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Binary and Ternary Semiconductor Quantum Rods: A Computational Route to Next-Generation All-Inorganic Photovoltaic Materials

Binary and Ternary Semiconductor Quantum Rods: A Computational Route to Next-Generation All-Inorganic Photovoltaic Materials
二元和三元半导体量子棒:下一代全无机光伏材料的计算路线
批准号:
0730365
负责人:
Ramamurthy Ramprasad
金额:
$20.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-01-01 至 2011-12-31

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中文摘要
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英文摘要
The efficiency of photovoltaic systems based on inorganic nanocrystals could far surpass that of currently used bulk thin film (e.g., Si) based architectures, as the quantum confinement in nanocrystals makes them significantly better at converting solar photons to electron-hole pairs (or excitons). Nevertheless, major challenges remain, concerning the dissociation of the exciton into electrons and holes-a necessary condition for the efficient overall conversion of solar to electrical energy. This proposal rests on the idea that carefully designed interfaces between materials of the right type within a quantum rod will help achieve enhanced exciton dissociation and therefore optimal photovoltaic performance. Intellectual Merit: The objective of this proposal is to use an integrated set of first principles computations based on density functional theory (DFT) to study a variety of binary and ternary quantum rod (QR) systems containing interfaces. Binary systems to be studied will include CdSe and CdTe, and ternary systems will include CdSe1-xTex, Cd1-xZnxSe, CdTe1-xSx, and ZnSe1-xTex. Crystal structure variation along the length of the binary systems, and composition (i.e., x value) variation along the QR radius or length will be considered so as to result in core/shell or end-contacted interfaces. The specific system choices were motivated (among other factors) by their potential for the creation of staggered Type II valence and conduction band edge offsets at interfaces. Engineering such Type II band offsets will be critical to increasing the extent of exciton dissociation. DFT computations will be used to assess the stability and electronic structure of these systems as a function of quantum confinement (i.e., QR radius) and the rapidity of composition variations across the interface. The DFT electronic eigenvalues and wavefunctions will then be used to investigate critical properties related to exciton dissociation such as variations in the band edge positions across interfaces, electron-hole binding energy as a function of electron and hole wavefunction position, barriers to exciton dissociation and exciton recombination lifetime. Broader Impact: An important component of this proposal is the education of students. The industrial experience of the PI will enhance the engineering education of students and will aid in broadening student exposure beyond the academic environment through interactions with industry (via internships, visits and joint publications). The PI will continue to refine and teach a Computational Materials Science course he developed in 2006, which is filling a gap in the current curricula of the Engineering, Physics and Chemistry departments at the UConn. Outreach activities will be fostered to increase public awareness in the areas of Alternative Energy Solutions and Nanotechnology, in collaboration with local establishments committed to community services (e.g., public libraries and museums). In particular, the PI has the strong support of the Tolland Public Library and local middle/high school teachers, in aiding his outreach efforts, and in packaging and propagating the excitement of his research, and of Science & Engineering in general, to the local communities.
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I-Corps: Using machine learning methods and polymer data to predict properties of new polymers and accelerate application-specific polymer design
  • 批准号:
    1953854
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    2020
  • 负责人:
    Ramamurthy Ramprasad
  • 依托单位:
PFI-TT: An Artificial Intelligence Capability to Accelerate Low-Cost Commercial Polymer Design
  • 批准号:
    1941029
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2020
  • 负责人:
    Ramamurthy Ramprasad
  • 依托单位:
CDS&E: D3SC: Accelerating Density Functional Theory Based Simulations and Materials Design with Machine Learning
  • 批准号:
    1900017
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.0万
  • 财政年份:
    2019
  • 负责人:
    Ramamurthy Ramprasad
  • 依托单位:
Accelerated Dynamics of Surface Chemical Reactions
  • 批准号:
    1821992
  • 项目类别:
    Standard Grant
  • 资助金额:
    $24.12万
  • 财政年份:
    2018
  • 负责人:
    Ramamurthy Ramprasad
  • 依托单位:
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