Tony N. Rogers

Tony N. Rogers

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  • Professor Emeritus, Chemical Engineering
  • PhD, Michigan Technological University

Biography

Process Simulation

Dr. Rogers has research and teaching experience with the ASPEN Plus®, UniSim®, and SuperTarget® simulation software. As a member of the U.S. EPA Center for Clean Industrial and Treatment Technologies (CenCITT), Dr. Rogers is experienced in design calculations for a variety of environmental unit operations: air and steam stripping, carbon adsorption, catalytic oxidation, activated-sludge wastewater treatment, and others.

Process & Product Improvement

Dr. Rogers is advancing environmentally conscious process design in two areas: (1) integrating pollution prevention concepts into chemical processes, and (2) developing new tools and strategies for process evaluation.  He has created software tools to evaluate processes by criteria such as economics, safety, toxicity, and environmental impact.  Dr. Rogers served as faculty advisor to Consumer Product Manufacturing (CPM) a client-sponsored enterprise in which students develop new consumer products, manufacturing equipment, and packaging/shipping options.

Physical Property Research

A major focus of Dr. Rogers' research is to address the need for reliable physical property data for process design and simulation. Under the direction of AIChE/DIPPR® (Design Institute for Physical Properties), Dr. Rogers has worked since 1991 to provide property data to industry in the environmental, safety, and health areas.  He has also conducted experimental VLE and LLE studies for air-water-organic systems and measured distribution ratios of organic chemicals between water and ionic liquid phases at equilibrium.

Electrical Energy Storage

Research sponsored by the U.S. DOE and the Michigan Universities Commercialization Initiative (MICU) has resulted in the development of a rechargeable asymmetric battery consisting of a nickel-carbon foam positive electrode and an electrolytic capacitor negative electrode.

Research Interests

  • Process simulation and improvement
  • Physical property prediction and measurement
  • Electrical energy storage