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Electronic Impurity Doping of a 2D Hybrid Lead Iodide Perovskite by Bi and Sn

PRX Energy 2023年第2期2卷 023010-023010页

作者： Haipeng Lu Gabrielle Koknat Yi Yao Ji Hao Xixi Qin Chuanxiao Xiao Ruyi Song Florian Merz Markus Rampp Sebastian Kokott Christian Carbogno Tianyang Li Glenn Teeter Matthias Scheffler Joseph J. Berry David B. Mitzi Jeffrey L. Blackburn Volker Blum Matthew C. Beard Material Chemical and Computational Science Directorate National Renewable Energy Laboratory Golden Colorado 80401 USA Department of Chemistry The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong SAR China Thomas Lord Department of Mechanical Engineering and Material Science Duke University Durham North Carolina 27708 USA Department of Chemistry Duke University Durham North Carolina 27708 USA Lenovo HPC Innovation Center Meitnerstr. 9 D-70563 Stuttgart Germany Max Planck Computing and Data Facility Giessenbachstrasse 2 D-85748 Garching Germany The NOMAD Laboratory at the FHI of the Max-Planck-Gesellschaft and IRIS-Adlershof of the Humboldt-Universität zu Berlin 14195 Berlin Germany Renewable and Sustainable Energy Institute University of Colorado Boulder Boulder Colorado 80309 USA Department of Physics University of Colorado Boulder Boulder Colorado 80309 USA

Control over conductivity and carrier type (electrons and holes) defines semiconductors. A primary approach to target carrier concentrations involves introducing a small population of aliovalent impurity dopant atoms. In a combined synthetic and computational study, we assess impurity doping by introducing Bi and Sn into the prototype 2D Ruddlesden-Popper hybrid perovskite phenylethylammonium lead iodide (PEA2PbI4). Experimentally, we demonstrate that Bi and Sn can achieve n- and p-type doping, respectively, but the doping efficiency is low. Simulations show that Bi introduces a deep defect energy level (∼0.5 eV below the conduction band minimum) that contributes to the low doping efficiency, but, to reproduce the low doping efficiency observed experimentally, an acceptor level must also be present that limits n-type doping. Experiments find that Sn achieves p-dopant behavior and simulations suggest that this occurs through the additional oxidation of Sn defects. We also study how substitutional Bi incorporation can be controlled by tuning the electrochemical environment during synthesis. First-principles impurity doping simulations can be challenging; typical dopant concentrations constitute less than 0.01% of the atoms, necessitating large supercells, while a high level of theory is needed to capture the electronic levels. We demonstrate simulations of complex defect-containing unit cells that include up to 3383 atoms, employing spin-orbit coupled hybrid density functional theory. While p- and n-type behavior can be achieved with Sn and Bi, simulations and experiments provide concrete directions where future efforts must be focused to achieve higher doping efficiency.

关键词： Energy materials Solar energy

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Coherent H ∞ control for Markovian jump linear quantum systems

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IFAC-PapersOnLine 2020年第2期53卷 269-274页

作者： Yanan Liu Daoyi Dong Ian R. Petersen Qing Gao Steven X. Ding Hidehiro Yonezawa School of Engineering and Information Technology University of New South Wales Canberra ACT 2600 Australia Center for Quantum Computation and Communication Technology Australian Research Council Canberra ACT 2600 Australia Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen. 47057 Duisburg Germany Research School of Electrical Energy and Materials Engineering The Australian National University Canberra ACT 2601 Australia School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing and also with Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China

The purpose of this paper is to design a coherent feedback controller for a Markovian jump linear quantum system suffering from a fault signal. The control objective is to bound the effect of the disturbance input on the output for the time-varying quantum system. We prove the relation between the H ∞ control problem, the dissipation properties, and the solutions of Riccati differential equations, by which the H ∞ controller of the Markovian jump linear quantum system is given by the solutions of Linear Matrix Inequalities (LMIs).

