Molecvue Workshop on Computational Chemistry in the Undergraduate Curriculum

Total Page：16

File Type：pdf, Size：1020Kb

MoleCVUE Workshop on Computational Chemistry in the Undergraduate Curriculum Coordinator: Carl Salter ([email protected]) Talk Title: "Introducing Molecular Models" Presenters: Carl Salter, Jim Foresman, Will Polik, and Kevin Range Schedule: 9:00 am: "Introducing Molecular Models", Carl Salter 9:30 am: "Exploring Chemistry with Electronic Structure Calculations", Jim Foresman 10:15 am: "Using WebMO throughout the Chemistry Curriculum to Explore Molecular Shapes, Conformations, Energy Surfaces, Spectroscopy, Orbitals, and Symmetry", Will Polik 11:15 am: "Computational Exercises in General Chemistry", Kevin Range 12:00 pm: Lunch 1:00 pm: Workshop: Develop activities using Gaussian and WebMO 4:00 pm: Report out Workshop description: WebMO is a web-based interface to modern computational chemistry programs (Gamess, Gaussian, Molpro, Mopac, NWChem, PQS, PSI, Quantum Espresso, VASP, Q- Chem, Tinker). Using just a web-browser, users can draw 3-D structures, run calculations, and view results. WebMO is simple enough for novice users (reasonable defaults are provided, and result are presented graphically) but flexible enough for experts (full access to input and output files is provided, and job types can be customized). Workshop topics will include: * Overview of WebMO features and capabilities * Drawing molecules using the WebMO Editor * Running various job types * Visualization of results using the WebMO Viewer * Importing and exporting structures and jobs * Customization WebMO job types * Using WebMO on Apple and Android portable devices * Installation and administration of a WebMO server This is a hands-on workshop suitable for high-school and college faculty. Participants are encouraged to bring their own Windows, Mac, or Linux laptop or Apple iPad. In addition to workshop activities, a WebMO developer will be available for questions and individual consultation. Time: Monday, June 5 from 9 am-5 pm Room: Tower 1 Notes: This room fits 40 banquet style. There are other MoleCVUE talks and activities that are part of the technical session on Sunday afternoon and Tuesday morning. .

Copy Link

Recommended publications

Integrated Tools for Computational Chemical Dynamics
UNIVERSITY OF MINNESOTA Integrated Tools for Computational Chemical Dynamics • Developpp powerful simulation methods and incorporate them into a user- friendly high-throughput integrated software su ite for c hem ica l d ynami cs New Models (Methods) → Modules → Integrated Tools UNIVERSITY OF MINNESOTA Development of new methods for the calculation of potential energy surface UNIVERSITY OF MINNESOTA Development of new simulation methods UNIVERSITY OF MINNESOTA Applications and Validations UNIVERSITY OF MINNESOTA Electronic Software structu re Dynamics ANT QMMM GCMC MN-GFM POLYRATE GAMESSPLUS MN-NWCHEMFM MN-QCHEMFM HONDOPLUS MN-GSM Interfaces GaussRate JaguarRate NWChemRate UNIVERSITY OF MINNESOTA Electronic Structure Software QMMM 1.3: QMMM is a computer program for combining quantum mechanics (QM) and molecular mechanics (MM). MN-GFM 3.0: MN-GFM is a module incorporating Minnesota DFT functionals into GAUSSIAN 03. MN-GSM 626.2:MN: MN-GSM is a module incorporating the SMx solvation models and other enhancements into GAUSSIAN 03. MN-NWCHEMFM 2.0:MN-NWCHEMFM is a module incorporating Minnesota DFT functionals into NWChem 505.0. MN-QCHEMFM 1.0: MN-QCHEMFM is a module incorporating Minnesota DFT functionals into Q-CHEM. GAMESSPLUS 4.8: GAMESSPLUS is a module incorporating the SMx solvation models and other enhancements into GAMESS. HONDOPLUS 5.1: HONDOPLUS is a computer program incorporating the SMx solvation models and other photochemical diabatic states into HONDO. UNIVERSITY OF MINNESOTA DiSftDynamics Software ANT 07: ANT is a molecular dynamics program for performing classical and semiclassical trajjyectory simulations for adiabatic and nonadiabatic processes. GCMC: GCMC is a Grand Canonical Monte Carlo (GCMC) module for the simulation of adsorption isotherms in heterogeneous catalysts.
