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The Molecular Sciences Software Institute
The Molecular Sciences Software Institute T. Daniel Crawford, Cecilia Clementi, Robert Harrison, Teresa Head-Gordon, Shantenu Jha*, Anna Krylov, Vijay Pande, and Theresa Windus http://molssi.org S2I2 HEP/CS Workshop at NCSA/UIUC 07 Dec, 2016 1 Outline • Space and Scope of Computational Molecular Sciences. • “State of the art and practice” • Intellectual drivers • Conceptualization Phase: Identifying the community and needs • Bio-molecular Simulations (BMS) Conceptualization • Quantum Mechanics/Chemistry (QM) Conceptualization • Execution Phase. • Structure and Governance Model • Resource Distribution • Work Plan 2 The Molecular Sciences Software Institute (MolSSI) • New project (as of August 1st, 2016) funded by the National Science Foundation. • Collaborative effort by Virginia Tech, Rice U., Stony Brook U., U.C. Berkeley, Stanford U., Rutgers U., U. Southern California, and Iowa State U. • Total budget of $19.42M for five years, potentially renewable to ten years. • Joint support from numerous NSF divisions: Advanced Cyberinfrastructure (ACI), Chemistry (CHE), Division of Materials Research (DMR), Office of Multidisciplinary Activities (OMA) • Designed to serve and enhance the software development efforts of the broad field of computational molecular science. 3 Computational Molecular Sciences (CMS) • The history of CMS – the sub-fields of quantum chemistry, computational materials science, and biomolecular simulation – reaches back decades to the genesis of computational science. • CMS is now a “full partner with experiment”. • For an impressive array of chemical, biochemical, and materials challenges, our community has developed simulations and models that directly impact: • Development of new chiral drugs; • Elucidation of the functionalities of biological macromolecules; • Development of more advanced materials for solar-energy storage, technology for CO2 sequestration, etc. -
Dmol Guide to Select a Dmol3 Task 1
DMOL3 GUIDE MATERIALS STUDIO 8.0 Copyright Notice ©2014 Dassault Systèmes. All rights reserved. 3DEXPERIENCE, the Compass icon and the 3DS logo, CATIA, SOLIDWORKS, ENOVIA, DELMIA, SIMULIA, GEOVIA, EXALEAD, 3D VIA, BIOVIA and NETVIBES are commercial trademarks or registered trademarks of Dassault Systèmes or its subsidiaries in the U.S. and/or other countries. All other trademarks are owned by their respective owners. Use of any Dassault Systèmes or its subsidiaries trademarks is subject to their express written approval. Acknowledgments and References To print photographs or files of computational results (figures and/or data) obtained using BIOVIA software, acknowledge the source in an appropriate format. For example: "Computational results obtained using software programs from Dassault Systèmes Biovia Corp.. The ab initio calculations were performed with the DMol3 program, and graphical displays generated with Materials Studio." BIOVIA may grant permission to republish or reprint its copyrighted materials. Requests should be submitted to BIOVIA Support, either through electronic mail to [email protected], or in writing to: BIOVIA Support 5005 Wateridge Vista Drive, San Diego, CA 92121 USA Contents DMol3 1 Setting up a molecular dynamics calculation20 Introduction 1 Choosing an ensemble 21 Further Information 1 Defining the time step 21 Tasks in DMol3 2 Defining the thermostat control 21 Energy 3 Constraints during dynamics 21 Setting up the calculation 3 Setting up a transition state calculation 22 Dynamics 4 Which method to use? -
Arxiv:1710.00259V1 [Physics.Chem-Ph] 30 Sep 2017 a Relativistically Correct Electron Interaction
One-step treatment of spin-orbit coupling and electron correlation in large active spaces Bastien Mussard1, ∗ and Sandeep Sharma1, y 1Department of Chemistry and Biochemistry, University of Colorado Boulder, Boulder, CO 80302, USA In this work we demonstrate that the heat bath configuration interaction (HCI) and its semis- tochastic extension can be used to treat relativistic effects and electron correlation on an equal footing in large active spaces to calculate the low energy spectrum of several systems including halogens group atoms (F, Cl, Br, I), coinage atoms (Cu, Au) and the Neptunyl(VI) dioxide radical. This work demonstrates that despite a significant increase in the size of the Hilbert space due to spin symmetry breaking by the spin-orbit coupling terms, HCI retains the ability to discard