关键词： Coherent quantum feedback H∞ control fault-tolerant control Markovian jump linear quantum systems

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From FAIR to CURE: Guidelines for Computational Models of Biological Systems

arXiv

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arXiv 2025年

作者： Sauro, Herbert M. Agmon, Eran Blinov, Michael L. Gennari, John H. Hellerstein, Joe Heydarabadipour, Adel Hunter, Peter Jardine, Bartholomew E. May, Elebeoba Nickerson, David P. Smith, Lucian P. Bader, Gary D. Bergmann, Frank Boyle, Patrick M. Dräger, Andreas Faeder, James R. Feng, Song Freire, Juliana Fröhlich, Fabian Glazier, James A. Gorochowski, Thomas E. Helikar, Tomas Hoops, Stefan Imoukhuede, Princess Keating, Sarah M. Konig, Matthias Laubenbacher, Reinhard Loew, Leslie M. Lopez, Carlos F. Lytton, William W. McCulloch, Andrew Mendes, Pedro Myers, Chris J. Myers, Jerry G. Mulugeta, Lealem Niarakis, Anna van Niekerk, David D. Olivier, Brett G. Patrie, Alexander A. Quardokus, Ellen M. Radde, Nicole Rohwer, Johann M. Sahle, Sven Schaff, James C. Sego, T.J. Shin, Janis Snoep, Jacky L. Vadigepalli, Rajanikanth Wiley, H. Steve Waltemath, Dagmar Moraru, Ion Department of Bioengineering University of Washington SeattleWA98195-5061 United States Intelligent Systems Engineering and Biocomplexity Institute Indiana University Street BloomingtonIN47408 United States Center for Cardiovascular Biology University of Washington SeattleWA98195-5061 United States eScience Institute University of Washington SeattleWA98195-5061 United States Institute for Stem Cell and Regenerative Medicine University of Washington SeattleWA98195-5061 United States School of Biological Sciences University of Bristol 24 Tyndall Avenue BristolBS8 1TQ United Kingdom Departments of Physiology & Pharmacology Neurology Downstate Health Science University BrooklynNY11203 United States Department of Neurology Kings County Hospital BrooklynNY11203 United States NASA-John H. Glenn Research Center MS 110-3 21000 Brookpark Road ClevelandOH44135 United States Center for Cell Analysis and Modeling UConn Health 263 Farmington Avenue FarmingtonCT06030-6406 United States Amsterdam Institute for Life and Environment Vrije Universiteit Amsterdam De Boelelaan 1108 Amsterdam1081 HZ Netherlands Department of Pathology and Genomic Medicine Thomas Jefferson University 1020 Locust St PhiladelphiaPA19107 United States Biological Sciences Division Pacific Northwest National Laboratory 902 Battelle Blvd RichlandWA99354 United States Auckland Bioengineering Institute University of Auckland Auckland1010 New Zealand Center of Integrative Biology University of Toulouse III-Paul Sabatier 165 Rue Marianne Grunberg-Manago Toulouse31400 France Lifeware Group Inria Building Alan Turing 1 Rue Honoré d’Estienne d’Orves Palaiseau91120 France Multiscale Modeling Group Altos Labs Redwood CityCA94065 United States partner site Tübingen Tübingen Germany Ottfried-Müller-Str. 37 Tübingen72076 Germany 06120 Germany Department of Computer Science Center for Data Science New York University New YorkNY11201 United States Department of Bi

Guidelines for managing scientific data have been established under the FAIR principles requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data and models are key to progress. For this reason, and recognizing that such models are a very special type of "data", we argue that computational models, especially mechanistic models prevalent in medicine, physiology and systems biology, deserve a complementary set of guidelines. We propose the CURE principles, emphasizing that models should be Credible, Understandable, Reproducible, and Extensible. We delve into each principle, discussing verification, validation, and uncertainty quantification for model credibility;the clarity of model descriptions and annotations for understandability;adherence to standards and open science practices for reproducibility;and the use of open standards and modular code for extensibility and reuse. We outline recommended and baseline requirements for each aspect of CURE, aiming to enhance the impact and trustworthiness of computational models, particularly in biomedical applications where credibility is paramount. Our perspective underscores the need for a more disciplined approach to modeling, aligning with emerging trends such as Digital Twins and emphasizing the importance of data and modeling standards for interoperability and reuse. Finally, we emphasize that given the non-trivial effort required to implement the guidelines, the community moves to automate as many of the guidelines as possible. © 2025, CC BY.

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Self-consistent potential correction for charged periodic systems

arXiv

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arXiv 2020年

作者： da Silva, Mauricio Chagas Lorke, Michael Aradi, Bálint Tabriz, Meisam Farzalipour Frauenheim, Thomas Rubio, Angel Rocca, Dario Deák, Peter Bremen Center for Computational Materials Science University of Bremen P.O. Box 330440 BremenD-28334 Germany Hamburg22761 Germany Université de Lorraine CNRS LPCT NancyF-54000 France Max Planck Computing and Data Facility Gießenbachstr. 2 GarchingD-85748 Germany Computational Science Research Center No.10 East Xibeiwang Road Beijing100193 China Computational Science and Applied Research Institute Shenzhen China Nano-Bio Spectroscopy Group Departamento de Fisica de Materiales Universidad del País Vasco UPV/EHU- 20018 San Sebastián Spain

Supercell models are often used to calculate the electronic structure of local deviations from the ideal periodicity in the bulk or on the surface of a crystal or in wires. When the defect or adsorbent is charged, a jellium counter charge is applied to maintain overall neutrality, but the interaction of the artificially repeated charges has to be corrected, both in the total energy and in the one-electron eigenvalues and eigenstates. This becomes paramount in slab or wire calculations, where the jellium counter charge may induce spurious states in the vacuum. We present here a self-consistent potential correction scheme and provide successful tests of it for bulk and slab calculations. Copyright © 2020, The Authors. All rights reserved.

