Lignin is a potential
resource for biobased aromatics with applications
in the field of fuel additives, resins, and bioplastics. Via a catalytic
depolymerization process using supercritical ethanol and a mixed metal
oxide catalyst (CuMgAlOx), lignin can
be converted into a lignin oil, containing phenolic monomers that
are intermediates to the mentioned applications. Herein, we evaluated
the viability of this lignin conversion technology through a stage-gate
scale-up methodology. Optimization was done with a day-clustered Box–Behnken
design to accommodate the large number of experimental runs in which
five input factors (temperature, lignin-to-ethanol ratio, catalyst
particle size, catalyst concentration, and reaction time) and three
output product streams (monomer yield, yield of THF-soluble fragments,
and yield of THF-insoluble fragments and char) were considered. Qualitative
relationships between the studied process parameters and the product
streams were determined based on mass balances and product analyses.
Linear mixed models with random intercept were employed to study quantitative
relationships between the input factors and the outcomes through maximum
likelihood estimation. The response surface methodology study reveals
that the selected input factors, together with higher order interactions,
are highly significant for the determination of the three response
surfaces. The good agreement between the predicted and experimental
yield of the three output streams is a validation of the response
surface methodology analysis discussed in this contribution.