NERSC Initiative for Scientific Exploration (NISE) 2013 Awards
NISE is a mechanism used for allocating the NERSC reserve (10% of the total allocation). In 2013 we made the second year of the two-year awards made in 2012, supplemented by projects selected by the NERSC director.
NERSC Application Readiness for Future Architectures
Katie Antypas, Lawrence Berkeley National Laboratory
NISE award: 250,000 hours
NERSC repository: m1759
It is now widely recognized that computing technology is undergoing radical change and that future systems will pose a wide variety of technology challenges. These challenges have arisen because hardware chip technologies are reaching physical scaling limits imposed by power constraints. Although transistor density continues to increase, chips will no longer yield faster clock speeds. Instead, vendors are increasing the number of cores on a chip such that within this decade, chips are expected to have over 100 times more processing elements than today. These innovations in architecture and vast increases in chip parallelism (referred to as ???manycore???) will affect computers of all sizes. Many of the challenges we anticipate in the exascale computing era are confronting us even today. Users of such systems will require new algorithms that run more efficiently, exploit parallelism at a much deeper level, accommodate far less memory per process space, and take much greater care in considering data placement and movement and machine resilience.
According to the summary report of the Advanced Scientific Computing Advisory Committee in the fall of 2010 entitled, ???The Opportunities and Challenges of Exascale Computing???, the transition required to adapt to these new architectures is expected to be as disruptive as that from vector machines to massively parallel systems in the early 1990s. While this transition was not easy, NERSC was able to work with the scientific user community to transform applications from a vector model to an entirely different programming model based on the Message Passing Interface (MPI). A high level of user engagement will again be necessary to help users transition to more energy efficient architectures due to the large number of applications running at NERSC.
Carbon Data Assimilation with a Coupled Ensemble Kalman Filter
Inez Fung, University of California Berkeley
NISE award: 750,000 hours
NERSC repository: m189
The contemporary increase in CO2 in the atmosphere is approximately half the CO2 emitted by fossil fuel combustion. The land and oceans have acted as repositories (sinks) for the remainder of the fossil fuel CO2, plus the CO2 released as a result of land use modification. The key to predicting future levels of atmospheric CO2 and the timing and magnitude of climate change is the prediction not only of the anthropogenic carbon sources, but also of the biogeochemical processes that determine the changing magnitudes and locations of the carbon sinks. These processes determine the rate of carbon exchange between the atmosphere, land and oceans, as well as the stability and longevity of carbon storage in each of these reservoirs in a changing environment.
Our research goals are to constrain the values of surface CO2 flows, using satellite and surface CO2 observations, to improve our understanding of the carbon cycle; and to construct vertical profiles of CO2 concentration to examine and improve the simulation of atmospheric dynamics in computer models.
Research on the response of the carbon cycle to future climate change has given varying predictions of future CO2 concentrations, primarily due to limitations in our understanding of the carbon cycle, especially near the Earth's surface. Improved understanding of the carbon cycle has the potential to narrow the range of CO2 concentrations and atmospheric temperatures predicted for the end of this century, which would help in planning for climate mitigation.
The objectives of the project are:
- to derive geographically-resolved estimates of the contemporary carbon sources and sinks and their uncertainties that are consistent with all atmospheric, terrestrial and oceanic observations of the carbon system as well as with contemporaneous observations of the varying meteorology, and
- to improve the representation of terrestrial carbon processes in coupled carbon-climate models.
A multi-decadal reforecast data set to improve weather forecasts for renewable energy applications
Thomas Hamill, National Oceanic & Atmospheric Administration
NISE award: 10,000 hours
NERSC repository: refcst
This project will allow NOAA to finalize the previous work of producing experimental long-lead probabilistic weather forecasts relevant to the renewable energy field, e.g., forecasts for solar, wind, and hydropower. Currently the emphasis has been on shorter-range forecasts, but there are many decisions that could be made weeks in advance given useful forecast guidance, such as when it may be least problematic to take some wind turbines offline for maintenance, or when it may be necessary to stockpile conventional fossil fuels because the wind power is expected to be marginal a week or two hence.