关键词： Electronic properties

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On information-theoretic characterizations of markov random fields and subfields

On information-theoretic characterizations of markov random ...

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作者： Yeung, Raymond W. Al-Bashabsheh, Ali Chen, Chao Chen, Qi Moulin, Pierre Institute of Network Coding Chinese University of Hong Kong Hong Kong Department of Information Engineering Chinese University of Hong Kong Hong Kong Big Data and Brain Computing Center Beihang University Beijing100191 China State Key Laboratory of Integrated Service Networks Xidian University Xi'an710071 China Department of Electrical and Computer Engineering University of Illinois UrbanaIL61801 United States Coordinated Science Laboratory University of Illinois UrbanaIL61801 United States

Let Xi, i ϵ V form a Markov random field (MRF) represented by an undirected graph G = (V,E) , and V′ be a subset of V. We determine the smallest graph that can always represent the subfield Xi, i ϵ V′ as an MRF. Based on this result, we obtain a necessary and sufficient condition for a subfield of a Markov tree to be also a Markov tree. When G is a path so that Xi, i ϵ V form a Markov chain, it is known that the I -Measure is always nonnegative (Kawabata and Yeung in 1992). We prove that Markov chain is essentially the only MRF such that the I -Measure is always nonnegative. By applying our characterization of the smallest graph representation of a subfield of an MRF, we develop a recursive approach for constructing information diagrams for MRFs. Our work is built on the set-theoretic characterization of an MRF (Yeung et al. in 2002). © 1963-2012 IEEE.

关键词： Markov processes

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Robust unsupervised feature selection by nonnegative sparse subspace learning

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Neurocomputing 2019年 334卷 156-171页

作者： Wei Zheng Hui Yan Jian Yang School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing PR China School of Computer Engineering Jinling Institute of Technology Nanjing PR China PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education and Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Key Laboratory of Trusted Cloud Computing and Big Data Analysis Nanjing Xiaozhuang University Nanjing PR China

Sparse subspace learning has been demonstrated to be effective in data mining and machine learning. In this paper, we cast the unsupervised feature selection scenario as a matrix factorization problem from the viewpoint of sparse subspace learning. By minimizing the reconstruction residual, the learned feature weight matrix with the l 2,1 -norm and the non-negative constraints not only removes the irrelevant features, but also captures the underlying low dimensional structure of the data points. Meanwhile in order to enhance the model's robustness, l 1 -norm error function is used to resistant to outliers and sparse noise. An efficient iterative algorithm is introduced to optimize this non-convex and non-smooth objective function and the proof of its convergence is given. Although, there is a subtraction item in our multiplicative update rule, we validate its non-negativity. The superiority of our model is demonstrated by comparative experiments on various original datasets with and without malicious pollution.

关键词： Subspace learning Non-negative matrix factorization Unsupervised feature selection

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MemNetAR: Memory Network with Adversative Relation for Target-Level Sentiment Classification

MemNetAR: Memory Network with Adversative Relation for Targe...

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2019 IEEE Global Communications Conference (GLOBECOM)

作者： Yiwei Gao Jianwei Niu Xuefeng Liu Kaili Mao Shui Yu State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC) Beihang University Hangzhou Innovation Research Institute Beihang University School of Computer Science and Cyber Engineering Guangzhou University Guangdong China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Target-level sentiment classification aims to identify the sentiment of multiple targets in a sentence. Although existing approaches based on neural network have achieved good performance in this task, we find that many approaches tend to give the same predictions for instances that have multiple targets, and this tendency can make a low accuracy for those instances that have different classes for different targets. Based on this observation, we propose MemNetAR, a memory network which can explicitly leverage the adversative relation among multiple targets in a sentence. Specifically, we add an adversative loss to the cross-entropy loss when there are adversative words between targets. The experimental results on public laptop and restaurant datasets prove that our model can improve 0.84% and 0.8% on total test dataset, and improve 2.97% and 2.68% on the dataset consisting of those instances with multiple targets but different classes by leveraging this new adversative information.