[Show full text]
Supporting Information
Electronic Supplementary Material (ESI) for RSC Advances. This journal is © The Royal Society of Chemistry 2020 Supporting Information How to Select Ionic Liquids as Extracting Agent Systematically? Special Case Study for Extractive Denitrification Process Shurong Gaoa,b,c,*, Jiaxin Jina,b, Masroor Abroc, Ruozhen Songc, Miao Hed, Xiaochun Chenc,* a State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, China b Research Center of Engineering Thermophysics, North China Electric Power University, Beijing, 102206, China c Beijing Key Laboratory of Membrane Science and Technology & College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, PR China d Office of Laboratory Safety Administration, Beijing University of Technology, Beijing 100124, China * Corresponding author, Tel./Fax: +86-10-6443-3570, E-mail: [email protected], [email protected] 1 COSMO-RS Computation COSMOtherm allows for simple and efficient processing of large numbers of compounds, i.e., a database of molecular COSMO files; e.g. the COSMObase database. COSMObase is a database of molecular COSMO files available from COSMOlogic GmbH & Co KG. Currently COSMObase consists of over 2000 compounds including a large number of industrial solvents plus a wide variety of common organic compounds. All compounds in COSMObase are indexed by their Chemical Abstracts / Registry Number (CAS/RN), by a trivial name and additionally by their sum formula and molecular weight, allowing a simple identification of the compounds. We obtained the anions and cations of different ILs and the molecular structure of typical N-compounds directly from the COSMObase database in this manuscript.
[Show full text]
Popular GPU-Accelerated Applications
LIFE & MATERIALS SCIENCES GPU-ACCELERATED APPLICATIONS | CATALOG | AUG 12 LIFE & MATERIALS SCIENCES APPLICATIONS CATALOG Application Description Supported Features Expected Multi-GPU Release Status Speed Up* Support Bioinformatics BarraCUDA Sequence mapping software Alignment of short sequencing 6-10x Yes Available now reads Version 0.6.2 CUDASW++ Open source software for Smith-Waterman Parallel search of Smith- 10-50x Yes Available now protein database searches on GPUs Waterman database Version 2.0.8 CUSHAW Parallelized short read aligner Parallel, accurate long read 10x Yes Available now aligner - gapped alignments to Version 1.0.40 large genomes CATALOG GPU-BLAST Local search with fast k-tuple heuristic Protein alignment according to 3-4x Single Only Available now blastp, multi cpu threads Version 2.2.26 GPU-HMMER Parallelized local and global search with Parallel local and global search 60-100x Yes Available now profile Hidden Markov models of Hidden Markov Models Version 2.3.2 mCUDA-MEME Ultrafast scalable motif discovery algorithm Scalable motif discovery 4-10x Yes Available now based on MEME algorithm based on MEME Version 3.0.12 MUMmerGPU A high-throughput DNA sequence alignment Aligns multiple query sequences 3-10x Yes Available now LIFE & MATERIALS& LIFE SCIENCES APPLICATIONS program against reference sequence in Version 2 parallel SeqNFind A GPU Accelerated Sequence Analysis Toolset HW & SW for reference 400x Yes Available now assembly, blast, SW, HMM, de novo assembly UGENE Opensource Smith-Waterman for SSE/CUDA, Fast short
[Show full text]
An Efficient Hardware-Software Approach to Network Fault Tolerance with Infiniband
