(6be) Fundamental Understanding of Non-Traditional Feedstock Conversion Processes

Toraman, H. E., University of Delaware
Research Interests:

The rapid development of novel processes based on utilization of non-traditional feedstocks for the production of fuels and chemicals is crucial for a sustainable and independent economy. The scientific advancements strongly depend on the systematic and fundamental understanding of these processes. In my future research, I will investigate processes for the direct conversion of shale gas and hydrocarbon polymers to chemicals and fuels by combining data science and experiments. Previously, I performed a systematic investigation on the effect of biomass composition on product composition using a large set of well-defined feedstocks with an engineered lignin composition. Statistical data analysis techniques enabled not only finding correlations within large datasets but also faster processing and evaluation of the results. Currently, I am investigating high-temperature catalytic processes where the interplay between gas phase and surface chemistry is poorly understood. Last but not least, I plan to use my experience in microkinetic modeling and reactor design to obtain detailed insights into the reaction chemistry and provide guidelines for process optimization.

Teaching Interests:

The future of our society lies with young people and well-educated chemical engineers will play a major role among others. As a faculty member, I will give the utmost importance to prepare my students with the right skills that will allow them to succeed in a dynamic, fast and challenging environment. Based on my chemical engineering background, I strongly believe that I can be involved in all chemical engineering courses at an undergraduate level. I will design my courses in a way that the students will actively take part and improve their critical thinking skills during the class via interactive exercises and team projects. I would also like to share my knowledge and research experience via specialized courses such as “Conversion Processes for Non-Traditional Feedstocks” and “Multivariate Data Analysis for Chemical Engineers”. The first course aims at setting the scene for challenges and opportunities for the valorization of non-traditional feedstocks for the production of fuels and chemicals whereas the latter will provide an introduction on how to use data science in chemical engineering to advance faster and become more efficient.