DOCSLIB.ORG

Postmodern Electronic Structure Theory by Joonho Lee A

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Postmodern Electronic Structure Theory by Joonho Lee A Postmodern Electronic Structure Theory by Joonho Lee A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Chemistry in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Martin P. Head-Gordon, Chair Professor Eran Rabani Professor Lin Lin Summer 2019 Postmodern Electronic Structure Theory Copyright 2019 by Joonho Lee 1 Abstract Postmodern Electronic Structure Theory by Joonho Lee Doctor of Philosophy in Chemistry University of California, Berkeley Professor Martin P. Head-Gordon, Chair This dissertation is concerned with the development and applications of approaches to the electron correlation problem. We start with an introduction that summarizes modern approaches to the electron correlation problem. In our view, there are two remaining challenges that modern density functional theory cannot satisfactorily solve. The first challenge is due to self-interaction error and the second is due to strong correlation. We discuss two methods developed by the author that attempt to make progress to address the second challenge. The first approach is useful in distinguishing strong and weak correlation in a computationally economical way. It is based on orbital optimization in the presence of regularized second-order Møller-Plesset perturbation theory (κ-OOMP2), which is an approximate method to obtain Br¨uckner orbitals. κ-OOMP2 includes weak correlation while attenuating strong correlation. As such, it distinguishes artificial and essential symmetry breaking which occur at the Hartree-Fock (HF) level. Ar- tificial symmetry breaking appears due to the lack of weak correlation, not due to the lack of strong correlation. Therefore, the common wisdom in quantum chem- istry, which equates symmetry breaking at the HF level and strong correlation, can result in a wrong understanding of the system. Essential symmetry breaking, on the other hand, signals strong correlation that is beyond the scope of simple perturba- tion theory. κ-OOMP2 has been shown to reliably distinguish these two: symmetry breaking in the κ-OOMP2 orbitals is essential. This has been applied to a recent con- troversy about whether C60 is strongly correlated. Starting from a broken-symmetry HF solution, κ-OOMP2 restores every symmetry. As such, C60 is not strongly cor- related. Moreover, κ-OOMP2 successfully predicts strong correlation for a known biradicaloid, C36, by showing essential symmetry breaking in its orbitals. We also exploited essential symmetry breaking in singlet biradicaloids using κ-OOMP2 and 2 showed quantitative accuracy in obtaining singlet-triplet gaps of various molecules. This new approach should be helpful for redefining the common wisdom in quantum chemistry. The second method is an exact, spin-pure, polynomial-scaling way to describe strong spin-correlation (SSC). SSC is present when there are many spatially separate open-shell electrons with small spin-flip energy cost. Describing SSC exactly requires the inclusion of all essential spin-couplings. The number of such spin-couplings scales exponentially with the number of electrons. Because of this, SSC was thought to require an exponential number of wavefunction parameters in general. However, new development suggests that there is an efficient way to obtain all these spin- couplings with only a quadratic number of wavefunction parameters, which is called the coupled-cluster valence-bond (CCVB) method. We discuss different challenges in CCVB: (1) its non-black-box nature and (2) its inability to describe SSC in spin- frustrated systems. We present two improved CCVB approaches that address these two challenges. These approaches were applied to describe emergent strong corre- lation in oligoacenes and SSC in spin-frustrated systems such as single molecular magnets and metalloenzymes. The remaining challenges in CCVB are the inclu- sion of ionic excitations which are not relevant for SSC, but crucial for obtaining quantitative accuracy. i To my wife Soojin ii Acknowledgments The first to thank is my advisor, Prof. Martin Head-Gordon. The best academic decision I made so far was to move from Caltech to Berkeley to work with Martin. The transfer was very difficult and the intellectual stimuli provided by Martin