CAREER: A Holistic Framework for Designing Multifunctional Materials and Structures Using Computational Optimization Methods

Drexel University, Philadelphia PA

Investigators

Abstract

This Faculty Early Career Development Program (CAREER) award contributes to national prosperity by improving methods for the design of advanced lightweight, environmentally friendly, and highly-efficient materials and structures to address major global challenges. The award supports fundamental research to extend traditional design of single-function materials and structures by formulating a new holistic framework for design of intricate multifunctional structures and materials through new multiphysics algorithms that are able to optimize material constituents and architectures simultaneously. Such materials are critical to many technologically advanced biomedical, clean energy, aerospace, and transportable electronics applications. This project offers design-themed educational and outreach activities to enhance public knowledge and attract talented students to STEM careers in the design area. The educational plan improves design-related educational activities by integrating several modular lectures based on the “philosophy of design” into design courses offered in engineering departments. The project also targets academically at-risk and underrepresented minority (URM) students to reduce school dropout via an out-of-school-time (OST) STEM education program. Overcoming current design limitations for multifunctional materials and structures is challenging because i) the mathematical models that are used to predict the performance of such designs are complex, ii) numerical solutions for such models are computationally expensive, and iii) it requires interdisciplinary/multiphysics design methods capable of tailoring materials at multiple scales to balance opposing design drivers. To address these challenges, this CAREER project will create a 3-M (Multiphysics, Multiscale, Multifunctional) Design framework that establishes new algorithms capable of optimizing paradoxical functions in a material system. The cores of this new framework are efficient reduced-order models (ROMs) and machine learning (ML)-based surrogate models integrated into multiphysics/multiscale optimization methods to enable the efficient design of such materials with desired multifunctional properties. The framework created in this project will allow tailoring multifunctional materials by balancing among conflicting design requirements that could not otherwise be achieved using single-function design strategies. To demonstrate the effectiveness of the new framework, the 3-M Design framework will be used to design structural battery (SBCs) and microvascular (MVCs) composites with superior properties. SBCs show significant potential in producing mass-less batteries used in the automotive, aviation, and robotics industries. Actively cooled MVCs make it possible to use fiber-reinforced polymer composites in high-temperature automobile, aerospace, and microelectronic applications. The 3-M Design framework is material independent and can be used for the design of different multifunctional materials that may have opposing design requirements. 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.