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[LCRC Accounts] Project Request: NEAMS_2018
by accounts＠lcrc.anl.gov 07 Sep '17

07 Sep '17

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: Chang-ho Lee Applicant's institution: ANL Applicant's division: NE Project Name: NEAMS_2018 Project title: Verification and Validation of NEAMS Neutronics Code Associated funding: DOE NEAMS Program Other Systems: NE Linux clusters, ALCF Science: The objective of the project funded by the DOE NEAMS program is to develop a high-fidelity neutronics code system (with capabilities required for reactor simulation) and verify and validate it using various nuclear reactor benchmark problems and experiments. Project description: The goal of the NEAMS neutronics project is to develop a high-fidelity neutronics toolkit for use in various nuclear reactor design and analysis. The neutronics code PROTEUS includes multiple neutron transport solver options including SN (discrete ordinate) and MOC (method of characteristics) based on finite-element unstructured meshes so that the code is able to model any geometry types. Recently, the transient calculation capability was implemented to PROTEUS, requiring verification and validation tests using benchmark problems and experiments. As an initial V&V effort, we are and will be simulating transient cases for the C5G7 OECD transient benchmark problem as well as the TREAT transient cases. For the C5G7 benchmark problem developed based on pressurized water reactor (PWR) geometry and material, 472,449 meshes per plane, 10 planes, 96 angles and 7 energy groups were specified which makes total 0.45 billion unknowns per group. A one-timestep transient calculation for 3D C5G7 takes 0.5 hr with 100 cores (50 core-hours). The whole transient calculation for C5G7 normally needs at least 500 time steps with 10 ms timestep (5 sec). Accordingly, about 500 hrs are required to complete 500 timesteps of transient calculations (25,000 core-hours). We may need several transient calculations for C5G7 during this fiscal year. For TREAT which is an air-cooled, graphite-moderated thermal reactor and for which transient experiments were made until 1994, a 3D core model requires 352,536 elements per plane, 24 planes, 320 angles and 11 energy groups, producing 2.7 billion unknowns per group. PROTEUS takes about 2 hours using 640 cores (1920 core-hours). Assuming that a calculation time for a one-timestep transient problem takes one-tenth of that for an eigenvalue problem, the whole transient calculation with 500 time steps is estimated to take ~100 hrs with 640 cores (64,000 core-hours). We will need a couple of transient calculations for this core. We have an allocation on ALCF that will be necessary for simulations of very large cases, but the benchmark problems, C5G7 and TREAT, that we are trying to run with PROTEUS are intermediate size, which are too large for local cluster, too small for Mira, but perfect size for LCRC machines. We may use more than 100,000 core-hours at the first half of FY18 and less later on, and we may add more test cases for the code V&V. Industry partnership: n/a Project URL: Requested allocation: 4000000 Q1: 1000000 Q2: 1000000 Q3: 1000000 Q4: 1000000 Justification: n/a Storage requirements: 1TB The requester has used undetermined amount 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] Yearly Allocation Request for qmc_for_nuclei
by accounts＠lcrc.anl.gov 07 Sep '17