were the only things that I could hold on to in the beginning. I am proud of having learned and contributed to his scientific philosophy and legacy. Among many things, I would like to thank Martin for having taught me how to critically assess not only other people's work but also my own work. Most importantly, I thank Martin for giving me intellectual freedom for the last 4 years. Without this freedom, I would not have become the scientist that I am now. I also thank Martin for proofreading every chapter of this dissertation carefully. Any remaining errors are my own. I would like to thank everyone with whom I interacted during my time in Berkeley. I must thank Prof. Eran Rabani and Prof. Lin Lin for giving me career advice and being approachable whenever I needed their help. I must thank Dr. Dave Small for teaching me everything I know about coupled-cluster theory. The second best thing that happened to me during my time in Berkeley was to work with Dave early on. I must thank Dr. Evgeny Epifanovsky for encouraging me to reimplement anything that interests me in Q-Chem. Without his encouragement, I would not have learned as much about scientific programming as I know now. I must thank Luke Bertels, Srimukh Prasad, and Matthias Loipersberger for being best friends, always standing by me, and working with me on projects that have taught me a lot. I spent more time with you guys than with my wife Soojin during Ph.D. and I am grateful for the quality time we had together. I must thank Evgeny once more, Dr. Jerome Gonthier, and Dr. Eloy Ramos for sharing the courage I had about periodic boundary conditions and following me down the path of endless implementations of missing features when no publication was guaranteed. Lastly, I thank other people with whom I interacted through Martin's group including Eric Sundstrom, Paul Horn, Narbe Mardirossian, Jonathan Thirman, Yuezhi Mao, Jon Witte, Alec White, Jon Weisberg, Brad Ganoe, Leo Cunha, Dr. Shane Yost, Dr. Udi Tsivion, Dr. Roberto Pevrati, Dr. Xintian Feng, Dr. Cameron Mackie, Dr. Tim Stauch, and Dr. Christopher Stein for being good co-workers. I must thank Eric once again for convincing me to transfer to Berkeley when I was unhappy about my scientific development. I thank Jessie Woodcock for making sure that I get paid on time. Outside the Head-Gordon group, I have many individuals to thank. First, I thank Prof. Eric Neuscamman, Luning Zhao, Brett Van Der Goetz, Sergio Flores, Dr. Peter Walters, and Leon Otis for welcoming me to the Neuscamman group's meetings and teaching me some aspects of variational Monte Carlo. I thank Luning once more for good friendship and always giving me good scientific arguments. I thank Lin again, iii Jiefu Zhang, Leo Zepeda, Michael Lindsey, and others in the Lin group for warm hospitality when I joined their meetings at Evans and teaching me useful applied math tricks from time to time. I thank Prof. Birgit Whaley and Donghyun Lee for welcoming me back to Berkeley and helping me finish my undergraduate project with them. I thank Donghyun again for sharing his dissertation template which saved me weeks when writing this dissertation. I must thank Birgit again and Bill Huggins for teaching me many things (mostly things that are not yet possible!) about quantum computing. I thank Dr. Miguel Morales and Fionn Malone for teaching me almost everything I know about quantum Monte Carlo (QMC). I thank Fionn once more for being patient with me when I ask millions of questions about QMC. I would also like to thank people from my Caltech time who helped me prepare for my Ph.D. journey at Berkeley. I thank Prof. Fred Manby for teaching me tricks in density functional theory and joys of working on quantum chemistry early on. I thank Mike Webb, Michiel Niesen, Dr. Pengfei Huo, Mark Fornace, and Kevin Shen for being good colleagues with me. I would like to thank Luke, Srimukh, and Fionn for proofreading the abstract, introduction, and conclusions of this dissertation. Finally, I am truly grateful to my family for all their support and patience. Thank you Soojin for your love, patience, understanding, encouragement, and everything else. I look forward to building our new home together (briefly in Berkeley and) in New York City and our future afterwards. Thank you my dad Hyungkeun, my mom Jungsook, and my sister Eunkyung for consistent support throughout my academic journey. iv Contents Contents iv List of Figures viii List of Tables xiii Note on Previously Published Work xix 1 Introduction 1 1.1 Modern Quantum Chemistry . 