Annual Review of Chemical and Biomolecular Engineering - Volume 11, 2020

I profile my personal and professional journey from being a girl of the 1950s, with expectations typical for the times, to a chemical engineering professor and still-enthusiastic researcher. I describe my family, my early education, my college and graduate school training in physics, my postdoc years in chemistry, and my subsequent transformation into a chemical engineering faculty member—one of the first women to be appointed to a chemical engineering faculty in the United States. I focus on the events that shaped me, the people who noticed and supported me, and the environment for women scientists and engineers in what some would call the “early days.” My initial research activities centered on applications of statistical mechanics to predict phase equilibria in simple systems. Over time, my interests evolved to focus on applying molecule-level computer simulations to systems of interest to chemical engineers, e.g., hydrocarbons and polymers. Eventually, spurred on by my personal interest in amyloid diseases and my wish to make a contribution to human health, I turned to more biologically oriented problems having to do with protein aggregation and protein design. I give a candid assessment of my strengths and weaknesses, successes and failures. Finally, I share the most valuable lessons that I have learned over a lifetime of professional and personal experience.

John Davidson was widely recognized as the founding father of fluidization in chemical engineering. He was a great thinker and had a tremendous ability to distill complicated problems into much simpler concepts. Much of his thinking was set out, along with that of his coauthor David Harrison, in their book Fluidised Particles, first published in 1963, a book that is still used today. John was still coming into his office in Cambridge until the very last weeks of his life, where he continued to work with final-year undergraduates and graduate students. Fluidization, and two-phase flows, continued to fascinate him, and that enthusiasm was transmitted to those around him. The following article was the last work that he wrote and was very much a reflection on his life and career. John passed away on Christmas Day 2019, with the article in its final stages of preparation.

Nature has evolved a wide range of strategies to create self-assembled protein nanostructures with structurally defined architectures that serve a myriad of highly specialized biological functions. With the advent of biological tools for site-specific protein modifications and de novo protein design, a wide range of customized protein nanocarriers have been created using both natural and synthetic biological building blocks to mimic these native designs for targeted biomedical applications. In this review, different design frameworks and synthetic decoration strategies for achieving these functional protein nanostructures are summarized. Key attributes of these designer protein nanostructures, their unique functions, and their impact on biosensing and therapeutic applications are discussed.

Further development of biomass conversions to viable chemicals and fuels will require improved atom utilization, process efficiency, and synergistic allocation of carbon feedstock into diverse products, as is the case in the well-developed petroleum industry. The integration of biological and chemical processes, which harnesses the strength of each type of process, can lead to advantaged processes over processes limited to one or the other. This synergy can be achieved through bioprivileged molecules that can be leveraged to produce a diversity of products, including both replacement molecules and novel molecules with enhanced performance properties. However, important challenges arise in the development of bioprivileged molecules. This review discusses the integration of biological and chemical processes and its use in the development of bioprivileged molecules, with a further focus on key hurdles that must be overcome for successful implementation.

We review the modern state of cellular automata (CA) applications for solving practical problems in chemistry and chemical technology. We consider the problems of material structure modeling and prediction of materials’ morphology-dependent properties. We review the use of the CA approach for modeling diffusion, crystallization, dissolution, erosion, corrosion, adsorption, and hydration processes. We also consider examples of hybrid CA-based models, which are combinations of various CA with other computational approaches and modeling methods. Finally, we discuss the use of high-performance parallel computing to increase the efficiency of CA.

Flow, heat, and mass transfer in fixed beds of catalyst particles are complex phenomena and, when combined with catalytic reactions, are multiscale in both time and space; therefore, advanced computational techniques are being applied to fixed bed modeling to an ever-greater extent. The fast-growing literature on the use of computational fluid dynamics (CFD) in fixed bed design reflects the rapid development of this subfield of reactor modeling. We identify recent trends and research directions in which successful methodology has been established, for example, in computer generation of packings of complex particles, and where more work is needed, for example, in the meshing of nonsphere packings and the simulation of industrial-size packed tubes. Development of fixed bed reactor models, by either using CFD directly or obtaining insight, closures, and parameters for engineering models from simulations, will increase confidence in using these methods for design along with, or instead of, expensive pilot-scale experiments.