07 Sep '17

Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Robert Wiringa Project Name: qmc_for_nuclei Division: PHY Project title: Quantum Monte Carlo Calculations of Light Nuclei Associated funding: DOE Office of Nuclear Physics Other Systems: ANL Blue Gene/Q (INCITE 57M hours for 12C studies) ANL Theta (ALCC 35M hours for chiral nuclear spectra) Science: This project uses Quantum Monte Carlo [Green's function (GFMC), variational (VMC), cluster VMC, and auxiliary-field diffusion (AFDMC)] methods to compute ground-state and low-lying excited-state expectation values of energies, densities, electroweak transitions and response, spectroscopic overlaps, etc., for light- and medium-mass nuclei and low-energy scattering reactions involving these nuclei. Realistic two- and three-nucleon potentials and one- and two-body electroweak charge and current operators are used. Our goal is a description of all of these systems using a Hamiltonian that also provides an excellent description of nucleon-nucleon scattering and nucleonic matter. Such a `standard nuclear model' can then be used, for example, to compute low-energy astrophysical reactions which cannot be experimentally measured. We are also actively engaged in making predictions that can and are being tested at experimental facilities such as ATLAS, NSCL, TRIUMF, and JL ab. Project description: A) Nuclear Structure with chiral effective field theory We have developed new nuclear Hamiltonians, including two- and three-nucleon (NN+3N) potentials, based on chiral effective field theory (XEFT) including Delta-isobar degrees of freedom and formulated in configuration space, in the last few years. XEFT potentials have become a popular way to formulate nuclear forces, but up to now they were only in momentum space, and not amenable to our very accurate quantum Monte Carlo methods which require predominantly local interactions. We have recently calculated in GFMC (VMC) more than 35 (100) nuclear ground and excited states up to A=12 for one of the new models, using both Blues and Theta. We have three more models to evaluate, and these will require a search to fit the 3N potential parameters to get the best reproduction of nuclear spectra. We also will be investigating higher-order 3N potentials. Larger nuclei will be computed on Theta, but Bebop will be more efficient for the lighter (A<10) nuclei. We request 300,000 cpu ho urs in FY18 for this purpose. B) A=11,12 nuclei Extensive effort has gone into GFMC calculations of 0+ states in 12C using Mira, but only a few exploratory calculations of other A>10 nuclei have been made. We have recently made progress on trial functions for 11B and 12Be, particularly with the help of optimization routines for the VMC input wave functions. However other cases like 11Be and 12B remain to be studied, particularly with wave functions that are "clusterized." The VMC codes for these trial functions are running well using a mix of OpenMP inside nodes and MPI between nodes, but some steps in the calculation can only use about 12-16 MPI ranks (with 8-16 OMP threads) efficiently. These steps are best performed on Bebop (rather than Theta). We will be using both our standard AV18+IL7 Hamiltonian and the newer chiral Hamiltonians mentioned above. We would like 300,000 cpu hours for this work in FY18. C) Weak decays of light nuclei We are studying the weak decays of light nuclei, including 3H, 6He, (7,8,9)Li, 7Be, 8B, and (9,10,11)C. A paper on 'easy' allowed and superallowed Fermi and Gamow-Teller transitions is being completed, but more difficult transitions remain to be evaluated. The calculations include both one- and two-body current operators consistent with our standard AV18+IL7 Hamiltonian. However we also need to investigate the new XEFT potentials. This work is relevant to ongoing experiments at ATLAS and at U. of Washington. We are also making model studies of neutrinoless double beta decay, a top priority as the next major DOE Nuclear Physics construction project, in (8,10)He and 12Be. We would like 200,000 cpu hours for this work in FY18. D) Neutron matter The auxiliary field diffusion Monte Carlo (AFDMC) method is a more efficient algorithm for dealing with larger nuclear systems compared to the GFMC. We will calculate the equation of state (EoS) of neutron matter by using AFDMC for the new XEFT interactions. The EoS of neutron matter is the key ingredient for predicting the structure and other properties of neutron stars. By performing calculations with different cutoffs regulating the short-range part of the interactions, we will give an estimate of theoretical uncertainties in the EoS as a function of the density. We request 200,000 cpu hours in FY18 for this work. Industry partnership: The URL window might not accept our project website, so I am listing it here: www.phy.anl.gov/theory www.phy.anl.gov/theory/research/av18/ www.phy.anl.gov/theory/research/QMCresults.html Project URL: http://www.phy.anl.gov/theory/research/QMCresults.html Current FY Hours Used: undetermined amount New FY Requested allocation: 1000000 Q1: 250000 Q2: 250000 Q3: 250000 Q4: 250000 Justification: Our QMC programs scale very well both with increasing number of OpenMP threads and MPI ranks. For example a GFMC job run on Bebop used 100 Broadwell nodes, each with 2 MPI ranks. Each rank used 16 OpenMP threads and 1 Pthead for memory management. The job ran for 110 minutes. The MPI efficiency (which we always measure by separately timing computational loops and communication calls) was 93.6%. This means that, on average, each rank spent 93.6% of its wall time doing calculations. An OpenMP scaling study of the wave function subroutines on a Broadwell node using avx2 used 1635, 908, 501, and 342 milliseconds for 2, 4, 9, and 18 threads. A KNL node used 1979 and 1210 milliseconds for 8 and 16 threads. Based on these results the above large run would now be made using 4 ranks/node with 8 threads each. We do not benefit much from the vector instructions. Using avx512 on the KNL nodes increased the subroutine speed by less than 2% compared to avx2. We find the KNL nodes to be much less efficient than the Broadwell ones. For example, using 4 ranks/node with 9 threads/rank on Broadwell or 16 threads/rank on KNL gives 40% less throughput on the KNL nodes. Storage requirements: no additional space required Thank You, The LCRC Accounts System

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New LCRC report submitted for chemexp
by support＠lcrc.anl.gov 07 Sep '17

07 Sep '17

Full project report at https://accounts.lcrc.anl.gov/reporting/project/2017/?project=chemexp

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[LCRC Accounts] Project Request: spectra_mine
by accounts＠lcrc.anl.gov 07 Sep '17