2 1.2 Author's Views on Pople's Criteria . 5 1.3 Challenges Addressed in This Dissertation . 8 1.4 Works Not Mentioned in This Dissertation . 13 1.5 Outline . 14 2 Regularized Orbital-Optimized Second-Order Møller-Plesset Per- turbation Theory 17 2.1 Introduction . 17 2.2 Theory . 20 2.2.1 OOMP2 Lagrangian in Spin-Orbital Basis . 20 2.2.2 Regularized OOMP2 . 24 2.3 Computational Details . 28 2.4 Results and Discussion . 29 2.4.1 ROOMP2 to UOOMP2 Stability Analysis . 29 2.4.2 Training the Regularization Parameter and Its Validation . 31 2.4.3 Application to Organic Singlet Biradicaloids . 37 2.5 Conclusions . 42 3 Distinguishing Artificial and Essential Symmetry Breaking in a Single Determinant 49 v 3.1 Introduction . 49 3.2 Theory . 52 3.2.1 Classification of HF Solutions . 52 3.2.2 Generalized MP2 . 53 3.2.3 Regularized Orbital-Optimized MP2 . 54 3.2.4 Classification of OOMP2 Solutions .
Load more

Recommended publications
  • Free and Open Source Software for Computational Chemistry Education
    Free and Open Source Software for Computational Chemistry Education Susi Lehtola∗,y and Antti J. Karttunenz yMolecular Sciences Software Institute, Blacksburg, Virginia 24061, United States zDepartment of Chemistry and Materials Science, Aalto University, Espoo, Finland E-mail: [email protected].fi Abstract Long in the making, computational chemistry for the masses [J. Chem. Educ. 1996, 73, 104] is finally here. We point out the existence of a variety of free and open source software (FOSS) packages for computational chemistry that offer a wide range of functionality all the way from approximate semiempirical calculations with tight- binding density functional theory to sophisticated ab initio wave function methods such as coupled-cluster theory, both for molecular and for solid-state systems. By their very definition, FOSS packages allow usage for whatever purpose by anyone, meaning they can also be used in industrial applications without limitation. Also, FOSS software has no limitations to redistribution in source or binary form, allowing their easy distribution and installation by third parties. Many FOSS scientific software packages are available as part of popular Linux distributions, and other package managers such as pip and conda. Combined with the remarkable increase in the power of personal devices—which rival that of the fastest supercomputers in the world of the 1990s—a decentralized model for teaching computational chemistry is now possible, enabling students to perform reasonable modeling on their own computing devices, in the bring your own device 1 (BYOD) scheme. In addition to the programs’ use for various applications, open access to the programs’ source code also enables comprehensive teaching strategies, as actual algorithms’ implementations can be used in teaching.
    [Show full text]
  • Identification of a Spin-Coupled Mo (III) in the Nitrogenase Iron
    Identification of a spin-coupled Mo(III) in the nitrogenase iron-molybdenum cofactor Ragnar Bjornsson, Frederico A. Lima, Thomas Spatzal, Thomas Weyhermueller, Pieter Glatzel, Eckhard Bill, Oliver Einsle, Frank Neese, Serena Debeer To cite this version: Ragnar Bjornsson, Frederico A. Lima, Thomas Spatzal, Thomas Weyhermueller, Pieter Glatzel, et al.. Identification of a spin-coupled Mo(III) in the nitrogenase iron-molybdenum cofactor. Chemical Science , The Royal Society of Chemistry, 2014, 5 (8), pp.3096-3103. 10.1039/c4sc00337c. hal- 01572851 HAL Id: hal-01572851 https://hal.archives-ouvertes.fr/hal-01572851 Submitted on 8 Aug 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Chemical Science View Article Online EDGE ARTICLE View Journal | View Issue Identification of a spin-coupled Mo(III)inthe nitrogenase iron–molybdenum cofactor† Cite this: Chem. Sci.,2014,5,3096 a a b a Ragnar Bjornsson,‡ Frederico A. Lima,‡§ Thomas Spatzal,{ Thomas Weyhermuller,¨ Pieter Glatzel,c Eckhard Bill,a Oliver Einsle,*b Frank Neese*a and Serena DeBeer*ad Nitrogenase is a complex enzyme that catalyzes the formation of ammonia utilizing a MoFe7S9C cluster. The presence of a central carbon atom was recently revealed, finally completing the atomic level description of the active site.
