检索结果-内蒙古大学图书馆

Deconvoluting clonal and cellular architecture in IDH-mutant acute myeloid leukemia

Cell stem cell 2025年

作者： Maria Sirenko Soobeom Lee Zhengxi Sun Ronan Chaligne Sanam Loghavi Georgios Asimomitis Charlotte K Brierley Elsa Bernard Sheng F Cai Robert M Myers Bettina Nadorp Junya Sango Morgan Lallo Max F Levine Dylan Domenico Juan E Arango Ossa Juan S Medina-Martinez Kamal Menghrajani Audrey Lasry Alice S Mims Helee Desai Andrea Laganson Chris Famulare Minal Patel Gerard Lozanski Kelly L Bolton Aaron D Viny Mikhail Roshal Ross L Levine Eirini P Papapetrou Eytan M Stein Dan A Landau Ann-Kathrin Eisfeld Iannis Aifantis Elli Papaemmanuil Department of Pathology New York University Grossman School of Medicine New York NY USA Laura and Isaac Perlmutter Cancer Center New York University Grossman School of Medicine New York NY USA Louis V. Gerstner Jr. Graduate School of Biomedical Sciences Memorial Sloan Kettering Cancer Center New York NY USA Computational Oncology Service Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA. Department of Biology New York University New York NY USA. Laura and Isaac Perlmutter Cancer Center New York University Grossman School of Medicine New York NY USA. Program for Computational and Systems Biology Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New York NY 10065 USA. Department of Hematopathology The University of Texas MD Anderson Cancer Center Houston TX USA. Computational Oncology Service Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Biomedical Systems Laboratory Department of Mechanical Engineering National Technical University of Athens Athens Greece. Medical Research Council Weatherall Institute of Molecular Medicine University of Oxford Oxford UK NIHR Biomedical Research Centre University of Oxford Oxford UK. Leukemia Service Department of Medicine Center for Hematologic Malignancies Memorial Sloan Kettering Cancer Center New York NY USA Human Oncology and Pathogenesis Program Memorial Sloan Kettering Cancer Center New York NY USA. Tri-Institutional MD-PhD Program Weill Cornell Medicine Rockefeller University Memorial Sloan Kettering Cancer Center New York NY USA. Division of Precision Medicine Department of Medicine New York University School of Medicine New York NY USA. Department of Oncological Sciences Tisch Cancer Institute Center for Advancement of Blood Cancer Therapies Icahn School of Medicine at Mount Sinai New York NY USA. Vilcek Institute of Graduate Biomedical Sciences NYU Grossman School of Medicine N

Isocitrate dehydrogenase 1/2 (IDH) mutations are early initiating events in acute myeloid leukemia (AML). The complex clonal architecture and cellular heterogeneity in IDH-mutant AML underlies the heterogeneous clinical presentation and outcomes. Integrating single-cell genotyping and transcriptomics, we demonstrate a stem-like and inflammatory phenotype of IDH-mutant AML and identify clone-specific programs associated with NPM1, NRAS, and SRSF2 co-mutations. Furthermore, these clones had distinct responses to treatment with combination IDH inhibitors and chemotherapy, including elimination, reconstitution of myeloid differentiation, or retention within progenitor populations. At relapse after IDH inhibitor monotherapy, we identify upregulated stemness, inflammation, mitochondrial metabolism, and anti-apoptotic factors, as well as downregulated major histocompatibility complex (MHC) class II antigen presentation. At the pre-leukemic stage, we observe upregulation of IDH2-associated pathways, including inflammation. We deliver a detailed phenotyping of IDH-mutant AML and a framework for dissecting contributions of recurrently mutated genes in AML at diagnosis and following therapy, with implications for precision medicine.

