Adsorption of gases and liquids in porous materials plays a significant role in separation processes. This project focuses on understanding the relationship between fluid adsorption and the mechanical properties of adsorbent materials. Specifically, novel theoretical approaches will be developed to predict how adsorbent materials deform during fluid adsorption and how this mechanical response affects the adsorption behavior of porous materials. Addressing these open questions will guide the development of smart porous materials, advance membrane separations processes and the design of soft robotics, and aid in engineering the next-generation of sensing devices. The ability to design advanced adsorbent and membrane materials may dramatically improve the efficiency of separation technologies, ultimately improving access to clean water and providing new strategies for carbon sequestration. The educational component of the project will include development and dissemination of an online programming course, as well as outreach activities with high-school students from underrepresented groups.
This CAREER project will result in an atomistic modeling framework with quantitative predictive capabilities to guide the engineering of smart porous materials with controlled mechanical responses to fluids adsorption. Classical molecular simulation techniques (Monte Carlo and molecular dynamics simulations) and finite element modeling will be used in a complementary fashion to predict materials responses from atomistic to macroscopic scales. The resulting computational framework will be applied to predict and develop fundamental understanding of adsorption-induced deformation in three classes of technologically relevant materials: zeolites, thin porous silica films, and porous polymers. The knowledge to emerge from the proposed research will transform the paths to development of these porous materials for applications such as membranes with controlled permeation, chemomechanical sensors, and actuators. The educational component of this project will tackle the development of an online course 'Python for Chemical Engineering Calculations,' which will help teach this powerful programming language to undergraduate chemical engineering students across the nation. The lecture videos and course materials will be made freely available to the public and disseminated through the web-based LearnChemE resource. A complementary set of educational modules targeting high-school and community college students will also be developed. The investigator will present these modules at neighboring New Jersey schools. These school visits will serve to engage traditionally underrepresented groups from Northern Jersey's diverse population in STEM activities.
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.
|Effective start/end date||6/1/20 → 5/31/25|
- National Science Foundation: $398,632.00