February 2011 - Allocations-admins - mailman3.cels.anl.gov

Re: [allocations-admins] [LCRC Accounts] Project Request: SOFC
by John Valdes 24 Feb '11

24 Feb '11

Wow, now that's what I call a project request. :) On Thu, Feb 24, 2011 at 11:57:48AM -0600, Bair, Raymond A. wrote: > We could start this project with 60K, which should last them through the end > of March. > [...] > Also, does MCS have a license for Matlab Parallel Computing Toolbox that we > could share or expand? No, MCS's license doesn't include the Parallel Computing Toolbox. Their license (which is the one we use on fusion, as we don't have our own) includes: 20 base licenses (one of which is needed for each running Matlab instance) 1 license for Curve Fitting Toolbox (which this project will need) 1 license for Image Toolbox (which this porject also will need) 2 licenses for Optimization Toolbox 4 licenses for Signal Toolbox > In Matlab terms, do we need a Group license or a Concurrent license for > Matlab Parallel Computing Toolbox? We could start small, e.g., 4 nodes (32 > cores). We would need a (floating) license for the Parallel Computing Toolbox. Each license for the toolbox provides for 8 worker processes on the local host, so this could be used, for example, by running an interactive job on 1 node and then running Matlab on that node. In addition to the Parallel Computing Toolbox, one can get the Matlab Distributed Computing Server, which allows one to run Matlab workers on a cluster either interactively or in batch. The way it was explained to me is that you could startup Matlab on a login node, for example, to setup the problem which you then submit to the job queues from within Matlab. The submitted job will then use worker licenses from the Distributed Computing Server while it runs on the compute nodes. While it runs, you can quit Matlab on the login node, thus freeing up the license used by that Matlab instance. http://www.mathworks.com/products/parallel-computing/ describes a little bit about the Parallel Computing Toolbox and the Distributed Computing Server. The cost for the Parallel Computing Toolbox licenses are $4,000 each. The cost for the Distributed Computing Server licenses are: 8 workers ........................ $6,000 16 workers ........................ 11,500 32 workers ........................ 21,000 64 workers ........................ 36,500 96 workers ........................ 50,000 128 workers ........................ 65,000 and so on. So not cheap. I'm guessing we'd probably need additional Curve Fitting and Image Processing toolbox licenses, but I don't know how much those would be (I'll ask our Matlab rep). Given the detailed project request, it sounds like the PI has used this workflow before, which suggests that he has (or had) Matlab licenses already somewhere. Maybe he already has his own licenses he could use? John

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Re: [allocations-admins] [LCRC Accounts] Project Request: SOFC
by Bair, Raymond A. 24 Feb '11