关键词： IDH inhibitors IDH1/2 mutations acute myeloid leukemia cellular hierarchy clonal architecture clonal evolution relapse single-cell transcriptomics targeted therapy treatment resistance

来源：评论

学校读者我要写书评

暂无评论

Dynamical charge structure factor of a one-dimensional ionic Hubbard model in the low-energy region

arXiv

引用

arXiv 2018年

作者： Komaki, Yuhei Iwase, Yuma Yanagimatsu, Shogo Muta, Yoshiyuki Maeshima, Nobuya Hino, Ken-ichi Doctoral Program in Materials Science Graduate School of Pure and Applied Sciences University of Tsukuba Tsukuba Ibaraki305-8573 Japan College of Engineering Sciences University of Tsukuba Tsukuba305-8573 Japan Center for Computational Sciences University of Tsukuba Tsukuba305-8577 Japan Division of Materials Science University of Tsukuba Tsukuba305-8573 Japan

We present a numerical study of the charge dynamical structure factor N(k, ω) of a one-dimensional (1D) ionic Hubbard model in the Mott insulator (MI) phase. We show that the low-energy spectrum of N(k, ω) is expressed in terms of the spin operators for the spin degrees of freedom. Numerical results for the spin degrees of freedom, obtained by the Lanczos diagonalization method, well reproduce the low-energy spectrum of N(k, ω) of the 1D ionic Hubbard model. In addition, we show that these spectral peaks probe the dispersion of the spin-singlet excitations of the system and are observed in the wide parameter region of the MI phase. Copyright © 2018, The Authors. All rights reserved.

关键词： Numerical methods

来源：评论

学校读者我要写书评

暂无评论

Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data

Research Square

引用

Research Square 2021年

作者： Zhang, Martin Jinye Hou, Kangcheng Pasaniuc, Bogdan Price, Alkes L. Dey, Kushal K. Jagadeesh, Karthik A. Weinand, Kathryn Sakaue, Saori Taychameekiatchai, Aris Rao, Poorvi Pisco, Angela Oliveira Zou, James Wang, Bruce Gandal, Michael Raychaudhuri, Soumya Harvard University United States Osaka University Japan Department of Epidemiology Harvard T.H. Chan School of Public Health BostonMA United States Program in Medical and Population Genetics Broad Institute of MIT and Harvard CambridgeMA United States Bioinformatics Interdepartmental Program University of California Los Angeles Los AngelesCA United States Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Center for Data Sciences Brigham and Women’s Hospital BostonMA United States Division of Genetics Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Division of Rheumatology Inflammation and Immunity Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Medicine and Liver Center University of California San Francisco San FranciscoCA United States Developmental and Stem Cell Biology Graduate Program University of California San Francisco San FranciscoCA United States Chan Zuckerberg Biohub San FranciscoCA United States Department of Electrical Engineering Stanford University Palo AltoCA United States Department of Biomedical Data Science Stanford University Palo AltoCA United States Department of Psychiatry David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Program in Neurobehavioral Genetics Semel Institute David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Versus Arthritis Centre for Genetics and Genomic

Gene expression at the individual cell-level resolution, as quantified by single-cell RNA-sequencing (scRNA-seq), can provide unique insights into the pathology and cellular origin of diseases and complex traits. Here, we introduce single-cell Disease Relevance Score (scDRS), an approach that links scRNA-seq with polygenic risk of disease at individual cell resolution;scDRS identifies individual cells that show excess expression levels for genes in a disease-specific gene set constructed from GWAS data. We determined via simulations that scDRS is well-calibrated and powerful in identifying individual cells associated to disease. We applied scDRS to GWAS data from 74 diseases and complex traits (average N =341K) in conjunction with 16 scRNA-seq data sets spanning 1.3 million cells from 31 tissues and organs. At the cell type level, scDRS broadly recapitulated known links between classical cell types and disease, and also produced novel biologically plausible findings. At the individual cell level, scDRS identified subpopulations of disease-associated cells that are not captured by existing cell type labels, including subpopulations of CD4+ T cells associated with inflammatory bowel disease, partially characterized by their effector-like states;subpopulations of hippocampal CA1 pyramidal neurons associated with schizophrenia, partially characterized by their spatial location at the proximal part of the hippocampal CA1 region;and subpopulations of hepatocytes associated with triglyceride levels, partially characterized by their higher ploidy levels. At the gene level, we determined that genes whose expression across individual cells was correlated with the scDRS score (thus reflecting co-expression with GWAS disease genes) were strongly enriched for gold-standard drug target and Mendelian disease genes. © 2021, CC BY.

