课题基金 / 基金详情

EAGER: CDS&E: An Open-Source Software Package for Assessing and Controlling Photocatalytic Reactions

EAGER: CDS&E: An Open-Source Software Package for Assessing and Controlling Photocatalytic Reactions
渴望:CDS
批准号:
1833218
负责人:
Bryan Wong
金额:
$20.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2020-08-31

项目摘要

项目成果

Bryan Wong的其他基金

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中文摘要
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英文摘要
Photocatalysis is the process by which sunlight is captured and used to provide energy for chemical reactions accelerated by catalytic materials. A good photocatalytic system is one which absorbs light efficiently, and also efficiently uses the photo-generated electrons to promote catalytic reactions. The interaction between light and chemical/material systems enables numerous photocatalytic applications, all of which contribute to renewable energy that can be used for applications as diverse as solar fuel generation, environmental remediation, and chemical manufacturing. The capability to fully harness these photocatalytic systems has tremendous potential to grow as we further our understanding of the light-initiated processes that occur in these systems. The physics and chemistry underlying photocatalytic processes are extremely complicated. Trial-and-error approaches to identifying new light-harvesting and photocatalytic materials have been aided in recent years by the development of computational techniques to calculate and understand the efficiency of photocatalytic processes using predictive quantum mechanical techniques. This project will further advance those techniques and provide a new, open-source software package for the general catalysis community to assess the efficiency of photocatalytic processes. The availability of fully open-source codes and computational capability encourages both students and researchers worldwide to obtain a deeper understanding of how these approaches and tools can be used to assess photocatalytic efficiencies and hasten the discovery of new photocatalytic materials and operating conditions.This project will utilize excited-state quantum computational methods to probe the electron dynamics in photocatalytic systems. The excited-state computational approaches used in this project will be coupled with quantum control algorithms to ultimately manipulate photo-induced reaction dynamics. The use of quantum control approaches in photocatalytic systems will have ground-breaking implications across multiple chemical engineering domains by providing a defined way to control reaction dynamics. Specifically, these computational techniques will give rigorous bounds on the wavelengths/frequencies of light that will lead to the desired reaction products. As such, the software tool developed in this EAGER project can serve as both (1) a diagnostic tool to verify that the correct frequency of light is indeed being used as intended in a photocatalysis experiment, as well as (2) a predictive tool for calculating the allowed frequencies of light required to control photocatalytic systems (which may be obtained as data sets obtained from calculation or experiment). Consequently, these computational methods open new avenues of cross-cutting research by establishing a rigorous formalism for manipulating the electron dynamics and understanding the optimal efficiencies that are possible in photocatalytic systems. Finally, the broader impacts of this project will result in an open-source suite of tools that both computational and experimental researchers in the CBET and catalysis communities can easily use for future development. The availability of the fully open-source codes developed in this project encourages researchers worldwide to get a detailed "look under the hood" to obtain a deeper understanding of how these algorithms are numerically incorporated in practice.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
NIC-CAGE: An open-source software package for predicting optimal control fields in photo-excited chemical systems
NIC-CAGE:用于预测光激发化学系统中最佳控制场的开源软件包
DOI: 10.1016/j.cpc.2020.107541
发表时间: 2021
期刊: Computer Physics Communications
影响因子: 6.3
作者: [Raza, Akber, Hong, Chengkuan, Wang, Xian, Kumar, Anshuman, Shelton, Christian R., Wong, Bryan M.]
通讯作者: Wong, Bryan M.
Harnessing deep neural networks to solve inverse problems in quantum dynamics: machine-learned predictions of time-dependent optimal control fields
利用深度神经网络解决量子动力学中的逆问题:依赖时间的最优控制场的机器学习预测
DOI: 10.1039/d0cp03694c
发表时间: 2020
期刊: Physical Chemistry Chemical Physics
影响因子: 3.3
作者: [Wang, Xian, Kumar, Anshuman, Shelton, Christian R., Wong, Bryan M.]
通讯作者: Wong, Bryan M.
Collaborative Research: DMREF: Organic Materials Architectured for Researching Vibronic Excitations with Light in the Infrared (MARVEL-IR)
  • 批准号:
    2323669
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2023
  • 负责人:
    Bryan Wong
  • 依托单位:
EAGER: CDS&E: Field Programmable Gate Arrays (FPGAs) for Enhancing the Speed and Energy Efficiency of Quantum Chemistry Simulations
  • 批准号:
    2028365
  • 项目类别:
    Standard Grant
  • 资助金额:
    $23.07万
  • 财政年份:
    2020
  • 负责人:
    Bryan Wong
  • 依托单位:
D3SC: Data-Driven Modeling and Experimental Investigation for Discovery of Aquatic Chemistry Reaction Kinetics: New Tools for Water Reuse Applications
  • 批准号:
    1808242
  • 项目类别:
    Standard Grant
  • 资助金额:
    $43.93万
  • 财政年份:
    2019
  • 负责人:
    Bryan Wong
  • 依托单位: