
Department of Chemical Engineering and Materials Science
The Department of Chemical Engineering and Materials Science at Stevens harnesses the synergy between two impactful disciplines to drive discoveries and innovation that change industry – and society.
Like other disciplines, engineering is becoming increasingly interdisciplinary, and the co-existence of these at the School of Engineering and Science has traditionally been a unique source of strength for the Department of Chemical Engineering and Materials Science.
We are a community of researchers, many with experience and backgrounds in both materials science and chemical engineering, striving to equip our graduates with a broad educational foundation, critical knowledge, and and skills from which to launch their careers. We produce engineers and scientists with the capacity to make a difference in increasingly vital areas such as sustainability issues related to our finite materials resources and the impact of materials utilization and disposal on the environment.
Choose Your Path
Our department offers programs in chemical engineering and materials science that are career springboards for everything from manufacturing and design to research and development.
Announcements
Jae Chul Kim awarded $300K from Samsung SDI to improve understanding of the behavior of lithium-ion batteries.
Assistant professor Jae Chul Kim will collaborate with battery and electronic materials manufacturer Samsung SDI to address one of today’s biggest challenges in battery technology. In his new project, “A Study on the Improvement of Life and Storage Characteristics of Cathode for High Voltage,” Kim and his team will investigate interphases between a cathode and an electrolyte, and tailor their electro-chemo-mechanical properties for next-generation lithium-ion batteries.
The future of electric vehicles will be driven in part by the ability to design battery materials that can store a large amount of electrons per unit volume. Lithium transition metal oxides (LiTMO2) show promise in this area, but how to effectively control their behaviors at high voltage is still not fully understood. To better design high-voltage cathode materials, the industry needs to establish a unified understanding about how cathode particles form, transform, and function.
Kim and his team will be exploring materials design and processing principles of a longer-lasting LiTMO2 cathode. First, they will develop an understanding about how transition metal compositions affect the reversible lithium extraction and insertion. They will clarify the effect of doping chemistry on the LiTMO2 physicochemical properties.
Pin-Kuang Lai Awarded $525,000 Department of Energy Grant to Develop Predictive Modeling of Metagenomic Metabolic Activity
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 (DOE) 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.
Funded through the Genomic Science Program under the DOE’s Biological and Environmental Research Program, the research could help optimize development of sustainable bioenergy resources.
Metabolism is a dynamic network of biochemical reactions that supply cellular building blocks and energy. 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. However, challenges arise from the lack of the ability to quantify the rates at which metabolic pathways are utilized.
In this project, Lai and team 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. (A metagenome is a collection of genomes from multiple organisms in an ecosystem.)
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.
The resulting tool and knowledge offer dual benefits of laying a solid foundation for metabolic engineering and integrating large-scale biochemical datasets.
Matthew Libera Receives $366,000 DTRA/ARO Award To Develop Functional Hydrogels for Colorimetric Sensors
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.
Jae Chul Kim awarded a $750,000 Early Career Award from the U.S. Department of Energy
Jae Chul Kim, an assistant professor in the Department of Chemical Engineering and Materials Science, is one of the 83 recipients of the 2022 Early Career Research Program by the Department of Energy (DOE). In his proposal entitled "Designing Chemical Disorder in Solid-State Superionic Conductors," Kim will develop fundamental understandings about how non-crystalline materials form, transform, and function, rationalizing discovery of non-crystalline solid electrolyte materials for solid-state battery applications. The award totals $750,000. Now in its thirteenth year, the DOE Early Career Research Program is "designed to bolster the nation’s scientific workforce by providing support to exceptional researchers during crucial early career years, when many scientists do their most formative work." The award is "a part of the DOE's Commitment to Supporting Next Generation of U.S. STEM Leaders who will solidify America’s role as the driver of science and innovation around the world,” according to DOE.
Jae Chul Kim awarded $300K from Samsung SDI to improve understanding of the behavior of lithium-ion batteries.
Assistant professor Jae Chul Kim will collaborate with battery and electronic materials manufacturer Samsung SDI to address one of today’s biggest challenges in battery technology. In his new project, “A Study on the Improvement of Life and Storage Characteristics of Cathode for High Voltage,” Kim and his team will investigate interphases between a cathode and an electrolyte, and tailor their electro-chemo-mechanical properties for next-generation lithium-ion batteries.
The future of electric vehicles will be driven in part by the ability to design battery materials that can store a large amount of electrons per unit volume. Lithium transition metal oxides (LiTMO2) show promise in this area, but how to effectively control their behaviors at high voltage is still not fully understood. To better design high-voltage cathode materials, the industry needs to establish a unified understanding about how cathode particles form, transform, and function.
Kim and his team will be exploring materials design and processing principles of a longer-lasting LiTMO2 cathode. First, they will develop an understanding about how transition metal compositions affect the reversible lithium extraction and insertion. They will clarify the effect of doping chemistry on the LiTMO2 physicochemical properties.
Pin-Kuang Lai Awarded $525,000 Department of Energy Grant to Develop Predictive Modeling of Metagenomic Metabolic Activity
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 (DOE) 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.
Funded through the Genomic Science Program under the DOE’s Biological and Environmental Research Program, the research could help optimize development of sustainable bioenergy resources.
Metabolism is a dynamic network of biochemical reactions that supply cellular building blocks and energy. 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. However, challenges arise from the lack of the ability to quantify the rates at which metabolic pathways are utilized.
In this project, Lai and team 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. (A metagenome is a collection of genomes from multiple organisms in an ecosystem.)
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.
The resulting tool and knowledge offer dual benefits of laying a solid foundation for metabolic engineering and integrating large-scale biochemical datasets.

Learn About Our Research
Our researchers advance discoveries in polymer processing, chemical processing, alternative energy production, biofuels, tissue microenvironment, nanomaterials, microchemical systems and more.
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Department of Chemical Engineering and Materials Science
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McLean Hall
103
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p. 201.216.5267