An Efficient Hardware-Software Approach to Network Fault Tolerance with InfiniBand Abhinav Vishnu1 Manoj Krishnan1 and Dhableswar K. Panda2 Pacific Northwest National Lab1 The Ohio State University2 Outline Introduction Background and Motivation InfiniBand Network Fault Tolerance Primitives Hybrid-IBNFT Design Hardware-IBNFT and Software-IBNFT Performance Evaluation of Hybrid-IBNFT Micro-benchmarks and NWChem Conclusions and Future Work Introduction Clusters are observing a tremendous increase in popularity Excellent price to performance ratio 82% supercomputers are clusters in June 2009 TOP500 rankings Multiple commodity Interconnects have emerged during this trend InfiniBand, Myrinet, 10GigE …. InfiniBand has become popular Open standard and high performance Various topologies have emerged for interconnecting InfiniBand Fat tree is the predominant topology TACC Ranger, PNNL Chinook 3 Typical InfiniBand Fat Tree Configurations 144-Port Switch Block Diagram Multiple leaf and spine blocks 12 Spine Available in 144, 288 and 3456 port Blocks combinations 12 Leaf Blocks Multiple paths are available between nodes present on different switch blocks Oversubscribed configurations are becoming popular 144-Port Switch Block Diagram Better cost to performance ratio 12 Spine Blocks 12 Spine 12 Spine Blocks Blocks 12 Leaf 12 Leaf Blocks Blocks 4 144-Port Switch Block Diagram 144-Port Switch Block Diagram Network Faults Links/Switches/Adapters may fail with reduced MTBF (Mean time between failures) Fortunately, InfiniBand provides mechanisms to handle
[Show full text]
Computer-Assisted Catalyst Development Via Automated Modelling of Conformationally Complex Molecules
www.nature.com/scientificreports OPEN Computer‑assisted catalyst development via automated modelling of conformationally complex molecules: application to diphosphinoamine ligands Sibo Lin1*, Jenna C. Fromer2, Yagnaseni Ghosh1, Brian Hanna1, Mohamed Elanany3 & Wei Xu4 Simulation of conformationally complicated molecules requires multiple levels of theory to obtain accurate thermodynamics, requiring signifcant researcher time to implement. We automate this workfow using all open‑source code (XTBDFT) and apply it toward a practical challenge: diphosphinoamine (PNP) ligands used for ethylene tetramerization catalysis may isomerize (with deleterious efects) to iminobisphosphines (PPNs), and a computational method to evaluate PNP ligand candidates would save signifcant experimental efort. We use XTBDFT to calculate the thermodynamic stability of a wide range of conformationally complex PNP ligands against isomeriation to PPN (ΔGPPN), and establish a strong correlation between ΔGPPN and catalyst performance. Finally, we apply our method to screen novel PNP candidates, saving signifcant time by ruling out candidates with non‑trivial synthetic routes and poor expected catalytic performance. Quantum mechanical methods with high energy accuracy, such as density functional theory (DFT), can opti- mize molecular input structures to a nearby local minimum, but calculating accurate reaction thermodynamics requires fnding global minimum energy structures1,2. For simple molecules, expert intuition can identify a few minima to focus study on, but an alternative approach must be considered for more complex molecules or to eventually fulfl the dream of autonomous catalyst design 3,4: the potential energy surface must be frst surveyed with a computationally efcient method; then minima from this survey must be refned using slower, more accurate methods; fnally, for molecules possessing low-frequency vibrational modes, those modes need to be treated appropriately to obtain accurate thermodynamic energies 5–7.
