Mentor Areas
Rui's research interests focus on understanding how the physical and chemical properties of metal nanocatalysts evolve while they are subjected to electrochemical conditions used in energy conversion chemical reactions. That involves the study of liquid-ion battery electrodes as well as chemical reactions, such as the oxygen and hydrogen evolution reactions. Rui uses and interprets data from a suite of techniques that include, ink-jet high-precision micro-deposition, scanning/transmission electron microscopy, electrochemical potentiometry, X-ray diffraction, photoelectron, and Raman spectroscopy. In a parallel project, he perform multi-variate analysis of catalytic rate data to model the kinetics and understand the reactions mechanism of important chemical reactions, such as methane upgrading to methanol and CO2 sequestration. He is advised by Prof. Eric Stach of MSE department.
Description:
Hydrogen (H2) is the most prominent feed-stock for hydrogen fuel cells. However, at ambient conditions H2 is a gas and under pressurized conditions it is dangerously explosive. For that reason, methanol - a liquid at ambient conditions - is used as an energy dense hydrogen reservoir (H2). To use methanol as the hydrogen source, we need to develop a viable technology that allows decentralized on-demand methanol decomposition to hydrogen (and other by-products). Ni3Sn and Ni3Al nanoparticles are cheap and stable catalysts for the decomposition of methanol to H2 at temperatures below 200 oC. However the reaction mechanism and kinetics of this reaction have not been elucidated in depth.
The student will be involved in a guided data mining project to collect, organize and normalize rate and selectivity data from previously published methanol decomposition to H2 experiments catalyzed by the Ni3Sn and Ni3Al. The student will then contribute for the statistical analysis of the data to relate productivity (activity) and selectivity to the catalyst properties and reaction conditions. This information will be used to infer about the underlying reaction mechanisms and to develop rate laws that model the reaction kinetics at different conditions.
Preferred Qualifications
- Proficiency with Microsoft Excel (or equivalent spreadsheet software) is necessary.
- Knowledge on statistics and interpretation of statistical tests is preferred
- Students with general interest in energy conversion science and technology are highly encouraged
Details:
Preferred Student Year
First-year, Second-Year, Junior, Senior
Volunteer
Yes
Yes indicates that faculty are open to volunteers.Paid
No
Yes indicates that faculty are open to paying students they engage in their research, regardless of their work-study eligibility.Work Study
No
Yes indicates that faculty are open to hiring work-study-eligible students.