Opportunities in Scientific Computing with Emphasis on Atomistic Simulations

1. Opportunities in Scientific Computing with Emphasis on Atomistic Simulations Texas Tech University, February 5, 2008 Scientific Computing/Computational Science CDSSIM – Cyberinfrastructure for Chemical Dynamics Simulations; Sailesh Baidya, U. Lourderaj, Yu Zhuang Chemical Dynamics Simulations ● Cl- + CH3I → ClCH3 + I- SN2 nucleophilic substitution reaction; Jiaxu Zhang, Upakarasamy Lourderaj ● Protonated peptide ion surface-induced dissociation; Bipasha Deb, Kyoyeon Park, Wenfang Hu,Kihyung Song

2. Research Group S. V. Addepalli Sailesh Baidya Wenfang Hu Kyoyeon Park Khatuna Kakhiani U. Lourderaj Mingying Xue Li Yang Jiaxu Zhang Acknowledgements Simulation Collaborations Kihyung Song NSF-PIRE Researchers Phil Smith (HPCC) Yu Zhuang Funding National Science Foundation Welch Foundation Computer Programs VENUS VENUS/MOPAC VENUS/NWChem VENUS/GAMESS

3. WEBSERVICES FOR CHEMICAL DYNAMICSRESEARCH AND EDUCATION • monte.chem.ttu.edu– animations of chemical dynamics simulations; tutorials for chemical dynamics instruction (high school, undergraduate, graduate), current tutorial for gas-phase SN2 reactions and more are planned. • cdssim.chem.ttu.edu–library of chemical dynamics computer programs and simulation models; user interface for modifying simulation models; resources for performing a chemical dynamics simulation and animating the result. • pire-europe.chem.ttu.edu–NSFPartnership in International Research and Education (PIRE), “Simulations of Electronic Non-Adiabatice for Reactions with Hydrocarbon Liquids, Macromolecules and Surfaces”

4. COMPUTATIONAL SCIENCE/SCIENTIFIC COMPUTING The term “computational science” was first used by Ken Wilson (awarded a Nobel Prize in physics) to refer to those activities in science and engineering (and now also medicine!) that exploit computing as their main tool. In the spring of 1994, the IEEE began publishing a magazine called “IEEE Computational Science and Engineering”

5. COMPUTATIONAL SCIENCE/SCIENTIFIC COMPUTING Computer Science Applied Math Scientific Computing Engineering/ Science/ Medicine

6. ATOMISTIC SIMULATION RESEARCH AT TTU ALGORITHM DEVELOPMENT FOR SCIENTIFIC COMPUTING Edward J. Allen (Mathematics) - development and analysis of numerical methods to solve nuclear engineering problems such as neutron transport and reactor kinetics. Thomas L. Gibson (Physics) - parallelization of sequential Monte Carlo code for   modelling lipids in cell membranes; development of the distributed Positron Model. William L. Hase (Chemistry) – efficient numerical integration algorithms for solving coupled, non-linear differential equations. Rajesh Khare (Chemical Engineering) – Efficient methods for saddle point determination on potential energy surfaces, multi-scale simulations. Jorge A. Morales (Chemistry) – efficient numerical integration algorithms for solving coupled, non-linear differential equations. Bill Poirier (Chemistry) – efficient linear solvers and eigensolvers for terascale parallel computing, linear partial differential equations, sparse linear algebra.

7. COMPUTATIONAL BIOLOGY William L. Hase (Chemistry) – dissociation of peptide ions, dynamics of enzyme catalysis. Rajesh Khare (Chemical Engineering) – molecular simulations of DNA dynamics, lubrication in human joints. Jorge A. Morales (Chemistry) – time-dependent, coherent-states dynamics of inter- and intra- molecular electron transfers coupled to nuclear motion in prototypical organic and biochemical molecules (e.g. small bridged donor- acceptor systems, small peptides) Mark Vaughn (Chemical Engineering) – 1. Molecular dynamics of lipid bilayer membranes with and without embedded protein. Single, binary and ternary lipid compositions. Particularly interested in mechanically strained membranes. 2. Molecular dynamics of solid-tethered DNA oligomers.

8. CHEMICAL REACTION DYNAMICS David Birney (Chemistry) – potential energy surfaces of organic reactions, pseudopericyclic, and pericyclic reactions. William L. Hase (Chemistry) – dynamics of organic reactions, gas-surface collisions, dynamics of unimolecular dissociation. Jorge A. Morales (Chemistry) – Development of a unifying quantum/classical coherent states (CS) dynamics for all molecular particles (nuclei and electrons) and for all the molecular degrees of freedom (i. e. translational, rotational, vibrational, and electronic CS) along with its computational implementation. Theory applied to reactive collisions and charge transfer processes. Bill Poirier (Chemistry) – exact quantum dynamics of gas phase reactions, thermal rate constants relevant to atmospheric and combustion chemistry, rovibrational dynamics of rare gas clusters.

9. MATERIALS SCIENCE Stefan K. Estreicher (Physics) – properties of defects in group IV and III-N semiconductors, free energies, vibrational dynamics, vibrational lifetimes, MD simulations. William L. Hase (Chemistry) – tribology dynamics, heat transfer and structures at interfaces. Rajesh Khare – molecular simulations of nanofluidic devices, lubrication, phase equilibria, properties of supercooled liquids and glassy polymers, rates of activated processes. Charles W. Myles (Physics) - theoretical and computational materials physics, with emphasis on semiconductor materials. High electric field transport. clathrates and other exotic materials. Electronic properties of defects, electronic bandstructures, properties of semiconductor alloys. Molecular Dynamics and Monte Carlo computer simulations. Mark Vaughn (Chemical Engineering) - probabilistic potential theory (a stochastic method for solving elliptic PDEs) to compute averaged properties of dense, reactive suspensions.

10. SOFTWARE DEVELOPMENT Thomas L. Gibson (Physics) - MPI computer programs (PATMOL) to calculate  the positron-molecule interaction potential for use in quantum scattering  calculations. William L. Hase (Chemistry) – computer programs for chemical dynamics simulations, VENUS and VENUS/NWChem; scientific computing website “cdsism.chem.ttu.edu”. Rajesh Khare (Chemical Engineering) – Molecular dynamics simulation codes (in FORTRAN) for nanofluidics and interfacial heat transfer. Jorge A. Morales (Chemistry) – development of the code CSTech (“Coherent States at Tech”) to implement the above-mentioned coherent states dynamics. This involves compute grid development and code parallelization inter alia. Bill Poirier (Chemistry) - development of the ScalIT package for performing sparse iterative linear algebra on massively parallel computers.

11. ENERGY OF MOLECULES Molecular Mechanics (MM) Potential Energy Function bond stretch bond angle  r torsion angle bend non-bonded r

12. ENERGY OF MOLECULES Time-independent Schrödinger Equation from Quantum Mechanics r - coordinates of electrons, q - coordinates of nuclei - Hamiltonian operator, - wave function Er - energy of electrons VN – nuclear-nuclear repulsion

13. ENERGY OF MOLECULES Solving (q are fixed) Expand in a basis set, developed from experience and chemical intuition: Variational Theorem: Minimize E(q) with respect to ci : Leads to a set of secular equations which are solved by linear algebra (i.e. matrix operations)

14. QUANTUM THEORY OF MATTER “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 applications of these laws leads to equations much too complicated to be soluble.” P. A. M. Dirac, 1929

15. COMPUTATIONAL AND THEORETICAL CHEMISTRY • Development of approximate models that are instructive and, after careful testing and further improvement, often give results in agreement with experiment and are predictive. • Nobel Prize in Quantum Chemistry • Walter Kohn – Density Functional Theory • John Pople – Method of Quantum Chemistry • Computations (embodied in the Gaussian • computer program)

16. ATOMIC-LEVEL MOTION • Classical Mechanics (approximate) • Newton’s equations of motion i = 1,..3N for N - atoms • Quantum Mechanics (exact)

17. CHEMICAL DYNAMICS SOFTWARE AND SIMULATION (CDSSIM) SYSTEM(http://cdssim.chem.ttu.edu) Libraryofopen source computer programs, documentation, and simulation models (input files) for distribution. Software Tools • To upload, modify, and build simulation models • Animate chemical dynamics simulations. Computational Resources for performing chemical dynamics simulations. Goal is to have grid computing resources. Cyberinfrastructure for sharing chemical dynamics software.