关键词： Task analysis Feature extraction Sentiment analysis Portable computers Machine learning Training Predictive models

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Ab initio evaluation of complexation energies for cyclodextrin drug inclusion complexes

arXiv

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arXiv 2020年

作者： Oqmhula, Kenji Hongo, Kenta Maezono, Ryo Ichibha, Tom School of Materials Science JAIST 1-1 Asahidai NomiIshikawa923-1292 Japan Research Center for Advanced Computing Infrastructure JAIST 1-1 Asahidai NomiIshikawa923-1292 Japan Center for Materials Research by Information Integration Research and Services Division of Materials Data and Integrated System National Institute for Materials Science 1-2-1 Sengen Tsukuba305-0047 Japan PRESTO Japan Science and Technology Agency 4-1-8 Honcho Kawaguchi-shi Saitama322-0012 Japan Computational Engineering Applications Unit RIKEN 2-1 Hirosawa Wako Saitama351-0198 Japan School of Information Science JAIST 1-1 Asahidai NomiIshikawa923-1292 Japan

We examined the reliability of exchange-correlation functionals for molecular encapsulations combined by van der Waals forces, comparing their predictions with those of diffusion Monte Carlo method. We established that functionals with D3 dispersion force correction and including sufficient proportion of exact-exchange in long-ranged interaction can comparatively reliably estimate the binding strength. Our finding agrees with a previous ab initio study on argon dimer. However we found that even such functionals may not be able to distinguish the energy differences among different conformations. Copyright © 2020, The Authors. All rights reserved.

关键词： Van der Waals forces

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Identifying High Potential Talent: A Neural Network Based Dynamic Social Profiling Approach

Identifying High Potential Talent: A Neural Network Based Dy...

引用

IEEE International Conference on data Mining (ICDM)

作者： Yuyang Ye Hengshu Zhu Tong Xu Fuzhen Zhuang Runlong Yu Hui Xiong Anhui Province Key Lab of Big Data Analysis and Application University of Science and Technology of China Baidu Talent Intelligence Center Baidu Inc Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology University of Chinese Academy of Sciences

How to identify high-potential talent (HIPO) earlier in their career always has strategic importance for human resource management. While tremendous efforts have been made in this direction, most existing approaches are still based on the subjective selection of human resource experts. This could lead to unintentional bias and inconsistencies. To this end, in this paper, we propose a neural network based dynamic social profiling approach for quantitatively identifying HIPOs from the newly-enrolled employees by modeling the dynamics of their behaviors in organizational social networks. A basic assumption is that HIPOs usually perform more actively and have higher competencies than their peers to accumulate their social capitals during their daily work practice. Along this line, we first propose to model the social profiles of employees with both Graph Convolutional Network (GCN) and social centrality analysis in a comprehensive way. Then, an adaptive Long Short Term Memory (LSTM) network with global attention mechanism is designed to capture the profile dynamics of employees in the organizational social networks during their early career. Finally, extensive experiments on real-world data clearly validate the effectiveness of our approach as well as the interpretability of our results.

关键词： Social networking (online) Companies Artificial neural networks Germanium Engineering profession

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An Advanced Quantum-Resistant Signature Scheme for Cloud Based on Eisenstein Ring

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Computers, Materials & Continua 2018年第7期56卷 19-34页

作者： Faguo Wu Xiao Zhang Wang Yao Zhiming Zheng Lipeng Xiang Wanpeng Li Key Laboratory of Mathematics Informatics and Behavioral SemanticsMinistry of EducationSchool of Mathematics and Systems ScienceBeihang UniversityBeijing100191China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing100191China The Fifth Electronics Research Institute of Ministry of Industry and Information Technology Guangzhou510610China Department of Electrical and Electronic Engineering City University of LondonUK

Signature,widely used in cloud environment,describes the work as readily identifying its *** existing signature schemes in the literature mostly rely on the Hardness assumption which can be easily solved by quantum *** this paper,we proposed an advanced quantum-resistant signature scheme for Cloud based on Eisenstein Ring(ETRUS)which ensures our signature scheme proceed in a lattice with higher *** proved that ETRUS highly improve the performance of traditional lattice signature ***,the Norm of polynomials decreases significantly in ETRUS which can effectively reduce the amount of polynomials convolution ***,storage complexity of ETRUS is smaller than classical ***,according to all convolution of ETRUS enjoy lower degree polynomials,our scheme appropriately accelerate 56.37%speed without reducing its security level.

关键词： Signature quantum-resistant Eisenstein Ring ETRUS

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