large parts of the low importance Hilbert space to deliver converged absolute and relative energies. For instance, by using just over 107 determinants we get converged excitation energies for Au atom in an active space containing (150o,25e) which has over 1030 determinants. We also investigate the accuracy of five different two-component relativistic Hamiltonians in which different levels of ap- proximations are made in deriving the one-electron and two-electrons Hamiltonians, ranging from Breit-Pauli (BP) to various flavors of exact two-component (X2C) theory. The relative accuracy of the different Hamiltonians are compared on systems that range in atomic number from first row atoms to actinides. I. INTRODUCTION can become large and it is more appropriate to treat them on an equal footing with the spin-free terms and electron Relativistic effects play an important role in a correlation. -
Arxiv:1911.06836V1 [Physics.Chem-Ph] 8 Aug 2019 A
Multireference electron correlation methods: Journeys along potential energy surfaces Jae Woo Park,1, ∗ Rachael Al-Saadon,2 Matthew K. MacLeod,3 Toru Shiozaki,2, 4 and Bess Vlaisavljevich5, y 1Department of Chemistry, Chungbuk National University, Chungdae-ro 1, Cheongju 28644, Korea. 2Department of Chemistry, Northwestern University, 2145 Sheridan Rd., Evanston, IL 60208, USA. 3Workday, 4900 Pearl Circle East, Suite 100, Boulder, CO 80301, USA. 4Quantum Simulation Technologies, Inc., 625 Massachusetts Ave., Cambridge, MA 02139, USA. 5Department of Chemistry, University of South Dakota, 414 E. Clark Street, Vermillion, SD 57069, USA. (Dated: November 19, 2019) Multireference electron correlation methods describe static and dynamical electron correlation in a balanced way, and therefore, can yield accurate and predictive results even when single-reference methods or multicon- figurational self-consistent field (MCSCF) theory fails. One of their most prominent applications in quantum chemistry is the exploration of potential energy surfaces (PES). This includes the optimization of molecular ge- ometries, such as equilibrium geometries and conical intersections, and on-the-fly photodynamics simulations; both depend heavily on the ability of the method to properly explore the PES. Since such applications require the nuclear gradients and derivative couplings, the availability of analytical nuclear gradients greatly improves the utility of quantum chemical methods. This review focuses on the developments and advances made in the past two decades. To motivate the readers, we first summarize the notable applications of multireference elec- tron correlation methods to mainstream chemistry, including geometry optimizations and on-the-fly dynamics. Subsequently, we review the analytical nuclear gradient and derivative coupling theories for these methods, and the software infrastructure that allows one to make use of these quantities in applications. -
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 -
Perturbational Treatment of Spin-Orbit Coupling for Generally Applicable High-Level Multi-Reference Methods
Perturbational treatment of spin-orbit coupling for generally applicable high-level multi-reference methods Sebastian Mai1, Thomas Müller2,a), Felix Plasser3, Philipp Marquetand1, Hans Lischka and Leticia González1 1Institute of Theoretical Chemistry, University of Vienna, Währinger Str. 17, 1090 Vienna, Austria 2Institute for Advanced Simulation, Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich, Germany 3Interdisciplinary Center for Scientific Computing, University of Heidelberg, Im Neuenheimer Feld 368, 69120 Heidelberg, Germany 4Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409-1061, USA Abstract An efficient perturbational treatment of spin-orbit coupling within the framework of high-level multi-reference techniques has been implemented in the most recent version of the COLUMBUS quantum chemistry package, extending the existing fully variational two-component (2c) multi-reference configuration interaction singles and doubles (MRCISD) method. The proposed scheme follows related implementations of quasi-degenerate perturbation theory (QDPT) model space techniques. Our model space is built either from uncontracted, large-scale scalar relativistic MRCISD wavefunctions or based on the scalar-relativistic solutions of the linear-response-theory-based multi-configurational averaged quadratic coupled cluster method (LRT-MRAQCC). The latter approach allows for a consistent, approximatively size-consistent and size-extensive treatment of spin-orbit coupling. The approach is described in -