18. COMPUTER PROGRAMS Current • RRKM – microcanonical RRKM calculations. • VENUS96 – classical trajectory simulations for a variety of initial conditions, and assortment of analytic potentials. Under Development • VENUS06 – gas/surface scattering, new integration algorithms, electronic non-adiabatic transitions (?), and other options. • VENUS/MOPAC – semiempirical QM and QM/MM direct dynamics. • VENUS/NWChem and VENUS/GAMESS – interfaces for QM and QM/MM direct dynamics. • Links – to other websites like POTLIB (Ron Duchovic) a library of analytic potentials to link to VENUS.

21. SIMULATION MODELS FOR VENUS06 Select Type of Simulation Model • Bimolecular Collisions Collision Between Two Gas-Phase Molecule • Unimolecular DecompositionDecomposition of a Vibrationally Excited Molecule • Intramolecular DynamicsDynamics of Vibrational Energy Flow Within a Molecule • Reaction Path Following and VTST Following the Reaction Path and Calculating the Variational Transition State Theory (VTST) Rate Constant for association of Two Particles • Normal Mode AnalysisVibrational Frequencies for a Molecule, Surface, Cluster, etc. • SN2 DynamicsDynamics of Gas-phase X- + CH3Y SN2 Nucleophilic Substitution Reactions • Minimum Energy Geometry OptimizationFinding a Minimum Energy Geometry for a Molecule, Surface, Cluster, etc. • Neutral Atom Small Molecule Collision with a Surface • Projectile Ion Collision with a Surface

22. Ar + H2O Collision Initial Conditions for H2O

23. Movie Maker

24. Diglycine-H+ + Diamond {111} Animation

25. CDSSIM: WEB-BASED CHEMICAL DYNAMICS SIMULATIONS A Tool for On-line Chemical Dynamics Simulations from Your Desk Computer • Chemical dynamics computer programs and documentation. • Tools for using existing, modifying, and building simulation models (input files). • Computational resources for performing simulations. • Tools to animate the simulations. Goal: Facilitate access to high-level chemical dynamics simulation tools and software, and motivate collaborative science.

26. Dynamics of the Cl- + CH3I → ClCH3 + I- SN2 Nucleophilic Substitution Reaction Collaboration: between Roland Wester Research Group, University of Freiburg, Germany (Experiments); and Bill Hase Research Group, Texas Tech University (Chemical Dynamics Simulations). Traditional Atomic-Level Reaction Mechanism: Cl- + CH3I → Cl----CH3I → ClCH3---I- → ClCH3 + I- Science 319, 183 (2008)

29. Direct mechanism

30. Roundabout mechanism

32. Surface:CF3(CF2)7S-Au Protonated peptide + TOP VIEW SIDE VIEW

33. Energy Transfer Dynamics

34. Cr+(CO)6, Ei= 30 eV, Θi = 45o. Samy Meroueh PCCP 3, 2306 (2001) Average per-cent transfer to ∆Eint for the H-SAM. Simulation: 10 %. Experiment: 11-12%; Cooks and co-workers.

35. Energy Transfer Dynamics

36. Cr+(CO)6, Ei= 30 eV, Θi = 45o. Samy Meroueh PCCP 3, 2306 (2001) Average per-cent transfer to ∆Eint for the H-SAM. Simulation: 10 %. Experiment: 11-12%; Cooks and co-workers.

37. Fragmentation Dynamics

38. Diglycine + Diamond {111}, Ei = 70 eV, θi= 0o QM+MM, Peptide described by AM1 (VENUS/MOPAC)

39. Diglycine + Diamond {111}, Ei = 70 eV, θi= 0o QM+MM, Peptide described by AM1 (VENUS/MOPAC)

40. SHATTERING FRACTION VERSUS COLLISION ENERGY FOR (gly)2-H+ + DIAMOND {111}a Y. Wang and K. Song, J. Am. Soc. Mass Spectrom.2003, 14, 1402. Collision Energy (eV) Shattering Fractionb 30 0.08 50 0.13 70 0.44 100 0.71 a. The collision angle is 0 degrees, perpendicular to the surface. The trajectories are QM+MM, with QM AM1 for the peptide. b. Fraction of the trajectories which shatter.

41. Thanks! Questions?