First Principles Molecular Dynamics Investigation of Carbon Dioxides
Yosuke Kanai, University of North Carolina at Chapel Hill
NISE award: 1,250,000 hours
NERSC repository: m1029
The aim of this project is to build a necessary foundation for a computational-science program focused on developing and improving novel carbon dioxide (CO2) capture/sequestration and reduction materials. CO2 engineering is inevitably one of the most important areas for both scientific and technological interests in this century. The expertise of our team in quantum simulations allows us to approach this challenge via a "bottom-up" strategy. That can be started by understanding CO2 at very fundamental level and to translate such detailed and accurate understanding into novel materials design for carbon capture and reduction technologies. In addition, the simulation can also explore new regime for materials design by controlling external conditions such as pressure or field. Our team has a long history in the area of high-accuracy quantum simulations, especially using frist-principles molecular dynamics approaches.
The project will lay a crucial foundation for a future program that is focused on improving materials for carbon dioxide capture/sequestration and reduction via computational simulations, by
- obtaining the accurate atomistic description of carbon dioxides under varying conditions for calculating dynamical/electronic properties
- addressing/assessing the importance of van-der-Waals dispersion force in FPMD for carbon dioxide under varying conditions.
Turbulent Reacting Flows for Multi-physics Model Development
Colleen Kaul, Stanford University
NISE award: 700,000 hours
NERSC repository: m1426
Turbulent reacting flows are important in a wide range of engineering devices. These devices include aircraft engines, automobile engines, and industrial combustors. All of these devices are governed by multi-physics phenomena that interact over a wide range of length and time scales. The existence of these disparate scales presents a tremendous challenge to the accurate numerical simulation of turbulent reactive flows. Using the resources provided by this grant, we will perform high fidelity direct numerical simulation (DNS) of flows governed by turbulent reactive physics. These DNS results will guide large eddy simulation (LES) model development, enabling accurate simulation of realistic combustion-based devices. The resulting modeling framework is expected to assist in both reducing the emissions and improving the efficiency of these technologies.
Electronic Properties of Novel Nitride Nanostructures
Emmanouil Kioupakis, University of Michigan
NISE award: 7,000,000 hours
NERSC repository: m1380
Light-emitting diodes (LEDs) made from nitride materials are efficient sources of light that can replace incandescent and fluorescent light bulbs for indoors lighting. They promise to significantly reduce the electricity cost and carbon-dioxide emissions that lighting generates. Currently, however, the efficiency of LED light bulbs is limited, and this brings up their cost. A promising solution is to use ideas from nanotechnology and fabricate LEDs out of thin nanowires about a millionth of an inch thick. Our theoretical work will study these new nanomaterials and provide a guide for the development of efficient light bulbs.
Multi-scale Multi-Compartment Computational Models of the Human Immune Response to Infection with M. tuberculosis
Denise Kirschner, University of Michigan
NISE award: 250,000 hours
NERSC repository: m1827
Tuberculosis (TB) is a global health problem and responsible for ~2 million deaths per year, despite the availability of antibiotic treatment. Approximately 1/3 of the world's population has a latent form of the disease, meaning that bacteria are present in the body and the possibility of active disease is ever-present. Drug resistant forms of the bacteria are becoming more common, risking a global increase in the disease unless more effective prevention and therapeutic methods are developed.
Our research takes a systems biology approach to understanding the immune response to the pathogen Mycobacterium tuberculosis. We develop computer simulations of the immune response and validate our simulation framework using available experimental data at the molecular, cellular, tissue, and organism level. We then use these simulations to better understand why the immune response does not eliminate the bacteria, to understand why some individuals develop active disease and others develop latent disease, to generate new systems-level hypotheses as to how the immune response fails, and to suggest new therapies for the disease.
Multiscale Modeling of Nanoparticle Self-Assembly and Molecular Electronics in Nanocarbons
Petr Kral, University of Illinois
NISE award: 1,500,000 hours
NERSC repository: m1201
The proposed multidisciplinary research encompasses self-assembly of ligated nanoparticles interacting with proteins which might impact molecular separation, activation (enzymatic processes at surfaces), delivery (nanomedicine), and related chemical, medicinal, and pharmaceutical areas of interest. We also plan to model molecular electronics in modified (porous) graphene. This might be important in preparing of novel electronic materials, building of new devices, and ultimately building faster and smaller computers.