07 Sep '17

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: David Bross Applicant's institution: ANL Applicant's division: CSE Project Name: spectra_mine Project title: Data mining physical chemistry literature for spectroscopic constants Associated funding: DoE BES Other Systems: My group is currently operating two computer linux clusters and have access to a third. The oldest cluster consists of 30 dual-CPU, 4-core 64-bit AMD Opteron nodes and 12 dual-CPU, 6-core 64-bit AMD Opteron nodes. These nodes have either 32GB or 64GB RAM per node and local disk capacity between 500GB and 1.2TB per node. The newer cluster consists of 11 dual-CPU 10-core Intel (Xeon E5-2680 v.2) nodes, 5 quartic-CPU 8-core AMD (Opteron 6278) nodes, 5 dual-CPU 8-core Intel (Xeon E5-2680 v. 1) nodes, 3 dual-CPU 6-core Intel (Xeon X5690) nodes, 8 quartic-CPU 12-core AMD (Opteron 6180 SE) nodes, and 16 single-CPU 12-core AMD (Opteron 6174) nodes. The memory for these nodes ranges between 66 and 396 GB RAM per node and the local disk capacity ranges from 1 to 1.6 TB per node. The communications for all of these nodes is 1 Gb/s ethernet. In addition to the two clusters we operate in house, we recently acquired 30 new nodes which have been installed on the Bl ues cluster in the Laboratory Computing Resource Center. These consist of 15 dual-CPU 16-core Intel (Xeon E5-2698 v.3) nodes and 15 dual-CPU 6-core Intel (Xeon E5-2620 v.3) nodes. Each node has 132 GB RAM and local 2 TB hard drive. Infiniband interconnect is used for communication. Science: There is an extensive body of physical chemistry literature containing extensive information that has intricate interdependencies on the physical constants, the definition of units, the physical model used to interpret it, and the assumptions that underlie the physical model. This makes the task of mining the literature extremely complicated, especially since the physical model and its underlying assumptions frequently generates a series of sequential dependences that traces back through other published works and usually this information is not readily available. Ideally the information should be stored as close to the actually measured or determined values as possible, enabling assumptions to depend on the rest of the available dataset at time of processing, rather than at time of input, and this will involve expanding the database efforts into virtually all physical chemistry disciplines (e.g. creating a database including kinetics and spectroscopi c data rather than the equilibrium constants and partition functions that depend on those spectroscopic constants). Natural Language Processing and machine learning classification techniques show promise as an approach to utilizing the available literature, and I will use these as an avenue of mining the extant literature. We initially begin this by attempting to mine the existing literature for spectroscopic constants. Project description: The project will use the python chemdataextractor package, primarily intending to use parallelism through the mpi4py implantation of Alvaro Vazquez from the Argonne Leadership Computing Facility. The task is primarily embarrassingly parallel, as each article must be mined before it can be used in a broader sense, and the project will probably involve modifications of the algorithms used to mine the articles and produce desired outputs. The LCRC allocation will be used to run initial test applications that can be developed later into a larger program that may have larger computing requirements. Industry partnership: Project URL: Requested allocation: 105000 Q1: 0 Q2: 35000 Q3: 35000 Q4: 35000 Justification: Storage requirements: The requester has used undetermined amount 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] Yearly Allocation Request for uo2_md
by accounts＠lcrc.anl.gov 07 Sep '17

