tianjin China Department of Earth Ocean and Atmospheric Science Florida State University Tallahassee USA Key Laboratory of Tibetan Environmental Changes and Land Surface Processes Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing China Center of Hydraulic Engineering Regulation and Management Jinzhou Waterwork Office Jinzhou China

Unfortunately, the online version of the original article has an error in authors’ names.

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Two-Level Additive Schwarz Methods Using Rough Polyharmonic Splines-Based Coarse Spaces

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Chinese Annals of Mathematics,Series B 2015年第5期36卷 803-812页

作者： Rui DU Lei ZHANG Mathematical Center for Interdisciplinary Research School of Mathematical Sciences Soochow University Institute of Natural Sciences and Department of Mathematics Ministry of Education Key Laboratory of Scientific and Engineering Computing Shanghai Jiaotong University

This paper introduces a domain decomposition preconditioner for elliptic equations with rough coefficients. The coarse space of the domain decomposition method is constructed via the so-called rough polyharmonic splines （RPS for short）. As an approximation space of the eUiptic problem, RPS is known to recover the quasi-optimal convergence rate and attain the quasi-optimal localization property. The authors lay out the formulation of the RPS based domain decomposition preconditioner, and numerically verify the performance boost of this method through several examples.

关键词： Numerical homogenization Domain decomposition Two-level Schwarz additive preconditioner Rough polyharmonic splines

Erratum to: Search for single top-quark production via flavour-changing neutral currents at 8 TeV with the ATLAS detector

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The European Physical Journal C 2022年第1期82卷 1-15页

作者： Aad, G. Abbott, B. Abdallah, J. Abdinov, O. Aben, R. Abolins, M. AbouZeid, O. S. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B. S. Adamczyk, L. Adams, D. L. Adelman, J. Adomeit, S. Adye, T. Affolder, A. A. Agatonovic-Jovin, T. Agricola, J. Aguilar-Saavedra, J. A. Ahlen, S. P. Ahmadov, F. Aielli, G. Akerstedt, H. Åkesson, T. P. A. Akimov, A. V. Alberghi, G. L. Albert, J. Albrand, S. Alconada Verzini, M. J. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Alimonti, G. Alio, L. Alison, J. Alkire, S. P. Allbrooke, B. M. M. Allport, P. P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Altheimer, A. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M. G. Amadio, B. T. Amako, K. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S. P. Amorim, A. Amoroso, S. Amram, N. Amundsen, G. Anastopoulos, C. Ancu, L. S. Andari, N. Andeen, T. Anders, C. F. Anders, G. Anders, J. K. Anderson, K. J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Anger, P. Angerami, A. Anghinolfi, F. Anisenkov, A. V. Anjos, N. Annovi, A. Antonelli, M. Antonov, A. Antos, J. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J. P. Arce, A. T. H. Arduh, F. A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A. J. Arnaez, O. Arnal, V. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Asai, S. Asbah, N. Ashkenazi, A. Åsman, B. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N. B. Augsten, K. Aurousseau, M. Avolio, G. Axen, B. Ayoub, M. K. Azuelos, G. Baak, M. A. Baas, A. E. Baca, M. J. Bacci, C. Bachacou, H. Bachas, K. Backes, M. Backhaus, M. Bagiacchi, P. Bagnaia, P. Bai, Y. Bain, T. Baines, J. T. Baker, O. K. Baldin, E. M. Balek, P. Balestri, T. Balli, F. Banas, E. Banerjee, Sw. Bannoura, A. A. E. Bansil, H. S. Barak, L. Barberio, E. L. Barberis, D. Barbero, M. Barillari, T. Barisonzi, M. Barklow, T. Barlow, N. Barnes, S. L. Barnett, B. M. Barnett, R. M. Barnovska, Z. Baroncelli, A. Barone, G. Barr, A. J. Barreiro, F. Barreiro Guimarães da Costa, J. Bartol CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman USA Institute of Physics Academia Sinica Taipei Taiwan Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Nikhef National Institute for Subatomic Physics and University of Amsterdam Amsterdam The Netherlands Department of Physics and Astronomy Michigan State University East Lansing USA Department of Physics University of Toronto Toronto Canada Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel Center for High Energy Physics University of Oregon Eugene USA Department of Physics Stockholm University Stockholm Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London UK AGH University of Science and Technology Faculty of Physics and Applied Computer Science Kraków Poland Physics Department Brookhaven National Laboratory Upton USA Department of Physics Northern Illinois University De Kalb USA Fakultät für Physik Ludwig-Maximilians-Universität München Munich Germany Particle Physics Department Rutherford Appleton Laboratory Didcot UK Oliver Lodge Laboratory University of Liverpool Liverpool UK Institute of Physics University of Belgrade Belgrade Serbia II Physikalisches Institut Georg-August-Universität Göttingen Germany Laboratório de Instrumentação e Física Experimental de Partículas-LIP Lisbon Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada Spain Department of Physics Boston University Boston USA Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN Sezione di Roma Tor Vergata Rome Italy Dipartimento di Fisica Università di Roma Tor Vergata Rome Italy Fysiska institutionen Lunds uni

A discontinuous galerkin method by patch reconstruction for biharmonic problem

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arXiv 2017年

作者： Li, Ruo Ming, Pingbing Sun, Zhiyuan Yang, Fanyi Yang, Zhijian CAPT LMAM and School of Mathematical Sciences Peking University Beijing100871 China State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences No.55 Zhong-Guan-Cun East Road Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences No. 19A Yu-Quan Road Beijing100049 China School of Mathematical Sciences Peking University Beijing100871 China School of Mathematics and Statistics Wuhan University Wuhan430072 China

We propose a new discontinuous Galerkin method based on the least-squares patch reconstruction for the biharmonic problem. We prove the optimal error estimate of the proposed method. The two-dimensional and three-dimensional numerical examples are presented to confirm the accuracy and efficiency of the method with several boundary conditions and several types of polygon meshes and polyhedral meshes.49N45, 65N21 Copyright © 2017, The Authors. All rights reserved.

关键词： Galerkin methods

A Parallel Line Search Subspace Correction Method for Composite Convex Optimization

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Journal of the Operations Research Society of China 2015年第2期3卷 163-187页

作者： Qian Dong Xin Liu Zai-Wen Wen Ya-Xiang Yuan State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijingChina Beijing International Center for Mathematical Research Peking UniversityBeijingChina

In this paper,we investigate a parallel subspace correction framework for composite convex *** variables are first divided into a few blocks based on certain *** each iteration,the algorithms solve a suitable subproblem on each block simultaneously,construct a search direction by combining their solutions on all blocks,then identify a new point along this direction using a step size satisfying the Armijo line search *** are called PSCLN and PSCLO,respectively,depending on whether there are overlapping regions between two imme-diately adjacent blocks of *** convergence is established under mild *** compare PSCLN and PSCLO with the parallel version of the fast iterative thresholding algorithm and the fixed-point continuation method using the Barzilai-Borwein step size and the greedy coordinate block descent method for solving the l1-regularized minimization *** numerical results showthatPSCLN andPSCLOcan run fast and return solutions notworse than those from the state-of-theart algorithms on most test *** is also observed that the overlapping domain decomposition scheme is helpful when the data of the problem has certain special structures.

关键词： Line search Block coordinate descent method Domain decomposition Jacobian-type iteration Distributed optimization

Simulations of fractal star cluster formation: I. new insights for measuring mass segregation of star clusters with substructure

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arXiv 2017年

作者： Yu, Jincheng Puzia, Thomas H. Lin, Congping Zhang, Yiwei Institute of Astrophysics Pontificia Universidad Católica de Chile Av. Vicuna Mackenna 4860 Macul Santiago7820436 National Astronomical Observatories Chinese Academy of Sciences 20A Datun Road Beijing100012 Center for Mathematical Science Huazhong University of Science and Technology 1037 Luoyu Road Wuhan4370074 Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology 1037 Luoyu road Wuhan430074 School of Mathematics and Statistics Huazhong University of Science and Technology 1037 Luoyu Road Wuhan4370074

We compare the existent methods including the minimum spanning tree based method and the local stellar density based method, in measuring mass segregation of star clusters. We find that the minimum spanning tree method reflects more the compactness, which represents the global spatial distribution of massive stars, while the local stellar density method reflects more the crowdedness, which provides the local gravitational potential information. It is suggested to measure the local and the global mass segregation simultaneously. We also develop a hybrid method that takes both aspects into account. This hybrid method balances the local and the global mass segregation in the sense that the predominant one is either caused either by dynamical evolution or purely accidental, especially when such information is unknown a priori. In addition, we test our prescriptions with numerical models and show the impact of binaries in estimating the mass segregation value. As an application, we use these methods on the Orion Nebula Cluster (ONC) observations and the Taurus cluster. We find that the ONC is significantly mass segregated down to the 20th most massive stars. In contrast, the massive stars of the Taurus cluster are sparsely distributed in many different subclusters, showing a low degree of compactness. The massive stars of Taurus are also found to be distributed in the high-density region of the subclusters, showing significant mass segregation at subcluster scales. Meanwhile, we also apply these methods to discuss the possible mechanisms of the dynamical evolution of the simulated substructured star clusters. Copyright © 2017, The Authors. All rights reserved.

关键词： Numerical methods