Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Classification and Mechanical Properties of Synthetic Polymers01:28

Classification and Mechanical Properties of Synthetic Polymers

Synthetic polymers are classified as elastomers, fibers, or plastics based on their crystallinity. Crystallinity, the degree of long-range order in the solid state, influences the mechanical properties (stretching or contracting) of elastomers. Elastomers are flexible polymers that can expand or contract easily upon the application of an external force. They have numerous crosslinks that pull them back into their original shape when stress is removed. Silicones, for instance, are highly elastic...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Diol-Induced Lignin Stabilization Facilitates Softwood Saccharification.

ChemSusChem·2026
Same author

A Robust and Universal LC-MS/MS Method for Determination of N-Nitrosodimethylamine in Pharmaceuticals Using a C30 Column.

Journal of separation science·2026
Same author

Diol-enhanced natural deep eutectic solvents for efficient poplar pretreatment.

Frontiers in chemistry·2026
Same author

Prevalence and Relative Proportions of MS, NMOSD, and MOGAD in the Republic of Korea.

Neurology·2026
Same author

Sustainable Protective Composite Textiles: Valorizing Hemp Hurd and Corn Stover Lignin via Electrospinning.

Polymers·2026
Same author

Initial Condition Decision to Ensure Reliable Circadian Phase Estimation With Shorter-Term Wearable Data.

Journal of biological rhythms·2026

Related Experiment Video

Updated: Jun 18, 2026

Towards Biomimicking Wood: Fabricated Free-standing Films of Nanocellulose, Lignin, and a Synthetic Polycation
11:26

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

Published on: June 17, 2014

16.5K

Real-Time Model Predictive Control of Lignin Properties Using an Accelerated kMC Framework with Artificial Neural

Juhyeon Kim1,2, Jiae Ryu3, Qiang Yang4

  • 1Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, Texas 77845, United States.

Industrial & Engineering Chemistry Research
|December 9, 2024
PubMed
Summary

This study introduces an AI-powered model to speed up lignin processing simulations. By integrating machine learning with kinetic Monte Carlo methods, it enables real-time control of complex lignin properties.

More Related Videos

High-throughput Screening of Recalcitrance Variations in Lignocellulosic Biomass: Total Lignin, Lignin Monomers, and Enzymatic Sugar Release
11:31

High-throughput Screening of Recalcitrance Variations in Lignocellulosic Biomass: Total Lignin, Lignin Monomers, and Enzymatic Sugar Release

Published on: September 15, 2015

9.9K
Ultrafast Lignin Extraction from Unusual Mediterranean Lignocellulosic Residues
09:22

Ultrafast Lignin Extraction from Unusual Mediterranean Lignocellulosic Residues

Published on: March 9, 2021

6.5K

Related Experiment Videos

Last Updated: Jun 18, 2026

Towards Biomimicking Wood: Fabricated Free-standing Films of Nanocellulose, Lignin, and a Synthetic Polycation
11:26

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

Published on: June 17, 2014

16.5K
High-throughput Screening of Recalcitrance Variations in Lignocellulosic Biomass: Total Lignin, Lignin Monomers, and Enzymatic Sugar Release
11:31

High-throughput Screening of Recalcitrance Variations in Lignocellulosic Biomass: Total Lignin, Lignin Monomers, and Enzymatic Sugar Release

Published on: September 15, 2015

9.9K
Ultrafast Lignin Extraction from Unusual Mediterranean Lignocellulosic Residues
09:22

Ultrafast Lignin Extraction from Unusual Mediterranean Lignocellulosic Residues

Published on: March 9, 2021

6.5K

Area of Science:

  • Biomass Conversion
  • Chemical Engineering
  • Computational Chemistry

Background:

  • Lignin's complex structure hinders understanding of reaction kinetics and property optimization.
  • Mathematical models like multiscale kinetic Monte Carlo (kMC) analyze lignin properties but face computational bottlenecks.
  • The vast number of lignin polymers makes rate calculations a bottleneck for kMC, limiting real-time applications.

Purpose of the Study:

  • To develop a computationally efficient method for simulating lignin properties.
  • To enable real-time control of intricate lignin characteristics.
  • To accelerate the optimization of lignin processing.

Main Methods:

  • Integration of machine learning (ML), specifically artificial neural networks (ANN), into the kMC framework.
  • Development of an ANN-accelerated multiscale kMC (AA-M-kMC) model to predict reaction probability distributions.
  • Incorporation of the AA-M-kMC model into a model predictive controller (MPC) for real-time control.

Main Results:

  • The ANN-accelerated kMC model significantly reduces computational burden compared to traditional kMC.
  • The developed AA-M-kMC model successfully predicts probability distributions, bypassing time-consuming rate calculations.
  • The integrated MPC system demonstrates effective real-time control of complex lignin properties.

Conclusions:

  • The AA-M-kMC approach offers a significant advancement in lignin processing by overcoming computational limitations.
  • This hybrid modeling strategy enhances the applicability of kMC for real-time optimization and control of lignin.
  • The study paves the way for more efficient and precise utilization of lignin in various industrial applications.