07 Sep '17

Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: John Russell Project Name: uo2_md Division: MSD Project title: Thermal conductivity of uranium oxide with embedded carbon nanotubes Associated funding: Other Systems: Science: Heat dissipation is an important factor in safely using and storing nuclear fuels. Uranium oxide has a low thermal conductivity which can allow temperatures to rise quickly. One strategy to improve heat flow in uranium oxide is to embed carbon nanomaterials in the oxide. We investigate by molecular dynamics the phonon thermal conductivity of uranium dioxide with embedded carbon nanotubes. In initial calculations, we find a three fold increase in thermal conductivity of a 50 nm uranium oxide model system with an embedded (10,0) CNT. Real values will likely be higher since phonon confinement effects in the relatively small model system result in systematically lower values. Project description: Uranium and uranium oxide spent fuels are stored in water to safely maintain temperatures well below the melting point. Power disruptions from a tsunami interupted cooling of fuel rods at the Fukushima Daichi power plant resulting in a meltdown [1, 2]. Increasing thermal conductivity of fuels will result in a faster cooling rate, which could improve safety. Embedded carbon nanotubes (CNTs) or nanofibers might be a strategy to improve thermal conductivity in bulk UO2. CNTs have large surface areas, high mechanical strength, chemical stability, and thermal conductivity which makes them an intriguing candidate for design of a hybrid material. The goal of this project is calculate structural and thermodynamic properties of UO2 and hybrid materials where experimental values may be unavailable. Our initial approach will be to use a partially ionic model (PIM) of the Born-Mayer-Huggins (BMH) potential to model the UO2 material [3, 4]. The PIM features a reduced ionicity with less than full ionic charge on U and O atoms, and it matches the UO2 lattice constant at temperatures over 1000K, which a full ionic model gets wrong. Likewise, electrostatics will be calculated with a linear-scaling Wolf summation. For coupling terms, C-C interactions will be handled by means of a Tersoff potential [5], and the remaining U-O and U-C interactions will be handled with Morse potentials fit to density functional theory (DFT) reference calculations. With respect to thermodynamic proprerties, we will calculate the thermal conductivity by means of the Muller-Plathe [6] method and the Green-Kubo method. In this way, our approach will capture the salient features of the problem, including ionicity of the UO2 and covalency of the CNTs. Our model systems will include free particles, surfaces and nanocrystalline materials. To calculate properties of our model system, we will conduct molecular dynamics simulations using LAMMPS and DFT calculations will be using CP2K and/or VASP. This modeling approach is well suited for large systems due to the favorable scaling of the potentials and software. LAMMPS is massively parallel with nearly linear scaling with system size which can allow for 100k+ atom models for tens of nanoseconds [7]. CP2K is an electronic structure package with good efficiency for serial and parallel systems and excellent accuracy. [8,9] Depending on the size of the model system, it may make more sense to use VASP with a larger number of K-Points. For this reason, we also include VASP, which is a standard electronic structure package with reasonable parallel scaling up to hundreds of cores. Our team has 5 members: John Russell (MD calculations), John Low (DFT calculations), Peter Zapol, Petr Kral, and Larry Curtiss providing scientific leadership and oversight. John Russell is also collaborating with John Low, Marius Stan, Jianwei Sun, and James Furness on a project related to testing the SCAN functional to see if it can avoid problems with metastable states in uranium oxides. So far, extensive DFT calculations have been conducted with the Abinit and VASP software packages. Conventional DFT calculations with uranium oxides are very challenging and calculations are often stuck in metastable low lying states. There may be some fundamental reasons why certain DFT functionals perform better than others. [1] D. Cyranoski, G. Brumfiel Nature 477, 139-140 (2011). [2] J. Medalia Congressional Research Service, R41728 (2011). [3] T. Arima, S. Yamasaki, Y. Inagaki, K. Idemitsu J. Alloys Compd. 400, 43-50 (2005). [4] T. Arima, S. Yamasaki, K. Idemitsu, Y. Inagaki J. Nucl. Mater. 376, 139-145 (2008). [5] P. Erhart and K. Albe Phys. Rev. B 71 035211 (2005). [6] F. Muller-Plathe J. Chem. Phys. 106 6082-6085 (1997). [7] S. Plimpton J. Comp. Phys. 117, 1-19 (1995). [8] J. VandeVondele, M. Krack, F. Mohamed, M. Parrinello, T. Chassaing and J. Hutter, Comp. Phys. Comm. 167, 103 (2005). Industry partnership: Project URL: Current FY Hours Used: undetermined amount New FY Requested allocation: 160000 Q1: 40000 Q2: 40000 Q3: 40000 Q4: 40000 Justification: Storage requirements: Thank You, The LCRC Accounts System

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[LCRC Accounts] Yearly Allocation Request for Hetero_Catalysis
by accounts＠lcrc.anl.gov 07 Sep '17

