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Related Experiment Video

Updated: Jul 6, 2025

Extraction of Lignin with High β-O-4 Content by Mild Ethanol Extraction and Its Effect on the Depolymerization Yield

Extraction of Lignin with High β-O-4 Content by Mild Ethanol Extraction and Its Effect on the Depolymerization Yield

Published on: January 7, 2019

Atomistic Simulations of Polydisperse Lignin Melts Using Simple Polydisperse Residue Input Generator.

Vaidyanathan Sethuraman¹, Josh V Vermaas², Luna Liang³

¹Center for Molecular Biophysics, Oak Ridge National Laboratory, 1-Bethel Valley Road, Oak Ridge, Tennessee 37830, United States.

Biomacromolecules

|December 29, 2023

Summary

We developed SPRIG to model lignin melts, finding that molecular weight distribution impacts dynamics above the glass transition temperature (Tg) but not static properties.

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Last Updated: Jul 6, 2025

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Towards Biomimicking Wood: Fabricated Free-standing Films of Nanocellulose, Lignin, and a Synthetic Polycation

Towards Biomimicking Wood: Fabricated Free-standing Films of Nanocellulose, Lignin, and a Synthetic Polycation

Published on: June 17, 2014

Area of Science:

Biophysics
Polymer Physics
Plant Science

Background:

Lignin's complex structure influences plant cell walls and biomass applications.
Understanding lignin physics is crucial for biofuels and bioproducts.
Current models often simplify lignin's natural polydisperse state.

Purpose of the Study:

To develop a computational tool (SPRIG) for generating atomic-detail models of random, polydisperse lignin melts.
To investigate the conformational and dynamic properties of switchgrass lignin melts using molecular dynamics (MD) simulations.
To assess the impact of polydispersity, branching, and sequence on lignin properties.

Main Methods:

Utilized SPRIG to create atomic-detail models of random polydisperse lignin copolymer melts.
Performed all-atom molecular dynamics (MD) simulations on these models.
Analyzed properties such as glass transition temperature (Tg), radius of gyration, and atomic mean squared displacements.

Main Results:

Polydispersity, branching, and monolignol sequence did not influence the glass transition temperature (Tg).
The Flory-Huggins scaling parameter indicated polymer chain statistics between globular and ideal Gaussian.
Above Tg, atomic dynamics (mean squared displacements) were dependent on molecular weight, decreasing with increasing weight.

Conclusions:

A monodisperse lignin melt model is sufficient for static property analysis.
Molecular weight distribution is a critical factor for understanding lignin dynamics, especially above Tg.
This work provides insights into lignin physics relevant to plant cell wall function and biomass conversion.