In this proposal we plan to study:
- Self-assembly of nanoparticles and proteins at liquid interfaces, and
- electron transport in porous nanocarbons. We believe that these studied may lead to significant advances of our knowledge in material sciences and discoveries of transport phenomena in molecular electronics.
Sampling Diffusive Dynamics on Long Timescales, and Simulating the Coupled Dynamics of Electrons and Nuclei
Thomas Miller, California Institute of Technology
NISE award: 15,000,000 hours
NERSC repository: m822
We aim to develop and employ novel simulation techniques to advance the understanding of enzymatic catalysis, photocatalysis, and protein targeting in cells. Key applications of this research include the chemistries of energy and health.
The goal of this research is to develop and employ new theoretical and computational methods for understanding the dynamics of complex systems. It is focused on two main areas:
- coupled electronic and nuclear dynamics in enzymes and photo-catalysts, and
- long-timescale dynamics in protein-tranport processes involving transmembrane channels.
A critical aspect of this research is the development of simulation algorithms to leverage the massively parallel computational systems. The support of NERSC computer resources is critical in our efforts to understand and design of chemical processes that are critical for solar energy conversion, enzyme catalysis, and biomolecular transport.
Large Eddy Simulation of Turbulence-Chemistry Interactions in Reacting Multiphase Flows
Joseph Oefelein, Sandia National Laboratories
NISE award: 4,400,000 hours
NERSC repository: m295
The importance of understanding and predicting fuel injection, atomization and dense spray dynamics in advanced combustion systems is widely recognized. The difficulties in measuring spray phenomena, especially in the dense regime, are also well recognized. One aspect that is not as well understood is the effect of pressure on the fundamental physics of injection. Depending on the pressure, injected fuel jets exhibit two distinctly different sets of evolutionary processes. At subcritical cylinder pressures, the classical situation exists where a well-defined interface separates the injected liquid from ambient gases due to the presence of surface tension. As chamber pressures exceed the critical pressure of the fuel, however, the situation becomes quite different. Under these conditions, a distinct gas-liquid interface does not exist. Instead, injected liquid jets undergo a transcritical change of state as interfacial fluid temperatures rise above the critical temperature of the local mixture. Effects of surface tension become diminished, and the lack of these inter-molecular forces promotes diffusion dominated mixing processes prior to atomization. Treating these phenomena requires detailed treatment of non-ideal thermodynamics and transport. We have recently established the framework for treating these phenomena for a wide range of hydrocarbon fuels. The framework has been tested on a wide variety of flows (both basic and applied) and is providing a key source of data to understand how to scale between atmospheric and high-pressure conditions from both the phenomenological and advanced diagnostic perspectives.
Turbulence over Complex Terrain: a Wind Energy Perspective
Edward Patton, National Center for Atmospheric Research
NISE award: 3,000,000 hours
NERSC repository: m917
Wind turbines are frequently deployed in regions of undulating topography to take advantage of the expected speed-up of wind as the atmosphere is forced up over the hill. A substantial portion of future wind farm deployments may also be offshore where turbines can be located close to consumers. Atmospheric interactions with these complex underlying surfaces produce highly variable and potentially damaging environments for turbines. Proper characterization of the connections between turbines and their environment is essential for wind turbine deployment strategies and for designing turbines capable of withstanding these environments. The project's goals include using numerical simulations to develop a fundamental understanding of the interconnections between wind turbines, vegetation, orography, water waves, heterogeneity, and stratification on turbulence within the Planetary Boundary Layer for improved turbine design, wind farm siting, and forecast skill.
Numerical Simulations of Nanocrystals, Interfaces, and Grain Boundaries in Complex Materials
Stephen Pennycook, Oak Ridge National Laboratory
NISE award: 4,000,000 hours
NERSC repository: mp221
The research projects in this proposal involve the investigation of the atomic-scale structure and the electronic properties of nanoparticles, interfaces, grain boundaries and defects in general in complex materials using state-of-the-art total-energy first-principles calculations based on density functional theory.