07 Sep '17

Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Cong Liu Project Name: Hetero_Catalysis Division: CSE Project title: Development of Novel Heterogeneous Catalysts for Effective CO2 Conversion to Fuels Associated funding: Catalysis group fundings Other Systems: Science: The conversion of CO2 to fuels is of use for renewables in carbon-neutral technologies and for developing approaches to mitigate global warming. The high thermodynamic stability of the CO2 molecule requires substantial input of energy for its reduction and conversion. Although a number of recent studies have helped to better understand CO2 activation/reduction using catalysts, the catalytic conversion of CO2 to hydrocarbon fuels (e.g., CH3OH, CH4) is still a challenging problem. For instance, although CO2 has been shown to be reduced directly on metal surfaces, the surfaces become quickly poisoned and deactivated by the reduction products (e.g., CO).[1] Studies have achieved the reduction of CO2 to CO and formate. However, further transformation of CO and formate to more useful products such as methane or methanol requires multiple hydrogenation steps, and has only been demonstrated with low efficiency. Our work in this area will be focused on using computational methods to understand the chemical insights of the reductive conversion of CO2 to hydrocarbons on supported transition metal nanomaterials. Materials including subnanometer metal clusters and 2-dimensional transition metal dichalcogenide (TMDC) nanoflakes are taken into account. The computational studies provided not only the molecular understanding and explanations for the experimental results, but also predicted critical trends of the catalytic properties of different materials, where were confirmed by the experimental studies. Project description: Previously, we have developed highly active transition metal dichalcogenide (TMDC) nanoflakes, i.e., WSe2, for CO2 electrochemical reduction to CO (Science, 2016, 353(6298); ACS Nano, 2017, 11, 453−460) In the following year, we are going to focus on more detailed studies and predictions of the catalytic properties of transition metal dichalcogenide nanoflakes for electrochemical CO2 reduction: 1. Electrochemical reduction of CO2 to hydrocarbons on TMDC nanoflakes. Previously, the computational and experimental efforts were only focused on CO2 reduction to CO. In our experimental device, the products are a mixture of CO and H2 (syn-gas), which can be used for the synthesis of hydrocarbon fuels. It would be a significant improvement of the catalytic system if CO2 can be converted directly to hydrocarbon fuels. Future computational studies will be focused on understanding the electrochemical reduction of CO2 to hydrocarbon fuels on TMDC nanomaterials, and predict effective catalytic systems prior to experiment. Reaction mechanisms and energetics will be investigated systematically for a series of TMDC materials, and the most promising catalyst system will be identified for further experimental studies. 2. Functions of ionic liquids and other electrolytes in the electrocatalysis of CO2 reduction. In our previous studies, we discovered that utilizing ionic liquids in the electrolyte system promotes the catalytic performance of the TMDC nanomaterials for CO2 reduction. However, the exact role of the ionic liquid is still unknown. In addition, carbonate and hydroxide electrolytes are also of great interest. In the future studies, we are going to carry out detailed computational studies to investigate the interactions between ionic liquid ions and the electrode (catalyst) active site, and the electronic effects of the ionic liquid in the electocatalytic process. Furthermore, the effect of using carbonate and hydroxide electrolytes will also be explored. Calculations will be focused on the distribution of different electrolyte ions near the catalyst surface and participation of these ions in the catalytic reactions. Both explicit and inexplicit solvent effects will be taken into account, and the effect of external potential will be studied. 3. Catalytic reaction pathways at different pH values will be investigated. Previously, our studies mainly were focused on acidic solutions, where protons are abundant in the electrolyte and act as proton donors during the electrocatalysis. However, our experimental collaborators have discovered that these TMDC materials work very well under pH neutral conditions. In this condition, H2O will likely act as the proton donor. Therefore, we will carry out calculations to investigate the reaction mechanisms of CO2 electrochemical reduction at pH neutral conditions and how pH affects the properties of the catalysts. A regular calculation will require 64 processors of about 10 hours of running time. Approximately 700 calculations will be carried out, and totally about 450000 cpu hours will be necessary. Industry partnership: Project URL: Current FY Hours Used: undetermined amount New FY Requested allocation: 480000 Q1: 120000 Q2: 120000 Q3: 120000 Q4: 120000 Justification: Storage requirements: Thank You, The LCRC Accounts System

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[LCRC Accounts] Yearly Allocation Request for lith_ox_md
by accounts＠lcrc.anl.gov 07 Sep '17

07 Sep '17

Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: John Russell Project Name: lith_ox_md Division: MSD Project title: Molecular Dynamics Calculations of Lithium Oxides Associated funding: Strategic LDRD project entitled Multiscale Modeling of Advanced Electrical Energy Storage Systems Other Systems: Science: We will perform molecular dynamics (MD) simulations on nanocrystalline lithium-oxide compounds (including Li2O and Li2O2) of relevance to lithium-air batteries. These simulations include determination of the structures, energies and some properties (such as the diffusivities) of the free surfaces and grain boundaries in these microstructures. A key feature of the simulation approach involves the use of a method to evaluate the Coulomb energy, forces and stresses by direct 1/r summation with spherical truncation (Wolf et al. 1999). This order-N method, which has recently been incorporated into the LAMMPS code that will be used for this work, is computationally superior to both the widely used Ewald method and fast-multipole methods while at the same time producing numerically identical and physically more transparent results. Using this approach, we are able to consider ionic systems consisting of a very large number of ions, thus enabling elucidation of microstructu ral phenomena and physical behavior that can subsequently be used as input to parameterize a physically realistic mesoscale battery model of microstructure evolution during the charge/discharge cycle. Project description: The goal of this project is calculate structural and thermodynamic properties of lithium-oxide materials and to develop parameters for collaborators studying mesoscale models where experimental values may be unavailable. Our initial approach will be to use a Buckingham potential to model covalent interactions and a Wolf summation potential for elecrostatic interactions in a fixed charge Li2O model as implemented in the LAMMPS molecular dynamics package. Our model systems will include free particles, surfaces and nanocrystalline materials. This modeling approach is well suited for large systems due to the favorable scaling of the potentials and software. LAMMPS is massively parallel with nearly linear scaling with system size which can allow for 100k+ atom models for tens of nanoseconds. We are also developing a variable charge lithium-oxide molecular dynamics potential suitable for modeling lithium superoxide, lithium peroxide, and Li2O. The computational cost of this method is estimated as 25x as expensive as a Buckingham pair potential, but with much greater flexibility to model different lithium-oxide stoichiometries. This request is for a modest allocation of ~20k core hours for testing and validation of a potential and finish this project. The key addition to the model will be the inclusion of polarization, which may be necessary to include in the model for a stable Li2O2 crystal. Industry partnership: Project URL: Current FY Hours Used: undetermined amount New FY Requested allocation: 20000 Q1: 5000 Q2: 5000 Q3: 5000 Q4: 5000 Justification: Storage requirements: Thank You, The LCRC Accounts System

