CAREER: Self-Assembly and Structure in Organic Mixtures

有机液体混合物中的自组装分子间结构对包括液晶、先进电子学和漏油修复在内的各种应用具有至关重要的作用。即使是简单的有机混合物分子组成的实验信息的缺乏，也阻碍了预测模型的发展，这些模型可以用于快速研究新的自组装策略。这个职业项目的目标是开发能够预测有机混合物中自组装结构的几何形状的模拟方法。该项目将结合模拟和实验方法，从原子到宏观尺度来理解和预测有机混合物中的流体结构。在原子尺度上，液态中子衍射和分子模拟将为有机混合物的分子结构提供实验上一致的见解。将创建一种名为结构优化势能精化(SOPR)的方法，该方法可以可靠地调整力场参数和粗粒度分子几何，以确保与结构的实验测量准确匹配。在宏观尺度上，新确定基准的原子化和粗粒度模拟的预测能力将与连续统特性进行比较，并由其提供信息。该职业项目的教育目标与拟议的研究相结合，以支持研究生和本科生的指导和课程开发。还将开发一个远程学习和指导平台，并将其用于针对服务不足的农村和美洲原住民社区的外联活动，以促进STEM在K-12学生中的外联和教育。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。

Self-assembled intermolecular structure in organic liquid mixtures is of critical importance to a diverse array of applications, including liquid crystals, advanced electronics, and oil spill remediation. The lack of experimental information on the molecular organization of even simple organic mixtures inhibits the development of predictive models that can be used for rapid investigation of new self-assembly strategies. The goal of this CAREER project is to develop simulation methodologies that can predict the geometry of self-assembled structures in organic mixtures. The project will combine simulation and experimental methods spanning the atomistic to the macro scale to understand and predict fluid structure in organic mixtures. On the atomistic scale, liquid phase neutron diffraction and molecular simulations will provide experimentally consistent insight into the intermolecular structure of organic mixtures. A method called Structurally-Optimized Potential Refinement (SOPR) will be created that can reliably tune force field parameters and coarse-grained molecular geometry to ensure an accurate match to experimental measurements of structure. On the macro scale, the predictive capabilities of newly benchmarked atomistic and coarse-grained simulations will be compared to and informed by continuum properties. The education goals of this CAREER project are integrated with the proposed research to support graduate and undergraduate student mentoring and course development. A distance learning and mentoring platform will also be developed and used in outreach activities targeting under-served rural and Native American communities to promote STEM outreach and education in K-12 students.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.