[Show full text]
Starting SCF Calculations by Superposition of Atomic Densities
Starting SCF Calculations by Superposition of Atomic Densities J. H. VAN LENTHE,1 R. ZWAANS,1 H. J. J. VAN DAM,2 M. F. GUEST2 1Theoretical Chemistry Group (Associated with the Department of Organic Chemistry and Catalysis), Debye Institute, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands 2CCLRC Daresbury Laboratory, Daresbury WA4 4AD, United Kingdom Received 5 July 2005; Accepted 20 December 2005 DOI 10.1002/jcc.20393 Published online in Wiley InterScience (www.interscience.wiley.com). Abstract: We describe the procedure to start an SCF calculation of the general type from a sum of atomic electron densities, as implemented in GAMESS-UK. Although the procedure is well known for closed-shell calculations and was already suggested when the Direct SCF procedure was proposed, the general procedure is less obvious. For instance, there is no need to converge the corresponding closed-shell Hartree–Fock calculation when dealing with an open-shell species. We describe the various choices and illustrate them with test calculations, showing that the procedure is easier, and on average better, than starting from a converged minimal basis calculation and much better than using a bare nucleus Hamiltonian. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 926–932, 2006 Key words: SCF calculations; atomic densities Introduction hrstuhl fur Theoretische Chemie, University of Kahrlsruhe, Tur- bomole; http://www.chem-bio.uni-karlsruhe.de/TheoChem/turbo- Any quantum chemical calculation requires properly deﬁned one- mole/),12 GAMESS(US) (Gordon Research Group, GAMESS, electron orbitals. These orbitals are in general determined through http://www.msg.ameslab.gov/GAMESS/GAMESS.html, 2005),13 an iterative Hartree–Fock (HF) or Density Functional (DFT) pro- Spartan (Wavefunction Inc., SPARTAN: http://www.wavefun.
[Show full text]
Benchmarking and Application of Density Functional Methods In
BENCHMARKING AND APPLICATION OF DENSITY FUNCTIONAL METHODS IN COMPUTATIONAL CHEMISTRY by BRIAN N. PAPAS (Under Direction the of Henry F. Schaefer III) ABSTRACT Density Functional methods were applied to systems of chemical interest. First, the effects of integration grid quadrature choice upon energy precision were documented. This was done through application of DFT theory as implemented in five standard computational chemistry programs to a subset of the G2/97 test set of molecules. Subsequently, the neutral hydrogen-loss radicals of naphthalene, anthracene, tetracene, and pentacene and their anions where characterized using five standard DFT treatments. The global and local electron affinities were computed for the twelve radicals. The results for the 1- naphthalenyl and 2-naphthalenyl radicals were compared to experiment, and it was found that B3LYP appears to be the most reliable functional for this type of system. For the larger systems the predicted site specific adiabatic electron affinities of the radicals are 1.51 eV (1-anthracenyl), 1.46 eV (2-anthracenyl), 1.68 eV (9-anthracenyl); 1.61 eV (1-tetracenyl), 1.56 eV (2-tetracenyl), 1.82 eV (12-tetracenyl); 1.93 eV (14-pentacenyl), 2.01 eV (13-pentacenyl), 1.68 eV (1-pentacenyl), and 1.63 eV (2-pentacenyl). The global minimum for each radical does not have the same hydrogen removed as the global minimum for the analogous anion. With this in mind, the global (or most preferred site) adiabatic electron affinities are 1.37 eV (naphthalenyl), 1.64 eV (anthracenyl), 1.81 eV (tetracenyl), and 1.97 eV (pentacenyl). In later work, ten (scandium through zinc) homonuclear transition metal trimers were studied using one DFT 2 functional.