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[LCRC Accounts] Yearly Allocation Request for Materials_Genome_SCs
by accounts＠lcrc.anl.gov 07 Sep '17

07 Sep '17

Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Antia Sanchez Botana Project Name: Materials_Genome_SCs Division: MSD Project title: Materials Genome Approach for Discovery of HTS Associated funding: Center for Emergent Superconductivity, an Energy Frontier Research Center funded by the US DOE, Office of Science Other Systems: Science: This project uses density functional theory-based methods to predict both the crystal and electronic structures of candidate correlated electron materials and high temperature superconductors. Our goal will be to provide a survey and database of potential correlated electron materials, with the capability to identify trends, project promising directions and explore competing orders giving rise/enhancing superconductivity. Project description: We intend to create a framework for designing novel superconductors combining first principles electronic-structure tools and materials databases. In particular, we will continue the search on possible nickelate superconductors and on mineral based quantum spin liquid candidates. We will intensively use DFT codes such as VASP, WIEN2k and Quantum Espresso that can be run efficiently on lcrc. Jobs requesting up to 10 nodes will be launched for a typical DFT-based calculation. Some of our latest calculations had to be run in biggpu nodes due to scratch storage issues with the consequent additional charge in terms of core hours. Industry partnership: Project URL: Current FY Hours Used: undetermined amount New FY Requested allocation: 200000 Q1: 50000 Q2: 50000 Q3: 50000 Q4: 50000 Justification: Storage requirements: Thank You, The LCRC Accounts System

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[LCRC Accounts] Project Request: Low-Emissivity-Coats
by accounts＠lcrc.anl.gov 07 Sep '17