    [Show full text]
  • A Model for Dinitrogen Binding in the E4 State of Nitrogenase† Cite This: Chem
    Chemical Science View Article Online EDGE ARTICLE View Journal | View Issue A model for dinitrogen binding in the E4 state of nitrogenase† Cite this: Chem. Sci.,2019,10, 11110 ab a ab All publication charges for this article Albert Th. Thorhallsson, Bardi Benediktsson and Ragnar Bjornsson * have been paid for by the Royal Society of Chemistry Molybdenum nitrogenase is one of the most intriguing metalloenzymes in nature, featuring an exotic iron– molybdenum–sulfur cofactor, FeMoco, whose mode of action remains elusive. In particular, the molecular and electronic structure of the N2-binding E4 state is not known. In this study we present theoretical QM/ MM calculations of new structural models of the E4 state of molybdenum-dependent nitrogenase and compare to previously suggested models for this enigmatic redox state. We propose two models as possible candidates for the E4 state. Both models feature two hydrides on the FeMo cofactor, bridging atoms Fe2 and Fe6 with a terminal sulfhydryl group on either Fe2 or Fe6 (derived from the S2B bridge) and the change in coordination results in local lower-spin electronic structure at Fe2 and Fe6. These structures appear consistent with the bridging hydride proposal put forward from ENDOR studies and are calculated to be lower in energy than other proposed models for E4 at the TPSSh-QM/MM level of Creative Commons Attribution 3.0 Unported Licence. theory. We critically analyze the DFT method dependency in calculations of FeMoco that has resulted in strikingly different proposals for this state. Importantly, dinitrogen binds exothermically to either Fe2 or Fe6 in our models, contrary to others, an effect rationalized via the unique ligand field (from the hydrides) at the Fe with an empty coordination site.
    [Show full text]
  • Core Software Blocks in Quantum Chemistry: Tensors and Integrals Workshop Program
    Core Software Blocks in Quantum Chemistry: Tensors and Integrals Workshop Program Start: Sunday, May 7, 2017 afternoon. Resort check-in at 4:00 pm. Finish: Wednesday, May 10, noon Lectures are in Scripps, posters are in Heather. Sunday 6:00-7:00: Dinner 7:30-9:00 Opening session 7:30–7:45 Anna Krylov (USC): “MolSSI and some lessons from previous workshop, goals of the workshop” 7:45-8:00 Theresa Windus (Iowa): “Mission of the Molecular Science Consortium” 8:00-9:00 Introduction of participants: 2 min presentation, can have one slide (send in advance) 9:00-10:30 Reception and posters Monday Breakfast: 7:30-9:00 9:00-11:45 Session I: Overview of tensors projects and current developments (moderator Daniel Smith) 9:00-9:10 Daniel Smith (MolSSI): Overview of tensor projects 9:10-9:30 Evgeny Epifanovsky (Q-Chem): Overview of Libtensor 9:30-9:50 Ed Solomonik: "An Overview of Cyclops Tensor Framework" 9:50-10:10 Ed Valeev (VT): "TiledArray: A composable massively parallel block-sparse tensor framework" 10:10-10:30 Coffee break 10:30-10:50 Devin Matthews (UT Austin): "Aquarius and TBLIS: Orthogonal Axes in Multilinear Algebra" 10:50-11:10 Karol Kowalskii (PNNL, NWChem): "NWChem, NWChemEX , and new tensor algebra systems for many-body methods" 11:10-11:30 Peng Chong (VT): "Many-body toolkit in re-designed Massively Parallel Quantum Chemistry package" 11:30-11:55 Moderated discussion: "What problems are we *still* solving?” Lunch: 12:00-1:00 Free time for unstructured discussions 5:00 Posters (coffee/tea) Dinner: 6-7:00 7:15-9:00 Session II: Computer
    [Show full text]
  • The Mysterious Central Atom in the Nitrogenase Femo Cofactor
