CCI Phase I: NSF Center for Adapting Flaws into Features

国家科学基金会缺陷转化特征研究中心（CAFF）是由化学学部化学创新中心（CCI）项目资助的。第一阶段中心由莱斯大学的克里斯蒂·兰德斯领导。赖斯大学团队的其他成员包括斯蒂芬·林克和彼得·罗斯基。其他团队成员包括斯坦福大学的Jennifer Dionne，伊利诺伊大学厄巴纳香槟分校的Martin Gruebele，石溪大学的Ben Levine，德克萨斯大学奥斯汀分校的Sean Roberts和威斯康星大学的Martin Zanni。铁器时代的冶金学家认识到，适当地添加杂质（镍、碳等）可以把材料性能差的金属（铁）变成坚固的钢工具。化学杂质，即“缺陷”，在某些情况下可能是有害的，但在其他情况下却具有独特的价值，它们创造了材料的理想“特征”。在现代，硅基电子学的发展利用了同样的概念。CAFF的首要目标是识别有希望的化学缺陷，了解使这些缺陷具有独特影响力的结构和电子特性，然后展示如何将相同的结构放大到宏观尺度。CAFF将研究原子、纳米和微观尺度上缺陷的类型、位置和稀疏度如何影响，特别是光学材料化学。对CAFF更广泛的影响包括快速跟踪本科教育的民主化，一方面关注那些在公共/K-12外展和本科/研究生培训之间跌落的化学家选民。关键是建立一个社区学院合作伙伴网络，包括代表性不足的城市社区和服务不足的农村社区。拥有独特技能的多样化教师和学生将成为合作伙伴，帮助形成美国科学的未来。美国国家科学基金会将缺陷转化为特征中心（CAFF）项目旨在改变对缺陷的思考、研究和利用方式，同时优化可广泛访问的新数据成像工具。现实世界的催化剂、涂料和电池从来都不是理想的，也不会在理想的条件下发挥作用。现实世界的合成化学家从来不会做出完全纯净的样品。因此，物理化学家必须找出方法，利用而不是避免缺陷的混乱现实，这样它们就可以变成特征。CAFF将致力于理解有机-有机界面上缺陷依赖的激子相互转换。该团队还将研究金属-金属纳米颗粒中异质性驱动的化学动力学。另一个目标是确定无机-有机混合材料中缺陷支持的能量转移机制。CAFF的目标是利用团队的综合专业知识，利用电子、隧道、高光谱显微镜以及超快激光光谱和理论等方法，预测、可视化和及时解决局部结构和动力学问题。总的研究和教育目标可以概括为：(i)原子和纳米尺度的可视化和化学固有缺陷的理解；（ii）将局部化学与整体化学行为联系起来；（ii）共同开发新的数据科学方法和模块化工具，以实现对大数据集的无缝实时、数据无损分析。更广泛的影响包括开发新的数据科学集成工具，在基础研究中具有潜在的广泛应用。预期的更广泛的科学成果包括开发价格合理的“智能”仪器和模块，包括实验和理论，具有适应时间、空间和光谱分辨率的能力。这些新工具将使化学家、生物物理学家、工程师和材料科学家能够研究隐藏在总体平均值内的缺陷亚群如何严格控制宏观水平的结果、性质和行为。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。

The NSF Center for Adapting Flaws into Features (CAFF) is supported by the Centers for Chemical Innovation (CCI) Program of the Division of Chemistry. This Phase I Center is led by Christy Landes of Rice University. Other Rice team members include Stephan Link and Peter Rossky. Additional team members are Jennifer Dionne from Stanford University, Martin Gruebele from the University of Illinois-Urbana Champaign, Ben Levine from Stony Brook University, Sean Roberts from the University of Texas-Austin, and Martin Zanni from the University of Wisconsin. Iron-age metallurgists learned that judicious addition of impurities (nickel, carbon, etc.) could transform a metal with poor materials properties (iron) into strong steel tools. Chemical impurities, ‘flaws’, can be detrimental in some situations and uniquely valuable in others, creating the desirable ‘features’ of a material. In modern times, the development of silicon-based electronics exploited the same concept. CAFF’s overarching goal is to identify chemical flaws that hold promise, understand the structural and electronic properties that make those flaws uniquely influential, and then to demonstrate how the same structures can be amplified to macroscopic scales. CAFF will examine how the type, location, and sparsity of defects on atomic, nano- and microscales influence, in particular, optical materials chemistry. Broader impacts for CAFF include fast-tracking the democratization of undergraduate education and focusing on a constituency of chemists that have fallen between the cracks of public/K-12 outreach on the one hand, and undergraduate/graduate training on the other. Key will be to build a network of Community College partners that includes underrepresented urban and underserved rural communities. A diverse set of faculty and students with unique skill sets will be partners who can help form the future of American science.The NSF Center for Adapting Flaws into Features (CAFF) project aims to transform how to think about, study, and exploit defects, while optimizing new data-informed imaging tools that are broadly accessible. Real-world catalysts, coatings, and batteries are never ideal nor function in ideal conditions. Real-world synthetic chemists never make completely pure samples. Hence, physical chemists must identify ways to exploit, rather than avoid, the messy reality of flaws, such that they can be turned into features. CAFF will pursue understanding of defect-dependent exciton interconversion at organic-organic interfaces. The team will also study heterogeneity-driven chemical dynamics in metal-metal nanoparticles. Another goal is to identify the mechanisms underlying defect-supported energy-transfer in inorganic-organic hybrids. CAFF aims to leverage the combined expertise of the team in predicting, visualizing, and resolving in time localized structure and dynamics, using methods such as electron, tunneling, and hyperspectral microscopy as well as ultrafast laser spectroscopy and theory. Overall research and educational goals may be summarized as: (i) Atomic and nanoscale visualization and understanding of defects inherent to chemistry; (ii) correlating local chemistry to ensemble chemical behavior; (ii) co-development of novel data science approaches and modular instruments to move toward seamless real-time, data loss-less analysis of large data sets. Broader impacts include the development of new data-science integrated tools with potentially broad applications in basic research. Expected broader scientific outcomes include the development of affordable ‘smart’ instruments and modules, both experimental and theoretical, with the ability to adapt in time, space, and spectral resolution. These new tools will allow chemists, biophysicists, engineers, and materials scientists to study how sub-populations of defects, obscured within the ensemble average, critically control macroscale-level outcomes, properties and behavior.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.