07 Sep '17

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: John J. Low Applicant's institution: ANL Applicant's division: CLS Project Name: Low-Emissivity-Coats Project title: Molecular Simulations of Low-Emissivity Coatings Associated funding: Other Systems: Science: Emissivity plays a crucial role in energy engineering. As a measure of how effective the surface of a material is to emit energy as thermal radiation becomes increasingly important in the context of functional building materials.[1] Typical buildings loose up to 30 % of energy through the building envelope.[1] Especially windows and glazings represent critical building components. To improve energy efficiency in buildings, energy saving windows are regarded as a promising and efficient strategy to save costs and reduce the heat loss. This can be achieved by low emissivity coatings. Advanced glazing coatings typically consist of one or more layer stacks[2,3,4]. The composition of a typical stack is illustrated in Scheme 1. In state of the art coatings, a high IR reflectance is achieved by using silver. While base and top layers govern the visible optical performance, seed and barrier layers are critical for the emissivity[3]. For the latter, metal oxides like ZnO, SnO2, or TiO2 are used.[5] Apart from the bulk material properties, the layer properties such as thickness and roughness affect the emissivity. Challenges for future developments are to increase the performance, reduce manufacturing cost and provide durability and stability over a wide range of conditions. New combinations of materials and different configurations are regarded as most promising approaches [1,3] Molecular modeling has become a powerful tool in product design because it allows to gain important insights at the atomistic level and to predict material properties efficiently. Ab initio methods have been used to calculate radiative properties and emissivity. These properties can be obtained by calculating the frequency dependent dielectric constant. In the work of Bao et al. [6], ab initio simulations on refractive properties of a semiconductor have been presented, and Avdoshenko et al. [7] have studied the influence of defects and disorder on the high-temperature emissivity of metal oxides. The role of adhesion in the context of emissivity has been discussed by Cornil et al. [5] who characterized the adhesion of silver and metal oxides at ab initio level. The goal of this study is to predict and screen the reflectance and emissivity of metal/metal oxide interfaces based on the frequency dependent dielectric constant and to characterize the adhesion of these interfaces. We will consider such metal/metal oxide combinations that are relevant for low emissivity coatings used in glass and solar heat collector industry. Density functional theory (DFT) calculations will be performed using Quantum Espresso [8] or Abinit [9]. Both software packages use a plane-wave pseudopotential approach and are suited to address questions involving solid state materials. References: [1] B. Jelle, S. Kalnæs, T. Gao, Low-emissivity materials for building applications: A state-of-the-art review and future research perspectives, Energy and Buildings, 96, 2015, 329-356. [2]J. Mohelnikova, 7 - Nanocoatings for architectural glass, In Woodhead Publishing Series in Metals and Surface Engineering, Woodhead Publishing, 2011, 182-202, Nanocoatings and Ultra-Thin Films [3]G. Ding and C. Clavero, Silver-Based Low-Emissivity Coating Technology for Energy- Saving Window Applications, Modern Technologies for Creating the Thin-film Systems and Coatings, Prof. N. Nikitenkov (Ed.), InTech, 2017, DOI:10.5772/67085. [4] J. Finley, PPG Industries, Inc. The future high performance Glazing in commercial buildings, 2008, Available from http://www.lehigh.edu/imi/teched/SolarWS/T6f_Finley.pdf [5] D. Cornil, H. Wiame, B. Lecomte, J. Cornil, and D. Beljonne, Which Oxide for Low-Emissivity Glasses? First-Principles Modeling of Silver Adhesion, ACS Applied Materials & Interfaces, 9 (21), 2017, 18346-18354 [6] H. Bao, X. Ruan, Ab initio calculations of thermal radiative properties: The semiconductor GaAs, International Journal of Heat and Mass Transfer, 53, 2010, 1308–1312 [7] S. M. Avdoshenko and A. Strachan, High-temperature emissivity of silica,zirconia and samaria from ab initio simulations: role of defects and disorder, Modelling Simul. Mater. Sci. Eng., 22, 2014, 075004 [8] Giannozzi, et al., QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials, J.Phys.:Condens.Matter, 21, 2009, 395502. [9] Gonze et al., ABINIT: First-principles approach to material and nanosystem properties, Computer Physics Communications. 180, 2009, 2582. Project description: As it is best practice, we will first carry out a convergence study to find suitable settings for the k-point grid and energy cut-offs. Metal/metal oxide interfaces will be geometry optimized, before calculating the frequency dependent dielectric constant. When investigating interfaces, the match of cell parameters of the different layers is a critical point. Either the cell size of the individual components needs to be scaled, or sufficiently large supercells need to be created to provide a reasonable fit. Following the latter approach leads to larger system sizes which are computationally more demanding, but the first approach can only be used, if the mismatch is only a few percent. For our studies, we will use the supercell approach, since it is generally applicable. Another aspect that needs to be evaluated is the surface plane. Different surface planes need to be evaluated to account for the polarity of the metal oxide surfaces. Also, we will ca lculate the work of adhesion as described by Cornil [5], as this has implications on the thickness of the metal layer which ultimately translates into reduced production costs. In the first part of the project, we will combine silver (Ag) as metal due to its industrial relevance for low-e coatings with several metal oxides that are typically used in the glass industry, i.e. ZnO, TiO2, ZrO2, and SnO2. Also, interfaces with MgO and NiO will be studied, as both oxides have been suggested as alternative seed layers to ZnO [10] because of their better lattice matching with Ag compared to ZnO. Figure 1 shows a possible Ag(200)/NiO(200) interface. In the second part of the project, the influence of the silver layer thickness on the properties will be investigated, because it is a critical factor concerning performance and cost. Three silver layer with varying thicknesses will be built and combined with two different metal oxides. The metal oxides will be chosen based on the results obtained in the first part. Finally, in the third part, ab initio molecular dynamics (AIMD) simulations will be performed to equilibrate three metal oxide/Ag interfaces at elevated temperatures to account for the temperature dependence of the spectral emissivity. This will allow studying the texture of the surfaces and the radiative properties under operating conditions. The metal oxides will be selected based on the results of the preceding parts. The computational effort of this study will be considerable. Ab initio simulations are fairly demanding since they take electronic effects into account in contrast to typical force-field based approaches. Geometry optimizations need to be performed for all systems of the first two parts, i.e. the various metal oxide/Ag combinations (6 combinations), surface planes of the metal oxides (2 surfaces per oxide), and different layer thicknesses of Ag (3 layer thicknesses combined with two metal oxides) which makes in total 18 systems. For the geometry optimized structures, the frequency dependent dielectric constant will be calculated and the work of adhesion which also involves simulations for the individual compounds (19 structures). A single point energy calculation of a 64 atom ZrO2 slab with a volume of 1700 Å^3 using a 5x5x1 k-point grid requires about 45 min on 16 cores. As explained above, the interface structures require large system sizes. An interface structure of ZrO2( 111)/Ag(111) with a cell depths of 4 and 5 for ZrO2 and Ag, respectively, contains about 300 atoms. Including a vacuum space of 20 Å, the cell volume is about 10,000 Å3. For calculating adhesion, 19 simulations will be needed which are expected to take about 2000 CPU hours, In order to geometry optimize the structures, which is computationally more demanding than single-point calculations as it involves several optimization cycles, we estimate about 65,000 CPU hours. For calculating radiative properties of the optimized structure, which is somewhat more demanding than pure energy calculations, about 20,000 CPU hours will be needed. In addition to that, we plan to carry out three AIMD simulations over 10 ps. An AIMD simulation of 6 atoms in a 70 Å^3 cell at the Γ point with a simulation time of 0.1 ps takes about 30 min on 8 cores using QuantumEspresso. Assuming a nearly ideal scaling behavior, 170,000 core hours would be needed for three AIMD simulations of interface str uctures like ZrO2(111)/Ag(111) containing 300 atoms in a 10,000 Å^3 cell at the Γ point. In total, the project is expected to take 265,000 CPU hours. We believe that the study will be valuable for designing optimized low-e coatings and provide important insights for applications in glass and solar industry. References [10] P. Ries, Silver thin films : improving the efficiency of low-E coatings by employing different seed layers, Aachen, Techn. Hochsch., Diss., 2015. Industry partnership: This colloboration with Scienomics. Scienomics was established in 2004 and with selected partnerships with the best-of-the-breed (e.g.: Sandia National Labs, Max Planck Institute, Fraunhofer Institute, University of Illinois, Demokritos, University of Shanghai), Scienomics’s MAPS platform offers a unique and powerful blend of multiscale and multiparadigm modeling and simulation modules. With high quality science and industrial solution oriented applied research, Scienomics has garnered collaborative projects with companies in the areas of energy and green chemistry, alternate fuels, catalysis, polymers, biodefense, auto exhaust, etc. This collaboration encourages the use of high performance computing in industry and should lead to future collaborations with other industries. Project URL: Requested allocation: 265000 Q1: 66250 Q2: 66250 Q3: 66250 Q4: 66250 Justification: Storage requirements: The requester has used undetermined amount 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] Yearly Allocation Request for ESMF
by accounts＠lcrc.anl.gov 07 Sep '17

