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EAGER: A Data-Intensive Instrument for Strongly Correlated System Material Design

EAGER: A Data-Intensive Instrument for Strongly Correlated System Material Design
EAGER:用于强相关系统材料设计的数据密集型工具
批准号:
1342921
负责人:
Gabriel Kotliar
金额:
$29.72万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-01 至 2015-02-28

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中文摘要
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英文摘要
Technical Description:This award from the National Science Foundation to Rutgers University in New Brunswick is for the development of a new computer architecture with multiple levels of interconnected memory, optimized for the simulation of strongly correlated materials from first principles calculations. Strongly correlated materials have the potential to be transformative, two examples: thermoelectric materials, which can generate electricity from waste heat with high efficiency; and, superconductors with potential for higher critical temperatures, fields, and currents, which can revolutionize the electric grid by reducing transmission losses. The use of computational methods to accelerate the pace of discovery of materials with desirable properties is one of the greatest challenges in condensed matter science. Materials with strongly correlated electron systems are particularly difficult to simulat because their physical properties cannot be accurately represented in terms of a system of independent particles moving in an average potential, thus requiring new methodologies and powerful supercomputers for their theoretical description. Non-Technical Description:This award from the National Science Foundation to Rutgers University in New Brunswick is for the development of a new computer architecture optimized for the dsicovery of new materials from first principles calculations. The new computer will enable collaborations between material synthesis groups and computational physicists. The instrument will drive computer science research, will be used as a resource for teaching computational science and engineering at Rutgers, and will serve as a prototype for a future supercomputer in the national cyber-infrastructure.
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Strongly Correlated Fermi Systems
  • 批准号:
    1733071
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $45.0万
  • 财政年份:
    2018
  • 负责人:
    Gabriel Kotliar
  • 依托单位:
DMREF/Collaborative Research: Designing, Understanding and Functionalizing Novel Superconductors and Magnetic Derivatives
  • 批准号:
    1435918
  • 项目类别:
    Standard Grant
  • 资助金额:
    $24.0万
  • 财政年份:
    2014
  • 负责人:
    Gabriel Kotliar
  • 依托单位:
Strongly Correlated Fermi Systems
  • 批准号:
    1308141
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $42.0万
  • 财政年份:
    2013
  • 负责人:
    Gabriel Kotliar
  • 依托单位:
Strongly Correlated Fermi Systems
  • 批准号:
    0906943
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $48.0万
  • 财政年份:
    2009
  • 负责人:
    Gabriel Kotliar
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: