(2iu) Theoretical and Computational Approaches for Upscaling Nanoengineered Materials to Design High Strength Polymeric Structural Materials

Carbon is the quintessential element that is among the most abundant in the universe, occurring in a rich diverse variety of organic compounds and has the key role in supporting all known life. From a structural and more specifically a mechanical perspective, carbon-based materials occur in two major varieties: (1) the highly robust nanoengineered materials like graphene and nanotubes and (2) the highly scalable and easy to synthesize polymeric materials. To be considered as suitable candidates for structural materials, both these key aspects - i.e., nanoengineered structure which is responsible for high mechanical strength and scalable synthesis, which is necessary for commercialization - are important. This is one of the reasons why space elevators have not yet been built with carbon nanotubes and cannot be built with polymers.

The overarching goal of my research will be to unite these two key aspects to make scalable nanoengineered materials that will have high stiffness and high specific strength as well as resistance to fracture and fatigue. In my research program I want to address this topic from two routes. The first route is to understand strategies that improve the scalability of nanoengineered materials. The primary question here is to investigate how important crystallinity is to impart high specific strength, especially when the most widespread structural material in use is concrete which is largely amorphous. Some of this work can be accomplished by exploring the defect energy landscape with clear understanding of their thermodynamics and kinetics while tuning defect concentrations from highly dilute (crystalline materials) to highly concentrated (amorphous/disordered materials) and their impact on mechanical strength.

The second route is to improve the structure of the scalable polymeric materials. Incidentally, in the last few years some significant developments have resulted in the successful synthesis of 2D polymers that have opened up a new paradigm of mechanically strong polymeric materials. Conventional polymers are made by collecting linear chains (like spaghetti) weakly packed together in space, such that they are only strongly bonded in one direction at any point. However, 2D polymers have sheet like monomers, that are strongly bonded together in a plane. If strategies similar to the CVD growth of graphene/nanotubes are explored and adopted to manufacture 2D polymers, then the problem of scalable nanoengineered structures can be solved.

My proposed independent research program will be built upon my research expertise that I obtained during my PhD and postdoctoral studies. As a Doctoral Researcher under the advisement of Prof. Boris Yakobson at Rice University, I worked on theoretical and computational modeling of the mechanical properties as well as the growth behavior of low dimensional nanomaterials. In particular I studied the nanomechanics of carbon nanotube fibers using coarse-grained modelling; developed the theory of evolutionary selection growth to synthesize infinitely large monocrystalline graphene; proposed the existence of D-loop defects in graphitic basal planes of carbon fibers; and developed the theory of conformal growth of 2D materials on curved substrates. As a Postdoctoral Researcher under the advisement of Prof. Arthi Jayaraman at University of Delaware, I entered the domain of soft and polymeric materials to understand their structure-property relationships. In this role I am currently working on developing structural representations of anisotropic soft materials that are investigated through small angle scattering experiments and using machine learning approaches to automate and predict relationships between structure-scattering-properties for forward and inverse design.

In my role as a principal investigator, I am interested in building upon my research direction to go beyond mechanical properties and explore other structure-property relationships that might arise from scalable nanoengineering of materials. I am also interested in collaborative endeavors that can promote or support experimental efforts to achieve improvements in mechanical properties, structural design or other avenues related to the physical aspects of materials. Especially after my postdoctoral experience I am looking forward to making use of machine learning and data driven modeling of materials as fruitful pursuits to gain deeper insights and understand complex experimental data that are affected by many simultaneously varying parameters. As a computational research group, my lab will not require any specialized equipment besides computational resources that are available either through my host university or can be accessed from federal research agencies.

Teaching Interests:

I have had significant exposure to teaching at the university level, and I feel happy and excited to have the opportunity to serve as an educator for my future department. As a junior undergraduate student in India, due to my involvement in robotics, I once took a class involving a live demonstration to teach a group of around 100 first year students how to make a ball-following robot. This was a formidable experience, where I inadvertently learned how well the students learned in their responses to a quiz, where they included their own recollections of the live demo in some cases with diagrams to get their points across. This had left an indelible impression and perhaps one of the reasons that drove me to pursue academia. During my PhD and Postdoctoral career, I have had more formal opportunities to teach a few classes to graduate students, which allowed me to understand the dynamics of classroom teaching such as using lecture slides vs. black board, encouraging classroom interactions, maintaining eye contact, etc. Some of these traits have been further refined due to the collection of detailed feedback at the end of the class from the students. In 2023, I also participated in the 2-week NSF funded NRT-Midas Effective Teaching Workshop which has profoundly affected my teaching philosophy. I now clearly understand that teaching in a classroom requires much more effort than what would otherwise be a research seminar, and the key focus for any class should be to plan your learning objectives, the course’s metacognitive aspects (understanding how students learn) and enhancing opportunities for active learning.

I am well suited to teach all core level courses in Materials Science like Solid State Physics, Mechanical Properties of Materials, Thermodynamics, and any other courses related to Nanoscience. Having experienced learning from three overlapping disciplines, viz., Materials Science (PhD), Chemical Engineering (Postdoc) and Mechanical Engineering (BS), I feel comfortable in teaching courses that lie at the confluence of these disciplines. I will especially enjoy teaching math-heavy courses that may also have a component of coding, solving differential equations or any kind of computational modeling. Due to my diverse research background, I would be interested in teaching graduate coursework in carbon nanomaterials, soft matter, and polymers. I am interested in developing new undergraduate and/or graduate courses that are multidisciplinary, and in addition may supplement knowledge and understanding for other courses.