    The mysterious central atom in the nitrogenase FeMo cofactor Kevin Hwang Literature Seminar December 6, 2011 The reduction of dinitrogen remains one of the biggest challenges in chemistry today. While industrial-scale production of ammonia has been made possible by the Haber- Bosch process, this process requires harsh conditions, with very high temperatures and pressures necessary in order to break the extremely robust N-N triple bond. In contrast, certain bacteria have evolved enzymes capable of catalytically reducing nitrogen to ammonia under ambient conditions (Eq. 1), a feat thus far unmatched by human ingenuity.1 As a result, substantial effort has been applied towards understanding the mechanism of bacterial nitrogenases, and in particular one of the most studied is the molybdenum- containing nitrogenase (Mo-nitrogenase).2 This review will cover recent work elucidating the structure of the iron-molybdenum cofactor, which in Mo-nitrogenase is believed to be the site of nitrogen binding and reduction. The structure of nitrogenase from Azotobacter vinelandii was first reported in 1992 by Kim and Rees.3 From this structure, the overall organization of nitrogenase was described. Nitrogenase contains two proteins - an iron-containing protein, with a [4Fe:4S] cluster used for electron transfer; and an iron-molybdenum protein, which contains a [8Fe:7S] cluster (the P cluster), also used for electron transfer, and an iron-molybdenum cluster known alternatively as the M cluster or the iron- molybdenum cofactor (FeMoco). The assigned structure contained a unique arrangement of seven iron atoms and one molybdenum atom, bridged by sulfur atoms, surrounding a cavity with diameter approximately 4Å (Figure 1).3 Investigation of MoFe-deficient variants of nitrogenase have suggested that this cluster is the site of nitrogen fixation, Figure 1.
    [Show full text]
  • Pyscf: the Python-Based Simulations of Chemistry Framework
    PySCF: The Python-based Simulations of Chemistry Framework Qiming Sun∗1, Timothy C. Berkelbach2, Nick S. Blunt3,4, George H. Booth5, Sheng Guo1,6, Zhendong Li1, Junzi Liu7, James D. McClain1,6, Elvira R. Sayfutyarova1,6, Sandeep Sharma8, Sebastian Wouters9, and Garnet Kin-Lic Chany1 1Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena CA 91125, USA 2Department of Chemistry and James Franck Institute, University of Chicago, Chicago, Illinois 60637, USA 3Chemical Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA 4Department of Chemistry, University of California, Berkeley, California 94720, USA 5Department of Physics, King's College London, Strand, London WC2R 2LS, United Kingdom 6Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA 7Institute of Chemistry Chinese Academy of Sciences, Beijing 100190, P. R. China 8Department of Chemistry and Biochemistry, University of Colorado Boulder, Boulder, CO 80302, USA 9Brantsandpatents, Pauline van Pottelsberghelaan 24, 9051 Sint-Denijs-Westrem, Belgium arXiv:1701.08223v2 [physics.chem-ph] 2 Mar 2017 Abstract PySCF is a general-purpose electronic structure platform designed from the ground up to emphasize code simplicity, so as to facilitate new method development and enable flexible ∗[email protected] [email protected] 1 computational workflows. The package provides a wide range of tools to support simulations of finite-size systems, extended systems with periodic boundary conditions, low-dimensional periodic systems, and custom Hamiltonians, using mean-field and post-mean-field methods with standard Gaussian basis functions. To ensure ease of extensibility, PySCF uses the Python language to implement almost all of its features, while computationally critical paths are implemented with heavily optimized C routines.
