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: $ 20万
• 依托单位: University of California-Riverside
• 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
• 起止时间: 2018-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1833218&HistoricalAwards=false
• 关键词: EAGER; CDS& Open; Source; Software

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.

光催化是一个过程，通过该过程，太阳光被捕获并用于为催化材料加速的化学反应提供能量。 良好的光催化体系是有效吸收光，并且还有效地利用光生电子来促进催化反应的体系。 光和化学/材料系统之间的相互作用使许多光催化应用成为可能，所有这些都有助于可再生能源，可用于太阳能燃料发电，环境修复和化学制造等各种应用。 充分利用这些光催化系统的能力具有巨大的潜力，因为我们进一步了解这些系统中发生的光引发过程。光催化过程的物理和化学过程是极其复杂的。 近年来，通过计算技术的发展，利用预测量子力学技术来计算和理解光催化过程的效率，从而有助于识别新的光捕获和光催化材料的试错方法。该项目将进一步推进这些技术，并为一般催化社区提供一个新的开源软件包，以评估光催化过程的效率。完全开放源代码和计算能力的可用性鼓励世界各地的学生和研究人员更深入地了解这些方法和工具如何用于评估光催化效率，并加速发现新的光催化材料和操作条件。本项目将利用激发态量子计算方法来探测光催化系统中的电子动力学。本项目中使用的激发态计算方法将与量子控制算法相结合，最终操纵光诱导反应动力学。在光催化系统中使用量子控制方法将通过提供一种确定的方法来控制反应动力学，从而在多个化学工程领域具有突破性的意义。具体地说，这些计算技术将对将导致所需反应产物的光的波长/频率给出严格的界限。因此，在EAGER项目中开发的软件工具可以用作（1）诊断工具，以验证正确的光频率确实如预期的那样用于光催化实验，以及（2）用于计算控制光催化系统所需的允许光频率的预测工具（可以作为从计算或实验获得的数据集获得）。因此，这些计算方法通过建立用于操纵电子动力学和理解光催化系统中可能的最佳效率的严格形式主义，开辟了交叉研究的新途径。最后，该项目的广泛影响将产生一套开源工具，CBET和催化社区的计算和实验研究人员可以轻松地用于未来的开发。该项目开发的完全开放源代码的可用性鼓励世界各地的研究人员获得详细的“引擎盖下的外观”，以更深入地了解这些算法是如何在实践中数字化的。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

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.