In my last blog, I emphasized that Green Chemistry Principles provide useful, actionable ways to drive innovation strategies and accelerate transformation in the pulp and paper (P&P) industry. Here, I will focus on a facilitating technology in the development and implementation of biomolecules, biomaterials, and bioproducts from biorefinery: molecular modeling (MM).
Since 1960, the rise in computing power (number of processors and capacity, speed and visualization), has allowed exponential growth of classical and quantum molecular modeling methods, leading to considerable progress in our understanding of fundamental processes.
Understanding molecular modeling
Molecular modeling encompasses all theoretical and computational methods used to model or mimic molecular behaviour. MM development began in the early 1960s, although the underlying math originated much earlier.
The common feature of all MM methods is the atomistic-level insights it provides. Many methods exist, including molecular mechanics, semi-empirical, density functional theory (DFT), molecular dynamics (MD), ab-initio, as well as sampling methods such as replica exchange molecular dynamics (REMD). Selecting a method hinges on whether a quick answer from classical methods (e.g. molecular mechanics) is desired, versus the very high accuracy but time consuming results from quantum-based calculations (ab initio) for small molecular systems.
The University of Tasmania’s Dr. Karen Stack is a P&P molecular modeling pioneer. Her early work on the interactions between poly(ethylene oxide) and phenol-formaldehyde resin remains a reference1. As we entered the new millennium, a concerted effort was needed to broaden the transfer of this technology into the industry.
It all began with the organization of an international symposium series. The 2005 (a global first for this industry), 2008 and 2011 Fundamental and Applied Pulp & Paper Modelling Symposia (FAPPMS) brought together experimental and theoretical scientists working at the cutting edge of papermaking chemistry. Their objectives were to promote use of molecular and classical modelling throughout the industry, and develop more effective molecular systems, in an effort to better understand the underlying mechanisms. Papermakers, suppliers and academics attended these peer-reviewed symposia, supported by PAPTAC, where theoretical and experimental scientists proved molecular and classical modelling are reliable, predictive, and powerful tools in solving real papermaking problems (Figure 1).
Interplay between theoretical and experimental work
One notable example of experimental and subsequent theoretical success was the discovery of nanotubes of styrene maleic anhydride (SMA) polymer, used as a papermaking sizing agent (minimizing ink penetration and improving paper sheet printing quality). The change in SMA particle size as a function of pH in water was first experimentally observed at McGill University in 2000 by Garnier et al2.
Later, Professor Malardier-Jugroot from Royal Military College of Canada used theoretical molecular modeling (in-silico method) to predict that SMA nanotubes exist at neutral pH3. Today, the Malardier-Jugroot discovery is evolving. Drugs are introduced into SMA-based nanotubes and subsequently released when encountering cancer cells, which are highly acidic. This phenomenon is caused by the systematic disruption of the SMA nanotubes when exposed to highly acidic or alkaline conditions.
Interestingly, during my own PhD work about half of my colleagues began with experimental results subsequently proven by MM, while the other half made theoretical discoveries (in-silico) which were then experimentally proven. It’s clear that MM can be used to explain underlying mechanisms and create new molecular and material models, which require validation by experimental evidence.
Case study: Molecular modeling of green chemistry
In 2003, during my PhD work the molecular modeling of solvated (PEO)6/TGG/(H2O)906 systems took five weeks to converge after 75 picoseconds (ps) of molecular time, using one processor4. Less than fifteen years later, my colleagues at Université de Montréal, Professor Normand Mousseau and Mr. Vincent Binette, and I are studying larger molecular systems in Alzheimer research (beta-amyloid protein, natural ligand and water). Running over 30 times 900 ns (27 µs in total molecular time), the 67,000-atom systems now take 2.5 months to converge, using 360 processors on a cutting-edge supercomputer.
This example highlights the remarkable evolution of molecular modeling, and its potential to help the biorefinery industry enter new application fields.
Benefits of MM in biorefinery
Within the biorefinery industry’s necessary transformation (biomolecules, biomaterials, and bio-products), MM can accelerate the development and implementation of numerous business opportunities. Obvious examples include green chemistry from forestry for the pharmaceutical and nanocellulose industries. Moreover, scientists can generate data and experimental evidence in the lab while molecular modeling calculations are processing!
More than ever, computing power is transforming our understanding of the world, from the atomic scale (e.g. details of chemical interactions between molecules) to our universe’s broadest horizons (e.g. galaxy formation). Clearly, molecular and classical modeling will continue to underpin prolific discoveries and development of sustainable innovations toward a greener future for the biorefinery industry.
1 Colloids Surf., 1991, 61, 205-218.
2 Association in Solution and Adsorption at an Air-Water Interface of Alternating Copolymers of Maleic Anhydride and Styrene, Langmuir 2000,16(8),3757.
3 2005, J. Phys. Chem. B2005,109,7022-7032.
4 Molecular Simulation, 32,1,2006,17–27.
The 2016 Canadian Green Chemistry and Engineering Award, sponsored by Green Centre Canada, was awarded to Dr. Roger Gaudreault for his significant contribution to Green Chemistry research and development through 30 years of dedicated work for the Pulp and Paper Industry, industrial water treatment and renewable energy.
Dr. Gaudreault's expertise notably spearheaded him to develop an integrated innovation Green Chemistry approach based on recycled fibres. His scientific and applied background helped developed strong partnerships between academia and industry. He has been a member of the Centre in Green Chemistry and Catalysis (CGCC) since 2011 and associate member of the Quebec Centre for Advanced Materials (QCAM) since 2018. Dr. Gaudreault's scientific interests include; green chemistry, neuroscience, kinetics of colloids, chemistry of pulping/bleaching and papermaking, recycling, corrosion inhibition, biomaterials and biofuels from wood biomass, and molecular modelling. Dr. Gaudreault did a Post-Doctoral Fellowship co-supervised by Professors David A. Weitz from Harvard University and Theo van de Ven from McGill University (2005-2006). He completed a PhD on molecular modelling from McGill University (2003); MSc. in Pulp and Paper from Université du Québec à Trois-Rivières (1991); and a BSc in Chemistry from Université du Québec à Chicoutimi (1986).
Dr. Gaudreault has also been named PAPTAC Fellow 2017 in recognition of his outstanding long-term and significant contribution to the Association, the pulp & paper and forest products industry and for the advancement of science and technology in the industry.