关键词： RNA

来源：评论

学校读者我要写书评

暂无评论

Author Correction: The lactate receptor HCAR1 drives the recruitment of immunosuppressive PMN-MDSCs in colorectal cancer

引用

Nature immunology 2025年第4期26卷 635页

作者： Jiacheng He Xiaolei Chai Qiansen Zhang Yang Wang Yijie Wang Xinyu Yang Jingbo Wu Bo Feng Jing Sun Weiwei Rui Shuyin Ze Yuanyuan Fu Yumiao Zhao Ying Zhang Yao Zhang Meizhen Liu Chuang Liu Meifu She Xiangfei Hu Xueyun Ma Huaiyu Yang Dawei Li Senlin Zhao Guichao Li Zhen Zhang Zhonghui Tian Yanlin Ma Lingyan Cao Bo Yi Dali Li Ruth Nussinov Charis Eng Timothy A Chan Eytan Ruppin J Silvio Gutkind Feixiong Cheng Mingyao Liu Weiqiang Lu Shanghai Key Laboratory of Regulatory Biology Institute of Biomedical Sciences and School of Life Sciences East China Normal University Shanghai China. Department of Urology and Department of Pathology The Fifth People's Hospital of Shanghai Fudan University Shanghai China. Department of General Surgery and Department of Pathology Ruijin Hospital Shanghai Jiaotong University School of Medicine Shanghai China. Research Center for Complexity Sciences Hangzhou Normal University Hangzhou China. Department of Colorectal Surgery Department of Radiation Oncology Fudan University Shanghai Cancer Center Shanghai China. School of Life Sciences Fudan University Shanghai China. Hainan Provincial Key Laboratory for Human Reproductive Medicine and Genetic Research Hainan Provincial Clinical Research Center for Thalassemia Department of Reproductive Medicine Key Laboratory of Reproductive Health Diseases Research and Translation (Hainan Medical University) Ministry of Education The First Affiliated Hospital of Hainan Medical University Haikou China. Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine College of Stomatology Shanghai Jiao Tong University Shanghai China. Department of Gastrointestinal Surgery The Third Xiangya Hospital Central South University Changsha China. Computational Structural Biology Section Basic Science Program Frederick National Laboratory for Cancer Research National Cancer Institute at Frederick Frederick MD USA. Department of Human Molecular Genetics and Biochemistry Sackler School of Medicine Tel Aviv University Tel Aviv Israel. Genomic Medicine Institute Lerner Research Institute Cleveland Clinic Cleveland OH USA. Department of Molecular Medicine Cleveland Clinic Lerner College of Medicine Case Western Reserve University Cleveland OH USA. Case Comprehensive Cancer Center Case Western Reserve University School of Medicine Cleveland OH USA. Center for Immunotherapy and Precision Immuno-Oncology Cleveland Clini

来源：评论

学校读者我要写书评

暂无评论

The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

引用

NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

来源：评论

学校读者我要写书评

暂无评论

Technology dictates algorithms: Recent developments in read alignment

arXiv

引用

arXiv 2020年

作者： Alser, Mohammed Rotman, Jeremy Taraszka, Kodi Shi, Huwenbo Baykal, Pelin Icer Yang, Harry Taegyun Xue, Victor Knyazev, Sergey Singer, Benjamin D. Balliu, Brunilda Koslicki, David Skums, Pavel Zelikovsky, Alex Alkan, Can Mutlu, Onur Mangul, Serghei Computer Science Department ETH Zürich Zürich8092 Switzerland Computer Engineering Department Bilkent University Bilkent Ankara 06800 Turkey Department of Computer Science University of California Los Angeles Los AngelesCA90095 United States Department of Epidemiology Harvard T.H. Chan School of Public Health MA02115 United States Program in Medical and Population Genetics Broad Institute of MIT and Harvard CambridgeMA02142 United States Department of Computer Science Georgia State University AtlantaGA30302 United States Bioinformatics Interdepartmental Ph.D. Program University of California Los Angeles Los AngelesCA90095 United States Division of Pulmonary and Critical Care Medicine Northwestern University Feinberg School of Medicine ChicagoIL60611 United States Department of Biochemistry & Molecular Genetics Northwestern University Feinberg School of Medicine United States Simpson Querrey Center for Epigenetics Northwestern University Feinberg School of Medicine ChicagoIL60611 United States Department of Computational Medicine University of California Los Angeles Los AngelesCA90095 United States Computer Science and Engineering Pennsylvania State University University ParkPA16801 United States Biology Department Pennsylvania State University University ParkPA16801 United States The Huck Institutes of the Life Sciences Pennsylvania State University University ParkPA16801 United States The Laboratory of Bioinformatics I.M. Sechenov First Moscow State Medical University Moscow119991 Russia Bilkent-Hacettepe Health Sciences and Technologies Program Ankara Turkey Department of Clinical Pharmacy School of Pharmacy University of Southern California Los AngelesCA90089 United States

Massively parallel sequencing techniques have revolutionized biological and medical sciences by providing unprecedented insight into the genomes of humans, animals, and microbes. Modern sequencing platforms generate enormous amounts of genomic data in the form of nucleotide sequences or reads. Aligning reads onto reference genomes enables the identification of individual-specific genetic variants and is an essential step of the majority of genomic analysis pipelines. Aligned reads are essential for answering important biological questions, such as detecting mutations driving various human diseases and complex traits as well as identifying species present in metagenomic samples. The read alignment problem is extremely challenging due to the large size of analyzed datasets and numerous technological limitations of sequencing platforms, and researchers have developed novel bioinformatics algorithms to tackle these difficulties. Importantly, computational algorithms have evolved and diversified in accordance with technological advances, leading to today’s diverse array of bioinformatics tools. Our review provides a survey of algorithmic foundations and methodologies across 107 alignment methods published between 1988 and 2020, for both short and long reads. We provide rigorous experimental evaluation of 11 read aligners to demonstrate the effect of these underlying algorithms on speed and efficiency of read aligners. We separately discuss how longer read lengths produce unique advantages and limitations to read alignment techniques. We also discuss how general alignment algorithms have been tailored to the specific needs of various domains in biology, including whole transcriptome, adaptive immune repertoire, and human microbiome studies. Copyright © 2020, The Authors. All rights reserved.

关键词： Bioinformatics

来源：评论

学校读者我要写书评

暂无评论

Steerable ePCA: Rotationally Invariant Exponential Family PCA

arXiv

引用

arXiv 2018年

作者： Zhao, Zhizhen Liu, Lydia T. Singer, Amit Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61820 United States Department of Electrical Engineering and Computer Sciences University of California at Berkeley BerkeleyCA94720 United States Department of Mathematics Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

—In photon-limited imaging, the pixel intensities are affected by photon count noise. Many applications, such as 3-D reconstruction using correlation analysis in X-ray free electron laser (XFEL) single molecule imaging, require an accurate estimation of the covariance of the underlying 2-D clean images. Accurate estimation of the covariance from low-photon count images must take into account that pixel intensities are Poisson distributed, hence the classical sample covariance estimator is sub-optimal. Moreover, in single molecule imaging, including in-plane rotated copies of all images could further improve the accuracy of covariance estimation. In this paper we introduce an efficient and accurate algorithm for covariance matrix estimation of count noise 2-D images, including their uniform planar rotations and possibly reflections. Our procedure, steerable ePCA, combines in a novel way two recently introduced innovations. The first is a methodology for principal component analysis (PCA) for Poisson distributions, and more generally, exponential family distributions, called ePCA. The second is steerable PCA, a fast and accurate procedure for including all planar rotations for PCA. The resulting principal components are invariant to the rotation and reflection of the input images. We demonstrate the efficiency and accuracy of steerable ePCA in numerical experiments involving simulated XFEL datasets and rotated Yale B face data. Copyright © 2018, The Authors. All rights reserved.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Isocitrate dehydrogenase 1 primes group-3 medulloblastomas for cuproptosis

