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ITR-(ASE)-(sim): Life-Size Atomistic Simulation of Fabrication and Operation of Multi-Component Nanostructures

ITR-(ASE)-(sim): Life-Size Atomistic Simulation of Fabrication and Operation of Multi-Component Nanostructures
ITR-(ASE)-(sim):多组分纳米结构的制造和操作的真实尺寸原子模拟
批准号:
0426870
负责人:
Simon Phillpot
金额:
$117.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-09-01 至 2011-08-31
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This award is funded by the Divisions of Materials Research and Chemistry and was made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." This award supports computational research to develop atomistic simulation methods for parallel computers to simulate nanostructures composed of multiple chemical species. This award also supports education from high school to post graduate level and course development. The PIs plan to develop and disseminate a flexible and robust computational framework for atomic-level simulation of structures in which chemically diverse materials coexist and function together. The framework will be scalable to very large systems and will be implemented in a parallel computing environment. The PIs will integrate three important developments in atomic-level simulation: (i) variable charge methods that allow the charge state of an ion to be determined self-consistently, (ii) fictional dynamics, applied to the evolution of the charge states, and (iii) a real-space, computationally very fast method for calculating Coulombic sums. The framework will allow the simulation of systems in the 50 million - 300 million atom size range, which are experimentally achievable nanostructure sizes. This simulation tool will be used to address fundamental issues associated with the deposition processes by which these structures are produced, confinement effects in nanostructures, and self-organization of domains at the nanoscale. The PIs will simulate the fabrication of devices in which the oxide ferroelectric (Ba, Sr) TiO3 is epitaxially grown on Si; the PIs will also elucidate the structure of the interfaces between the ferroelectric and various electrode materials. The PIs also plan to address fundamental issues associated with the organization of domain structures and with domain dynamics in Pb (Zr, Ti) O3-based thin-films and nanostructures. These simulations will answer fundamental questions associated with the chemistry of processing through physical and chemical deposition, and the effects of temperature, strain, microstructure and confinement effects on domain organization in nanostructures. Each of these simulation efforts will be coordinated with the work of experimental colleagues. Broader impacts of the proposed work include: (i) training and professional development of postdoctoral associates, and graduate and undergraduate students, with an emphasis on members of underrepresented groups in science and engineering, (ii) involving and training high school students from underrepresented groups through the University of Florida Student Science Training Program, (iii) developing and expanding courses taught by the PIs, and (iv) disseminating results and educational materials through websites developed by the PIs, through the General Utility Lattice Program (GULP), and the NSF-funded Network for Computational Nanotechnology at Purdue University. %%%This award is funded by the Divisions of Materials Research and Chemistry and was made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." This award supports computational research to develop atomistic simulation methods for parallel computers to simulate nanostructures composed of multiple chemical species. This award also supports education from high school to post graduate level and course development.Chemically complex material structures containing metals, ionic materials, and covalent semiconductors within a single functional structure are increasingly common. The integration of dissimilar materials is driving significant new technologies ranging from smart chemical and biological sensors, with defense and homeland security applications, to fuel cells for the hydrogen economy, to microelectronics and microelectromechanical systems (MEMS). Simultaneously, feature sizes are rapidly decreasing; The International Technology Roadmap for Semiconductors calls for 50 nm (roughly 5 million atoms) by 2011. The scales on which experimental devices are built are still much larger than the scales at which atomic-scale computer simulations have been carried out, especially for structures composed of dissimilar materials. As feature sizes continue to shrink and computer power continues to grow, it is becoming feasible to model nanometer-scale devices entirely at the atomic level. The PIs will develop a robust computational framework for parallel computers to simulate nanostructures accessible to experiment. The PIs will use this simulation tool to study fundamental issues related to the growth and structure of nanostructures.Broader impacts of the proposed work include: (i) training and professional development of postdoctoral associates, and graduate and undergraduate students, with an emphasis on members of underrepresented groups in science and engineering, (ii) involving and training high school students from underrepresented groups through the University of Florida Student Science Training Program, (iii) developing and expanding courses taught by the PIs, and (iv) disseminating results and educational materials through websites developed by the PIs, through the General Utility Lattice Program (GULP), and the NSF-funded Network for Computational Nanotechnology at Purdue University. ***
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