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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. -
Metalloboranes from First-Principles Calculations: a Candidate for High-Density Hydrogen Storage
Metalloboranes from first-principles calculations: A candidate for high-density hydrogen storage A. R. Akbarzadeh, D. Vrinceanu, and C.J. Tymczak Department of Physics, Texas Southern University, Houston, Texas 77004, USA Abstract Using first principles calculations, we show the high hydrogen storage capacity of a new class of compounds, metalloboranes. Metalloboranes are transition metal (TM) and borane compounds that obey a novel-bonding scheme. We have found that the transition metal atoms can bind up to 10 H2-molecules with an average binding energy of 30 kJ/mole of H2, which lies favorably within the reversible adsorption range. Among the first row TM atoms, Sc and Ti are found to be the optimum in maximizing the H2 storage on the metalloborane cluster. Additionally, being ionically bonded to the borane molecule, the TMs do not suffer from the aggregation problem, which has been the biggest hurdle for the success of TM- decorated graphitic materials for hydrogen storage. Furthermore, since the borane 6-atom ring has identical bonding properties as carbon rings it is possible to link the metalloboranes into metal organic frameworks (MOF’s), which are thus able to adsorb hydrogen via Kubas interaction as well as the well-known van der Waals interaction. Finally, we construct a simple Monte-Catlo algorithm for Hydrogen uptake and show that Titanium metalloboranes in a MOF5 structure can absorb up to 11.5% hydrogen per weight at 100 bar of pressure. I. Introduction Due to the geographical distribution and supply limitation of fossil fuel resources and the increasing perceived negative impact of carbon dioxide emission in the environment, it is advantageous for the societies to take action in the search and implementation of alternative energy systems. -
Living at the Top of the Top500: Myopia from Being at the Bleeding Edge
Living at the Top of the Top500: Myopia from Being at the Bleeding Edge Bronson Messer Oak Ridge Leadership Computing Facility & Theoretical Astrophysics Group Oak Ridge National Laboratory Department of Physics & Astronomy University of Tennessee Friday, July 1, 2011 Outline • Statements made without proof • OLCF’s Center for Accelerated Application Readiness • Speculations on task-based approaches for multiphysics applications in astrophysics (e.g. blowing up stars) 2 Friday, July 1, 2011 Riffing on Hank’s fable... 3 Friday, July 1, 2011 The Effects of Moore’s Law and Slacking 1 on Large Computations Chris Gottbrath, Jeremy Bailin, Casey Meakin, Todd Thompson, J.J. Charfman Steward Observatory, University of Arizona Abstract We show that, in the context of Moore’s Law, overall productivity can be increased for large enough computations by ‘slacking’orwaiting for some period of time before purchasing a computer and beginning the calculation. According to Moore’s Law, the computational power availableataparticular price doubles every 18 months. Therefore it is conceivable that for sufficiently large numerical calculations and fixed budgets, computing power will improve quickly enough that the calculation will finish faster if we wait until the available computing power is sufficiently better and start the calculation then. The Effects of Moore’s Law and Slacking 1Figureon Large 1: Computations Chris Gottbrath, Jeremy Bailin, Casey Meakin, Todd Thompson, J.J. Charfman 1 The Effects of Moore’sSteward Observatory, Law and University Slacking of Arizona on Large astro-ph/9912202 Computations Abstract Chris Gottbrath, Jeremy Bailin, Casey Meakin, Todd Thompson, We show that, in the context of Moore’s Law, overall productivity can be increased forJ.J. -
A Deep Dive Into ASUS Solutions
From DataCenters to Supercomputers A Deep Dive Into ASUS Solutions Christopher Liang / Server/WS Product manager ASUS is a global technology leader in the Who is ASUS? digital era. We focus on the mastery of technological innovation and design perfection. We’re very critical of our own work when it comes to only delivering consumers our very best. ASUS Worldwide ASUS has a strong presence in over 50 countries, with offices in Europe, Asia, Australia and New Zealand, the Americas, and South Africa. • > 11,000 employees worldwide (source : HR dept ) • > 3,100 R&D employees (source : HR dept ) • 900+ support centers worldwide (source : TSD dept ) Business Update 11 (estimated) ASUS closed 2011 on a high, with revenues around US$11.8 billion. As of September 2010, the brand is estimated to be worth US$1.285 billion*. 10.1 *2010 Top Taiwan Global Brand (Interbrand) ** Due to Q1-Q2 worldwide economy crisis 8.21 7.66** 6.99 5.087 3.783 3.010 2.081 Revenue US$ (billions) Leader in Performance and Reliability #1 Motherboard Since 1989, ASUS has shipped over 420 million motherboards. Placed end to end, they can form a chain long enough to circumnavigate the globe more than three times. #1 Windows-based Desktop PC Reliability Ranked most reliable Window’s based PC brand 2 years in a row by PCWorld. The 2011 PCWorld Reliability and Service survey was conducted with 63,000 PCWorld readers. 1. Though design thinking to provide cutting Why ASUS ? edge SPEC 2. BIOS – superior performance through increased functionality and upgradeability 3. -
An Overview on the Libxc Library of Density Functional Approximations
An overview on the Libxc library of density functional approximations Susi Lehtola Molecular Sciences Software Institute at Virginia Tech 2 June 2021 Outline Why Libxc? Recap on DFT What is Libxc? Using Libxc A look under the hood Wrapup GPAW 2021: Users' and Developers' Meeting Susi Lehtola Why Libxc? 2/28 Why Libxc? There are many approximations for the exchange-correlation functional. But, most programs I ... only implement a handful (sometimes 5, typically 10-15) I ... and the implementations may be buggy / non-standard GPAW 2021: Users' and Developers' Meeting Susi Lehtola Why Libxc? 3/28 Why Libxc, cont'd This leads to issues with reproducibility I chemists and physicists do not traditionally use the same functionals! Outdated(?) stereotype: B3LYP vs PBE I how to reproduce a calculation performed with another code? GPAW 2021: Users' and Developers' Meeting Susi Lehtola Why Libxc? 4/28 Why Libxc, cont'd The issue is compounded by the need for backwards and forwards compatibility: how can one I reproduce old calculations from the literature done with a now-obsolete functional (possibly with a program that is proprietary / no longer available)? I use a newly developed functional in an old program? GPAW 2021: Users' and Developers' Meeting Susi Lehtola Why Libxc? 5/28 Why Libxc, cont'd A standard implementation is beneficial! I no need to keep reinventing (and rebuilding) the wheel I use same collection of density functionals in all programs I new functionals only need to be implemented in one place I broken/buggy functionals only need to be fixed in one place I same implementation can be used across numerical approaches, e.g. -
Presidential Search Committee Meets, Reviews Upcoming Work
ETHEMedford, MA 02155 TUFTSTuesday, November 26,1991 DAILYJVol XXIII, Number 58 Faculty tables vote on Presidential search committee World Civ proposal meets, reviews upcoming work courses iUC to be intcrdiscipli by SCHAEF1cR nary. intcgr;ltblg disciplines fr()n by MAUREEN LENIHAN Senior Staff Writer Daily Editorial Board and PATRICK HEALY at leiist three of the five distribu The 19-member search com- Dally Edil(~r1alhtUd tion areas. mittee fonned to begin the pro- Although the proposed World Since 1986. threeteamsoffac cess of selecting anew university CivilizationsFoundation rcquire- ult y. including one professor frorr president met for the first time inent was briefly presented at the the School ofEngineering,devel yesterday, familiariz,ing them- Liberal Arts and Jackson facully oped three two-semester course: selves with their task and the meeting yesterday. the LAM fac- which were ultiinately opened tc committee‘s initial duties includ- ulty postponed further discussion students to take on a voluntce ing formali~inga Job description and voting on the prognun until basis. These courses, titled “P for the post. Dec. 11. Sense of Place.” “Time and Cal The committee. representing Dean of College of Liberal endars,“and “Memory and Iden trustees. administrators, faculty Arts and Jackson Mary Ella tity.“wereestablishedwith fincan members. staff members. stu- Fcinleibmoved tocrcate the Dec. cia1 support from ihe Davis Foun dents. and alumni, was fonncd in 1 I meeting since other meeting dation. the National Endowmen response toai miouiiccmcnt last topics preceding the World Civ for the Humimities, and the Uni May that University president presentation took up most of the versit y. -
Density-Functional Theory of Atoms and Molecules • W
3.320: Lecture 7 (Feb 24 2005) DENSITYDENSITY--FUNCTIONALFUNCTIONAL THEORY,THEORY, ANDAND DENSITYDENSITY--FUNCTIONALFUNCTIONAL PRACTICEPRACTICE Feb 24 2005 3.320 Atomistic Modeling of Materials -- Gerbrand Ceder and Nicola Marzari Hartree-Fock Equations r rr ϕϕαβ()rr11() L ϕν()r1 ϕϕ()rrr ()rrϕ()r rr r 1 αβ22L ν2 ψ (,rr12,...,rn )= n! MMOM r rr ϕϕαβ()rrnn()L ϕν()rn ⎡⎤1 2 r r r ⎢⎥−∇iI+∑VR()−riϕλ ()ri + ⎣⎦2 I ⎡⎤1 ϕϕ* ()rrrr()drrϕ ()rr − ⎢⎥∑ ∫ µµjjr r jλ i ⎣⎦⎢⎥µ ||rrji− ⎡⎤1 ϕϕ* ()rdrrϕϕ()rrr r(rr)= ε(r) ∑ ⎢⎥∫ µµj rrλ j j i λ i µ ⎣⎦⎢⎥||rrj − i Feb 24 2005 3.320 Atomistic Modeling of Materials -- Gerbrand Ceder and Nicola Marzari Image removed for copyright reasons. Screenshot of online article. “Nobel Focus: Chemistry by Computer.” Physical Review Focus, 21 October 1998. http://focus.aps.org/story/v2/st19 Feb 24 2005 3.320 Atomistic Modeling of Materials -- Gerbrand Ceder and Nicola Marzari The Thomas-Fermi approach • Let’s try to find out an expression for the energy as a function of the charge density • E=kinetic+external+el.-el. • Kinetic is the tricky term: how do we get the curvature of a wavefunction from the charge density ? • Answer: local density approximation Feb 24 2005 3.320 Atomistic Modeling of Materials -- Gerbrand Ceder and Nicola Marzari Local Density Approximation • We take the kinetic energy density at every point to correspond to the kinetic energy density of the homogenous electron gas 5 T(rr) = Aρ 3 (rr) 5 1 ρ(rr)ρ(rr ) E [ρ] = A ρ 3 (rr)drr + ρ(rr)v (rr)drr + 1 2 drrdrr Th−Fe ∫ ∫ ext ∫∫ r r 1 2 2 | r1 − r2 | Feb 24 2005 -
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. -
O (N) Methods in Electronic Structure Calculations
O(N) Methods in electronic structure calculations D R Bowler1;2;3 and T Miyazaki4 1London Centre for Nanotechnology, UCL, 17-19 Gordon St, London WC1H 0AH, UK 2Department of Physics & Astronomy, UCL, Gower St, London WC1E 6BT, UK 3Thomas Young Centre, UCL, Gower St, London WC1E 6BT, UK 4National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047, JAPAN E-mail: [email protected] E-mail: [email protected] Abstract. Linear scaling methods, or O(N) methods, have computational and memory requirements which scale linearly with the number of atoms in the system, N, in contrast to standard approaches which scale with the cube of the number of atoms. These methods, which rely on the short-ranged nature of electronic structure, will allow accurate, ab initio simulations of systems of unprecedented size. The theory behind the locality of electronic structure is described and related to physical properties of systems to be modelled, along with a survey of recent developments in real-space methods which are important for efficient use of high performance computers. The linear scaling methods proposed to date can be divided into seven different areas, and the applicability, efficiency and advantages of the methods proposed in these areas is then discussed. The applications of linear scaling methods, as well as the implementations available as computer programs, are considered. Finally, the prospects for and the challenges facing linear scaling methods are discussed. Submitted to: Rep. Prog. Phys. arXiv:1108.5976v5 [cond-mat.mtrl-sci] 3 Nov 2011 O(N) Methods 2 1. -
(DFT) and Its Application to Defects in Semiconductors
Introduction to DFT and its Application to Defects in Semiconductors Noa Marom Physics and Engineering Physics Tulane University New Orleans The Future: Computer-Aided Materials Design • Can access the space of materials not experimentally known • Can scan through structures and compositions faster than is possible experimentally • Unbiased search can yield unintuitive solutions • Can accelerate the discovery and deployment of new materials Accurate electronic structure methods Efficient search algorithms Dirac’s Challenge “The underlying physical laws necessary for the mathematical theory of a large part of physics and the whole of chemistry are thus completely known, and the difficulty is only that the exact application of these laws leads to equations much too complicated to be soluble. It therefore becomes desirable that approximate practical methods of applying quantum mechanics should be developed, which can lead to an P. A. M. Dirac explanation of the main features of Physics Nobel complex atomic systems ... ” Prize, 1933 -P. A. M. Dirac, 1929 The Many (Many, Many) Body Problem Schrödinger’s Equation: The physical laws are completely known But… There are as many electrons in a penny as stars in the known universe! Electronic Structure Methods for Materials Properties Structure Ionization potential (IP) Absorption Mechanical Electron Affinity (EA) spectrum properties Fundamental gap Optical gap Vibrational Defect/dopant charge Exciton binding spectrum transition levels energy Ground State Charged Excitation Neutral Excitation DFT -
Curriculum Vitae
CURRICULUM VITAE Christopher J. Tymczak Tenured Associate Professor Director Department of Physics Texas Southern University High Texas Southern University Performance Computing Center Houston, Texas 77004 Texas Southern University Office: (713) 313-1849 Houston, Texas 77004 Email: [email protected] (http://hpcc.tsu.edu/) (http://physics.tsu.edu/) Co-Director Visiting Research Scientist NSF CREST Center for Research on Group T-1 Complex Networks Los Alamos National Laboratory Texas Southern University Los Alamos, New Mexico, 87507 Houston, Texas 77004 I specialize in the identification, development, and implementation of new scientific codes for exploiting advanced computing resources impacting large scale computation in diverse areas in Many-body physics, Quantum Chemistry and ab initio Molecular Dynamics. I am a tenured associate professor of physics at Texas Southern University, where I am spearheading the integration of supercomputing resources into various STEM programs. I am also the founder and director of the Texas Southern High Performance Computing Center (TSU-HPCC). At Los Alamos National Laboratory, I am a permanent scientific associate within the FreeON initiative, involving the development of massively parallel linear scaling quantum chemistry methods, currently under development in collaboration with Dr. Matt Challacombe (T-12) and Dr. Anders Niklasson (T-1). I was one of the first to exploit wavelet-based methods in large scale computing for understanding the electronic structure of materials. For the last six years, I have advanced the FreeON development through the exploitation of advanced data structures and advanced machine architectures. FreeON is now recognized as one of the first quantum chemical codes with demonstrable scalable parallelism within large- scale parallel clusters. -
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.