引用

Cancer Cell 2025年第6期43卷 1159-1174.e8页

作者： Dang, Derek Deogharkar, Akash McKolay, John Smith, Kyle S. Panwalkar, Pooja Hoffman, Simon Tian, Wentao Ji, Sunjong Azambuja, Ana P. Natarajan, Siva Kumar Lum, Joanna Bayliss, Jill Manzeck, Katie Sweha, Stefan R. Hamanishi, Erin Pun, Matthew Patel, Diya Rau, Sagar Animasahun, Olamide Achreja, Abhinav Ogrodzinski, Martin P. Diessl, Jutta Cotter, Jennifer Hawes, Debra Yang, Fusheng Doherty, Robert Franson, Andrea T. Hanaford, Allison R. Eberhart, Charles G. Raabe, Eric H. Orr, Brent A. Wechsler-Reya, Robert J. Chen, Brandon Lyssiotis, Costas A. Shah, Yatrik M. Lunt, Sophia Y. Banerjee, Ruma Judkins, Alexander R. Prensner, John R. Koschmann, Carl Waszak, Sebastian M. Nagrath, Deepak Simoes-Costa, Marcos Northcott, Paul A. Venneti, Sriram Laboratory of Brain Tumor Metabolism and Epigenetics Department of Pathology University of Michigan Ann Arbor MI United States Department of Developmental Neurobiology Neurobiology and Brain Tumor Program St. Jude Children's Research Hospital Memphis TN United States Center of Excellence in Neuro-Oncology Sciences St. Jude Children's Research Hospital Memphis TN United States Department of Pediatrics Michigan Medicine Ann Arbor MI United States Department of Pathology Boston Children's Hospital Boston MA United States Department of Systems Biology Harvard Medical School Boston MA United States Cancer Biology and Genetics Program Memorial Sloan Kettering Cancer Center New York NY United States Department of Chemical Engineering University of Michigan Ann Arbor MI United States Laboratory for Systems Biology of Human Diseases University of Michigan Ann Arbor MI United States Biointerfaces Institute University of Michigan Ann Arbor MI United States Department of Biomedical Engineering University of Michigan Ann Arbor MI United States Rogel Cancer Center University of Michigan Ann Arbor MI United States Department of Biochemistry and Molecular Biology Michigan State University East Lansing MI United States Department of Biological Chemistry University of Michigan Medical School Ann Arbor 48109 MI United States Department of Pathology and Laboratory Medicine Children's Hospital Los Angeles Los Angeles CA United States Keck School of Medicine University of Southern California Los Angeles CA United States Department of Pathology Johns Hopkins School of Medicine Baltimore MD United States Division of Neuropathology Department of Pathology School of Medicine Johns Hopkins University Baltimore MD United States Sidney Kimmel Comprehensive Cancer Center School of Medicine Johns Hopkins University Baltimore MD United States Division of Pediatric Oncology Department of Oncology School of Medicine Johns Hopkins University Baltimore MD United

