RobJustRob

[RobJustRob @Robert_Newman97]

@frhung @AntonRepnikov @NU_ChemE @michaelnguy14 @JenLi67269204 This is especially apparent when defining components for the simulation, where SuperPro has more biological components already defined (i.e. biomass) while Aspen relies more on user-defined components.

[RobJustRob @Robert_Newman97]

@frhung @AntonRepnikov @NU_ChemE @michaelnguy14 @JenLi67269204 Thanks! While both programs have the ability to handle biological processes, we found Aspen to be more tailored towards modeling thermodynamic interactions and SuperPro to be better equipped for biological ones (i.e. cell growth, AAV production, etc.).

[RobJustRob @Robert_Newman97]

@CocoonitL @NU_ChemE Great job with the poster, the proof-of-concept results especially are extensive and informative!

Just a quick question regarding Figure3(B): How did you measure the % of droplets gelled?

[RobJustRob @Robert_Newman97]

@TheRealNatural @cwribaudo @nour_naja @PateraMagdalini @CharlesChierico @NU_ChemE Great job developing the poster, the colorimetry analysis is especially interesting!

Since you mention three readings per sample for the experiment, how large would you estimate your margin for error is within your results for average transmittance%?

[RobJustRob @Robert_Newman97]

@sofiakcatalina @MaryLouNadeau @katelynripley @paigekru @AlexisDubs The poster looks great, especially the wealth of experimental data!

Would you be open to elaborating on the model you used, and specifically on the equations and/or key parameters incorporated into the model you used to predict battery response throughout cycling?