Bioenergy and Water Management


To expand our research in the biofuel and water management areas to secure the availability of drinking water and water needed for agriculture and industry, which are pivotal components in shortening our pathway to a sustainable economy


  • Establish a program on biological-based energy production and sustainability (BEPS) in collaboration with Illinois Institute of Technology’s Institute for Food Safety and Health (IFSH)
  • Continue to expand research on the conversion of algae to biofuel and the utilization of the integration of algae growth with coal/waste gasification processes to decrease the carbon footprint of gasification processes
  • Continue to expand efforts in the analysis and research of biofuels through their full life-cycle steps including biomass production, conversion to biofuel, and engine performance evaluations of biofuels
  • Expand research in developing smart, energy-efficient, and economically feasible wastewater utilization and treatment processes
  • Develop innovative approaches in using treated municipal wastewater to extract energy and replace freshwater in thermoelectric power plants
  • Develop research in water desalination

For more information, contact Fouad Teymour


  • 2017: Optimizing Biofilm-Electrode Properties for Developing Sustainable Microbial Fuel Cells. PI: Seok Hoon Hong, Co-PI: David Sanchez (University of Pittsburgh)
  • 2013: Exploration of the Feasibility of Development of Symbiotic Photosynthetic Ecologies for Direct Production of Biofuels. PI: Fouad Teymour (ChBE), Co-PIs: Omar Khalil (ChBE), Satish Parulekar (ChBE), Philip Laible (Argonne National Laboratory)
  • 2010: Enhancing Bioethanol Production from Biomass Using Bacterial Hemoglobin Technology. PI: Benjamin Stark (BIOL), Co-PI: Krishna Pagilla (CAEE)
  • 2010: Preliminary Studies in Support of “EMERALD FOREST” Vision. PI: Fouad Teymour (ChBE), Co-PIs: Wei Zhang (BCPS), Satish Parulekar (ChBE)

Javad Abbasian (ChBE): Biomass gasification, process design, utilization of municipal wastewater for cooling in thermoelectric plants

Paul Anderson (CAEE): Water and wastewater, resource recovery, water quality modeling

Hamid Arastoopour (ChBE/MMAE): Utilization of municipal wastewater for cooling in thermoelectric power plants

Carrie Hall (MMAE): Utilization of biofuel

Adam Hock (CHEM): Materials for photovoltaics

Omar Khalil (ChBE): Bioenergy

Nasrin Khalili (SSB): Evaluation of water footprints

Ali Khounsary (PHYS): Energy efficiency, bioenergy

Sohail Murad (ChBE): Bioenergy

Satish Parulekar (ChBE): Bioenergy

Francisco Ruiz (MMAE): Combustion of bioenergy

Fouad Teymour (ChBE): Bioenergy

Selected Current Projects

PI: Carrie Hall, (MMAE)

This project examines methods of enabling efficient and clean use of renewable fuels in internal combustion engines. Some more advanced engines that leverage more complex combustion processes have been shown to be able to achieve high efficiencies and low emissions when using alternative fuels. This group at Illinois Tech focuses on studying the dynamics of such high-efficiency engines operating with renewable fuels and developing control methodologies that can enable them to be viable in production vehicles.

PI: Javad Abbasian

To get a firmer grasp on our ecosystem, mitigate global warming effects, and build a sustainable future, we need to invest in becoming more efficient in utilizing renewable resources such as biomass, mainly due to its life cycle carbon-neutrality and the potential to substitute fossil fuel to produce a variety of energy-related products. A broad range of organic carbon-containing materials such as agriculture and forestry residue and negative-value feedstocks such as coke and municipal solid waste can be converted into different products through various thermal conversion processes. This research focuses on developing a general mathematical model to accurately predict the properties of the syngas produced in the gasification of biomass in fluidized bed reactors. Our approach is based on employing artificial intelligence and machine learning techniques to systematically quantify the collective impact of different critical factors in the process. This approach generally involves the characterization of the solid fuel, identification of multiple measures of associations between biomass constituents, and the operating condition. Such a model will allow one to optimize the blend of biomass fuel and operating conditions to meet desirable specifications for various applications of interest including power, hydrogen, methanol, and Fischer-Tropsch products.

PI: Sohail Murad (ChBE)

Molecular simulation methods such as molecular dynamics allow screening potential membranes for their ability to prevent the permeation of various ions (including Na+ and Cl-, which are of interest in desalination). With support from a grant from the National Science Foundation (CBET 1545560), we recently completed several studies to examine a range of zeolite membranes for their ability to remove ions found as water pollutants including monovalent alkali ions (Li+, Na+, K+, Rb+, Cs+), bivalent alkaline earth ions (Mg2+, Ca2+, Sr2+, Ba2+), and ions from various groups (Ag+, V2+, Fe2+, Zn2+, Al3+, Ti3+, Fe3+, Cr3+). These studies permit choosing the most suitable membranes for removing selected pollutants from water.

PI: Paul Anderson (CAEE)

Soft sensors are mathematical or statistical approaches for predicting information from data that are historical, readily acquired, and/or anticipated (such as weather forecasts). Soft sensors are attractive because they are relatively low cost, they have fast response times, and they can be used in parallel or integrated with hard sensors to enhance the reliability of process control. Soft sensors do not have to take the place of conventional hard sensors; they can complement and add value to the existing information. Additional benefits of soft sensors include the ability to predict future information, the capacity for learning and communication, and the ability to identify errors in the data. In this work, we are examining how soft sensors and data analytics can be applied to wastewater treatment processes to develop an intelligent process management system, which integrates soft sensors, process controls, and energy efficiency evaluation, to help reduce operating (energy) costs, maintain effluent quality, and improve process resilience.

PI: Paul Anderson (CAEE)

A substantial amount of thermal energy leaves industrial, commercial, and residential facilities with their wastewater. In this project, we are assessing energy distribution in a wastewater collection system to develop a model of the spatial and temporal distribution of heat and identify the most promising sites for installation of wastewater source heat pumps for energy recovery. The assessment will consider capital and operating costs and greenhouse gas reductions for space heating, hot water production, and space cooling.

PI: Paul Anderson (CAEE)

Illinois Tech is collaborating with In-Pipe Technology (IPT) LLC to further develop its bioaugmentation service. The IPT approach transforms a wastewater collection system into a series of biological reactors, increasing the overall treatment efficiency and reducing energy consumption in the wastewater treatment process. The service takes advantage of suitable environmental conditions in the collection system and adds beneficial bacteria along with the collection system. The bioaugmentation approach makes it possible to treat contaminants prior to the wastewater treatment plant.

PI: Paul Anderson (CAEE)

The objective of this work is to develop a framework to improve the utility of watershed and water quality models with a Bayesian Network that explicitly incorporates uncertainty into the model to improve communications between model developers and other stakeholders in the watershed. The work includes a critical review of existing studies on the total maximum daily load (TMDL) to determine how the margin of safety (MOS) depends on waterbody and watershed size, watershed population, impairment type, and the designated use of the water body. In addition, we will assess potential relationships between the MOS value and factors such as the cost of TMDL implementation and the expected water quality. Ultimately, we hope to develop an approach for estimating a risk-based MOS for watershed studies based on the aforementioned factors.

PI: Paul Anderson (CAEE)

Although arsenic contamination of water resources is a global problem, there are still no rapid, reliable, low-cost sensors for on-site detection of low concentrations of arsenic in water. This study combines molecular dynamics modeling with computational fluid dynamics to examine how a metal-organic framework (MOF) compound could be used to develop such a sensor. Design criteria for the sensor include low cost, stability, durability, selectivity, and the ability to function over a range of pH values.