(9f) Effect of Ionic Liquid On Microfluidic Electrophoretic Separation of Phenolic Acids | AIChE

(9f) Effect of Ionic Liquid On Microfluidic Electrophoretic Separation of Phenolic Acids

Authors 

Chang, S. T. - Presenter, Sandia National Laboratories
Bharadwaj, R. - Presenter, Sandia National Laboratories, Joint BioEnergy Institute
Singh, S. - Presenter, Sandia National Laboratory
Singh, A. K. - Presenter, Sandia National Laboratories


There is a growing interest in the production of biofuels from a variety of cellulosic feedstock crops such as Switchgrass, Miscanthus, and Corn Stover. The presence of lignin in the plant cell walls is a major source of biomass recalcitrance. Recently, several studies have shown that ionic liquids (ILs) can effectively de-polymerize biomass and enable enhanced enzymatic hydrolysis rates. However, due to a lack of IL-compatible analytical techniques, the molecular level understanding of the biomass deconstruction process is difficult. This limits the rational optimization of biomass pretreatment processes. Our aim is to develop a label-free IL-compatible electrophoresis approach to quantify lignin degradation products. Our approach leverages the autofluorescene of phenolic compounds, such as Ferulic acid and p-Coumaric acid, for label-free detection. We have also investigated the effect of room temperature ionic liquid, 1-ethyl-3-methylimmidazolium acetate (EMIM-Acetate), on electrokinetic properties of glass microchips. Interestingly, even as little as 0.2% (v/v) IL solution can reduce the electroosmotic flow (EOF) by 10-fold at highly basic pH (> 9.0). In addition, there is a distinct timescale associated with the rate of decrease of EOF at a fixed IL concentration. This indicates that EMIM-Acetate adsorbs to the surface of the glass microchip. We are developing electrokinetic models to investigate the dynamics of IL adsorption and EOF suppression in glass microchips. We have demonstrated the microfluidic electrophoretic separation of model phenolic compounds in presence of IL within 60 s with a detection limit of around 5 µg/mL. We are currently extending the approach to analyze real-world cellulosic biomass samples to optimize pretreatment processes for bioenergy production.