Multilevel Mesoscale Complexities in Mesoregimes: Challenges in Chemical and Biochemical Engineering

Abstract

This review discusses the complex behaviors in diverse chemical and biochemical systems to elucidate their commonalities and thus help develop a mesoscience methodology to address the complexities in even broader topics. This could possibly build a new scientific paradigm for different disciplines and could meanwhile provide effective tools to tackle the big challenges in various fields, thus paving a path toward combining the paradigm shift in science with the breakthrough in technique developments. Starting with our relatively fruitful understanding of chemical systems, the discussion focuses on the relatively pristine but very intriguing biochemical systems. It is recognized that diverse complexities are multilevel in nature, with each level being multiscale and the complexity emerging always at mesoscales in mesoregimes. Relevant advances in theoretical understandings and mathematical tools are summarized as well based on case studies, and the convergence between physics and mathematics is highlighted. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering, Volume 13 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Molecular Dynamics Simulation of In Situ Polymerization: Chain Conformation Transition

“…These observations above seem to share similarities with the complex structures in chemical/biochemical engineering. 36,37 In the in situ polymerization system, the spatiotemporal heterogeneous distribution and orientation of the nascent chains are controlled by at least two dominant mechanisms. Consequently, three distinct regimes occur successively as the relative dominance of the cohesive energy arising from nascent chains surpasses the attractive energy arising from the sidewalls and the transition structures in the compromising regime.…”

“…In the case of polymer synthesis, where the molecular composition and reaction pathways are well-defined, researchers seek to understand the evolution of polymer conformation and aggregation structures during the growth process and the underlying dominant mechanisms, which is a mesoscale problem between the growth and motion of the nascent chain. 36,37 Therefore, when investigating conformational transitions during polymerization, it is common to sacrifice a certain degree of precision and simplify the polymerization process into bond formation under certain conditions. The nonreactive atoms in the polymerization system follow classical molecular dynamics, while the reaction process is achieved using the connection-altering atomistic Monte Carlo (MC) method.…”

“…Density functional theory (DFT), based on quantum mechanical principles, can accurately describe the electronic structures and free energy changes, making it widely used in simulating chemical reaction processes. , Additionally, the development of the reactive force field (ReaxFF) within the molecular dynamics (MD) method allows for some of the polymer reaction simulation. − Although these methods exhibit high accuracy and can predict intermediate and deep-level reaction products, the system size is limited to thousands of atoms, with simulation time ranging from tens to hundreds of picoseconds, which is far from meeting the requirement of in situ polymerization simulation. In the case of polymer synthesis, where the molecular composition and reaction pathways are well-defined, researchers seek to understand the evolution of polymer conformation and aggregation structures during the growth process and the underlying dominant mechanisms, which is a mesoscale problem between the growth and motion of the nascent chain. , Therefore, when investigating conformational transitions during polymerization, it is common to sacrifice a certain degree of precision and simplify the polymerization process into bond formation under certain conditions. The nonreactive atoms in the polymerization system follow classical molecular dynamics, while the reaction process is achieved using the connection-altering atomistic Monte Carlo (MC) method. , The hybrid MD–MC algorithm expands the simulation dimension of the polymer reaction system and has been applied in investigating polymer cross-linking and entanglement .…”