The goal of this project is to understand at the fundamental level the electronic and optical structure properties relationships of materials at the atomic scale.
All the materials studied in this project are used directly or indirectly in energy related applications. Direct examples are LiFePo4, which is one the most used cathode materials in batteries; CdSe for new generation of LED, graphene which is the building block for all graphite-like electrodes in super cell and batteries. The study of their electronic properties is desired in order to obtain a new generation of materials with improved properties.
Joint Center for Energy Storage Research
Kristin Persson, Lawrence Berkeley National Laboratory
NISE award: 4,000,000 hours
NERSC repository: jcesr
JCESR will be the nation's leading center of energy storage R&D, supporting a wide array of related industries and leading innovation in a high-growth sector of advanced batteries with an international market projected to grow from $10 billion today and exceed $50 billion within the next five to seven years. The range of potential markets for advanced energy storage technologies and products is vast: hybrid and electric vehicles, the Smart Grid, stationary storage for electrical utilities, medicine, military, aerospace, construction, and consumer electronics Â¿ anything that can use a rechargeable battery.
The Materials Genome
Kristin Persson, Lawrence Berkeley National Laboratory
NISE award: 4,000,000 hours
NERSC repository: matgen
The energy and climate problem facing the world has highlighted the urgent need to accelerate the search and development of new materials. Many technologies to create, transfer, save, or store energy are critically dependent on materials innovation. We will accelerate the design of new materials needed for these technologies by 1) using scalable high-throughput ab-initio computations at an unprecedented scale, to rapidly predict and mine data on all inorganic materials in nature, in order to more rapidly and efficiently design new materials in the energy field. 2) make that data available in an organized way to the larger materials community, so that informed and effective choices can be made in materials research and development programs focused on energy.
Calibration of 3D Upper Mantle Structure in Eurasia Using Regional and Teleseismic Full Waveform Seismic Data
Barbara Romanowicz, University of California Berkeley
NISE award: 3,000,000 hours
NERSC repository: m554
Seismic imaging at all scales has traditionally made extensive use of approximate theories and methodologies, in order to facilitate model recovery at modest computational expense. However, it has recently become feasible to reduce our dependence upon these approximations, and treat wave propagation through complex 3D models of earth structure directly using highly accurate numerical methods, such as the spectral element method. Our goal is both to develop new approaches for regional and global seismic tomography using these high-accuracy numerical schemes and to apply these methodologies toward obtaining high-resolution models of seismic structure.
Quantum Transport Simulation of Nano Scale Electronic Devices for Ultra Low Power Computing
Sayeef Salahuddin, University of California Berkeley
NISE award: 200,000 hours
NERSC repository: m946
We propose to build up a parallel simulation platform for the so-called Spin torque transfer (STT) devices which, by using exotic material properties at the nanoscale, promises to significantly reduce energy dissipation in electronic devices. Our transport calculation will be based on the Non Equilibrium Green's Function (NEGF) formalism which is currently regarded to be the state of the art for quantum transport simulation within the single electron picture. In a latter section we shall briefly describe the NEGF formalism and what is involved from a computational point of view. While this proposal is focused on the STT devices, the same transport platform can be used to simulate transport in other nanostructures where quantum effects are of significant importance, for example, nanoscale transistors and memory devices, electrical nano sensors and molecular electronics. Hence the simulation platform built during this work, the algorithms developed and the insights gained, will be generally applicable to a large array of different nano-structures.
Surface and Interface of Photocatalytic Metal Oxide Materials
Annabella Selloni, Princeton University
NISE award: 3,275,000 hours
NERSC repository: m944
This research involves the study of transition metal oxide surfaces and their interfaces with water for many years. Recently, we have focused on fundamental interface properties relevant to the photo-catalytic and electrochemical oxidation of water. In the following, we briefly describe a few different subprojects on TiO2 and cobalt oxide interfaces.
