Planning: PREC: Developing an Underrepresented Research Student Pipeline Between CSUF and C-CAS

在这项由美国国家科学基金会化学部资助的计划拨款中，加州州立大学富勒顿分校（CSUF）的Michael Groves教授和Ryan Cammarota教授正在与计算机辅助合成中心（C-CAS）合作，以形成未来提交给化学研究和教育伙伴关系（PREC）计划的基础。CSUF是一所服务于西班牙裔的主要本科机构（PUI）。将建立一个全面的研究生态系统，鼓励CSUF学生，特别是来自代表性不足群体（URG）的学生获得化学科学研究生学位，扩大STEM人才库，解决“失踪的数百万人”问题。这是通过加强CSUF所有化学专业必须完成的顶点项目来实现的，并鼓励学生在他们的职业生涯中尽早完成它。CSUF和C-CAS教师的持续指导将突出研究生研究的价值，因为它与学生的职业规划有关。建议进行跨学科研究，特别是全氟烷基物质（PFAS）的修复，也被称为“永远的化学品”。实验/计算/数据科学项目的结合将使CSUF学生能够参加C-CAS站点的有偿暑期研究经历，得到C-CAS学生和教师的同行指导，并在申请研究生院时得到培训和支持。该项目的预期成果：(i)将在教育早期招募来自URGs的CSUF学生，以有意义地参与研究；（ii）科考人员的支援，有助加强中央科学基金教师的研究工作，并提升他们的研究能力，使他们能进行更有抱负的研究项目，并更能争取资助；（iii）政府资助基金项目主任的专业知识，将有助加强中文院校的中文院校项目，并加强中文院校的工作，透过改善招收教资会学生，以增加多元化；（iv） C-CAS学员将指导CSUF学生并与PUI进行有意义的互动，从而为C-CAS学员未来在PUI的职业生涯做好准备。这些成果的进展将通过C-CAS内建立的评估基础设施进行量化，使CSUF pi和C-CAS能够制定计划，扩大最有效的干预措施，作为未来PREC提案的一部分。这项计划拨款将与中国科学院建立战略关系，作为建立一个全面研究生态系统的一部分，鼓励来自代表性不足群体的CSUF学生在STEM（科学、技术、工程和数学）领域攻读研究生学位。利用计算化学和机器学习指导下的实验催化剂评估，学生将研究NHC （n -杂环碳）配体和全氟烷基物质中的导向基团如何使金属破坏C-F键，从而修复这些“永远的化学物质”。通过使用无监督学习工具来映射和聚类计算化学性质空间，将选择具有代表性的配体进行实验评估。使用贝叶斯算法优化反应条件，确定理想的溶剂/碱/导向基团组合，以评估全套代表性配体。最后，将实验结果与计算性质相结合，构建氢脱氟（HDF）反应的催化剂适应度函数。教育目标是试点方法，鼓励CSUF学生在二年级或三年级进入强制性的顶点研究项目，从而最大限度地扩大研究经验的好处。将在CSUF试点的举措包括：(1)建立一个数据库，以便早期招募研究学生；(2)建立指导流程，帮助学生识别和申请暑期研究机会；（三）举办研究生申请研修班；(4)与中国科学院研究生导师建立同侪导师制。该项目将建立中国科学基金的研究能力，并使中国科学院的机构能够加强努力，增加化学研究的多样性。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

In this planning grant, funded by the Chemistry Division at NSF, Professors Michael Groves and Ryan Cammarota of California State University-Fullerton (CSUF), a Hispanic-serving and primarily undergraduate institution (PUI), are working with the Center for Computer Assisted Synthesis (C-CAS) to develop a partnership that could form the basis of a future submission to the Partnerships for Research and Education in Chemistry (PREC) program. A comprehensive research ecosystem will be built that encourages CSUF students, especially those from underrepresented groups (URG), to attain graduate degrees in the chemical sciences, expanding the pool of talent in STEM and addressing the “Missing Millions” problem. This is accomplished by enhancing the capstone projects all chemistry majors at CSUF must complete and encouraging students to complete it earlier in their career. Continuous mentoring by CSUF and C-CAS faculty will highlight the value of graduate research as it relates to the students’ career plans. Interdisciplinary research is proposed, particularly remediation of perfluoroalkyl substances (PFAS), also known as “forever chemicals.” The combination of experimental/computational/data science projects will enable CSUF students to participate in paid summer research experiences at C-CAS sites, be peer-mentored by C-CAS students and faculty, and be trained and supported as they apply for graduate school. Expected outcomes from this project: (i) CSUF students from URGs will be recruited earlier in their education to meaningfully participate in research; (ii) support from C-CAS personnel will enhance the research conducted by CSUF faculty members and build research capacity by enabling them to pursue more ambitious projects and better compete for funding; (iii) the expertise of CSUF PIs will enhance C-CAS projects and strengthen efforts at C-CAS institutions to increase diversity by improving recruitment of URG students; and (iv) C-CAS trainees will mentor CSUF students and meaningfully interact with a PUI, thus preparing the C-CAS trainees for future careers at PUIs. Progress toward these outcomes will be quantified by the assessment infrastructure established within C-CAS, allowing the CSUF PIs and C-CAS to formulate a plan for scaling up the most effective interventions as part of a future PREC proposal. This planning grant will form strategic relationships with C-CAS as part of building a comprehensive research ecosystem that encourages CSUF students from underrepresented groups to pursue graduate degrees in STEM (science, technology, engineering and mathematics) fields. Using experimental catalyst evaluation guided by computational chemistry and machine learning, students will study how an NHC (N-heterocyclic carbene) ligand and the directing groups within perfluoroalkyl substances enable a metal to break C–F bonds, remediating these “forever chemicals”. Representative ligands will be selected for experimental evaluation by using unsupervised learning tools to map and cluster computed chemical property space. Reaction condition optimization using a Bayesian algorithm will be used to identify an ideal solvent/base/directing group combination for evaluating the full set of representative ligands. Finally, the experimental outputs and the computed properties will be integrated to build a catalyst fitness function for the hydrodefluorination (HDF) reaction. The education goal is to pilot methods for encouraging CSUF students to enter the mandatory capstone research project in their sophomore or junior year, thus maximizing the benefits of an extended research experience. Initiatives that will be piloted at CSUF include: (1) building a database for earlier recruitment of research students; (2) establishing a guided process for helping students identify and apply for summer research opportunities; (3) standing up workshops on applying to graduate school; and (4) instituting a peer-mentorship system with C-CAS graduate student mentors. The project will build research capacity at CSUF and enable C-CAS institutions to strengthen efforts to increase diversity in chemistry research.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.