[Show full text]
Computational Studies on Carbohydrates: I. Density Functional Ab Initio Geometry Optimization on Maltose Conformations
Computational Studies on Carbohydrates: I. Density Functional Ab Initio Geometry Optimization on Maltose Conformations F. A. MOMANY, J. L. WILLETT Plant Polymer Research, National Center for Agricultural Utilization Research, USDA, Agricultural Research Service, 1815 N. University St., Peoria, Illinois 61604 Received 10 September 1999; accepted 10 May 2000 ABSTRACT: Ab initio geometry optimization was carried out on 10 selected conformations of maltose and two 2-methoxytetrahydropyran conformations using the density functional denoted B3LYP combined with two basis sets. The 6-31G∗ and 6-311CCG∗∗ basis sets make up the B3LYP/6-31G∗ and B3LYP/6-311CCG∗∗ procedures. Internal coordinates were fully relaxed, and structures were gradient optimized at both levels of theory. Ten conformations were studied at the B3LYP/6-31G∗ level, and five of these were continued with ∗∗ full gradient optimization at the B3LYP/6-311CCG level of theory. The details of the ab initio optimized geometries are presented here, with particular attention given to the positions of the atoms around the anomeric center and the effect of the particular anomer and hydrogen bonding pattern on the maltose ring structures and relative conformational energies. The size and complexity of the hydrogen-bonding network prevented a rigorous search of conformational space by ab initio calculations. However, using empirical force fields, low-energy conformers of maltose were found that were subsequently gradient optimized at the two ab initio levels of theory. Three classes of conformations were studied, as defined by the clockwise or counterclockwise direction of the hydroxyl groups, or a flipped conformer in which the -dihedral is rotated by ∼180◦.Different combinations of ! side-chain rotations gave energy differences of more than 6 kcal/mol above the lowest energy structure found.
[Show full text]
Quantum Chemistry (QC) on Gpus Feb
Quantum Chemistry (QC) on GPUs Feb. 2, 2017 Overview of Life & Material Accelerated Apps MD: All key codes are GPU-accelerated QC: All key codes are ported or optimizing Great multi-GPU performance Focus on using GPU-accelerated math libraries, OpenACC directives Focus on dense (up to 16) GPU nodes &/or large # of GPU nodes GPU-accelerated and available today: ACEMD*, AMBER (PMEMD)*, BAND, CHARMM, DESMOND, ESPResso, ABINIT, ACES III, ADF, BigDFT, CP2K, GAMESS, GAMESS- Folding@Home, GPUgrid.net, GROMACS, HALMD, HOOMD-Blue*, UK, GPAW, LATTE, LSDalton, LSMS, MOLCAS, MOPAC2012, LAMMPS, Lattice Microbes*, mdcore, MELD, miniMD, NAMD, NWChem, OCTOPUS*, PEtot, QUICK, Q-Chem, QMCPack, OpenMM, PolyFTS, SOP-GPU* & more Quantum Espresso/PWscf, QUICK, TeraChem* Active GPU acceleration projects: CASTEP, GAMESS, Gaussian, ONETEP, Quantum Supercharger Library*, VASP & more green* = application where >90% of the workload is on GPU 2 MD vs. QC on GPUs “Classical” Molecular Dynamics Quantum Chemistry (MO, PW, DFT, Semi-Emp) Simulates positions of atoms over time; Calculates electronic properties; chemical-biological or ground state, excited states, spectral properties, chemical-material behaviors making/breaking bonds, physical properties Forces calculated from simple empirical formulas Forces derived from electron wave function (bond rearrangement generally forbidden) (bond rearrangement OK, e.g., bond energies) Up to millions of atoms Up to a few thousand atoms Solvent included without difficulty Generally in a vacuum but if needed, solvent treated classically
[Show full text]
Software Modules and Programming Environment SCAI User Support
Software modules and programming environment SCAI User Support Marconi User Guide https://wiki.u-gov.it/confluence/display/SCAIUS/UG3.1%3A+MARCONI+UserGuide Modules Set module variables module load <module_name> Show module variables, prereq (compiler and libraries) and conflict module show <module_name> Give info about the software, the batch script, the available executable variants (e.g, single precision, double precision) module help <module_name> Modules Set the variables of the module and its dependencies (compiler and libraries) module load autoload <module name> module load <compiler_name> module load <library _name> module load <module_name> Profiles and categories The modules are organized by