TiO2 is well-known for its capability to split water. Much attention is currently focused on the mechanism of the oxygen evolution reaction (OER) which is the bottleneck of water oxidation. OER consists of 4 proton coupled electron transfer steps. For TiO2, first principles calculations have found that the first oxidation step is the most difficult one due to the fact that the relative free energy of a surface hydroxyl radical is quite high. To proceed, we intend to study the detailed mechanism of the first oxidation step. We next need to characterize a hydroxyl radical species on the TiO2 surface. Based on such understanding, we will then proceed to study the dynamics of the hole transfer process. A controversial issue about this process is whether this is a nucleophilic attack chemical reaction or Marcus like charge transfer reaction. We hope our work will shed some light on this interesting question.
We are also interested in studying the vibrational properties of adsorbed molecules on the anatase TiO2 (101) surface. In particular we shall consider adsorbed CO and formic acid, for which experimental data have recently become available.
Thermodynamics of Secondary Aerosol Formation: The Role of Binary and Ternary Nucleation
George Shields, Bucknell University
NISE award: 100,000 hours
NERSC repository: m1226
While the aerosols in the lower troposphere are widely thought to have a large cooling effect in global climate models, their formation and growth is not very well understood at a molecular level. Since the small gas phase clusters that form at the initial stages of aerosol growth are beyond the reach of experimental techniques, computer simulations provide an invaluable insight into the nascent stages of aerosol formation. The accurate thermodynamic information we provide can be used to refine existing climate models and minimize the uncertainty regarding the role of aerosols in global warming.
The main intention of this project is to understand the formation of atmospheric aerosols at the molecular level. Current experimental techniques can detect cluster/aerosols containing 50 or more waters, but anything smaller is beyond the reach of experiment. Using computational chemistry tools that have been developed over the last 100 years, we can study the formation of gas phase clusters and project a mechanism by which they can grow into aerosol particles.
Next Generation Bioimaging Institute
David Skinner, Lawrence Berkeley National Laboratory
NISE award: 200,000 hours
NERSC repository: ngbi
An image from a microscope can contain arbitrary types of detailed structure. In many cases however the detail and structure is describable in informatic or semantic forms that can inform the input to biological models. "This image contains 342 vacuoles with an average diameter of 2 um" is a piece of biological knowledge that can, with the proper algorithms, be derived from pixel data. When such knowledge is registered and organized in reference to semantic data regarding the sample the image came from, the microscopy done, along with ontologies of the features derived from the data ( cell, organelle, vacuole, etc.) it can build a knowledge network that can:
- enable comparative analysis across bio-imaging modalities
- define and model pathologies in a statistical sense
- provide a central anchor for higher level biological models
- combine best of bread between machine learning and expert annotation of biosystems
- scale out high throughput phenomics for all the right reasons
Static and Dynamic Solutions for Heavy Nuclei
Ionel Stetcu, Los Alamos National Laboratory
NISE award: 5,000,000 hours
NERSC repository: m1451
Atomic nuclei are complex quantum-mechanical systems whose description requires considerable computational resources. However, the nuclei are never isolated so the complexity increases even more when one considers the large number of processes in which they are involved. Such processes, from the nuclear response to electroweak probes, to nuclear reactions, or nuclear fusion and fission are of fundamental interest and have important applications in energy production, global security (e.g., nuclear forensics, nuclear detection, non-proliferation), medical applications, etc. Most of the approaches to describe nuclear systems, especially those involving nuclei with more than 20 nucleons, rely on phenomenological models which involve parameters fitted to reproduce experimental data. The extrapolation of the phenomenological models is unreliable and many times fails. We propose the use of a quantum-mechanical approach, the density functional theory and its extension to time-dependent phenomena, to describe nuclear systems and processes of interest. Such an approach has been widely applied in atomic physics and chemistry, but it was computationally too intensive to be applied to nuclei. We have taken advantage of the recent advances in computational power, developing the theoretical and software tools to attack the difficult description of nuclear systems.
Attribution of Extreme Weather Risk to Anthropogenic Emissions
Daithi Stone, Lawrence Berkeley National Laboratory
NISE award: 9,500,000 hours
NERSC repository: m1517
Whenever a damaging weather event occurs these days people ask "Was this caused by our emissions?" Currently climate scientists lack a resource that would allow them to respond both accurately and promptly. This project would generate a dataset that would allow researchers to quickly assess the degree to which our emissions have changed the odds of certain extreme weather events.
This work will contribute to two projects: the Weather Risk Attribution Forecast (WRAF), and the Attribution of Climate-related Events (ACE) activity of the Climate of the 20th Century project (a collaboration of about 30 climate modelling centres around the world). Both projects seek to examine the degree to which the probabilities of extreme weather events have been altered because of anthropogenic emissions of greenhouse gases and aerosols. This project would contribute simulations of the CAM5.1 atmospheric model. For the ACE project, 50 simulations at 1-degree horizontal resolution, each with slightly different initial conditions, would be run with evolving ocean surface temperatures, greenhouse gas concentrations, and aerosol concentrations over the last 50 years. Two more sets of 50 simulations would then be run under two estimates of the conditions of the world that might have been had humans never interfered with the climate (i.e. with greenhouse gas and aerosol concentrations at pre-industrial levels, and with ocean surface temperatures cooled according to two estimates of the warming pattern attributable to anthropogenic emissions). For the WRAF project these simulations would be incrementally advanced each month as observations of surface temperatures become available for the previous month, thus producing a near-real-time dataset for attribution study. Comparison of the frequency of extreme weather events in these different ensembles will provide a much-needed quantitative estimate of the degree to which past emissions are affecting our current weather.
Advanced Simulation of Pore Scale Reactive Transport Processes Associated with Carbon Sequestration
David Trebotich, Lawrence Berkeley National Laboratory
NISE award: 25,000,000 hours
NERSC repository: m1516
The injection of CO2 into the Earth's subsurface forces the subsurface system far from equilibrium, where a range of self-organizing processes can lead to emergent, time-dependent structures. Current focus is on the structures that emerge due to process coupling at the pore scale, since this is ultimately the framework within which the fluids migrate and/or reside, and minerals dissolve and precipitate. Research within the DOE Energy Frontier Research Center (EFRC) for Nanoscale Control of Geologic CO2 aims to establish the rules governing emergent behavior at the pore scale under far from equilibrium conditions, and to do so, is bringing to bear a new generation of experimental, imaging and modeling tools specifically designed to address this scale as it pertains to carbon sequestration. The intent of modeling and simulation is to not only inform the experiments a priori, but to also help interpret the experimental results, and to generalize the computational results to the larger (porous-continuum) scales for the purpose of more accurate macroscopic field scale modeling, which is ultimately the scale of interest in carbon sequestration. The primary objective of this project is to perform high resolution simulations of pore scale reactive transport processes to support and validate the experimental effort of EFRC while providing the basis for upscaling to the continuum (reservoir) scale.
Computational Prediction and Discovery of Magnet Materials
Cai-Zhuang Wang, Ames Laboratory, Iowa State University
NISE award: 12,000,000 hours
NERSC repository: m1515
This proposal covers two projects.
Firstly, permanent magnetic materials are essential in electrical generators using wind, water, and even carbon based fuels. Permanent magnets are also essential in electric motors for vehicles and other electro-mechanical devices, including levitators. Because of the role of such devices in new energy economies there is a great increased demand for strong permanent magnet materials. Currently, most widely used permanent magnetic materials use rare earth materials. Due to the potential shortage in resources and supply of rear earth materials, There is a strategic national need to find replacement materials beyond rare earth to meet the performance and cost goals for advanced electric drive motors.
Secondly, he urgent demand for new energy technologies has greatly exceeded the capabilities of today's materials and chemical processes. New materials and processes are critical pacing elements for progress in advanced energy systems and virtually all industrial technologies. The ability to predict the crystal and interface structures for any given stoichiometry by using computational algorithms is crucial for aiding the material design and accelerating the pace of technological advances. Accurate theoretical structure/property determinations will complement the traditional experimental efforts in material searches if they can be done rapidly. The algorithms, code, and experience created in this effort will be directly applicable to other accelerated materials discovery efforts. The database created will also become public and be available for other materials discovery efforts aimed at optimizing different material properties.
