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CAREER: Computational transformation of organic photovoltaics manufacturing

CAREER: Computational transformation of organic photovoltaics manufacturing
职业:有机光伏制造的计算转型
批准号:
1653954
负责人:
Eric Jankowski
金额:
$50.25万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-08-01 至 2023-07-31

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中文摘要
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题目:职业:有机光伏制造的计算转换提案1653954:Jankowski, eric有机太阳能电池或有机光伏(opv)主要是基于塑料的薄膜,为可再生电力提供了低成本的途径。制造有机光伏电池类似于报纸印刷,可以制造灵活、轻便的电池,可以整合到织物和曲面上。它们的薄膜结构允许创造性地集成到建筑围护结构中,扩大了在更广泛的基础设施和建筑应用中使用太阳能发电的机会。这个研究项目可能有助于低成本的有机光伏发电。使用该技术的一个主要障碍是,与主要由无机材料(如硅)制成的光伏电池相比,opv目前的效率较低。这个CAREER项目的研究目标是控制塑料太阳能电池的结构,以彻底改变可持续能源的产生。这项研究将使用先进的计算机模拟来了解有机光伏电池中使用的分子如何排列成纳米结构,从而善于将阳光转化为电能。通过确定稳定形成有利纳米结构的分子和条件,该项目将改进制造太阳能电池系统的配方。该项目将通过博伊西州立大学与爱达荷州非营利性探索中心(该州唯一的公共实践科学博物馆)的服务学习项目促进地区利益。在这里,大学生将开发展览作为课堂的一部分,并将直接与孩子和他们的家人接触。该项目还包括将计算教育整合到博伊西州立大学材料工程课程中。总之,这些努力将加强大学工程专业学生的参与、保留、多样性和准备。热力学自组装为设计有机光伏活性层的纳米结构提供了一条途径,但目前还不知道哪种结构最好,或者哪种成分最适合组装它们。这个基础工程科学研究项目采用高性能计算来筛选数千种潜在的成分组合,以获得最佳结构。项目团队将使用粗粒度分子动力学模拟和图形处理单元加速来预测实验相关的形态。研究人员将使用从粗糙形态衍生的原子构型,从第一性原理计算中生成电子结构,并为电荷迁移率的动力学蒙特卡罗模拟提供信息。在热力学和动力学有机结构的自组装的基本知识将产生。最后,为了验证制造方案,该团队将与国家可再生能源实验室的研究人员合作,制造并表征预计将在OPV太阳能电池中坚固地组装成高效结构的成分。
英文摘要
Title: CAREER: Computational transformation of organic photovoltaics manufacturingProposal 1653954: Jankowski, EricOrganic solar cells or organic photovoltaics (OPVs) are primarily plastic based films that offer a low-cost route to renewable electricity. Manufacturing organic photovoltaics is similar to newspaper printing and makes flexible, lightweight cells that can be incorporated into fabrics and curved surfaces. Their thin film configuration allows creative integration into building envelopes, expanding the opportunity to use solar energy for electricity generation in a wider range of infrastructure and building applications. This research project could contribute towards low-cost organic photovoltaics. A main barrier for use of this technology is that OPVs currently have lower efficiency compared to photovoltaics made with primarily inorganic materials (e.g. silicon). The research goal of this CAREER project is to control the structure of plastic solar cells in order to revolutionize sustainable energy generation. This research will use advanced computer simulations to understand how molecules used in organic photovoltaics can be arranged into nanostructures that are good at converting sunlight into electricity. By determining the molecules and conditions that robustly form favorable nanostructures, this project will improve recipes towards making solar cell systems. The project will facilitate regional benefits through a Boise State University service-learning project with the non-profit Discovery Center of Idaho, the state's only public hands-on science museum. Here, university students will develop exhibits as part of class and will engage directly with children and their families. The project will also include integrating computational education into the Boise State materials engineering curriculum. Together, these efforts will enhance participation, retention, diversity, and preparedness of university engineering students.Thermodynamic self-assembly offers a path to engineer the nanostructure of organic photovoltaic active layers, but it is not yet known which structures are best or which ingredients best assemble them. This fundamental engineering science research project employs high performance computing to screen thousands of potential ingredient combinations for those with the best structures. The project team will use coarse-grained molecular dynamics simulations accelerated with graphics processing units to predict experimentally relevant morphologies. Researchers will use atomistic configurations derived from the coarse morphologies to generate electronic structures from first principles calculations and to inform kinetic Monte Carlo simulations of charge mobility. Fundamental knowledge in the thermodynamics and kinetics of self-assembly of organic structures will be generated. Finally, to validate manufacturing protocols, the team will fabricate and characterize ingredients predicted to robustly assemble into high-efficiency structures in OPV solar cells in collaboration with National Renewable Energy Laboratory researchers.
期刊论文(8)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1021/acs.jpcc.7b09701
发表时间: 2017-11-30
期刊: JOURNAL OF PHYSICAL CHEMISTRY C
影响因子: 3.7
作者: [Henry, Michael M., Jones, Matthew L., Jankowski, Eric]
通讯作者: Jankowski, Eric
DOI: 10.1016/j.commatsci.2019.109129
发表时间: 2020-01
期刊: Computational Materials Science
影响因子: 3.3
作者: [Eric Jankowski;Neale Ellyson;Jenny W Fothergill;Michael M. Henry;Mitchell H. Leibowitz;Evan D Miller;Mone’t Alberts;Samantha Chesser;Jaime D. Guevara;Chris D. Jones;M. Klopfenstein;Kendra K. Noneman;Rachel Singleton;Ramon A. Uriarte-Mendoza;Stephen Thomas;Carla E. Estridge;Matthew L Jones]
通讯作者: Eric Jankowski;Neale Ellyson;Jenny W Fothergill;Michael M. Henry;Mitchell H. Leibowitz;Evan D Miller;Mone’t Alberts;Samantha Chesser;Jaime D. Guevara;Chris D. Jones;M. Klopfenstein;Kendra K. Noneman;Rachel Singleton;Ramon A. Uriarte-Mendoza;Stephen Thomas;Carla E. Estridge;Matthew L Jones
Machine learning predictions of electronic couplings for charge transport calculations of P3HT
用于 P3HT 电荷传输计算的电子耦合的机器学习预测
DOI: 10.1002/aic.16760
发表时间: 2019
期刊: AIChE Journal
影响因子: 3.7
作者: [Miller, Evan D., Jones, Matthew L., Henry, Mike M., Stanfill, Bryan, Jankowski, Eric]
通讯作者: Jankowski, Eric
DOI: 10.3390/polym10121358
发表时间: 2018-11
期刊: Polymers
影响因子: 5
作者: [Evan D Miller;Matthew L Jones;Eric Jankowski]
通讯作者: Evan D Miller;Matthew L Jones;Eric Jankowski
7
    Collaborative Research: CyberTraining: Implementation: Medium: Establishing Sustainable Ecosystem for Computational Molecular Science Training and Education
    • 批准号:
      2118217
    • 项目类别:
      Standard Grant
    • 资助金额:
      $10.5万
    • 财政年份:
      2021
    • 负责人:
      Eric Jankowski
    • 依托单位:
    Collaborative Research: NSCI Framework: Software for Building a Community-Based Molecular Modeling Capability Around the Molecular Simulation Design Framework (MoSDeF)
    • 批准号:
      1835593
    • 项目类别:
      Standard Grant
    • 资助金额:
      $23.5万
    • 财政年份:
      2018
    • 负责人:
      Eric Jankowski
    • 依托单位:
    国内基金
    海外基金
    Computational Methods for Analyzing Toponome Data