CAREER: Intelligent Synthesis of Colloidal Nanocrystals Enabled by Microreaction Engineering in Flow

职业：流动微反应工程实现胶体纳米晶体的智能合成

• 批准号: 1940959
• 负责人: Milad Abolhasani
• 金额: $ 55.88万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1940959&HistoricalAwards=false
• 关键词: CAREER; Intelligent; Synthesis; Colloidal; Nanocrystals

The goal of this CAREER project is to develop the fundamental scientific knowledge that will enable the design of modular flow reactors for the synthesis of nanocrystals (quantum dots) of perovskites. The target materials will be lead halide perovskite quantum dots that have potential applications in high-efficiency solar cells, high-definition color displays, and photocatalysis. This project will employ modular flow reactors to study the complex nucleation and growth mechanisms of these materials and develop the necessary process-structure-property relations required for optimal synthesis of perovskite quantum dots with tailored properties. The research program will be integrated with education and outreach programs aimed at training graduate and undergraduate students on flow chemistry, engaging grade 6-12 students through a modular reactor competition, educating the general public through YouTube videos, and recruiting members of underrepresented groups into STEM careers.The proposed research will be focused on studying the nucleation process, growth kinetics and composition tuning of perovskite nanocrystals by deconvoluting the mixing and reaction times in a modular flow reactor using in situ monitoring of the crystal growth process. The fundamentals of perovskite nanocrystal nucleation will be studied under a controlled microscale mixing environment in the presence of stabilizing surface ligands. The reaction kinetics of crystal growth and composition tuning mediated by halide exchange reactions in flow will be studied using machine learning (ML)-enhanced process optimization to achieve precise tuning of emission bandgap (between 1.7 and 3 eV) with narrow linewidth (90 meV and high photoluminescence (PL) quantum yield (90%) to enable commercial applications of these materials. The structure (composition)-property (PL) relationship of lead halide perovskite nanocrystals enabled by halide exchange reactions in the modular flow reactor will be studied with the purpose of developing a platform for on-demand intelligent synthesis of perovskite nanocrystals with tailored properties. In addition to training a graduate student and two undergraduate students in research, the project will involve graduate and undergraduate curriculum development on flow chemistry and outreach activities aimed at grade 6-12 students, the general public, and at recruiting members of underrepresented groups into STEM careers in collaboration with the Women in Science and Engineering (WISE) and the Summer Transition Program for incoming minority freshmen in Engineering at North Carolina State University.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.

该职业项目的目标是开发基础科学知识，以便设计用​​于合成钙钛矿纳米晶体（量子点）的模块化流动反应器。目标材料将是卤化铅钙钛矿量子点，其在高效太阳能电池、高清彩色显示器和光催化方面具有潜在应用。该项目将采用模块化流动反应器来研究这些材料的复杂成核和生长机制，并开发优化合成具有定制特性的钙钛矿量子点所需的必要的工艺-结构-性能关系。该研究计划将与教育和推广计划相结合，旨在培训研究生和本科生进行流动化学，通过模块化反应器竞赛吸引 6-12 年级的学生，通过 YouTube 视频对公众进行教育，并招募代表性不足群体的成员加入 STEM拟议的研究将侧重于通过使用原位监测对模块化流动反应器中的混合和反应时间进行解卷积来研究钙钛矿纳米晶体的成核过程、生长动力学和成分调整。晶体生长过程。将在稳定表面配体存在的受控微尺度混合环境下研究钙钛矿纳米晶成核的基本原理。将使用机器学习 (ML) 增强的工艺优化来研究流动中卤化物交换反应介导的晶体生长和成分调节的反应动力学，以实现窄线宽（90 meV 和高光致发光 (PL) 量子产率 (90%) 使这些材料能够实现商业应用卤化铅钙钛矿纳米晶体的结构（成分）-性能 (PL) 关系。该项目将研究模块化流动反应器中的卤化物交换反应，目的是开发一个按需智能合成具有定制特性的钙钛矿纳米晶体的平台。除了培训一名研究生和两名本科生进行研究外，该项目还将涉及研究生。与科学与工程女性 (WISE) 和夏季过渡项目合作，针对 6-12 年级学生和公众开展流动化学和本科生课程开发以及外展活动，并招募代表性不足群体的成员进入 STEM 职业生涯北卡罗来纳州立大学工程系针对少数族裔新生的计划。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Flow Chemistry: A Sustainable Voyage Through the Chemical Universe en Route to Smart Manufacturing

流动化学：在化学领域迈向智能制造的可持续之旅

• DOI: 10.1146/annurev-chembioeng-092120-024449
• 发表时间: 2022-06
• 期刊: Annual Review of Chemical and Biomolecular Engineering
• 影响因子: 8.4
• 作者: Volk, Amanda A.;Campbell, Zachary S.;Ibrahim, Malek Y.S.;Bennett, Jeffrey A.;Abolhasani, Milad
• 通讯作者: Abolhasani, Milad

Modern nanoscience: Convergence of AI, robotics, and colloidal synthesis

现代纳米科学：人工智能、机器人技术和胶体合成的融合

• DOI: 10.1063/5.0061799
• 发表时间: 2021-12-01
• 期刊: Applied Physics Reviews
• 影响因子: 15
• 作者: Robert W. Epps;M. Abolhasani
• 通讯作者: M. Abolhasani

Role of AI in experimental materials science

人工智能在实验材料科学中的作用

• DOI: 10.1557/s43577-023-00482-y
• 发表时间: 2023-02
• 期刊: MRS Bulletin
• 影响因子: 5
• 作者: Abolhasani, Milad;Brown, Keith A.
• 通讯作者: Brown, Keith A.

Ultrafast cation doping of perovskite quantum dots in flow

• DOI: 10.1016/j.matt.2021.04.025
• 发表时间: 2021-05-25
• 期刊: Matter
• 影响因子: 18.9
• 作者: Fazel Bateni;Robert W. Epps;Kameel Abdel;Rokas Dargis;Suyong Han;Am;a A. Volk;a;Mahdi Ramezani;Tong Cai;Ou Chen;M. Abolhasani
• 通讯作者: M. Abolhasani

Universal self-driving laboratory for accelerated discovery of materials and molecules

用于加速材料和分子发现的通用自动驾驶实验室

• DOI: 10.1016/j.chempr.2021.09.004
• 发表时间: 2021-10
• 期刊: Chem
• 影响因子: 23.5
• 作者: Epps, Robert W.;Volk, Amanda A.;Ibrahim, Malek Y.S.;Abolhasani, Milad
• 通讯作者: Abolhasani, Milad