24 Feb '11

We could start this project with 60K, which should last them through the end of March. In Matlab terms, do we need a Group license or a Concurrent license for Matlab Parallel Computing Toolbox? We could start small, e.g., 4 nodes (32 cores). Also, does MCS have a license for Matlab Parallel Computing Toolbox that we could share or expand? Ray On 2/24/11 10:38 AM, "accounts(a)lcrc.anl.gov" <accounts(a)lcrc.anl.gov> wrote: > Hello, > > A new project on the LCRC cluster has been requested. Please forward > the information on to the LCRC Allocation sub-committee. > > Applicant's name: Yuxin Wang > Applicant's institution: ANL > Applicant's division: XSD > Project Name: SOFC > Project title: Imaging, Analysis and Simulation of Heterogeneous > Functional Materials > Associated funding: DoE > Other Systems: Primarily workstations at present. > Science: The DOE Energy Frontier Research Center (EFRC) on > Heterogeneous Functional Materials for Energy Systems (HeteroFoaM Center), led > by the University of South Carolina, is a collaboration with scientists at > APS, University of Connecticut, Princeton University, University of Utah, the > Georgia Institute of Technology, Rochester Institute of Technology, and the > University of California-Santa Barbara. The central objective of this EFRC, > funded by DOE-SC Office of Basic Energy Sciences, is to build a scientific > basis for bridging the gap between making nano-structured materials and > understanding how they function in a variety of energy applications > (www.science.doe.gov/bes/EFRC/CENTERS/HeteroFoaM/efrc_HeteroFoaM.html) > > Energy devices such as fuel cells, electrolyzers, combustion and fuel > processing devices consist of multiple materials interacting at multiple > scales. Establishing a fundamental understanding of the functional behavior of > these material systems at multiple length and time scales as the basis for > providing a scientific foundation for the conceptual design, simulation and > fabrication of nano-structured heterogeneous materials for energy systems is > the objective of the EFRC. Central to this effort is the formulation of > science-based theory and computational methods for the analysis and simulation > of the functional performance of these materials based on their composition, > configuration and nano-morphology. Central themes in understanding functional > materials in non-equilibrium states involves understanding transport, > conversion, transfer of mass, momentum, energy and charge, as well as > stability and durability for long-term performance. > > The present proposal seeks the computational resources required for the > reconstruction and analysis of materials imaged using a transmission x-ray > microscope at APS beamline 32-ID-C. Structures, elemental and chemistry > information obtained will be used to perform quantum chemical & mechanical, > and mesoscale (phase-field and lattice Boltzmann) modeling and simulation of > the non-equilibrium thermodynamics and diffusion/reaction kinetics at the > atomic scale at interfaces in heterogeneous materials, stability of films as > function of morphology, and predictive estimation of properties and functional > behavior. The methodologies that will be applied include i) quantum-mechanical > atomic level simulations to understand how materials behave at interfaces and > as function of morphology, dopants, and nano-sized features, ii) mesoscale > simulations to incorporate geometrical effects with atomic detail, iii) > evaluation of new material properties, and iv) multiscale physics analysis of > solid > oxide fuel cells (SOFCs). > > Project description: In the proposed work, a transmission x-ray > microscope (TXM) with high resolution x-ray nanotomography will be used to > obtain a detailed geometric description of SOFC electrodes at 30 nm resolution > useing a tunable synchrotron light source at APS beamline 32-ID-C. The XCT > technique is a non-destructive method used to image and reconstruct actual > SOFC microstructures. X-rays penetrate the sample mounted on a rotation stage, > then passes through a scintillation screen and captured by a camera. The > sample is rotated through 180 degrees with sample projections produced at > specified angle intervals and exposure times. Images are captured over a field > of view of up to 100 Î¼m by using stitching methods and reconstructed into a > 3-D volume of the pore structure. To achieve elemental sensitivity for Ni at > the Ni-YSZ interface, the microscopy experiments were carried at 8.317 keV and > 8.357 keV, corresponding to 16 eV below and 24 eV above the Ni K-edge (8.333 > ke > V), respectively. Once the TXM data has been obtained, slice-by-slice > reconstruction will be carried out to convert the image data to digitized 3D > reconstructed volumes. This approach has been successfully validated. The > digitized 3D geometry will be used as model input. > > The nanotomography data obtained require further processing before the > microstructure of the samples can be fully characterized. Chromatic focusing > of the TXM zoneplate lens during the measurements can cause non-negligible > variation in the magnification of the sample over the energy range > investigated. The images were scaled to eliminate this variation. The > transmission images from two different energy levels were processed to isolate > the Ni phases to produce two separate nanotomography data sets, one > representing Ni and another phase. Each of these data sets was aligned on a > central rotation axis, and reconstructed using the iterative algebraic > reconstruction technique (i-ART) algorithm. The output from the > reconstruction is two image stacks corresponding to each phase of interest. > These stacks are processed separately with segmentation steps performed using > the ImageJ software. After performing fine alignment to account for minor > variations in stage positioning, the p > rocessed stacks are merged to produce one final volumetric data set, with > discrete identification of each phase. This volumetric data is used as an > input to previously developed microstructural characterization codes. > > Image processing is a compute intensive task, but necessary to obtain useful > structures and elemental/chemical information for quantum chemical > simulations, atomistic simulations, and mesoscale phase-field and lattice > Boltzmann simulations. > > Quantum chemical simulations & Quantum mechanical calculations > > It is the objective of the quantum chemical calculations for this project to > rationally design new nano-structured heterogeneous functional materials from > the â€œatom-upâ€ˇ and to identify the scientific relationship between > structure and property/function. Quantum chemical simulations will be based > on density functional theory (DFT) and transition state theory which permits > connecting atomistic information with meso- and macroscopic information and > therefore ultimately the simulation of materials at experimental time and > length scales. For the anode electrode of the SOFC, key properties of > interest are high electronic conductivity, oxygen ion mobility, tolerance to > sulfur impurities in the fuel stream, and tolerance to carbon poisoning. For > the cathode electrode, key properties are high electronic conductivity, oxygen > ion mobility, and oxygen dissociation rate. We aim at identifying a minimal > set of independent descriptors for these material properties that allows > ration > al material selection, particularly dopant selection. > > Unfortunately, no one quantum chemical method can calculate accurately all > properties of interest. The workhorse method for condensed matter electronic > structure calculations at present is DFT within the generalized gradient > approximation (GGA) to electron exchange and correlation. And while the SOFC > electrolyte, YSZ, is well described by DFT-GGA, many materials of interest for > the anode and cathode electrode of the SOFC are reduced oxides with transition > metal or lanthanide ions with open shell 3d- and 4f- electrons that are > described incorrectly by DFT-GGA because their approximate exchange energies > do not exactly cancel the spurious Coulomb repulsion of each open-shell > d-electron with itself, leading to the so-called â€œself-interaction error > (SIE)â€ˇ. The consequences of the inexact cancellation are not just > quantitative but qualitative failure, e.g., with semiconductors sometimes > predicted to be metals (e.g., NiO and FeO). This class of materials is > referred to as st > rongly correlated, and cannot be described properly in a static mean field > theory, such as DFT. > > Although several first principles quantum mechanics methods of treating such > materials exist, we will employ electronic structure methods that provide the > correct physics at minimal extra cost beyond a conventional DFT calculation. > These are the periodic electrostatic embedded cluster (PEEC) method with > hybrid and double-hybrid density functionals and the DFT+U method, originally > proposed by Anisimov, Lichtenstein and coworkers,[1-3] in which the spurious > intra-atomic self-Coulomb repulsion of the open-shell d and/or f electrons is > cancelled by using exact intra-atomic Hartree-Fock (HF) exchange, while the > rest of the electrons are described within DFT. > > Materials of interest for the anode side of the SOFC are doped perovskite and > double perovskite structures such as SrTiO3 and Sr2Fe1.5Mo0.5O6-Î´. Double > perovskite structures based on Mo can easily be doped with various transition > metals, permitting a significant variation of the material properties. > Materials of interest for the cathode side are gadolinium-doped ceria > (Gd-doped CeO2 or GDC), lanthanum strontium cobaltate (La0.6Sr0.4CoO3 LSC, the > Fe-doped analog (LSCF), Sr2Fe1.5Mo0.5O6-Î´, and lanthanum strontium manganate > (LSM). > > We will employ DFT+U based calculations to characterize the bulk and surface > electronic structure and kinetic processes of the SOFC cathode materials LSCF > and LSM. DFT+U requires as input a parameter that is the difference between > the averaged Coulomb (U) and exchange (J) interactions for the electrons of a > specific angular momentum localized on each atomic site. We use the method of > Mosey, Liao, and Carter[4] for calculating U and J ab initio from unrestricted > Hartree-Fock (UHF) calculations on electrostatically embedded clusters, so as > to render the DFT+U method nonempirical. > > We are interested in improving oxygen ion transport in mixed electron-ion > conductors such as LSCF and LSM by doping or alloying these parent materials. > To predict the kinetics of oxygen diffusion through the SOFC cathode material, > we will employ the nudged elastic band (NEB)[5] method to locate the minimum > energy path for diffusion. This technique determines the transition state from > which we can calculate the activation energy and, by calculating the > vibrational frequencies associated with the minimum and transition state, the > pre-exponential factor for the diffusion constant.[6-7] > > DFT with the GGA and LDA functionals also fail to accurately describe the bond > energy of dioxygen. This failure occurs not only because of the SIE mentioned > earlier but also the open-shell triplet ground state of O2 is not a pure spin > eigenfunction of the single determinant wavefunction employed in DFT. To > overcome this failure, we will employ embedded configuration interaction > (ECI)[8] calculations. Here the system is broken into a small region of > interest treated with a highly accurate quantum mechanical method (e.g., > multi-reference single and double excitation CI, MRSDCI) and a background > region described with a lower-level method (DFT+U or electrostatic embedding) > that defines an embedding potential for the region of interest. In addition > to providing an accurate description of oxygen bond dissociation energetics, > this method allows for the explicit inclusion of an electron at the LSCF and > LSM surface. In this way, we can model the electrochemical reduction > processes > occurring at the SOFC cathode. > > Using these methods, we aim to predict the kinetics of the different cathode > processes which influence the overall performance of the SOFC. From our > calculations, we will seek to understand how material composition affects the > different kinetic parameters as well as determining which processes may serve > as key descriptors of the overall cathode kinetics. > > Mesoscale Phase-field Simulations > > In order to address the issue of microstructural stability in SOFCs over > extended operation times, a coarse-grained continuum approach is required. > The so-called â€œdiffuse-interfaceâ€ˇ or â€œphase-fieldâ€ˇ (PF) modeling > framework, in which Prof. Mikko Haataja has extensive experience[12,13,14], > has become very popular over the past several years as a tool to simulate > evolving microstructures in multicomponent, multiphase materials. In this > approach, several continuum fields (â€œorder parametersâ€ˇ) are first > introduced to account for both the local phase (solid vs. pore) and > composition/structure (Ni vs. YSZ). Then, a thermodynamic free energy, which > accounts for the thermodynamics of bulk phases and relevant interfacial > energies, is constructed. Finally, the dynamics of the order parameters are > obtained from the free energy via variational principles, leading to coupled > non-linear partial differential equations defined in the whole computational > domain. > > One of the strengths of the PF method is that it conveniently handles complex > topological changes occurring during the microstructural evolution process, > while the numerical challenge is to integrate stiff PDEs over extended > simulation times in a 3D computational domain. > > Lattice Boltzmann calculations > > Over the past decade, the lattice Boltzmann method (LBM) has been applied to > solve an astonishingly large variety of problems in various disciplines, > particularly at the mesoscale. LBM techniques are CPU and memory intensive. > This often restricts the lattice resolution that can be used on standard > cluster computers. Now that massively parallel computers such as the FUSION > system are available, these CPU and memory issues can be addressed so problems > that were previously intractable using the LBM can be brought within reach. > The LBM scheme has been shown to scale well on large computing systems. > Excellent scale-up was observed up to 1024 processors by Oliker et al. using a > 512^3 lattice to study flow turbulence[15]. For a turbulence application, a > sustained performance of 2 TFlops was achieved on 256 NEC vector CPUs. This > indicates that the LBM is a very promising candidate for large scale computing > platforms like FUSION. > > Mathematical modeling of transport phenomenon in a fuel cell is very useful > for analyzing and optimizing fuel cells. For example, team member Prof. Wilson > K. S. Chiu has used three-dimensional (3D) LBM models to investigate > multi-component mass transport with electrochemistry and reformation in porous > SOFCs[16-18]. The imaging technology required to reconstruct the 3D SOFC > electrode geometry is available[19], and 3D LBM simulations would > significantly increase the accuracy of the SOFC mass transport model. The goal > of our research is to model the diffusive flow of three gaseous species (H2, > H2O, and N2) through the porous anode structure of a SOFC. Our model uses a 3D > representation of the porous anode, obtained from x-ray nanotomography at APS > beamline 32-ID-C, with resolution as low as 30 nm[19]. > > Such analysis is often very expensive on scalar and smaller cluster systems > and often restricts the resolution that can be used to model the problem of > interest. However, now that massively parallel computers such as FUSION are > available, these memory issues can be addressed and problems that were > intractable using the LBM only a few years ago are within reach. > > > Computational Detail - Resource Needs > > Image processing > All image processing will be performed using Matlab with three toolboxes > (image processing toolbox, parallel computing (version 2010b), and curve > fitting). We will reconstruct an average of 20 samples per week requiring an > average of 48 node hours per calculation (50000 node hours per year). We will > also be performing additional image processing of each sample requiring > approximately 30 node hours per calculation (30000 node hours per year). All > calculations will require up to 100 GB of memory. > > Quantum chemical simulations & Quantum mechanical calculations > Our DFT calculations will be performed using the Vienna Ab Initio Simulation > Package (VASP)20,21 which solves the Kohn-Sham equations subject to periodic > boundary conditions using a planewave basis set. We will perform an average > of 40 single-point energy calculations each week requiring an average of 20 > node hours per calculation (41600 node hours per year). We will also be > performing an average of three nudged elastic band calculations each week > requiring approximately 1200 node hours per calculation ( node hours per > year). > > All PEECM calculations will be performed with the Turbomole code (based on > Gaussian-type basis sets) using hybrid and double-hybrid density functionals. > Transition states required for the calculation of reaction rates will be > located with our own highly efficient growing string[22] and improved > dimer[23] algorithms. Recent tests on EMSL Chinook confirmed that both VASP > and Turbomole scale well up to hundreds of nodes. Overall, we expect that > computations required for quantum chemical calculations on the anode side of > the SOFC will require approximately 750,000 node-hours per year and 500 GB of > memory. This estimate is based on submitting 150 geometry optimizations and > 20 transition state searches per year for each the perovskite and double > perovskite structures (optimization of a perovskite structure requires on > FUSION about 5000 node hours; optimization for a double perovskite structure > requires about 12,500 node hours; transition state searches require about 10 > times mo > re time than a structure optimization). > > Phase-field Simulations > Our continuum PF simulations will be performed with a parallel MPI code > written in-house. While we have not benchmarked this particular code, our > experience with similar codes in the past suggests that it should scale well > up to 32 or 64 CPUs on the FUSION system. Furthermore, we estimate that a > simulation with 128^3 (256^3) grid points will require 240 (1920) node-hours > wall clock time and 100 GB (800GB) of memory. On an annual basis, we expect > that our simulations of SOFC anode microstructural evolution phenomena require > on the order of 200,000 node hours and 1 TB of memory on the FUSION system, > corresponding to 100 high-resolution simulations. > > > Lattice Boltzmann Calculations > Our LBM simulation of 3D mass transport and electrochemistry in solid oxide > fuel cells scales well up to 64 CPU on a local SGI Altix 850 system. For the > FUSION system, we estimate that a single case using low resolution 81^3 > lattice will require 350 node-hours wall-clock time and 100 GB memory on the > FUSION system. A high resolution 674^3 lattice will enable us to simulate > realistic physical domain sizes and lead to better accuracy of the model > predictions, but each case will require 22,400 node-hours wall-clock time and > 1 TB memory on the FUSION system. Our annual estimated EFRC project needs on > the FUSION system are 300,000 node hours: two low resolution lattice cases per > week (36,400 node-hours wall-clock time per year), and one high resolution > lattice case per month (268,800 node-hours wall-clock time per year). > > > Summary of Computing Resource Needs (March 2011 to September 2011) > > Software Requirements Node Hours > Storage GB > Image Processing Matlab with toolboxes 30,000 > 100 > Quantum chemical simulations Turbomole 140,000 > 500 > Quantum mechanical calculations VASP 40,000 > 500 > Phase-field simulations Intel C++ Compiler 45,000 > 1500 > Lattice Boltzmann calculations Intel Fortran Compiler 45,000 > 1500 > > Total > 300,000 3000 > > Matlab will require the (1) image processing toolbox, (2) parallel computing > toolbox (version 2010b), and (3) curve fitting toolbox. > > > References > > 1. V. Anisimov, J. Zaanen, O. K. Andersen, â€œBand theory and Mott > insulators: Hubbard U instead of Stoner Iâ€ˇ, Physical Review B, vol. 44, pp. > 943-954 (1991). > 2. V. Anisimov, F. Aryasetiawan, A. I. Lichtenstein, â€œFirst-principles > calculations of the electronic structure and spectra of strongly correlated > systems: the LDA+U methodâ€ˇ, Journal of Physics: Condensed Matter, vol. 9, > pp. 767-808 (1997). > 3. S. L. Dudarev, A. I. Lichtenstein, M. R. Castell, G. A. D. Briggs, A. > P. Sutton, â€œSurface states on NiO (100) and the origin of the contrast > reversal in atomically resolved scanning tunneling microscope imagesâ€ˇ, > Physical Review B, vol. 56, pp. 4900-4908 (1997). > 4. N. J. Mosey, P. Liao, E. A. Carter, â€œRotationally invariant ab > initio evaluation of Coulomb and exchange parameters for DFT+U > calculationsâ€ˇ, Journal of Chemical Physics, vol. 129, pp. 014103 (2008). > 5. H. JÃ³nsson, G. Mills, K. Jacobsen, â€œNudged elastic band method for > finding minimum energy paths of transitionsâ€ˇ in Classical and Quantum > Dynamics in Condensed Phase Simulations, pp. 385-404, World Scientific, 1998. > 6. K. A. Marino and E. A. Carter, â€œThe effect of platinum on diffusion > kinetics is Î²-NiAl: Implications for thermal barrier coating lifetimesâ€ˇ, > ChemPhysChem, vol. 10, pp. 226, (2009). > 7. K. A. Marino and E. A. Carter, â€œFirst-principles characterization of > Ni diffusion kinetics in Î²-NiAlâ€ˇ, Physical Review B, vol. 78, pp. 184105 > (2008). > 8. P. Huang and E. A. Carter, â€œSelf-consistent embedding theory for > locally correlated configuration interaction wave functions in condensed > matterâ€ˇ, Journal of Chemical Physics, vol. 125, pp. 084102 (2006). > 9. R. M. Shroll, and T. P. Straatsma, â€œMolecular Dynamics Simulations > of the Goethite-Water Interfaceâ€ˇ, Molecular Simulation, 29, 1-11 (2003) > 10. R. M. Shroll, and T. P. Straatsma, â€œMolecular Basis for Microbial > Adhesion to Geochemical Surfaces: Computer Simulation of Pseudomonas > aeruginosa Adhesion to Goethiteâ€ˇ, Biophysical Journal, 84, 1765-1772 (2003). > 11. T. P. Straatsma and J. A. McCammon, â€œMulticonfiguration > thermodynamic integrationâ€ˇ, J. Chem. Phys., 95, 1175-1188 (1991). > 12. S. Sreekala and M. Haataja, â€œRecrystallization kinetics: A coupled > coarse-grained dislocation density and phase-field approachâ€ˇ, Phys. Rev. B > 76, 094109 (2007). > 13. M. Haataja and F. LÃ©onard, â€œSpinodal decomposition in the presence > of mobile dislocationsâ€ˇ, Phys. Rev. B 69, 081201 (R) (2004). > 14. M. Haataja, J. MÃ¼ller, A. D. Rutenberg, and M. Grant, â€œDislocations > and morphological instabilities: Continuum modeling of misfitting > heteroepitaxial filmsâ€ˇ, Phys. Rev. B 65, 165414 (2002). > 15. L. Oliker, A. Canning, J. Carter, C. Iancu, M. Lijewski, S. Kamil, J. > Shalf, H. Shan, E. Strohmaier, S. Ethier, T. Goodale (2007) Scientific > Application Performance on Candidate Petascale Platforms, International > Parallel and Distributed Processing Symposium (IPDPS), March 24 â€“ 30, 2007, > Long Beach, CA. > 16. A. S. Joshi, K. N. Grew, J. R. Izzo, Jr., A. A. Peracchio, and W. K. > S. Chiu, â€œLattice Boltzmann Modeling of Three-Dimensional, Multicomponent > Mass Diffusion in a Solid Oxide Fuel Cell Anode,â€ˇ ASME Journal of Fuel Cell > Science and Technology, vol. 7, pp. 011006-1-011006-8 (2010). > 17. A. S. Joshi, K. N. Grew, A. A. Peracchio and W. K. S. Chiu, â€œLattice > Boltzmann Modeling of 2D Gas Transport in a Solid Oxide Fuel Cell Anode,â€ˇ > Journal of Power Sources, vol. 164, pp. 631-638 (2007). > 18. K. N. Grew, A. S. Joshi, A. A. Peracchio, and W. K. S. Chiu, > â€œPore-Scale Investigation of Mass Transport and Electrochemistry in a Solid > Oxide Fuel Cell Anode,â€ˇ Journal of Power Sources, vol. 195, pp. 2331â€“2345 > (2010). > 19. K. N. Grew, Y. S. Chu, J. Yi, A. A. Peracchio, J. R. Izzo, Jr., F. De > Carlo, Y. Hwu and W. K. S. Chiu, â€œNondestructive Nanoscale 3D Elemental > Mapping and Analysis of a Solid Oxide Fuel Cell Anode,â€ˇ Journal of the > Electrochemical Society, vol. 157(5), (2010). > 20. G. Kresse and J. FurthmÃ¼ller, â€œEfficiency of ab-initio total energy > calculations for metals and semiconductors using a plane-wave basis setâ€ˇ, > Computational Materials Science, vol. 6, pp. 15-50, 1996. > 21. G. Kresse and J. FurthmÃ¼ller, â€œEfficient iterative schemes for ab > initio total-energy calculations using a plane-wave basis setâ€ˇ, Physical > Review B, vol. 54, pp. 11169-11186 (1996). > 22. Peters, B., Heyden, A., Bell, A. T., Chakraborty, A., A growing string > method for determining transition states: Comparison to the nudged elastic > band and string methods. J. Chem. Phys. 120, 7877-7886 (2004). > 23. Heyden, A., Bell, A. T., Keil, F. J., Efficient methods for finding > transition states in chemical reactions: Comparison of modified dimer method > and partitioned rational function optimization method. J. Chem. Phys. 123, > 224101-14 (2005). > > > > > Project URL: > http://www.science.doe.gov/bes/EFRC/CENTERS/HeteroFoaM/efrc_HeteroFoaM.html > Requested allocation: 400000 > Justification: N/A > > > The requester has used 0 hours of their initial startup project. > > In addition to approving an initial amount, please specify a Category > and Subcategory for this project. For a list of the current selection > of approved categories, please see: > > https://wiki.lcrc.anl.gov/wiki/Processes/Categories > > Once the Allocation committee has approved the project, please go to > the Project Management page to create it: > > https://accounts.lcrc.anl.gov/projects.php > > Thank You, > The LCRC Accounts System ----------------------------------------- Ray Bair Computing, Environment, and Life Sciences Argonne National Laboratory and the University of Chicago TCS Building 240, Room 4126 9700 South Cass Avenue Argonne, IL 60439 email: rbair(at)anl.gov Phone: (630)252-5751