    [Show full text]
  • Jaguar 5.5 User Manual Copyright © 2003 Schrödinger, L.L.C
    Jaguar 5.5 User Manual Copyright © 2003 Schrödinger, L.L.C. All rights reserved. Schrödinger, FirstDiscovery, Glide, Impact, Jaguar, Liaison, LigPrep, Maestro, Prime, QSite, and QikProp are trademarks of Schrödinger, L.L.C. MacroModel is a registered trademark of Schrödinger, L.L.C. To the maximum extent permitted by applicable law, this publication is provided “as is” without warranty of any kind. This publication may contain trademarks of other companies. October 2003 Contents Chapter 1: Introduction.......................................................................................1 1.1 Conventions Used in This Manual.......................................................................2 1.2 Citing Jaguar in Publications ...............................................................................3 Chapter 2: The Maestro Graphical User Interface...........................................5 2.1 Starting Maestro...................................................................................................5 2.2 The Maestro Main Window .................................................................................7 2.3 Maestro Projects ..................................................................................................7 2.4 Building a Structure.............................................................................................9 2.5 Atom Selection ..................................................................................................10 2.6 Toolbar Controls ................................................................................................11
    [Show full text]
  • Femo Cofactor Maturation on Nifen SPECIAL FEATURE
    FeMo cofactor maturation on NifEN SPECIAL FEATURE Yilin Hu*, Mary C. Corbett†, Aaron W. Fay*, Jerome A. Webber*, Keith O. Hodgson†‡§, Britt Hedman‡§, and Markus W. Ribbe*§ *Department of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697-3900; †Department of Chemistry, Stanford University, Stanford, CA 94305; and ‡Stanford Synchrotron Radiation Laboratory, Stanford Linear Accellerator Center, Stanford University, 2575 Sand Hill Road, MS 69, Menlo Park, CA 94025-7015 Edited by Douglas C. Rees, California Institute of Technology, Pasadena, CA, and approved May 10, 2006 (received for review March 31, 2006) FeMo cofactor (FeMoco) biosynthesis is one of the most compli- Unlike the P cluster, FeMoco, which contains additional hetero- cated processes in metalloprotein biochemistry. Here we show that metal (Mo) and organic moiety (homocitrate), is first assembled on Mo and homocitrate are incorporated into the Fe͞S core of the a scaffold protein (17, 18) and then inserted into its destined FeMoco precursor while it is bound to NifEN and that the resulting location in MoFe protein (‘‘ex situ’’ assembly). Biosynthesis of fully complemented, FeMoco-like cluster is transformed into a FeMoco presumably starts with the production of the Fe͞Scoreby mature FeMoco upon transfer from NifEN to MoFe protein through NifB (encoded by nifB) (19, 20), which is then transferred to, and direct protein–protein interaction. Our findings not only clarify the further processed on, the ␣2␤2 tetrameric NifEN protein (17, 21). process of FeMoco
    [Show full text]
  • Trends in Atomistic Simulation Software Usage [1.3]
    A LiveCoMS Perpetual Review Trends in atomistic simulation software usage [1.3] Leopold Talirz1,2,3*, Luca M. Ghiringhelli4, Berend Smit1,3 1Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingenierie Chimiques, Valais, École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland; 2Theory and Simulation of Materials (THEOS), Faculté des Sciences et Techniques de l’Ingénieur, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; 3National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; 4The NOMAD Laboratory at the Fritz Haber Institute of the Max Planck Society and Humboldt University, Berlin, Germany This LiveCoMS document is Abstract Driven by the unprecedented computational power available to scientific research, the maintained online on GitHub at https: use of computers in solid-state physics, chemistry and materials science has been on a continuous //github.com/ltalirz/ rise. This review focuses on the software used for the simulation of matter at the atomic scale. We livecoms-atomistic-software; provide a comprehensive overview of major codes in the field, and analyze how citations to these to provide feedback, suggestions, or help codes in the academic literature have evolved since 2010. An interactive version of the underlying improve it, please visit the data set is available at https://atomistic.software. GitHub repository and participate via the issue tracker. This version dated August *For correspondence: 30, 2021 [email protected] (LT) 1 Introduction Gaussian [2], were already released in the 1970s, followed Scientists today have unprecedented access to computa- by force-field codes, such as GROMOS [3], and periodic tional power.