functional category (compilers, libraries, tools, applications ,). collected in different profiles (base, advanced, .. ) The profile is a group of modules that share something Profiles Programming profiles They contain only compilers, libraries and tools modules used for compilation, debugging, profiling and pre -proccessing activity BASE Basic compilers, libraries and tools (gnu, intel, intelmpi, openmpi--gnu, math libraries, profiling and debugging tools, rcm,) ADVANCED Advanced compilers, libraries and tools (pgi, openmpi--intel, .) Profiles Production profiles They contain only libraries, tools and applications modules used for production activity They match the most important scientific domains. For this reason we call them “domain” profiles: CHEM PHYS LIFESC BIOINF ENG Profiles Programming and production and profile ARCHIVE It contains
[Show full text]
A Summary of ERCAP Survey of the Users of Top Chemistry Codes
A survey of codes and algorithms used in NERSC chemical science allocations Lin-Wang Wang NERSC System Architecture Team Lawrence Berkeley National Laboratory We have analyzed the codes and their usages in the NERSC allocations in chemical science category. This is done mainly based on the ERCAP NERSC allocation data. While the MPP hours are based on actually ERCAP award for each account, the time spent on each code within an account is estimated based on the user’s estimated partition (if the user provided such estimation), or based on an equal partition among the codes within an account (if the user did not provide the partition estimation). Everything is based on 2007 allocation, before the computer time of Franklin machine is allocated. Besides the ERCAP data analysis, we have also conducted a direct user survey via email for a few most heavily used codes. We have received responses from 10 users. The user survey not only provide us with the code usage for MPP hours, more importantly, it provides us with information on how the users use their codes, e.g., on which machine, on how many processors, and how long are their simulations? We have the following observations based on our analysis. (1) There are 48 accounts under chemistry category. This is only second to the material science category. The total MPP allocation for these 48 accounts is 7.7 million hours. This is about 12% of the 66.7 MPP hours annually available for the whole NERSC facility (not accounting Franklin). The allocation is very tight. The majority of the accounts are only awarded less than half of what they requested for.
[Show full text]
Porting the DFT Code CASTEP to Gpgpus
Porting the DFT code CASTEP to GPGPUs Toni Collis [email protected] EPCC, University of Edinburgh CASTEP and GPGPUs Outline • Why are we interested in CASTEP and Density Functional Theory codes. • Brief introduction to CASTEP underlying computational problems. • The OpenACC implementation http://www.nu-fuse.com CASTEP: a DFT code • CASTEP is a commercial and academic software package • Capable of Density Functional Theory (DFT) and plane wave basis set calculations. • Calculates the structure and motions of materials by the use of electronic structure (atom positions are dictated by their electrons). • Modern CASTEP is a re-write of the original serial code, developed by Universities of York, Durham, St. Andrews, Cambridge and Rutherford Labs http://www.nu-fuse.com CASTEP: a DFT code • DFT/ab initio software packages are one of the largest users of HECToR (UK national supercomputing service, based at University of Edinburgh). • Codes such as CASTEP, VASP and CP2K. All involve solving a Hamiltonian to explain the electronic structure. • DFT codes are becoming more complex and with more functionality. http://www.nu-fuse.com HECToR • UK National HPC Service • Currently 30- cabinet Cray XE6 system – 90,112 cores • Each node has – 2×16-core AMD Opterons (2.3GHz Interlagos) – 32 GB memory • Peak of over 800 TF and 90 TB of memory http://www.nu-fuse.com HECToR usage statistics Phase 3 statistics (Nov 2011 - Apr 2013) Ab initio codes (VASP, CP2K, CASTEP, ONETEP, NWChem, Quantum Espresso, GAMESS-US, SIESTA, GAMESS-UK, MOLPRO) GS2NEMO ChemShell 2%2% SENGA2% 3% UM Others 4% 34% MITgcm 4% CASTEP 4% GROMACS 6% DL_POLY CP2K VASP 5% 8% 19% http://www.nu-fuse.com HECToR usage statistics Phase 3 statistics (Nov 2011 - Apr 2013) 35% of the Chemistry software on HECToR is using DFT methods.
[Show full text]