Direct Air Capture Post Doc

The overall objective of this multi-year effort is to focus and coordinate NETL R&IC efforts toward the development of a DAC demonstration module for testing in the DAC center in EY 26. This integrated experience will be accomplished by optimizing the properties of an NETL-developed DAC sorbent, designing a DAC process that capitalizes on the strengths of the sorbent and culminating in EY25 with a prototype process at a scale appropriate to the DAC center. Developing and testing of the subscale module assembles in EY23 will provide validation data for CFD and systems studies guiding the research. The final product (in EY25) will be a design for a 3000 scfm module for testing in the DAC center.

In the first year of the effort, the ORISE research associate (RA) will investigate the physical DAC reactor configuration for this unique capture material being developed at NETL. The initial form of the capture material is a fiber. The fiber, provided to this task effort, needs to be made into various devise configurations that minimize reactor/adsorber pressure drop while maximizing CO2 uptake. It is planned to look at a number of parallel and cross flow concepts which the RA will make. There is an inherent optimization required as maximizing the fiber capture material in the contactor will increase/maximize the CO2 uptake – but will also maximize the pressure drop (energy consumption).  So, the question arises that needs experimental validation at multiple scales; what is the best configuration where the CO2 uptake on a daily/cycle average is maximized for an acceptable pressure drop. Additionally, what is the functionality of this uptake with acceptable pressure drop. 

We are seeking, ideally, a Ph.D. in Chemical Engineering or equivalent (MS with 2 years course and work experience or BS with 3+ years course and work experience) with experience in solid - gas systems, ex. CO2 capture with solid sorbents. Experience in building reactor devices with particle or structured sorbents or solid reactants. Hands on experience with comfort in assembling various reactor configurations and testing them. Familiar with: (1) Bayesian statistical and/or other AI analysis techniques to optimize the configuration, (2) use of PYTHON and (3) time series analysis techniques. Exposure to CFD software applications would be a plus – but this position is a handson experimental position.