In the wake of sustainable development, materials research is going through a green revolution that is putting energy-efficient and environmentally friendly materials and methods in the limelight. In this quest for greener alternatives, covalent organic frameworks (COFs) have emerged as a new generation of designable crystalline porous polymers for a wide array of clean-energy and environmental applications. In this contribution, we categorically review the merits and shortcomings of COF bulk powders, nanosheets, freestanding thin films/membranes, and membranes on porous supports in various separation processes, including separation of gases, pervaporation, organic solvent nanofiltration, water purification, radionuclide sequestration, and chiral separations, with particular reference to COF material pore size, host–guest interactions, stability, selectivity, and permeability. This review covers the fabrication strategies of nanosheets, films, and membranes, as well as performance parameters, and provides an overview of the separation landscape with COFs in relation to other porous polymers, while seeking to interpret the future research opportunities in this field.

Cells adapt to changing environments. Perturb a cell and it returns to a point of homeostasis. Perturb a population and it evolves toward a fitness peak. We review quantitative models of the forces of adaptation and their visualizations on landscapes. While some adaptations result from single mutations or few-gene effects, others are more cooperative, more delocalized in the genome, and more universal and physical. For example, homeostasis and evolution depend on protein folding and aggregation, energy and protein production, protein diffusion, molecular motor speeds and efficiencies, and protein expression levels. Models provide a way to learn about the fitness of cells and cell populations by making and testing hypotheses.

The production of thermoset polymers is increasing globally owing to their advantageous properties, particularly when applied as composite materials. Though these materials are traditionally used in more durable, longer-lasting applications, ultimately, they become waste at the end of their usable lifetimes. Current recycling practices are not applicable to traditional thermoset waste, owing to their network structures and lack of processability. Recently, researchers have been developing thermoset polymers with the right functionalities to be chemically degraded under relatively benign conditions postuse, providing a route to future management of thermoset waste. This review presents thermosets containing hydrolytically or solvolytically cleavable bonds, such as esters and acetals. Hydrolysis and solvolysis mechanisms are discussed, and various factors that influence the degradation rates are examined. Degradable thermosets with impressive mechanical, thermal, and adhesion behavior are discussed, illustrating that the design of material end-of-life need not limit material performance.

Design in the chemical industry increasingly aims not only at economic but also at environmental targets. Environmental targets are usually best quantified using the standardized, holistic method of life cycle assessment (LCA). The resulting life cycle perspective poses a major challenge to chemical engineering design because the design scope is expanded to include process, product, and supply chain. Here, we first provide a brief tutorial highlighting key elements of LCA. Methods to fill data gaps in LCA are discussed, as capturing the full life cycle is data intensive. On this basis, we review recent methods for integrating LCA into the design of chemical processes, products, and supply chains. Whereas adding LCA as a posteriori tool for decision support can be regarded as established, the integration of LCA into the design process is an active field of research. We present recent advances and derive future challenges for LCA-based design.

Chromatography has long been, and remains, the workhorse of downstream processing in the production of biopharmaceuticals. As bioprocessing has matured, there has been a growing trend toward seeking a detailed fundamental understanding of the relevant unit operations, which for some operations include the use of mechanistic modeling in a way similar to its use in the conventional chemical process industries. Mechanistic models of chromatography have been developed for almost a century, but although the essential features are generally understood, the specialization of such models to biopharmaceutical processing includes several areas that require further elucidation. This review outlines the overall approaches used in such modeling and emphasizes current needs, specifically in the context of typical uses of such models; these include selection and improvement of isotherm models and methods to estimate isotherm and transport parameters independently. Further insights are likely to be aided by molecular-level modeling, as well as by the copious amounts of empirical data available for existing processes.

Peptide–polymer conjugates are a class of soft materials composed of covalently linked blocks of protein/polypeptides and synthetic/natural polymers. These materials are practically useful in biological applications, such as drug delivery, DNA/gene delivery, and antimicrobial coatings, as well as nonbiological applications, such as electronics, separations, optics, and sensing. Given their broad applicability, there is motivation to understand the molecular and macroscale structure, dynamics, and thermodynamic behavior exhibited by such materials. We focus on the past and ongoing molecular simulation studies aimed at obtaining such fundamental understanding and predicting molecular design rules for the target function. We describe briefly the experimental work in this field that validates or motivates these computational studies. We also describe the various models (e.g., atomistic, coarse-grained, or hybrid) and simulation methods (e.g., stochastic versus deterministic, enhanced sampling) that have been used and the types of questions that have been answered using these computational approaches.

New experimental technology and theoretical approaches have advanced battery research across length scales ranging from the molecular to the macroscopic. Direct observations of nanoscale phenomena and atomistic simulations have enhanced the understanding of the fundamental electrochemical processes that occur in battery materials. This vast and ever-growing pool of microscopic data brings with it the challenge of isolating crucial performance-decisive physical parameters, an effort that often requires the consideration of intricate interactions across very different length scales and timescales. Effective physics-based battery modeling emphasizes the cross-scale perspective, with the aim of showing how nanoscale physicochemical phenomena affect device performance. This review surveys the methods researchers have used to bridge the gap between the nanoscale and the macroscale. We highlight the modeling of properties or phenomena that have direct and considerable impact on battery performance metrics, such as open-circuit voltage and charge/discharge overpotentials. Particular emphasis is given to thermodynamically rigorous multiphysics models that incorporate coupling between materials’ mechanical and electrochemical states.