Spin-lattice Coupling in Magnetic Phase Transition
Yi Wang, Pennsylvania State University
NISE award: 8,800,000 hours
NERSC repository: m891
Quantitatively considering the role of the freedom of spin in thermodynamics has to be the key in understanding most advanced materials and phenomena. Solution of this can reveal the microscopic origin of the intriguing properties of many materials. The fundamental examples are the elemental metals Fe, Co, and Ni, each of which undergoes the well-documented ferromagnetic-paramagnetic transition at its Curie temperature.
However, since the discovery of the electron spin, it has been an enduring problem on how to precisely formulate the interplay among spin fluctuation, electromagnetism, and thermodynamics near the intervening critical regime in solid-state phase transitions. The current frontier is how to account for the effects of spin fluctuations at finite temperature on the Helmholtz energy within the framework of first-principles calculation. We have proposed a general theoretical framework for a magnetic system at finite temperature. This is accomplished by reaching the partition function with specifying explicitly the microscopic Hamiltonian.
Understanding Multiple Exciton Generation and Charge Extraction in Nanoparticle-based Solar Cells
Stefan Wippermann, University of California Davis
NISE award: 5,000,000 hours
NERSC repository: m1518
Semiconductor nanoparticles (NPs) are remarkably promising for increasing solar cell efficiency and are expected to play an important role in upcoming 3rd generation solar cell architectures. Ideally, this project will 1) contribute to the fundamental understanding of nanoparticle-based solar cells and 2) will allow for qualitative predictions about how to optimize both the efficiency of charge extraction and generation of multiple electron-hole pairs per photon in realistic solar cell applications. This project will thus directly help to increase the energy conversion efficiency of next generation solar cells.
Guest-Host Interactions in Hydrate Lattices: Implications for Hydrogen Storage and Carbon Dioxide Sequestration
Sotiris Xantheas, Pacific Northwest National Laboratory
NISE award: 8,000,000 hours
NERSC repository: m1513
Hydrogen hydrate, a clathrate hydrate generated from hydrogen guest molecules inside hydrate host lattices, is one of the promising hydrogen storage materials. Its applicability as a low-cost hydrogen storage alternative providing a higher storage capacity is still debated because of issues related to its thermal stability near ambient conditions. The maximum hydrogen capacity of the hydrogen hydrate is 5.3 wt.% (mass H2 per mass H2O) for cubic structure II (sII) at pressures of P = 300 MPa and temperatures of T = 250 K, a value that is close to the US DOE's 2015 goal of 5.5 wt.%. Experiments have previously indicated that up to four H2 molecules can occupy the large cages and up to two H2 molecules the smaller cages. However, the high-pressure requirement for the stability of the hydrogen hydrate places a limiting constraint on its practical application. An alternative approach to reduce the storage conditions near ambient conditions (e.g. at P = 5 MPa and T = 280 K) is to use a binary hydrate with hydrogen and tetrahydrofuran (THF) with the expense of dramatically reducing the hydrogen storage capacity down to ?2 wt.%. A scientific challenge is therefore associated with devising ways to increase the hydrogen storage capacity in hydrogen hydrates near ambient conditions. We propose to perform first principles electronic structure simulations of hydrogen accommodation inside mixed hydrate lattices and suggest possible scenarios for enhancing the hydrogen storage capacity of those molecular scaffolds.
Development of ITM Oxygen Technology for Integration with Advanced Industrial Systems
Bi-Cheng Zhou, Pennsylvania State University
NISE award: 265,000 hours
NERSC repository: m1606
This project is for designing an optimum chemistry and process conditions for Ion Transport Membrane, which is used by Air Products and Chemicals Inc. The company is using this membrane to make gas productions. The aim is to reduce the cost of gas production, save energy, and be environmentally friendly, by making use of perovksite membranes.
We use CALPHAD technique by thermo-calc, together with computational intensive calcualtions by VASP, to help get an accurate defect mechanism and thermodynamic properties for the material in use. Besides, we would also be able to answer scientific questions in phase transformations of perovskite.