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[LCRC Accounts] Project Request: SOFC
by accounts＠lcrc.anl.gov 24 Feb '11

24 Feb '11

Hello, A new project on the LCRC cluster has been requested. Please forward the information on to the LCRC Allocation sub-committee. Applicant's name: Yuxin Wang Applicant's institution: ANL Applicant's division: XSD Project Name: SOFC Project title: Imaging, Analysis and Simulation of Heterogeneous Functional Materials Associated funding: DoE Other Systems: Primarily workstations at present. Science: The DOE Energy Frontier Research Center (EFRC) on Heterogeneous Functional Materials for Energy Systems (HeteroFoaM Center), led by the University of South Carolina, is a collaboration with scientists at APS, University of Connecticut, Princeton University, University of Utah, the Georgia Institute of Technology, Rochester Institute of Technology, and the University of California-Santa Barbara. The central objective of this EFRC, funded by DOE-SC Office of Basic Energy Sciences, is to build a scientific basis for bridging the gap between making nano-structured materials and understanding how they function in a variety of energy applications (www.science.doe.gov/bes/EFRC/CENTERS/HeteroFoaM/efrc_HeteroFoaM.html) Energy devices such as fuel cells, electrolyzers, combustion and fuel processing devices consist of multiple materials interacting at multiple scales. Establishing a fundamental understanding of the functional behavior of these material systems at multiple length and time scales as the basis for providing a scientific foundation for the conceptual design, simulation and fabrication of nano-structured heterogeneous materials for energy systems is the objective of the EFRC. Central to this effort is the formulation of science-based theory and computational methods for the analysis and simulation of the functional performance of these materials based on their composition, configuration and nano-morphology. Central themes in understanding functional materials in non-equilibrium states involves understanding transport, conversion, transfer of mass, momentum, energy and charge, as well as stability and durability for long-term performance. The present proposal seeks the computational resources required for the reconstruction and analysis of materials imaged using a transmission x-ray microscope at APS beamline 32-ID-C. Structures, elemental and chemistry information obtained will be used to perform quantum chemical & mechanical, and mesoscale (phase-field and lattice Boltzmann) modeling and simulation of the non-equilibrium thermodynamics and diffusion/reaction kinetics at the atomic scale at interfaces in heterogeneous materials, stability of films as function of morphology, and predictive estimation of properties and functional behavior. The methodologies that will be applied include i) quantum-mechanical atomic level simulations to understand how materials behave at interfaces and as function of morphology, dopants, and nano-sized features, ii) mesoscale simulations to incorporate geometrical effects with atomic detail, iii) evaluation of new material properties, and iv) multiscale physics analysis of solid oxide fuel cells (SOFCs). Project description: In the proposed work, a transmission x-ray microscope (TXM) with high resolution x-ray nanotomography will be used to obtain a detailed geometric description of SOFC electrodes at 30 nm resolution useing a tunable synchrotron light source at APS beamline 32-ID-C. The XCT technique is a non-destructive method used to image and reconstruct actual SOFC microstructures. X-rays penetrate the sample mounted on a rotation stage, then passes through a scintillation screen and captured by a camera. The sample is rotated through 180 degrees with sample projections produced at specified angle intervals and exposure times. Images are captured over a field of view of up to 100 μm by using stitching methods and reconstructed into a 3-D volume of the pore structure. To achieve elemental sensitivity for Ni at the Ni-YSZ interface, the microscopy experiments were carried at 8.317 keV and 8.357 keV, corresponding to 16 eV below and 24 eV above the Ni K-edge (8.333 ke V), respectively. Once the TXM data has been obtained, slice-by-slice reconstruction will be carried out to convert the image data to digitized 3D reconstructed volumes. This approach has been successfully validated. The digitized 3D geometry will be used as model input. The nanotomography data obtained require further processing before the microstructure of the samples can be fully characterized. Chromatic focusing of the TXM zoneplate lens during the measurements can cause non-negligible variation in the magnification of the sample over the energy range investigated. The images were scaled to eliminate this variation. The transmission images from two different energy levels were processed to isolate the Ni phases to produce two separate nanotomography data sets, one representing Ni and another phase. Each of these data sets was aligned on a central rotation axis, and reconstructed using the iterative algebraic reconstruction technique (i-ART) algorithm. The output from the reconstruction is two image stacks corresponding to each phase of interest. These stacks are processed separately with segmentation steps performed using the ImageJ software. After performing fine alignment to account for minor variations in stage positioning, the p rocessed stacks are merged to produce one final volumetric data set, with discrete identification of each phase. This volumetric data is used as an input to previously developed microstructural characterization codes. Image processing is a compute intensive task, but necessary to obtain useful structures and elemental/chemical information for quantum chemical simulations, atomistic simulations, and mesoscale phase-field and lattice Boltzmann simulations. Quantum chemical simulations & Quantum mechanical calculations It is the objective of the quantum chemical calculations for this project to rationally design new nano-structured heterogeneous functional materials from the “atom-up” and to identify the scientific relationship between structure and property/function. Quantum chemical simulations will be based on density functional theory (DFT) and transition state theory which permits connecting atomistic information with meso- and macroscopic information and therefore ultimately the simulation of materials at experimental time and length scales. For the anode electrode of the SOFC, key properties of interest are high electronic conductivity, oxygen ion mobility, tolerance to sulfur impurities in the fuel stream, and tolerance to carbon poisoning. For the cathode electrode, key properties are high electronic conductivity, oxygen ion mobility, and oxygen dissociation rate. We aim at identifying a minimal set of independent descriptors for these material properties that allows ration al material selection, particularly dopant selection. Unfortunately, no one quantum chemical method can calculate accurately all properties of interest. The workhorse method for condensed matter electronic structure calculations at present is DFT within the generalized gradient approximation (GGA) to electron exchange and correlation. And while the SOFC electrolyte, YSZ, is well described by DFT-GGA, many materials of interest for the anode and cathode electrode of the SOFC are reduced oxides with transition metal or lanthanide ions with open shell 3d- and 4f- electrons that are described incorrectly by DFT-GGA because their approximate exchange energies do not exactly cancel the spurious Coulomb repulsion of each open-shell d-electron with itself, leading to the so-called “self-interaction error (SIE)”. The consequences of the inexact cancellation are not just quantitative but qualitative failure, e.g., with semiconductors sometimes predicted to be metals (e.g., NiO and FeO). This class of materials is referred to as st rongly correlated, and cannot be described properly in a static mean field theory, such as DFT. Although several first principles quantum mechanics methods of treating such materials exist, we will employ electronic structure methods that provide the correct physics at minimal extra cost beyond a conventional DFT calculation. These are the periodic electrostatic embedded cluster (PEEC) method with hybrid and double-hybrid density functionals and the DFT+U method, originally proposed by Anisimov, Lichtenstein and coworkers,[1-3] in which the spurious intra-atomic self-Coulomb repulsion of the open-shell d and/or f electrons is cancelled by using exact intra-atomic Hartree-Fock (HF) exchange, while the rest of the electrons are described within DFT. Materials of interest for the anode side of the SOFC are doped perovskite and double perovskite structures such as SrTiO3 and Sr2Fe1.5Mo0.5O6-δ. Double perovskite structures based on Mo can easily be doped with various transition metals, permitting a significant variation of the material properties. Materials of interest for the cathode side are gadolinium-doped ceria (Gd-doped CeO2 or GDC), lanthanum strontium cobaltate (La0.6Sr0.4CoO3 LSC, the Fe-doped analog (LSCF), Sr2Fe1.5Mo0.5O6-δ, and lanthanum strontium manganate (LSM). We will employ DFT+U based calculations to characterize the bulk and surface electronic structure and kinetic processes of the SOFC cathode materials LSCF and LSM. DFT+U requires as input a parameter that is the difference between the averaged Coulomb (U) and exchange (J) interactions for the electrons of a specific angular momentum localized on each atomic site. We use the method of Mosey, Liao, and Carter[4] for calculating U and J ab initio from unrestricted Hartree-Fock (UHF) calculations on electrostatically embedded clusters, so as to render the DFT+U method nonempirical. We are interested in improving oxygen ion transport in mixed electron-ion conductors such as LSCF and LSM by doping or alloying these parent materials. To predict the kinetics of oxygen diffusion through the SOFC cathode material, we will employ the nudged elastic band (NEB)[5] method to locate the minimum energy path for diffusion. This technique determines the transition state from which we can calculate the activation energy and, by calculating the vibrational frequencies associated with the minimum and transition state, the pre-exponential factor for the diffusion constant.[6-7] DFT with the GGA and LDA functionals also fail to accurately describe the bond energy of dioxygen. This failure occurs not only because of the SIE mentioned earlier but also the open-shell triplet ground state of O2 is not a pure spin eigenfunction of the single determinant wavefunction employed in DFT. To overcome this failure, we will employ embedded configuration interaction (ECI)[8] calculations. Here the system is broken into a small region of interest treated with a highly accurate quantum mechanical method (e.g., multi-reference single and double excitation CI, MRSDCI) and a background region described with a lower-level method (DFT+U or electrostatic embedding) that defines an embedding potential for the region of interest. In addition to providing an accurate description of oxygen bond dissociation energetics, this method allows for the explicit inclusion of an electron at the LSCF and LSM surface. In this way, we can model the electrochemical reduction processes occurring at the SOFC cathode. Using these methods, we aim to predict the kinetics of the different cathode processes which influence the overall performance of the SOFC. From our calculations, we will seek to understand how material composition affects the different kinetic parameters as well as determining which processes may serve as key descriptors of the overall cathode kinetics. Mesoscale Phase-field Simulations In order to address the issue of microstructural stability in SOFCs over extended operation times, a coarse-grained continuum approach is required. The so-called “diffuse-interface” or “phase-field” (PF) modeling framework, in which Prof. Mikko Haataja has extensive experience[12,13,14], has become very popular over the past several years as a tool to simulate evolving microstructures in multicomponent, multiphase materials. In this approach, several continuum fields (“order parameters”) are