MYC-driven group-3 medulloblastomas (MBs) are malignant pediatric brain cancers without cures. To define actionable metabolic dependencies, we identify upregulation of dihydrolipoyl transacetylase (DLAT), the E2-subunit of pyruvate dehydrogenase complex (PDC) in a subset of group-3 MB with poor prognosis. DLAT is induced by c-MYC and targeting DLAT lowers TCA cycle metabolism and glutathione synthesis. We also note upregulation of isocitrate dehydrogenase 1 (IDH1) gene expression in group-3 MB patient tumors and suppression of IDH1 epigenetically reduces c-MYC and downstream DLAT levels in multiple c-MYC amplified cancers. DLAT is a central regulator of cuproptosis (copper-dependent cell death) induced by the copper ionophore elesclomol. DLAT expression in group-3 MB cells correlates with increased sensitivity to cuproptosis. Elesclomol is brain-penetrant and suppresses tumor growth in vivo in multiple group-3 MB animal models. Our data uncover an IDH1/c-MYC dependent vulnerability that regulates DLAT levels and can be targeted to kill group-3 MB by cuproptosis. © 2025 Elsevier Inc.

关键词： cancer metabolism cell death copper cuproptosis elesclomol epigenetics pediatric brain tumor protein lipoylation

来源：评论

学校读者我要写书评

暂无评论

How to verify the precision of density-functional-theory implementations via reproducible and universal workflows

arXiv

引用

arXiv 2023年

作者： Bosoni, Emanuele Beal, Louis Bercx, Marnik Blaha, Peter Blügel, Stefan Bröder, Jens Callsen, Martin Cottenier, Stefaan Degomme, Augustin Dikan, Vladimir Eimre, Kristjan Flage-Larsen, Espen Fornari, Marco Garcia, Alberto Genovese, Luigi Giantomassi, Matteo Huber, Sebastiaan P. Janssen, Henning Kastlunger, Georg Krack, Matthias Kresse, Georg Kühne, Thomas D. Lejaeghere, Kurt Madsen, Georg K.H. Marsman, Martijn Marzari, Nicola Michalicek, Gregor Mirhosseini, Hossein Müller, Tiziano M.A. Petretto, Guido Pickard, Chris J. Poncé, Samuel Rignanese, Gian-Marco Rubel, Oleg Ruh, Thomas Sluydts, Michael Vanpoucke, Danny E.P. Vijay, Sudarshan Wolloch, Michael Wortmann, Daniel Yakutovich, Aliaksandr V. Yu, Jusong Zadoks, Austin Zhu, Bonan Pizzi, Giovanni Institut de Ciència de Materials de Barcelona ICMAB-CSIC Campus UAB Bellaterra08193 Spain Univ. Grenoble-Alpes CEA IRIG-MEM-L Sim Grenoble38000 France LausanneCH-1015 Switzerland Institute for Materials Chemistry Technical University of Vienna Getreidemarkt 9/165-TC ViennaA-1060 Austria Peter Grünberg Institut Institute for Advanced Simulation Forschungszentrum Jülich JARA JülichD-52425 Germany Forschungszentrum Jülich JülichD-52425 Germany Department of Electromechanical Systems and Metal Engineering Ghent University Belgium Ghent University Belgium Institute of Atomic and Molecular Sciences Academia Sinica Taipei10617 Taiwan Norwegian EuroHPC Competence Center Sigma2 AS Norway SINTEF Industry Materials Physics Oslo Norway Department of Physics Science of Advanced Materials Program Central Michigan University Mount PleasantMI48859 United States Université catholique de Louvain Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium LausanneCH-1015 Switzerland Kongens Lyngby2800 Denmark VilligenCH-5232 Switzerland University of Vienna Faculty of Physics Center for Computational Materials Science Kolingasse 14-16 ViennaA-1090 Austria VASP Software GmbH Sensengasse 8 ViennaA-1090 Austria Helmholtz-Zentrum Dresden-Rossendorf GörlitzD-02826 Germany Center for Sustainable Systems Design University of Paderborn PaderbornD-33098 Germany OCAS NV ArcelorMittal Global R&D Gent Pres. J. F. Kennedylaan 3 ZelzateB-9060 Belgium Dynamics of Condensed Matter Theoretical Chemistry University of Paderborn PaderbornD-33098 Germany HPE HPC EMEA Research Lab BaselCH-4051 Switzerland Department of Materials Science & Metallurgy University of Cambridge 27 Charles Babbage Road CambridgeCB3 0FS United Kingdom Advanced Institute for Materials Research Tohoku University 2-1-1 Katahira Aoba Sendai980-8577 Japan Department of Materials Science and Engineering McMaster University 1280 Main Street West HamiltonONL8S 4L8 Canada ePot

