Collaborative Research: Concurrent Design of Quasi-Random Nanostructured Material Systems (NMS) and Nanofabrication Processes using Spectral Density Function

Iowa State University, Ames IA

Investigators

Abstract

This award supports an interdisciplinary research to create a novel concurrent design framework that unifies the design of functional quasi-random nano/microstructures and the design of nanofabrication processes to accelerate the development of robust nanostructured material systems with superior performance. Quasi-random nanostructures are playing an increasingly important role in developing advanced material systems with various functionalities. These structures comprise no periodic repetition of identical unit-cells but a seemingly random material distribution with underlying spatial correlation. Compared to periodic designs that usually require expensive and time intensive fabrications, quasi-random nanostructures can be synthesized by low-cost and scalable manufacturing processes. However, due to the lack of appropriate computational design paradigms, there is often a mismatch between microstructure designs and feasible nanofabrication techniques. Although the testbed is focused on organic photovoltaic cells, this research will establish the applicability of the approach for a wide range of microstructural systems where the properties/performance of interest mainly depends on the spatial correlations instead of local geometries of microstructures. The broad range of potential industrial and military applications includes bio-medical devices, ultra-strong materials, consumer electronics, photonics, and telecommunications using nano-scale structures/devices. The research also offers unique collaborative experiences for researchers across the fields of design, nanomanufacturing, materials, and mechanics. Research will be integrated with education through cross-university teaching and assessment, and co-located and co-advised student training. The concurrent design approach creates a shift from existing deterministic computational materials engineering to non-deterministic microstructure design that is compatible with the intrinsic stochasticity of bottom-up nanomanufacturing processes. The key novelty is to use the physics-aware Spectral Density Function, a non-deterministic microstructure representation, as the link between the processing-structure and the structure-performance mappings in the design of engineered material systems. The approach facilitates rapid exploration of feasible and compatible processing and structure solutions, with a significantly reduced design dimensionality. An atomic resolution high-performance computational exploration will be achieved using coarse grained molecular dynamics to understand the fundamental transport mechanisms based on the materials processing dependent evolution of the structural morphologies. The bottom-up fabrication processes and multiscale imaging techniques created will offer a platform for validation of the approach, calibration and validation of computational findings, and deep scientific discovery. Finally, in addition to the intrinsic robustness of quasi-random nanostructures, the approach offers robust nanostructured material systems designs considering not only the variations in processing conditions but also the uncertainty of the computer model itself.