first introduced to account for both the local phase (solid vs. pore) and composition/structure (Ni vs. YSZ). Then, a thermodynamic free energy, which accounts for the thermodynamics of bulk phases and relevant interfacial energies, is constructed. Finally, the dynamics of the order parameters are obtained from the free energy via variational principles, leading to coupled non-linear partial differential equations defined in the whole computational domain. One of the strengths of the PF method is that it conveniently handles complex topological changes occurring during the microstructural evolution process, while the numerical challenge is to integrate stiff PDEs over extended simulation times in a 3D computational domain. Lattice Boltzmann calculations Over the past decade, the lattice Boltzmann method (LBM) has been applied to solve an astonishingly large variety of problems in various disciplines, particularly at the mesoscale. LBM techniques are CPU and memory intensive. This often restricts the lattice resolution that can be used on standard cluster computers. Now that massively parallel computers such as the FUSION system are available, these CPU and memory issues can be addressed so problems that were previously intractable using the LBM can be brought within reach. The LBM scheme has been shown to scale well on large computing systems. Excellent scale-up was observed up to 1024 processors by Oliker et al. using a 512^3 lattice to study flow turbulence[15]. For a turbulence application, a sustained performance of 2 TFlops was achieved on 256 NEC vector CPUs. This indicates that the LBM is a very promising candidate for large scale computing platforms like FUSION. Mathematical modeling of transport phenomenon in a fuel cell is very useful for analyzing and optimizing fuel cells. For example, team member Prof. Wilson K. S. Chiu has used three-dimensional (3D) LBM models to investigate multi-component mass transport with electrochemistry and reformation in porous SOFCs[16-18]. The imaging technology required to reconstruct the 3D SOFC electrode geometry is available[19], and 3D LBM simulations would significantly increase the accuracy of the SOFC mass transport model. The goal of our research is to model the diffusive flow of three gaseous species (H2, H2O, and N2) through the porous anode structure of a SOFC. Our model uses a 3D representation of the porous anode, obtained from x-ray nanotomography at APS beamline 32-ID-C, with resolution as low as 30 nm[19]. Such analysis is often very expensive on scalar and smaller cluster systems and often restricts the resolution that can be used to model the problem of interest. However, now that massively parallel computers such as FUSION are available, these memory issues can be addressed and problems that were intractable using the LBM only a few years ago are within reach. Computational Detail - Resource Needs Image processing All image processing will be performed using Matlab with three toolboxes (image processing toolbox, parallel computing (version 2010b), and curve fitting). We will reconstruct an average of 20 samples per week requiring an average of 48 node hours per calculation (50000 node hours per year). We will also be performing additional image processing of each sample requiring approximately 30 node hours per calculation (30000 node hours per year). All calculations will require up to 100 GB of memory. Quantum chemical simulations & Quantum mechanical calculations Our DFT calculations will be performed using the Vienna Ab Initio Simulation Package (VASP)20,21 which solves the Kohn-Sham equations subject to periodic boundary conditions using a planewave basis set. We will perform an average of 40 single-point energy calculations each week requiring an average of 20 node hours per calculation (41600 node hours per year). We will also be performing an average of three nudged elastic band calculations each week requiring approximately 1200 node hours per calculation ( node hours per year). All PEECM calculations will be performed with the Turbomole code (based on Gaussian-type basis sets) using hybrid and double-hybrid density functionals. Transition states required for the calculation of reaction rates will be located with our own highly efficient growing string[22] and improved dimer[23] algorithms. Recent tests on EMSL Chinook confirmed that both VASP and Turbomole scale well up to hundreds of nodes. Overall, we expect that computations required for quantum chemical calculations on the anode side of the SOFC will require approximately 750,000 node-hours per year and 500 GB of memory. This estimate is based on submitting 150 geometry optimizations and 20 transition state searches per year for each the perovskite and double perovskite structures (optimization of a perovskite structure requires on FUSION about 5000 node hours; optimization for a double perovskite structure requires about 12,500 node hours; transition state searches require about 10 times mo re time than a structure optimization). Phase-field Simulations Our continuum PF simulations will be performed with a parallel MPI code written in-house. While we have not benchmarked this particular code, our experience with similar codes in the past suggests that it should scale well up to 32 or 64 CPUs on the FUSION system. Furthermore, we estimate that a simulation with 128^3 (256^3) grid points will require 240 (1920) node-hours wall clock time and 100 GB (800GB) of memory. On an annual basis, we expect that our simulations of SOFC anode microstructural evolution phenomena require on the order of 200,000 node hours and 1 TB of memory on the FUSION system, corresponding to 100 high-resolution simulations. Lattice Boltzmann Calculations Our LBM simulation of 3D mass transport and electrochemistry in solid oxide fuel cells scales well up to 64 CPU on a local SGI Altix 850 system. For the FUSION system, we estimate that a single case using low resolution 81^3 lattice will require 350 node-hours wall-clock time and 100 GB memory on the FUSION system. A high resolution 674^3 lattice will enable us to simulate realistic physical domain sizes and lead to better accuracy of the model predictions, but each case will require 22,400 node-hours wall-clock time and 1 TB memory on the FUSION system. Our annual estimated EFRC project needs on the FUSION system are 300,000 node hours: two low resolution lattice cases per week (36,400 node-hours wall-clock time per year), and one high resolution lattice case per month (268,800 node-hours wall-clock time per year). Summary of Computing Resource Needs (March 2011 to September 2011) Software Requirements Node Hours Storage GB Image Processing Matlab with toolboxes 30,000 100 Quantum chemical simulations Turbomole 140,000 500 Quantum mechanical calculations VASP 40,000 500 Phase-field simulations Intel C++ Compiler 45,000 1500 Lattice Boltzmann calculations Intel Fortran Compiler 45,000 1500 Total 300,000 3000 Matlab will require the (1) image processing toolbox, (2) parallel computing toolbox (version 2010b), and (3) curve fitting toolbox. References 1. V. Anisimov, J. Zaanen, O. K. Andersen, “Band theory and Mott insulators: Hubbard U instead of Stoner I”, Physical Review B, vol. 44, pp. 943-954 (1991). 2. V. Anisimov, F. Aryasetiawan, A. I. Lichtenstein, “First-principles calculations of the electronic structure and spectra of strongly correlated systems: the LDA+U method”, Journal of Physics: Condensed Matter, vol. 9, pp. 767-808 (1997). 3. S. L. Dudarev, A. I. Lichtenstein, M. R. Castell, G. A. D. Briggs, A. P. Sutton, “Surface states on NiO (100) and the origin of the contrast reversal in atomically resolved scanning tunneling microscope images”, Physical Review B, vol. 56, pp. 4900-4908 (1997). 4. N. J. Mosey, P. Liao, E. A. Carter, “Rotationally invariant ab initio evaluation of Coulomb and exchange parameters for DFT+U calculations”, Journal of Chemical Physics, vol. 129, pp. 014103 (2008). 5. H. Jónsson, G. Mills, K. Jacobsen, “Nudged elastic band method for finding minimum energy paths of transitions” in Classical and Quantum Dynamics in Condensed Phase Simulations, pp. 385-404, World Scientific, 1998. 6. K. A. Marino and E. A. Carter, “The effect of platinum on diffusion kinetics is β-NiAl: Implications for thermal barrier coating lifetimes”, ChemPhysChem, vol. 10, pp. 226, (2009). 7. K. A. Marino and E. A. Carter, “First-principles characterization of Ni diffusion kinetics in β-NiAl”, Physical Review B, vol. 78, pp. 184105 (2008). 8. P. Huang and E. A. Carter, “Self-consistent embedding theory for locally correlated configuration interaction wave functions in condensed matter”, Journal of Chemical Physics, vol. 125, pp. 084102 (2006). 9. R. M. Shroll, and T. P. Straatsma, “Molecular Dynamics Simulations of the Goethite-Water Interface”, Molecular Simulation, 29, 1-11 (2003) 10. R. M. Shroll, and T. P. Straatsma, “Molecular Basis for Microbial Adhesion to Geochemical Surfaces: Computer Simulation of Pseudomonas aeruginosa Adhesion to Goethite”, Biophysical Journal, 84, 1765-1772 (2003). 11. T. P. Straatsma and J. A. McCammon, “Multiconfiguration thermodynamic integration”, J. Chem. Phys., 95, 1175-1188 (1991). 12. S. Sreekala and M. Haataja, “Recrystallization kinetics: A coupled coarse-grained dislocation density and phase-field approach”, Phys. Rev. B 76, 094109 (2007). 13. M. Haataja and F. Léonard, “Spinodal decomposition in the presence of mobile dislocations”, Phys. Rev. B 69, 081201 (R) (2004). 14. M. Haataja, J. Müller, A. D. Rutenberg, and M. Grant, “Dislocations and morphological instabilities: Continuum modeling of misfitting heteroepitaxial films”, Phys. Rev. B 65, 165414 (2002). 15. L. Oliker, A. Canning, J. Carter, C. Iancu, M. Lijewski, S. Kamil, J. Shalf, H. Shan, E. Strohmaier, S. Ethier, T. Goodale (2007) Scientific Application Performance on Candidate Petascale Platforms, International Parallel and Distributed Processing Symposium (IPDPS), March 24 – 30, 2007, Long Beach, CA. 16. A. S. Joshi, K. N. Grew, J. R. Izzo, Jr., A. A. Peracchio, and W. K. S. Chiu, “Lattice Boltzmann Modeling of Three-Dimensional, Multicomponent Mass Diffusion in a Solid Oxide Fuel Cell Anode,” ASME Journal of Fuel Cell Science and Technology, vol. 7, pp. 011006-1-011006-8 (2010). 17. A. S. Joshi, K. N. Grew, A. A. Peracchio and W. K. S. Chiu, “Lattice Boltzmann Modeling of 2D Gas Transport in a Solid Oxide Fuel Cell Anode,” Journal of Power Sources, vol. 164, pp. 631-638 (2007). 18. K. N. Grew, A. S. Joshi, A. A. Peracchio, and W. K. S. Chiu, “Pore-Scale Investigation of Mass Transport and Electrochemistry in a Solid Oxide Fuel Cell Anode,” Journal of Power Sources, vol. 195, pp. 2331–2345 (2010). 19. K. N. Grew, Y. S. Chu, J. Yi, A. A. Peracchio, J. R. Izzo, Jr., F. De Carlo, Y. Hwu and W. K. S. Chiu, “Nondestructive Nanoscale 3D Elemental Mapping and Analysis of a Solid Oxide Fuel Cell Anode,” Journal of the Electrochemical Society, vol. 157(5), (2010). 20. G. Kresse and J. Furthmüller, “Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set”, Computational Materials Science, vol. 6, pp. 15-50, 1996. 21. G. Kresse and J. Furthmüller, “Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set”, Physical Review B, vol. 54, pp. 11169-11186 (1996). 22. Peters, B., Heyden, A., Bell, A. T., Chakraborty, A., A growing string method for determining transition states: Comparison to the nudged elastic band and string methods. J. Chem. Phys. 120, 7877-7886 (2004). 23. Heyden, A., Bell, A. T., Keil, F. J., Efficient methods for finding transition states in chemical reactions: Comparison of modified dimer method and partitioned rational function optimization method. J. Chem. Phys. 123, 224101-14 (2005). Project URL: http://www.science.doe.gov/bes/EFRC/CENTERS/HeteroFoaM/efrc_HeteroFoaM.html Requested allocation: 400000 Justification: N/A The requester has used 0 hours of their initial startup project. In addition to approving an initial amount, please specify a Category and Subcategory for this project. For a list of the current selection of approved categories, please see: https://wiki.lcrc.anl.gov/wiki/Processes/Categories Once the Allocation committee has approved the project, please go to the Project Management page to create it: https://accounts.lcrc.anl.gov/projects.php Thank You, The LCRC Accounts System

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Re: [allocations-admins] [LCRC Accounts] Project Request: CAT-engine-modeling
by John Valdes 23 Feb '11

23 Feb '11

90K, Pri 3, same as foam-engineprocesses. On Wed, Feb 23, 2011 at 08:51:59AM -0600, accounts(a)lcrc.anl.gov wrote: > Hello, > > A new project on the LCRC cluster has been requested. Please forward > the information on to the LCRC Allocation sub-committee. > > Applicant's name: Shashi Aithal > Applicant's institution: ANL > Applicant's division: MCS > Project Name: CAT-engine-modeling > Project title: Detailed Engine modeling using CONVERGE > Associated funding: > Other Systems: CATERPILLAR Cluster > Science: The primary goal of this project is to study scaling issues using the commercial code CONVERGE with detailed chemistry. As a part of this exercise, complete 3-D simulation of a single cylinder diesel engine will be conducted. A series of chemistry models with increasing complexity (species and reactions) will be included. The objective is to find the optimum reaction mechanism and cores that will provide useful design information not obtained from 2-D and reduced chemistry models. > Project description: The commercial CFD code, CONVERGE will be used to conduct 3-D diesel engine simulations. Currently, CONVERGE has been run on FUSION on 24 cores. Good scaling has been seen up to 24 cores. The current study aims to increase the computational load using greater resolution, bigger chemistry mechanism and possibly more complicated geometries. Scaling of CONVERGE on a larger number of cores will be studied. It is expected that 3 ANL researchers along with 3 CAT engineers will be using these core hours. > Project URL: > Requested allocation: 90000 > Justification: > > > The requester has used 0 hours of their initial startup project. > > In addition to approving an initial amount, please specify a Category > and Subcategory for this project. For a list of the current selection > of approved categories, please see: > > https://wiki.lcrc.anl.gov/wiki/Processes/Categories > > Once the Allocation committee has approved the project, please go to > the Project Management page to create it: > > https://accounts.lcrc.anl.gov/projects.php > > Thank You, > The LCRC Accounts System > _______________________________________________ > allocations-admins mailing list > allocations-admins(a)lists.lcrc.anl.gov > https://lists.lcrc.anl.gov/mailman/listinfo/allocations-admins

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Re: [allocations-admins] [LCRC Accounts] Project Request: HPCC
by John Valdes 23 Feb '11

23 Feb '11

Grant 30K, Pri 3, P:Chem, Curtiss On Tue, Feb 15, 2011 at 10:23:40AM -0600, accounts(a)lcrc.anl.gov wrote: > Hello, > > A new project on the LCRC cluster has been requested. Please forward > the information on to the LCRC Allocation sub-committee. > > Applicant's name: Amit Sharma > Applicant's institution: ANL > Applicant's division: CSE > Project Name: HPCC > Project title: Ab-initio chemical kinetics study of high pressure combustion: A theoretical study of the radical-complex mechanism. > Associated funding: Department of Energy > Other Systems: A small cluster (named: Pople) in the CSE fundamental interaction theory group. > Science: Recent experimental studies of the falloff curve of the radical-radical association reaction show an unexpected additional rise of the rate constants at pressures above 300 bar in the 300 to 400 K temperature range. Contribution from the radical-complex (RC) mechanism, in addition to the usual energy-transfer (ET) mechanism, is believed to be the dominant factor for this phenomena. The radical-complex mechanism, which has not been theoretically studied and quantified, is the formation of the radical-bath gas (R-M) complex and the stabilization/complexation is related to the strength of the R-M bond in the van der Waals complexes. The decomposition of these R-M complex to stabilized reactants yields an increase in the net association rate. > > We propose to study the radical-complex mechanism using high level ab-initio kinetics approach and first principle electronic structure methods. The theoretical/computational approach involves development of a reduced dimensional, semi-global, potential energy surface (PES). This PES development is a novel approach due to high-dimensionality of the molecular system under study. For example, a simple oxidation reaction of CH3 with O2 in a monoatomic bath gas is a 15 dimensional system. The PES is developed by fitting high-level electronic structure energies for the radical-radical addition channel and R-M molecular system.The rate constant for the association reaction is calculated using variable reaction coordinate-transition state theory (VRC-TST) for different bath gas species. > Project description: > The computational methods used for the electronic structure calculations are available in codes like Molpro, Gaussian and similar quantum chemistry packages. The VRC-TST code is developed within our group. The size of calculations, typically, is about 40,000 to 50,000 electronic structure calculations for each system. The computational cost of each electronic calculation depend on the size of the basis set, electronic structure methods and other auxiliary routines. This can vary anywhere between 0.5 hours to couple of hours for a single electronic structure calculation, for the system we propose to study. There will be 3 to 4 people working on this project who will be using the computational resources. About 30-40% of the allocation will use non-parallel computations. > > This work is part of Combustion EFRC. Please see this web link for a brief overview. http://www.princeton.edu/cefrc/ > Project URL: > Requested allocation: 200000 > Justification: > > > The requester has used 0 hours of their initial startup project. > > In addition to approving an initial amount, please specify a Category > and Subcategory for this project. For a list of the current selection > of approved categories, please see: > > https://wiki.lcrc.anl.gov/wiki/Processes/Categories > > Once the Allocation committee has approved the project, please go to > the Project Management page to create it: > > https://accounts.lcrc.anl.gov/projects.php > > Thank You, > The LCRC Accounts System > _______________________________________________ > allocations-admins mailing list > allocations-admins(a)lists.lcrc.anl.gov > https://lists.lcrc.anl.gov/mailman/listinfo/allocations-admins

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Re: [allocations-admins] [LCRC Accounts] Project Allocation Request
by John Valdes 23 Feb '11

23 Feb '11

Advance 70K. On Tue, Feb 22, 2011 at 09:22:09AM -0600, accounts(a)lcrc.anl.gov wrote: > Hello, > > A change in allocation has been requested: > > Requester: roux (Benoit Roux) > Project: kcsa > Title: Computational study of ion selectivity in the KcsA channel > Description: Understanding quantitatively the microscopic factors controlling ion selectivity remains a great challenge. In simple terms, the concept of selectivity means that the "correct" ion, is able to binding more favorably than an "incorrect" ion. At a physical level, it is to be anticipated that energetics and solvation play a key role in this process, although different aspects of energetics may be highlighted by the various experimental methods used to probe the system. Some experimental measurements are more sensitive to the relative depth of free energy wells, while others are more sensitive to the relative height of free energy barriers. In the case of ion channels, the large hydration energy of the ions contrasts with the small free energy barriers necessary for the fast conduction observed experimentally. This implies that ion-protein association is ultimately controlled by a delicate balance of very strong interactions. Frequently, permeation involves th > e partial dehydration of an ion, followed by the binding to a proteinaceous environment. This archetype is well illustrated by the crystal structure of the KcsA channel. The pore of the KcsA channel comprises a wide aqueous vestibular entryway, lined by non-polar residues on the intracellular side, leading up on the extracellular side to a narrow region lined by backbone carbonyl oxygens. This region of the pore, formed by the residues corresponding to the signature sequence TTVGYG common to all K+ channels, acts as a "selectivity filter" by allowing only the passage of nearly dehydrated K+ ions across the cell membrane. In such narrow molecular pores, a permeating ion must shed most of its surrounding water molecules and the large energetic loss due to dehydration must be compensated by coordination with the backbone carbonyl oxygens. > > The most informative strategy to address such issues is to compute the multi-ion PMF corresponding to the microscopic process in question (Berneche and Roux, Nature 2001). In particular, the calculation of the PMF enables us to pin-point the location of the largest barrier opposing the passage of a single Na+ ion while there are two K+ ions elsewhere in the pore. We carry those type of calculations using umbrella sampling MD simulations. Another strategy is free energy perturbation (FEP), which allows to compute the relative free energy of different ions at precise location in the pore. > > There are 2 sub-projects: > > 1) Compute the multi-ion PM for Na+ permeation through the KcsA channel using the open state structure that was recently determined by X-ray crystallography in the Perozo laboratory. We have already done a similar calculation for the KcsA in the closed state (Egwolf and Roux, JMB 2010). Umbrella sampling MD simulations are used to obtain W(z1,z2,z3) the 3-ion PMF function of the coordinate of the 3 ions in the selectivity filter. To understand the effect of selectivity, two systems must be considered: with 3 K+ ions, and with 1 Na+ and 2 K+ ions. Based on our experience with similar computations, we know that a grand total of 3931 MD window simulations is needed for two systems. Each window should be simulated for 0.6 ns, the first 0.1 ns being used for equilibration and the last 0.5 ns for sampling proper, for total aggregate MD simulation time of 2.4 microseconds for each of the two systems. The unbiased 3D PMFs are then calculated using the weighted histogram method ( > WHAM). The simulations are generated with NAMD, which is the most efficient program for classical MD. > > 2) Use FEP to compute the relative free energy of Na+ and K+ in a KcsA pore with DFT/MM simulations. For this computation we are using CHARMM combined with the DFT program DEMON (developed by Denys Salahub in Calgary). This enables us to treat the ions and the nearby protein atoms with DFT and the remainder with the force field of molecular dynamics. > > Software requirements > > NAMD, CHARMM, DEMON > > > Expected number of project members: > > Benoit Roux, David Medovoy (multi-ion PMF calculation) and Chris Rowley (selectivity with density function theory and MD force field) > > REFERENCES > > Noskov, SY; Berneche, S; Roux, B > Control of ion selectivity in potassium channels by electrostatic and dynamic properties of carbonyl ligands. NATURE Volume: 431 Issue: 7010 Pages: 830-834 Published: OCT 14 2004 > > Egwolf, B; Roux, B > Ion Selectivity of the KcsA Channel: A Perspective from Multi-Ion Free Energy Landscapes. JOURNAL OF MOLECULAR BIOLOGY Volume: 401 Issue: 5 Pages: 831-842 Published: 2010 > > > > > > Current: undetermined amount > Justification: The umbrella sampling calculations described here constitute a major part of the PhD thesis of David Medovoy, a graduate student in Biophysics at the University of Chicago. The total requested allocation for this project is: 500,000 SU = (3931 windows) * (0.6 ns/window) * ((8*cores)*(12 hour)/ns). > > The planned FEP simulations for with DFT/MM will be carried out by Chris Rowley, a postdoc in the lab who has a fellowship from the Canadian NSERC. His work will be a new attack on the problem. Never before has someone computed relative free energies in those channels with DFT/MM. We anticipate this those FEP calculations will require about 500,000 SUs during the year. Demon scales up to about 64 processors, but we are investigating the dependencies on grid density (in DFT) to see how it affects the performance. > > > > > > Requested: 450000 > > A specific reason has been given: > Our current allocation is -2344. Fusion is currently the best platform for the ab initio calculations needed for this project. > > This needs to be approved and the final allocation amount decided upon. > > Thank You, > The LCRC Accounts System > _______________________________________________ > allocations-admins mailing list > allocations-admins(a)lists.lcrc.anl.gov > https://lists.lcrc.anl.gov/mailman/listinfo/allocations-admins