07 Sep '17

Hello, A yearly allocation for the LCRC cluster has been requested with the following updated information: Submitter/PI: Silverio Vasquez Project Name: ESMF Division: MCS Project title: Earth System Modeling Framework Associated funding: DOD, NASA, NSF, NOAA Other Systems: external: NERSC, NCAR, ORNL, NCSA, NASA, NOAA Science: The science objective of the project is to improve model fidelity and predictive skill by providing accurate, high performance coupling infrastructure. The infrastructure includes the Earth System Modeling Framework (ESMF), a set of tools for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, which adds templates (driver, model, mediator, etc.) that increase component interoperability. The infrastructure also includes the widely used ESMPy grid remapping package. Science improvements are both direct, by using the infrastructure to couple new processes, and indirect, as interoperability of components promotes exchange of software and knowledge. The ESMF/ESMPy grid remapping packages support environmental research and assessments through incorporation into data analysis and visualization packages such as UV-CDAT, NCL, and PyFerret. Standard ESMF/NUOPC Layer component interfaces have been implemented in most of the m ajor climate and weather codes in the U.S.: CESM, NASA GEOS-5 and ModelE, NOAA NEMS, NRL COAMPS and NavGEM, and the GFDL MOM ocean. In the past, componentization was implemented at the level of major physical domains, where simulated interactions require inter-component data communications (e.g. atmosphere, ocean). That is changing as there is increasing interest in nested regions and representation of model sub-processes using component hierarchies. Project description: The ESMF/NUOPC Layer project is continually evolving in response to user requests. It has a large user base with about 7000 downloads, and a dedicated support team. Tasks are prioritized periodically by a change review board that represents major customers. Current work includes the following areas: - Inclusion of the DOE MOAB finite element mesh (FEM) framework as a more powerful alternate or replacement internal "engine" for ESMF grid remapping. ESMF currently uses a FEM developed in-house. Conservative remapping using MOAB is complete and bilinear and other interpolation methods are still in progress. - Improvements to the grid remapping. Recent work includes addition of a higher-order conservative grid remapping method and shortcuts for cubed sphere grid creation. ESMPy added support for cubed sphere grids as well, and support for Python 3.5/3.6. Upcoming work will add dynamic masking to grid remapping. - Ongoing optimizations to memory and performance. ESMF, ESMPy and the NUOPC Layer are tested extensively, using a suite of about 8000 unit tests, system tests, and examples in order to ensure portability. Currently ESMF is regression tested daily on Blues with: -- gfortran with mvapich2, and mpich3 -- intel with mvapich2 and mpich2 -- nag with mpich2, mpich3, and openmpi -- pgi with mvapich2 and mpich3 On the Blues gfortran, benchmark testing is included to detect any unexpected change in the performance of the software. ESMPy is also tested on Blues with mvapich2. On Fusion, ESMF is regression tested with: -- g95 with mvapich2 -- gfortran with mvapich2 and mpich2 -- intel mvapich2 mpich2 . The regression test includes: - building the ESMF software and installing it, - building and testing 6 applications, - building and running system tests, examples and unit tests bundled with the software. The entire test suite is run with debug and optimized settings. In addition, two versions of ESMF are regression tested, the head of the development, and a branch based on the last public release where limited development has continued. Industry partnership: Project URL: http://www.earthsystemmodeling.org Current FY Hours Used: undetermined amount New FY Requested allocation: 120000 Q1: 30000 Q2: 30000 Q3: 30000 Q4: 30000 Justification: Storage requirements: Thank You, The LCRC Accounts System

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