    [Show full text]
  • Lawrence Berkeley National Laboratory Recent Work
    Lawrence Berkeley National Laboratory Recent Work Title From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape. Permalink https://escholarship.org/uc/item/4sm897jh Journal Chemical reviews, 121(8) ISSN 0009-2665 Authors Kowalski, Karol Bair, Raymond Bauman, Nicholas P et al. Publication Date 2021-04-01 DOI 10.1021/acs.chemrev.0c00998 Peer reviewed eScholarship.org Powered by the California Digital Library University of California From NWChem to NWChemEx: Evolving with the computational chemistry landscape Karol Kowalski,y Raymond Bair,z Nicholas P. Bauman,y Jeffery S. Boschen,{ Eric J. Bylaska,y Jeff Daily,y Wibe A. de Jong,x Thom Dunning, Jr,y Niranjan Govind,y Robert J. Harrison,k Murat Keçeli,z Kristopher Keipert,? Sriram Krishnamoorthy,y Suraj Kumar,y Erdal Mutlu,y Bruce Palmer,y Ajay Panyala,y Bo Peng,y Ryan M. Richard,{ T. P. Straatsma,# Peter Sushko,y Edward F. Valeev,@ Marat Valiev,y Hubertus J. J. van Dam,4 Jonathan M. Waldrop,{ David B. Williams-Young,x Chao Yang,x Marcin Zalewski,y and Theresa L. Windus*,r yPacific Northwest National Laboratory, Richland, WA 99352 zArgonne National Laboratory, Lemont, IL 60439 {Ames Laboratory, Ames, IA 50011 xLawrence Berkeley National Laboratory, Berkeley, 94720 kInstitute for Advanced Computational Science, Stony Brook University, Stony Brook, NY 11794 ?NVIDIA Inc, previously Argonne National Laboratory, Lemont, IL 60439 #National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831-6373 @Department of Chemistry, Virginia Tech, Blacksburg, VA 24061 4Brookhaven National Laboratory, Upton, NY 11973 rDepartment of Chemistry, Iowa State University and Ames Laboratory, Ames, IA 50011 E-mail: [email protected] 1 Abstract Since the advent of the first computers, chemists have been at the forefront of using computers to understand and solve complex chemical problems.