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Re: [allocations-admins] [LCRC Accounts] Project Allocation Request
by John Valdes 23 Feb '11

23 Feb '11

Advance 150K. On Tue, Feb 22, 2011 at 09:23:14AM -0600, accounts(a)lcrc.anl.gov wrote: > Hello, > > A change in allocation has been requested: > > Requester: roux (Benoit Roux) > Project: Drude > Title: Development and validation of new polarizable force field for molecular dynamics > Description: At the present time, MD simulations are not only limited by the computational resources but also by the physical correctness and accuracy of the underlying atomic models. Without a systematic approach to generate, test and validate the accuracy of the force fields, the value of MD simulations will always remain in question. The development of potential functions for computer simulations has a long history and is still a very active field. Essentially all of the MD simulations of complex molecular systems (biological or not) are currently carried out using fixed-charge non-polarizable force fields, even though there is a broad consensus that electronic polarization effect ought to be included. The important role of polarization is particularly obvious for self-assembling amphiphilic molecules, containing polar or charged groups as well as nonpolar moieties (see below). A number of research groups are working at developing new algorithm to treat polarization, eit > her with inducible point dipoles, fluctuating charges, or classical Drude oscillators. The latter approach, which we have adopted, is the most advantageous due to its simplicity and computational efficiency. > > The goal is to develop, optimize, and validate the functional form and parameters of a new force field accounting for induced polarization in molecular dynamics simulations. We are particularly interested in ion solvation properties. > > > # computational methods > > The computational method involves ab initio quantum mechanics, as well as classical molecular dynamics simulations and free energy perturbation. The induced polarization is represented by introducing a small auxiliary charged particle attached to the nucleus by a spring. The pair forms a Drude oscillator. It can be shown that this construction accounts properly for the physics of induced polarization in molecular interactions. > > > # scalability issues > > The new force field is developed to be implementable in a wide range of existing molecular dynamics codes. Currently, the model is supported by CHARMM, which has modest scalability. Our initial implementation of the methods in NAMD has allowed to run some benchmark systems with 75,000 water molecules with the polarizable force field. These NAMD simulatinos scale up to 1,000 cores without problems. > > > # experiments planned > > We are also developing ion solvation models in water, liquid N-methylacetamide, and liquid ethanol. Those are needed to model biomolecular systems. The work will comprise > > - divalent ions solvation in N-methylacetamide > - CPMD run of K+ in ethanol > - CPMD run of Na+ in ethanol > - high level ab initio on small clusters > - free energy perturbation MD of K+ in ethanol > - free energy perturbation MD of Na+ in ethanol > - osmotic pressure MD for NaCl and KCl > - conductivity of KCl and NaCl > > > > # software requirements > > We use Gaussian, Qchem, CPMD, CHARMM, and NAMD. > > # sizes of calculations run on and/or planned for Fusion or other systems > > On single MD runs, we expect to use up to 256 or 512 cores in parallel. The CPMD does not scale as well (perhaps up to 64). The FEP simulations are trivially distributed (thermodynamic integration). The osmotic pressure and the conductivity require several MD at increasingly high ionic concentrations with large systems. > > > # expected number of project members: > > The number of members is expected to be 5-6, including Benoit Roux, Karen Callahan (ions in ethanol), Yun Luo (osmotic pressure), Chris Rowley (divalent ions), from the University of Chicago. > > > REFERENCES > > Yu, H; Mazzanti, CL; Whitfield, TW, et al. > A Combined Experimental and Theoretical Study of Ion Solvation in Liquid N-Methylacetamide. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY Volume: 132 Issue: 31 Pages: 10847-10856 Published: 2010 > > Baker, CM; Lopes, PEM; Zhu, X, et al. > Accurate Calculation of Hydration Free Energies using Pair-Specific Lennard-Jones Parameters in the CHARMM Drude Polarizable Force Field. JOURNAL OF CHEMICAL THEORY AND COMPUTATION Volume: 6 Issue: 4 Pages: 1181-1198 Published: 2010 > > Yu, HB; Whitfield, TW; Harder, E, et al. > Simulating Monovalent and Divalent Ions in Aqueous Solution Using a Drude Polarizable Force Field. JOURNAL OF CHEMICAL THEORY AND COMPUTATION Volume: 6 Issue: 3 Pages: 774-786 Published: 2010 > > > Harder, E; MacKerell, AD; Roux, B > Many-Body Polarization Effects and the Membrane Dipole Potential. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY Volume: 131 Issue: 8 Pages: 2760-+ Published: 2009 > > > Harder, E; Anisimov, VM; Whitfield, TW, et al. > Understanding the dielectric properties of liquid amides from a polarizable force field. JOURNAL OF PHYSICAL CHEMISTRY B Volume: 112 Issue: 11 Pages: 3509-3521 Published: 2008 > > > Whitfield, TW; Varma, S; Harder, E, et al. > Theoretical study of aqueous solvation of K+ comparing ab initio, polarizable, and fixed-charge models. JOURNAL OF CHEMICAL THEORY AND COMPUTATION Volume: 3 Issue: 6 Pages: 2068-2082 Published: 2007 > > > Current: undetermined amount > Justification: We have an excellent track record of publication in this field, and we will make good use of the allocated time. The project involves a variety of different computations (MD, ab initio, CPMD), which are all very important to develop good models. We could easily ask for more resource, and we will definitely utilize all the allocation requested. > > Requested: 450000 > > A specific reason has been given: > This allocation is currently negative. Can we reset this to 450,000 to allow us to pursue the work on the drude force field? > > This needs to be approved and the final allocation amount decided upon. > > Thank You, > The LCRC Accounts System > _______________________________________________ > allocations-admins mailing list > allocations-admins(a)lists.lcrc.anl.gov > https://lists.lcrc.anl.gov/mailman/listinfo/allocations-admins

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[LCRC Accounts] Project Request: CAT-engine-modeling
by accounts＠lcrc.anl.gov 23 Feb '11

23 Feb '11

Hello, A new project on the LCRC cluster has been requested. Please forward the information on to the LCRC Allocation sub-committee. Applicant's name: Shashi Aithal Applicant's institution: ANL Applicant's division: MCS Project Name: CAT-engine-modeling Project title: Detailed Engine modeling using CONVERGE Associated funding: Other Systems: CATERPILLAR Cluster Science: The primary goal of this project is to study scaling issues using the commercial code CONVERGE with detailed chemistry. As a part of this exercise, complete 3-D simulation of a single cylinder diesel engine will be conducted. A series of chemistry models with increasing complexity (species and reactions) will be included. The objective is to find the optimum reaction mechanism and cores that will provide useful design information not obtained from 2-D and reduced chemistry models. Project description: The commercial CFD code, CONVERGE will be used to conduct 3-D diesel engine simulations. Currently, CONVERGE has been run on FUSION on 24 cores. Good scaling has been seen up to 24 cores. The current study aims to increase the computational load using greater resolution, bigger chemistry mechanism and possibly more complicated geometries. Scaling of CONVERGE on a larger number of cores will be studied. It is expected that 3 ANL researchers along with 3 CAT engineers will be using these core hours. Project URL: Requested allocation: 90000 Justification: The requester has used 0 hours of their initial startup project. In addition to approving an initial amount, please specify a Category and Subcategory for this project. For a list of the current selection of approved categories, please see: https://wiki.lcrc.anl.gov/wiki/Processes/Categories Once the Allocation committee has approved the project, please go to the Project Management page to create it: https://accounts.lcrc.anl.gov/projects.php Thank You, The LCRC Accounts System

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[LCRC Accounts] Project Allocation Request
by accounts＠lcrc.anl.gov 22 Feb '11