Regulatory bodies worldwide consider N-glycosylation to be a critical quality attribute for immunoglobulin G (IgG) and IgG-like therapeutics. This consideration is due to the importance of posttranslational modifications in determining the efficacy, safety, and pharmacokinetic properties of biologics. Given its critical role in protein therapeutic production, we review N-glycosylation beginning with an overview of the myriad interactions of N-glycans with other biological factors. We examine the mechanism and drivers for N-glycosylation during biotherapeutic production and the several competing factors that impact glycan formation, including the abundance of precursor nucleotide sugars, transporters, glycosidases, glycosyltransferases, and process conditions. We explore the role of these factors with a focus on the analytical approaches used to characterize glycosylation and associated processes, followed by the current state of advanced glycosylation modeling techniques. This combination of disciplines allows for a deeper understanding of N-glycosylation and will lead to more rational glycan control.

This review article discusses the solution of population balance equations, for the simulation of disperse multiphase systems, tightly coupled with computational fluid dynamics. Although several methods are discussed, the focus is on quadrature-based moment methods (QBMMs) with particular attention to the quadrature method of moments, the conditional quadrature method of moments, and the direct quadrature method of moments. The relationship between the population balance equation, in its generalized form, and the Euler-Euler multiphase flow models, notably the two-fluid model, is thoroughly discussed. Then the closure problem and the use of Gaussian quadratures to overcome it are analyzed. The review concludes with the presentation of numerical issues and guidelines for users of these modeling approaches.

Positron emission particle tracking (PEPT) is a noninvasive technique capable of imaging the three-dimensional dynamics of a wide variety of powders, particles, grains, and/or fluids. The PEPT technique can track the motion of particles with high temporal and spatial resolution and can be used to study various phenomena in systems spanning a broad range of scales, geometries, and physical states. We provide an introduction to the PEPT technique, an overview of its fundamental principles and operation, and a brief review of its application to a diverse range of scientific and industrial systems.

Fluid–solid systems play a major role in a wide variety of industries, from pharmaceutical and consumer goods to chemical plants and energy generation. Along with this variety of fields comes a diversity in apparatuses and applications, most prominently fluidized and spouted beds, granulators and mixers, pneumatic conveying, drying, agglomeration, coating, and combustion. The most promising approach for modeling the flow in these systems is the CFD-DEM method, coupling computational fluid dynamics (CFD) for the fluid phase and the discrete element method (DEM) for the particles. This article reviews the progress in modeling particle–fluid flows with the CFD-DEM method. A brief overview of the basic method as well as methodical extensions of it are given. Recent applications of this simulation approach to separation and classification units, fluidized beds for both particle formation and energy conversion, comminution units, filtration, and bioreactors are reviewed. Future trends are identified and discussed regarding their viability.

We review the impact of control systems and strategies on the energy efficiency of chemical processes. We show that, in many ways, good control performance is a necessary but not sufficient condition for energy efficiency. The direct effect of process control on energy efficiency is manyfold: Reducing output variability allows for operating chemical plants closer to their limits, where the energy/economic optima typically lie. Further, good control enables novel, transient operating strategies, such as conversion smoothing and demand response. Indirectly, control systems are key to the implementation and operation of more energy-efficient plant designs, as dictated by the process integration and intensification paradigms. These conclusions are supported with references to numerous examples from the literature.

Quorum sensing (QS) is a molecular signaling modality that mediates molecular-based cell–cell communication. Prevalent in nature, QS networks provide bacteria with a method to gather information from the environment and make decisions based on the intel. With its ability to autonomously facilitate both inter- and intraspecies gene regulation, this process can be rewired to enable autonomously actuated, but molecularly programmed, genetic control. On the one hand, novel QS-based genetic circuits endow cells with smart functions that can be used in many fields of engineering, and on the other, repurposed QS circuitry promotes communication and aids in the development of synthetic microbial consortia. Furthermore, engineered QS systems can probe and intervene in interkingdom signaling between bacteria and their hosts. Lastly, QS is demonstrated to establish conversation with abiotic materials, especially by taking advantage of biological and even electronically induced assembly processes; such QS-incorporated biohybrid devices offer innovative ways to program cell behavior and biological function.