Department of Chemical Engineering and Materials Science

Jacob Gissinger, assistant professor in the Department of Chemical Engineering and Materials Science, has received a $205,761 grant from NASA to help equipment on space missions better stand up to the stresses of space travel.

Gissinger and his team will work on predictive models to estimate how certain carbon-based resins can transform into graphite-like materials when exposed to extreme temperature. The project, titled “Predicting Graphitzability of High-Temperature Resins,” will use detailed computer modeling instead of the more time-consuming and expensive product testing.

The team’s model will simulate real-life manufacturing processes to study the chemical structure of resins. They will test methods for transforming the resin into graphite-like structures and test their virtual lab test results against real data, with the ultimate goal of improving how resins are made.

A successful computer model could also reveal design truths that then become rules of thumb for materials development, such as identifying a universal additive that could control graphitizability in high-temperature resins without sacrificing other important properties.

Gissinger and his team will work with NASA Langley Research Center, where they have access to the ultra-high-temperature furnaces and other equipment needed to test these materials under extreme conditions.

Assistant Professor Jacob Gissinger from Stevens’ Department of Chemical Engineering and Materials Science has received a grant for $289,124 from the National Science Foundation to further polymer research via the professor’s Multiscale Polymer Toolkit (MuPT).

Synthetic polymers are everywhere, from advanced space-faring components to daily-use packaging, textiles and electronics. Modeling polymeric materials is difficult due to their complex nanostructure. The Multiscale Polymer Toolkit will make it easier for researchers, especially those new to the field of computational modeling, to predict the properties of novel functional polymers.

The project, titled “Enabling Reproducible Research in Soft Materials With the Multiscale Polymer Toolkit” aims to improve the research capabilities in emerging polymer technologies such as biogels, purification membranes, recyclable plastics and advanced composites. Research in these areas is often hindered by insufficient tools and simulation capabilities. MuPT enables reproducible and extensible computational research on polymer materials through its expanding suite of Python software libraries built on top of previously funded open-source software tools.

MuPT aims to deliver a multiscale software representation for polymers that enables data conversion between major simulation engines, an interface that allows researchers to integrate existing software tools, a searchable repository of community-vetted polymer simulation workflows, best-practice documentation and improved materials recommendations for training software engineers. The scientific and software needs of universities, national labs, industry and international consortia are incorporated to maximize MuPT’s impact.

Pin-Kuang Lai, an assistant professor in the Department of Chemical Engineering and Materials Science, was recently awarded a $525,000 grant from the Department of Energy for his project, “Toward Metagenome-Scale Metabolic Flux and Free-Energy Analysis via Deep Learning.” Part of a $1.05-million collaborative research grant with the University of California, Los Angeles, the project seeks to develop software that can analyze and predict the metabolic activities of large, complex biological systems.

Precisely controlling metabolic pathways to redirect biochemical and energetic resources would enable efficient and sustainable production of advanced biofuels and bioproducts for sustainable energy use.

Lai will develop a computational toolset for quantifying metabolic pathway utilization and the thermodynamic driving force behind it in order to measure the energy and activity of metabolic pathways of microbial communities on an individual (one genome) and metagenomic (multiple genomes) scale.

Combining deep learning with stable isotope tracing and simulation techniques, Lai’s team will develop software that uses multilayer neural networks to pattern, reveal and predict how metabolism occurs and is controlled in an individual organism and across multiple species.

Department of Chemical Engineering and Materials Science Professor Matthew Libera was recently awarded $366,000 by the Defense Threat Reduction Agency and Army Research Office of the U.S. Department of Defense for his project titled, “Functional Hydrogels for Colorimetric Sensors.”

The project aims to establish the basic design principles for developing colorimetric toxin sensors, or sensors that change color in the presence of toxins, by integrating photonic crystals within functional hydrogels.

The structure of photonic crystals allows them to interact with visible light. When the lattice spacing, or distance between atoms or molecules, within a photonic crystal changes, the crystal is capable of changing color.

Libera seeks to leverage this phenomenon by embedding such crystals within hydrogels that are able to swell or shrink in response to a change in the local environment. If a hydrogel were to increase or decrease in size in response to the presence of a particular toxin, the alteration in the hydrogel’s shape should affect the structure of the photonic crystal embedded within it, triggering the crystal to change color.

Libera’s project will determine the optimal design and materials for developing the hydrogel platform for enabling such a toxin sensor system.