22 Feb '11

Hello, A change in allocation has been requested: Requester: roux (Benoit Roux) Project: Drude Title: Development and validation of new polarizable force field for molecular dynamics Description: At the present time, MD simulations are not only limited by the computational resources but also by the physical correctness and accuracy of the underlying atomic models. Without a systematic approach to generate, test and validate the accuracy of the force fields, the value of MD simulations will always remain in question. The development of potential functions for computer simulations has a long history and is still a very active field. Essentially all of the MD simulations of complex molecular systems (biological or not) are currently carried out using fixed-charge non-polarizable force fields, even though there is a broad consensus that electronic polarization effect ought to be included. The important role of polarization is particularly obvious for self-assembling amphiphilic molecules, containing polar or charged groups as well as nonpolar moieties (see below). A number of research groups are working at developing new algorithm to treat polarization, eit her with inducible point dipoles, fluctuating charges, or classical Drude oscillators. The latter approach, which we have adopted, is the most advantageous due to its simplicity and computational efficiency. The goal is to develop, optimize, and validate the functional form and parameters of a new force field accounting for induced polarization in molecular dynamics simulations. We are particularly interested in ion solvation properties. # computational methods The computational method involves ab initio quantum mechanics, as well as classical molecular dynamics simulations and free energy perturbation. The induced polarization is represented by introducing a small auxiliary charged particle attached to the nucleus by a spring. The pair forms a Drude oscillator. It can be shown that this construction accounts properly for the physics of induced polarization in molecular interactions. # scalability issues The new force field is developed to be implementable in a wide range of existing molecular dynamics codes. Currently, the model is supported by CHARMM, which has modest scalability. Our initial implementation of the methods in NAMD has allowed to run some benchmark systems with 75,000 water molecules with the polarizable force field. These NAMD simulatinos scale up to 1,000 cores without problems. # experiments planned We are also developing ion solvation models in water, liquid N-methylacetamide, and liquid ethanol. Those are needed to model biomolecular systems. The work will comprise - divalent ions solvation in N-methylacetamide - CPMD run of K+ in ethanol - CPMD run of Na+ in ethanol - high level ab initio on small clusters - free energy perturbation MD of K+ in ethanol - free energy perturbation MD of Na+ in ethanol - osmotic pressure MD for NaCl and KCl - conductivity of KCl and NaCl # software requirements We use Gaussian, Qchem, CPMD, CHARMM, and NAMD. # sizes of calculations run on and/or planned for Fusion or other systems On single MD runs, we expect to use up to 256 or 512 cores in parallel. The CPMD does not scale as well (perhaps up to 64). The FEP simulations are trivially distributed (thermodynamic integration). The osmotic pressure and the conductivity require several MD at increasingly high ionic concentrations with large systems. # expected number of project members: The number of members is expected to be 5-6, including Benoit Roux, Karen Callahan (ions in ethanol), Yun Luo (osmotic pressure), Chris Rowley (divalent ions), from the University of Chicago. REFERENCES Yu, H; Mazzanti, CL; Whitfield, TW, et al. A Combined Experimental and Theoretical Study of Ion Solvation in Liquid N-Methylacetamide. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY Volume: 132 Issue: 31 Pages: 10847-10856 Published: 2010 Baker, CM; Lopes, PEM; Zhu, X, et al. Accurate Calculation of Hydration Free Energies using Pair-Specific Lennard-Jones Parameters in the CHARMM Drude Polarizable Force Field. JOURNAL OF CHEMICAL THEORY AND COMPUTATION Volume: 6 Issue: 4 Pages: 1181-1198 Published: 2010 Yu, HB; Whitfield, TW; Harder, E, et al. Simulating Monovalent and Divalent Ions in Aqueous Solution Using a Drude Polarizable Force Field. JOURNAL OF CHEMICAL THEORY AND COMPUTATION Volume: 6 Issue: 3 Pages: 774-786 Published: 2010 Harder, E; MacKerell, AD; Roux, B Many-Body Polarization Effects and the Membrane Dipole Potential. JOURNAL OF THE AMERICAN CHEMICAL SOCIETY Volume: 131 Issue: 8 Pages: 2760-+ Published: 2009 Harder, E; Anisimov, VM; Whitfield, TW, et al. Understanding the dielectric properties of liquid amides from a polarizable force field. JOURNAL OF PHYSICAL CHEMISTRY B Volume: 112 Issue: 11 Pages: 3509-3521 Published: 2008 Whitfield, TW; Varma, S; Harder, E, et al. Theoretical study of aqueous solvation of K+ comparing ab initio, polarizable, and fixed-charge models. JOURNAL OF CHEMICAL THEORY AND COMPUTATION Volume: 3 Issue: 6 Pages: 2068-2082 Published: 2007 Current: undetermined amount Justification: We have an excellent track record of publication in this field, and we will make good use of the allocated time. The project involves a variety of different computations (MD, ab initio, CPMD), which are all very important to develop good models. We could easily ask for more resource, and we will definitely utilize all the allocation requested. Requested: 450000 A specific reason has been given: This allocation is currently negative. Can we reset this to 450,000 to allow us to pursue the work on the drude force field? This needs to be approved and the final allocation amount decided upon. Thank You, The LCRC Accounts System

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[LCRC Accounts] Project Allocation Request
by accounts＠lcrc.anl.gov 22 Feb '11

22 Feb '11

Hello, A change in allocation has been requested: Requester: roux (Benoit Roux) Project: kcsa Title: Computational study of ion selectivity in the KcsA channel Description: Understanding quantitatively the microscopic factors controlling ion selectivity remains a great challenge. In simple terms, the concept of selectivity means that the "correct" ion, is able to binding more favorably than an "incorrect" ion. At a physical level, it is to be anticipated that energetics and solvation play a key role in this process, although different aspects of energetics may be highlighted by the various experimental methods used to probe the system. Some experimental measurements are more sensitive to the relative depth of free energy wells, while others are more sensitive to the relative height of free energy barriers. In the case of ion channels, the large hydration energy of the ions contrasts with the small free energy barriers necessary for the fast conduction observed experimentally. This implies that ion-protein association is ultimately controlled by a delicate balance of very strong interactions. Frequently, permeation involves th e partial dehydration of an ion, followed by the binding to a proteinaceous environment. This archetype is well illustrated by the crystal structure of the KcsA channel. The pore of the KcsA channel comprises a wide aqueous vestibular entryway, lined by non-polar residues on the intracellular side, leading up on the extracellular side to a narrow region lined by backbone carbonyl oxygens. This region of the pore, formed by the residues corresponding to the signature sequence TTVGYG common to all K+ channels, acts as a "selectivity filter" by allowing only the passage of nearly dehydrated K+ ions across the cell membrane. In such narrow molecular pores, a permeating ion must shed most of its surrounding water molecules and the large energetic loss due to dehydration must be compensated by coordination with the backbone carbonyl oxygens. The most informative strategy to address such issues is to compute the multi-ion PMF corresponding to the microscopic process in question (Berneche and Roux, Nature 2001). In particular, the calculation of the PMF enables us to pin-point the location of the largest barrier opposing the passage of a single Na+ ion while there are two K+ ions elsewhere in the pore. We carry those type of calculations using umbrella sampling MD simulations. Another strategy is free energy perturbation (FEP), which allows to compute the relative free energy of different ions at precise location in the pore. There are 2 sub-projects: 1) Compute the multi-ion PM for Na+ permeation through the KcsA channel using the open state structure that was recently determined by X-ray crystallography in the Perozo laboratory. We have already done a similar calculation for the KcsA in the closed state (Egwolf and Roux, JMB 2010). Umbrella sampling MD simulations are used to obtain W(z1,z2,z3) the 3-ion PMF function of the coordinate of the 3 ions in the selectivity filter. To understand the effect of selectivity, two systems must be considered: with 3 K+ ions, and with 1 Na+ and 2 K+ ions. Based on our experience with similar computations, we know that a grand total of 3931 MD window simulations is needed for two systems. Each window should be simulated for 0.6 ns, the first 0.1 ns being used for equilibration and the last 0.5 ns for sampling proper, for total aggregate MD simulation time of 2.4 microseconds for each of the two systems. The unbiased 3D PMFs are then calculated using the weighted histogram method ( WHAM). The simulations are generated with NAMD, which is the most efficient program for classical MD. 2) Use FEP to compute the relative free energy of Na+ and K+ in a KcsA pore with DFT/MM simulations. For this computation we are using CHARMM combined with the DFT program DEMON (developed by Denys Salahub in Calgary). This enables us to treat the ions and the nearby protein atoms with DFT and the remainder with the force field of molecular dynamics. Software requirements NAMD, CHARMM, DEMON Expected number of project members: Benoit Roux, David Medovoy (multi-ion PMF calculation) and Chris Rowley (selectivity with density function theory and MD force field) REFERENCES Noskov, SY; Berneche, S; Roux, B Control of ion selectivity in potassium channels by electrostatic and dynamic properties of carbonyl ligands. NATURE Volume: 431 Issue: 7010 Pages: 830-834 Published: OCT 14 2004 Egwolf, B; Roux, B Ion Selectivity of the KcsA Channel: A Perspective from Multi-Ion Free Energy Landscapes. JOURNAL OF MOLECULAR BIOLOGY Volume: 401 Issue: 5 Pages: 831-842 Published: 2010 Current: undetermined amount Justification: The umbrella sampling calculations described here constitute a major part of the PhD thesis of David Medovoy, a graduate student in Biophysics at the University of Chicago. The total requested allocation for this project is: 500,000 SU = (3931 windows) * (0.6 ns/window) * ((8*cores)*(12 hour)/ns). The planned FEP simulations for with DFT/MM will be carried out by Chris Rowley, a postdoc in the lab who has a fellowship from the Canadian NSERC. His work will be a new attack on the problem. Never before has someone computed relative free energies in those channels with DFT/MM. We anticipate this those FEP calculations will require about 500,000 SUs during the year. Demon scales up to about 64 processors, but we are investigating the dependencies on grid density (in DFT) to see how it affects the performance. Requested: 450000 A specific reason has been given: Our current allocation is -2344. Fusion is currently the best platform for the ab initio calculations needed for this project. This needs to be approved and the final allocation amount decided upon. Thank You, The LCRC Accounts System

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