    [Show full text]
  • Openmolcas: from Source Code to Insight Ignacio Fdez
    Article Cite This: J. Chem. Theory Comput. XXXX, XXX, XXX−XXX pubs.acs.org/JCTC OpenMolcas: From Source Code to Insight Ignacio Fdez. Galvan,́ 1,2 Morgane Vacher,1 Ali Alavi,3 Celestino Angeli,4 Francesco Aquilante,5 Jochen Autschbach,6 Jie J. Bao,7 Sergey I. Bokarev,8 Nikolay A. Bogdanov,3 Rebecca K. Carlson,7,9 Liviu F. Chibotaru,10 Joel Creutzberg,11,12 Nike Dattani,13 Mickael̈ G. Delcey,1 Sijia S. Dong,7,14 Andreas Dreuw,15 Leon Freitag,16 Luis Manuel Frutos,17 Laura Gagliardi,7 Fredé rić Gendron,6 Angelo Giussani,18,19 Leticia Gonzalez,́ 20 Gilbert Grell,8 Meiyuan Guo,1,21 Chad E. Hoyer,7,22 Marcus Johansson,12 Sebastian Keller,16 Stefan Knecht,16 Goran Kovacevič ,́ 23 Erik Kallman,̈ 1 Giovanni Li Manni,3 Marcus Lundberg,1 Yingjin Ma,16 Sebastian Mai,20 Joaõ Pedro Malhado,24 Per Åke Malmqvist,12 Philipp Marquetand,20 Stefanie A. Mewes,15,25 Jesper Norell,11 Massimo Olivucci,26,27,28 Markus Oppel,20 Quan Manh Phung,29 Kristine Pierloot,29 Felix Plasser,30 Markus Reiher,16 Andrew M. Sand,7,31 Igor Schapiro,32 Prachi Sharma,7 Christopher J. Stein,16,33 Lasse Kragh Sørensen,1,34 Donald G. Truhlar,7 Mihkel Ugandi,1,35 Liviu Ungur,36 Alessio Valentini,37 Steven Vancoillie,12 Valera Veryazov,12 Oskar Weser,3 Tomasz A. Wesołowski,5 Per-Olof Widmark,12 Sebastian Wouters,38 Alexander Zech,5 J. Patrick Zobel,12 and Roland Lindh*,2,39 1Department of Chemistry − Ångström Laboratory, Uppsala University, P.O.
    [Show full text]
  • Electronic Structure Calculations in Quantum Chemistry
    Electronic Structure Calculations in Quantum Chemistry Alexander B. Pacheco User Services Consultant LSU HPC & LONI [email protected] HPC Training Louisiana State University Baton Rouge Nov 16, 2011 Electronic Structure Calculations in Quantum Chemistry Nov 11, 2011 HPC@LSU - http://www.hpc.lsu.edu 1 / 55 Outline 1 Introduction 2 Ab Initio Methods 3 Density Functional Theory 4 Semi-empirical Methods 5 Basis Sets 6 Molecular Mechanics 7 Quantum Mechanics/Molecular Mechanics (QM/MM) 8 Computational Chemistry Programs 9 Exercises 10 Tips for Quantum Chemical Calculations Electronic Structure Calculations in Quantum Chemistry Nov 11, 2011 HPC@LSU - http://www.hpc.lsu.edu 2 / 55 Introduction What is Computational Chemistry? Computational Chemistry is a branch of chemistry that uses computer science to assist in solving chemical problems. Incorporates the results of theoretical chemistry into efficient computer programs. Application to single molecule, groups of molecules, liquids or solids. Calculates the structure and properties of interest. Computational Chemistry Methods range from 1 Highly accurate (Ab-initio,DFT) feasible for small systems 2 Less accurate (semi-empirical) 3 Very Approximate (Molecular Mechanics) large systems Electronic Structure Calculations in Quantum Chemistry Nov 11, 2011 HPC@LSU - http://www.hpc.lsu.edu 3 / 55 Introduction Theoretical Chemistry can be broadly divided into two main categories 1 Static Methods ) Time-Independent Schrödinger Equation H^ Ψ = EΨ ♦ Quantum Chemical/Ab Initio /Electronic Structure Methods ♦ Molecular Mechanics 2 Dynamical Methods ) Time-Dependent Schrödinger Equation @ { Ψ = H^ Ψ ~@t ♦ Classical Molecular Dynamics ♦ Semi-classical and Ab-Initio Molecular Dynamics Electronic Structure Calculations in Quantum Chemistry Nov 11, 2011 HPC@LSU - http://www.hpc.lsu.edu 4 / 55 Tutorial Goals Provide a brief introduction to Electronic Structure Calculations in Quantum Chemistry.
    [Show full text]