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

在这项由NSF化学部资助的规划拨款中，加州州立大学富勒顿分校(CSUF)的迈克尔·格罗夫斯教授和瑞安·卡马罗塔教授正在与计算机辅助合成中心(C-CAS)合作，发展一种伙伴关系，这种伙伴关系可能成为未来提交给化学研究和教育伙伴关系(PREC)计划的基础。将建立一个全面的研究生态系统，鼓励CSUF学生，特别是那些来自代表不足群体(URG)的学生，获得化学科学研究生学位，扩大STEM人才库，并解决“数百万人失踪”的问题。这是通过加强所有CSUF化学专业的学生必须完成的顶峰项目，并鼓励学生在职业生涯中更早完成它来实现的。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，特别是对全氟烷基物质(PFAS)的修复，也被称为“永久化学品”。实验/计算/数据科学项目的结合将使CSUF的学生能够参加C-CAS站点的有偿暑期研究体验，得到C-CAS学生和教职员工的同行指导，并在他们申请研究生院时得到培训和支持。这项计划的预期成果：(I)中南大学的学生将会在教育的早期阶段被招募，以便有意义地参与研究工作；(Ii)中南大学教师的支援将加强中南大学教职员进行的研究，并加强他们的研究能力，使他们能够进行更雄心勃勃的项目和更好地竞争拨款；(Iii)中南大学私人机构的专业知识将加强中南学院的项目，并通过改善招收中超学院学生的工作，加强中南学院各院校的努力，以增加多样性；以及(Iv)中南学院的学员将指导中南大学的学生，并与PUI进行有意义的互动，从而为中南学院的学员在PUIS未来的职业生涯做好准备。实现这些成果的进展将通过在C-CAS内建立的评估基础设施来量化，使CSUF PIs和C-CAS能够制定一项计划，以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科院建立战略关系，作为建立全面研究生态系统的一部分，该生态系统鼓励来自代表性不足群体的CSUF学生攻读STEM(科学、技术、工程和数学)领域的研究生学位。利用计算化学和机器学习指导的实验催化剂评估，学生将研究NHC(N-杂环卡宾)配体和全氟烷基物质中的导向基团如何使金属断裂C-F键，修复这些“永远的化学物质”。将选择具有代表性的配体进行实验评估，方法是使用非监督学习工具绘制计算的化学性质空间图并对其进行聚类。使用贝叶斯算法的反应条件优化将被用来确定理想的溶剂/碱/直接基团组合，以评估全套代表性配体。最后，将实验结果和计算性质结合起来，建立加氢脱氟(HDF)反应的催化剂适应度函数。教育目标是试行鼓励CSUF学生在二年级或三年级参加强制性顶石研究项目的方法，从而最大限度地发挥延长研究经验的好处。将在CSUF试行的措施包括：(1)建立一个更早招收研究生的数据库；(2)建立一个指导程序，帮助学生寻找和申请暑期研究机会；(3)关于申请研究生院的站立工作坊；以及(4)与C-CAS研究生导师建立同行导师制度。该项目将建设CSUF的研究能力，并使C-CAS机构能够加强努力，增加化学研究的多样性。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.