Experimental and modelling studies of the diffusion and rotational dynamics of simple lignin derivatives

The dynamics of key components of lignin pyrolysis oil (anisole, guaiacol and all three cresol isomers) have been studied through a combined quasielastic neutron scattering (QENS) and molecular dynamics (MD) simulation approach from 330-390 K. QENS revealed both jump diffusion (with diffusion coefficients in the range of 9–72 × 10 − 10 m 2 s −1 ) and isotropic rotation (7–22 × 10 10 s −1 ) over the timescale of the instrument, with jump diffusion rates decreasing in the sequence: anisole > guaiacol ≈ o -cresol > p -cresol ≈ m -cresol. The study shows the impact of functional group type and molecular shape on diffusion behaviours, where the absence of a hydroxyl group in anisole facilitated the fastest diffusion. Guaiacol and o -cresol showed faster diffusion than the m - and p - cresol isomers due to the placement of a methyl or methoxy group in the ortho position relative to the hydroxyl group, which hindered intermolecular hydrogen bonding. By mapping the MD output onto the experimental space, similar rates of jump diffusion were observed. The slightly slower diffusion rates for cresol isomers in the simulations compared to experiment were attributed to an overestimation of hydrogen bonding interactions. Calculations of the mean-squared-displacement over longer timescales revealed slower self-diffusion coefficients than those calculated from the MD jump diffusion analysis by a factor of ∼1.5–5 depending on temperature, highlighting issues in extracting accurate translational and rotational coefficients using the conventional analytical models often applied to QENS, from MD simulations. • Lignin derivatives anisole, guaiacol, and cresol isomer dynamics studied via QENS and MD. • Anisole diffuses fastest; hydrogen bonding reduces cresol isomer mobility. • Conventional (QENS) models struggle to extract accurate diffusion and rotation coefficients. • Slower bulk self-diffusion observed over longer timescales, highlighting model limitations. • Analytical (QENS) models still useful for verifying MD trends in bulk behaviour.