In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter physics and materials science research. Only in 2016, however, their precision (i.e., to which extent properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. We discuss here general recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z=1 to 96 and characterizing 10 prototypical cubic compounds for each element: 4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Such effort is facilitated by deploying AiiDA common workflows that perform automatic input parameter selection, provide identical input/output interfaces across codes, and ensure full reproducibility. Finally, we discuss the extent to which the current results for total energies can be reused for different goals (e.g., obtaining formation energies). © 2023, CC BY.

关键词： Density functional theory

来源：评论

学校读者我要写书评

暂无评论

MoSi2N4single-layer: A novel two-dimensional material with outstanding mechanical, thermal, electronic, optical, and photocatalytic properties

arXiv

引用

arXiv 2020年

作者： Bafekry, A. Faraji, M. Hoat, Do M. Fadlallah, M.M. Shahrokhi, M. Shojaei, F. Gogova, D. Ghergherehchi, M. Department of Physics University of Guilan Rasht41335-1914 Iran Department of Physics University of Antwerp Groenenborgerlaan 171 AntwerpB-2020 Belgium Micro and Nanotechnology Graduate Program TOBB University of Economics and Technology Sogutozu Caddesi No 43 Sogutozu Ankara06560 Turkey Computational Laboratory for Advanced Materials and Structures Advanced Institute of Materials Science Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Physics Faculty of Science Benha University Benha13518 Egypt University Lyon ENS de Lyon CNRS Universit Claude Bernard Lyon 1 Laboratoire de Chimie UMR 5182 LyonF-69342 France Department of Chemistry Faculty of Sciences Persian Gulf University Bushehr75169 Iran Department of Physics University of Oslo P.O. Box 1048 Blindern Oslo Norway College of Electronic and Electrical Engineering Sungkyun Kwan University Suwon Korea Republic of

Very recently, the two-dimensional (2D) form of MoSi2N4has been successfully fabricated [Hong et al., Sci. 369, 670 (2020)]. Motivated by theses recent experimental results, herein we investigate the structural, mechanical, thermal, electronic, optical and photocatalytic properties using hybrid density functional theory (HSE06-DFT). Phonon band dispersion calculations reveal the dynamical stability of MoSi2N4monolayer structure. Furthermore, the mechanical study confirms the stability of MoSi2N4monolayer. As compared to the corresponding value of graphene, we find the Young's modulus decreases by ∼ 30% while the Poisson's ratio increases by ∼ 30%. In addition, its work function is very similar to that of phosphorene and MoS2 monolayers. The electronic structure investigation shows the MoSi2N4monolayer is an indirect bandgap semiconductor. We have determined the bandgap using the HSE06 (GGA) is 2.35 (1.79) eV, which is an overestimated (underestimated) value of the experimental bandgap (1.99 eV). The thermoelectric study shows a good thermoelectric performance of the MoSi2N4monolayer with a figure of merit slightly larger than unity at high temperatures. The optical analysis using the RPA method constructed over HSE06 shows that the first absorption peak of the MoSi2N4monolayer for in-plane polarization is located in the visible range of spectrum, i.e. it is a promising candidate for advancing optoelectronic nanodevices. The photocatalytic study indicates the MoSi2N4monloayer can be a promising photocatalyst for water splitting as well as and CO2 reduction. In summary, the fascinating MoSi2N4monloayer is a promising 2D material in many applications due to its unique physical properties. Copyright © 2020, The Authors. All rights reserved.

关键词： Molybdenum compounds

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：