Rheostructurally-informed Neural Networks for Geopolymer Material Design

Project Personnel

Safa Jamali

Principal Investigator

Northeastern University


Emanuela Del Gado

Georgetown University


Norman Wagner

University of Delaware


Hilmar Koerner

Air Force Research Laboratory

Jacob Monzel

Air Force Research Laboratory

Funding Divisions

Division of Chemical, Bioengineering, Environmental, and Transport Systems (CBET), Division of Materials Research (DMR)

Geopolymers are inorganic and non-crystalline structural materials that can be obtained from natural soils via a chemical activation. They have great potential as additives to reduce cement consumption in construction and thus can help reducing green-house gas emissions of cement manufacturing. They also promote the adoption of local soil resources for traditional and 3D printing-based construction. Important for human space exploration, geopolymers can be also formed from lunar and Martian soils with limited water, and thus are excellent candidates for space infrastructure such as landing pads and shelters. However, at present processing of geopolymers into desirable structures remains far behind their laboratory scale performance, due to the wide range of chemistries and characteristics of different indigenous geopolymers. 

This award combines experiments, microscopic simulations, and machine learning approaches that will enable scientists and engineers to effectively design and control geopolymers properties and performances. In collaboration with the Air Force Research Laboratory, the team will educate and train future materials researchers with multi-tool skills that span experiments, simulations, and data-driven algorithms.