CHEM:4480 Introduction to Molecular Modeling
CHEM:4480:001 Introduction to Molecular Modeling Fall 2018 Instructor Dr. Sara E. Mason Office: W339 CB, Phone: (319) 335-2761, Email: [email protected] Lecture 11:00 AM - 12:15 PM, Tuesday/Thursday. Primary Location: W228 CB. Please note that we will often meet in one of the Chemistry Computer Labs. Notice about class being held outside of the primary location will be posted to the course ICON site by 24 hours prior to the start of class. Office Tuesday 12:30-2 PM (EXCEPT for DoC faculty meeting days 9/4, 10/2, 10/9, 11/6, Hour and 12/4), Thursday 12:30-2, or by appointment Department Dr. James Gloer DEO Administrative Office: E331 CB Administrative Phone: (319) 335-1350 Administrative Email: [email protected] Text Instead of a course text, assigned readings will be given throughout the semester in forms such as journal articles or library reserves. Website http://icon.uiowa.edu Course To develop practical skills associated with chemical modeling based on quantum me- Objectives chanics and computational chemistry such as working with shell commands, math- ematical software, and modeling packages. We will also work to develop a basic understanding of quantum mechanics, approximate methods, and electronic struc- ture. Technical computing, pseudopotential generation, density functional theory software, (along with other optional packages) will be used hands-on to gain experi- ence in data manipulation and modeling. We will use both a traditional classroom setting and hands-on learning in computer labs to achieve course goals. Course Topics • Introduction: It’s a quantum world! • Dirac notation and matrix mechanics (a.k.a. -
US DOE SC ASCR FY11 Software Effectiveness SC GG 3.1/2.5.2 Improve Computational Science Capabilities
US DOE SC ASCR FY11 Software Effectiveness SC GG 3.1/2.5.2 Improve Computational Science Capabilities K. J. Roche High Performance Computing Group, Pacific Northwest National Laboratory Nuclear Theory Group, Department of Physics, University of Washington Presentation to ASCAC, Washington, D.C. , November 2, 2011 Tuesday, November 1, 2011 1 LAMMPS Paul Crozier, Steve Plimpton, Mark Brown, Christian Trott OMEN, NEMO 5 Gerhard Klimeck, Mathieu Luisier, Sebastian Steiger, Michael Povolotskyi, Hong-Hyun Park, Tillman Kubis OSIRIS Warren Mori, Ricardo Fonseca, Asher Davidson, Frank Tsung, Jorge Vieira, Frederico Fiuza, Panagiotis Spentzouris eSTOMP Steve Yabusaki, Yilin Fang, Bruce Palmer, Manojkumar Krishnan Rebecca Hartman-Baker Ricky Kendall Don Maxwell Bronson Messer Vira j Paropkari David Skinner Jack Wells Cary Whitney Rice HPC Toolkit group DOE ASCR, OLCF and NERSC staf Tuesday, November 1, 2011 2 • Metric Statement, Processing • FY11 Applications Intro Problems Enhancements Results • FY12 Nominations Tuesday, November 1, 2011 3 US OMB PART DOE SC ASCR Annual Goal with Quarterly Updates (SC GG 3.1/2.5.2) Improve computational science capabilities, defined as the average annual percentage increase in the computational effectiveness (either by simulating the same problem in less time or simulating a larger problem in the same time) of a subset of application codes. To those ‘on the clock’ with this work, it means more than just satisfying the language of this metric. Tuesday, November 1, 2011 4 accept • COMPLEXITY LP LR PROBLEMS M M M • reject • ALGORITHMS • MACHINES Measured time for machine M to generate the language of the problem plus time to generate the language of the result plus the time to accept or reject the language of the result. -
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. -
Efficient Two-Component Relativistic Method to Obtain Electronic
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by DSpace at Waseda University Efficient Two-Component Relativistic Method to Obtain Electronic and Molecular Structures of Heavy-Element Systems ͷిࢠঢ়ଶ͓ΑͼࢠߏͷͨΊͷܥॏݩૉ ޮతͳ 2 ૬ର๏ February 2017 Waseda University Graduate School of Advanced Science and Engineering Department of Chemistry and Biochemistry, Research on Electronic State Theory Yuya NAKAJIMA தౢɹ༟ Contents Chapter 1 General introduction 1 References . ................................ 6 Chapter 2 Theoretical background 7 2.1 Dirac Hamiltonian . ....................... 7 2.2 The IODKH method ....................... 9 2.3 The LUT scheme . ........................ 12 2.4 Spin-free and spin-dependent formalisms . ......... 14 2.5 The FCP method . ........................ 16 2.6 The GHF method . ........................ 19 2.7 The Analytical energy derivative for the GHF method . 21 References . ................................ 24 Chapter 3 Analytical energy gradient for spin-free infinite-order Douglas–Kroll–Hess method with local unitary transfor- mation 25 3.1 Introduction . .......................... 25 3.2 Theory and implementation . ................. 27 3.2.1 Energy gradient for IODKH . ........... 27 3.2.2 Analytical derivative for the space transformation matrices . ......................... 30 3.2.3 Energy gradient for LUT-IODKH . .......... 32 3.2.4 Implementation . ................... 33 i 3.3 Numerical assessments . .................. 34 3.3.1 Computational details . ................ 34 3.3.2 Numerical gradient values ............... 37 3.3.3 Accuracies of IODKH/C and LUT-IODKH/C methods 38 3.3.4 Computational cost of the LUT scheme ........ 45 3.3.5 Metal complexes . ................... 47 3.3.6 Heavier analogues of ethylene . ........... 48 3.3.7 Harmonic frequencies of diatomic molecules . 49 3.4 Conclusion . -
The Electron Affinity of the Uranium Atom
The electron affinity of the uranium atom Cite as: J. Chem. Phys. 154, 224307 (2021); https://doi.org/10.1063/5.0046315 Submitted: 02 February 2021 . Accepted: 18 May 2021 . Published Online: 10 June 2021 Sandra M. Ciborowski, Gaoxiang Liu, Moritz Blankenhorn, Rachel M. Harris, Mary A. Marshall, Zhaoguo Zhu, Kit H. Bowen, and Kirk A. Peterson ARTICLES YOU MAY BE INTERESTED IN Ultrahigh sensitive transient absorption spectrometer Review of Scientific Instruments 92, 053002 (2021); https://doi.org/10.1063/5.0048115 A dual-magneto-optical-trap atom gravity gradiometer for determining the Newtonian gravitational constant Review of Scientific Instruments 92, 053202 (2021); https://doi.org/10.1063/5.0040701 How accurate is the determination of equilibrium structures for van der Waals complexes? The dimer N2O⋯CO as an example The Journal of Chemical Physics 154, 194302 (2021); https://doi.org/10.1063/5.0048603 J. Chem. Phys. 154, 224307 (2021); https://doi.org/10.1063/5.0046315 154, 224307 © 2021 Author(s). The Journal ARTICLE of Chemical Physics scitation.org/journal/jcp The electron affinity of the uranium atom Cite as: J. Chem. Phys. 154, 224307 (2021); doi: 10.1063/5.0046315 Submitted: 2 February 2021 • Accepted: 18 May 2021 • Published Online: 10 June 2021 Sandra M. Ciborowski,1 Gaoxiang Liu,1 Moritz Blankenhorn,1 Rachel M. Harris,1 Mary A. Marshall,1 Zhaoguo Zhu,1 Kit H. Bowen,1,a) and Kirk A. Peterson2,a) AFFILIATIONS 1 Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA 2 Department of Chemistry, Washington State University, Pullman, Washington 99162, USA a)Authors to whom correspondence should be addressed: [email protected] and [email protected] ABSTRACT The results of a combined experimental and computational study of the uranium atom are presented with the aim of determining its electron affinity. -
Computational Chemistry: a Practical Guide for Applying Techniques to Real-World Problems
Computational Chemistry: A Practical Guide for Applying Techniques to Real-World Problems. David C. Young Copyright ( 2001 John Wiley & Sons, Inc. ISBNs: 0-471-33368-9 (Hardback); 0-471-22065-5 (Electronic) COMPUTATIONAL CHEMISTRY COMPUTATIONAL CHEMISTRY A Practical Guide for Applying Techniques to Real-World Problems David C. Young Cytoclonal Pharmaceutics Inc. A JOHN WILEY & SONS, INC., PUBLICATION New York . Chichester . Weinheim . Brisbane . Singapore . Toronto Designations used by companies to distinguish their products are often claimed as trademarks. In all instances where John Wiley & Sons, Inc., is aware of a claim, the product names appear in initial capital or all capital letters. Readers, however, should contact the appropriate companies for more complete information regarding trademarks and registration. Copyright ( 2001 by John Wiley & Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic or mechanical, including uploading, downloading, printing, decompiling, recording or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the Publisher. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 605 Third Avenue, New York, NY 10158-0012, (212) 850-6011, fax (212) 850-6008, E-Mail: PERMREQ @ WILEY.COM. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold with the understanding that the publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional person should be sought.