Annual review of chemical and biomolecular engineering最新文献

Electrocatalytic conversion of carbon dioxide to valuable chemicals and fuels driven by renewable energy plays a crucial role in achieving net-zero carbon emissions. Understanding the structure-activity relationship and the reaction mechanism is significant for tuning electrocatalyst selectivity. Therefore, characterizing catalyst dynamic evolution and reaction intermediates under reaction conditions is necessary but still challenging. We first summarize the most recent progress in mechanistic understanding of heterogeneous CO₂/CO reduction using in situ/operando techniques, including surface-enhanced vibrational spectroscopies, X-ray- and electron-based techniques, and mass spectroscopy, along with discussing remaining limitations. We then offer insights and perspectives to accelerate the future development of in situ/operando techniques.

Thermophysical properties of fluid mixtures are important in many fields of science and engineering. However, experimental data are scarce in this field, so prediction methods are vital. Different types of physical prediction methods are available, ranging from molecular models over equations of state to models of excess properties. These well-established methods are currently being complemented by new methods from the field of machine learning (ML). This review focuses on the rapidly developing interface between these two approaches and gives a structured overview of how physical modeling and ML can be combined to yield hybrid models. We illustrate the different options with examples from recent research and give an outlook on future developments.

There is growing interest in identifying antibodies that protect against infectious diseases, especially for high-risk individuals and pathogens for which no vaccine is yet available. However, pathogens that manifest as opportunistic or latent infections express complex arrays of virulence-associated proteins and are adept at avoiding immune responses. Some pathogens have developed strategies to selectively destroy antibodies, whereas others create decoy epitopes that trick the host immune system into generating antibodies that are at best nonprotective and at worst enhance pathogenesis. Antibody engineering strategies can thwart these efforts by accessing conserved neutralizing epitopes, generating Fc domains that resist capture or degradation and even accessing pathogens hidden inside cells. Design of pathogen-resistant antibodies can enhance protection and guide development of vaccine immunogens against these complex pathogens. Here, we discuss general strategies for design of antibodies resistant to specific pathogen defense mechanisms.

Scientific and engineering capabilities in hydrocarbon supply chains developed over decades in international oil and gas companies (IOCs) uniquely position these companies to drive rapid scale-up and transition to a net-zero emission economy. Flexible large-scale production of energy carriers such as hydrogen, ammonia, methanol, and other synthetic fuels produced with low- or zero-emission renewable power, nuclear energy, or hydrogen derived from natural gas with carbon capture and storage will enable long-distance transport and permanent storage options for clean energy. Use of energy carriers can overcome the inherent constraints of a fully electrified energy system by providing the energy and power densities, as well as transport and storage capacity, required to achieve energy supply and security in a net-zero emission economy, and over time allow optimization to the lowest cost for a consumer anywhere on the globe.

The storage of electric energy in a safe and environmentally friendly way is of ever-growing importance for a modern, technology-based society. With future pressures predicted for batteries that contain strategic metals, there is increasing interest in metal-free electrode materials. Among candidate materials, nonconjugated redox-active polymers (NC-RAPs) have advantages in terms of cost-effectiveness, good processability, unique electrochemical properties, and precise tuning for different battery chemistries. Here, we review the current state of the art regarding the mechanisms of redox kinetics, molecular design, synthesis, and application of NC-RAPs in electrochemical energy storage and conversion. Different redox chemistries are compared, including polyquinones, polyimides, polyketones, sulfur-containing polymers, radical-containing polymers, polyphenylamines, polyphenazines, polyphenothiazines, polyphenoxazines, and polyviologens. We close with cell design principles considering electrolyte optimization and cell configuration. Finally, we point to fundamental and applied areas of future promise for designer NC-RAPs.

Natural products are a diverse class of biologically produced compounds that participate in fundamental biological processes such as cell signaling, nutrient acquisition, and interference competition. Unique triple-bond functionalities like isonitriles and alkynes often drive bioactivity and may serve as indicators of novel chemical logic and enzymatic machinery. Yet, the biosynthetic underpinnings of these groups remain only partially understood, constraining the opportunity to rationally engineer biomolecules with these functionalities for applications in pharmaceuticals, bioorthogonal chemistry, and other value-added chemical processes. Here, we focus our review on characterized biosynthetic pathways for isonitrile and alkyne functionalities, their bioorthogonal transformations, and prospects for engineering their biosynthetic machinery for biotechnological applications.

Machine learning (ML) has become a part of the fabric of high-throughput screening and computational discovery of materials. Despite its increasingly central role, challenges remain in fully realizing the promise of ML. This is especially true for the practical acceleration of the engineering of robust materials and the development of design strategies that surpass trial and error or high-throughput screening alone. Depending on the quantity being predicted and the experimental data available, ML can either outperform physics-based models, be used to accelerate such models, or be integrated with them to improve their performance. We cover recent advances in algorithms and in their application that are starting to make inroads toward (a) the discovery of new materials through large-scale enumerative screening, (b) the design of materials through identification of rules and principles that govern materials properties, and (c) the engineering of practical materials by satisfying multiple objectives. We conclude with opportunities for further advancement to realize ML as a widespread tool for practical computational materials design.

Optogenetics has been used in a variety of microbial engineering applications, such as chemical and protein production, studies of cell physiology, and engineered microbe-host interactions. These diverse applications benefit from the precise spatiotemporal control that light affords, as well as its tunability, reversibility, and orthogonality. This combination of unique capabilities has enabled a surge of studies in recent years investigating complex biological systems with completely new approaches. We briefly describe the optogenetic tools that have been developed for microbial engineering, emphasizing the scientific advancements that they have enabled. In particular, we focus on the unique benefits and applications of implementing optogenetic control, from bacterial therapeutics to cybergenetics. Finally, we discuss future research directions, with special attention given to the development of orthogonal multichromatic controls. With an abundance of advantages offered by optogenetics, the future is bright in microbial engineering.

There is an urgent need for new technologies to enable circularity for synthetic polymers, spurred by the accumulation of waste plastics in landfills and the environment and the contributions of plastics manufacturing to climate change. Chemical recycling is a promising means to convert waste plastics into molecular intermediates that can be remanufactured into new products. Given the growing interest in the development of new chemical recycling approaches, it is critical to evaluate the economics, energy use, greenhouse gas emissions, and other life cycle inventory metrics for emerging processes,relative to the incumbent, linear manufacturing practices employed today. Here we offer specific definitions for classes of chemical recycling and upcycling and describe general process concepts for the chemical recycling of mixed plastics waste. We present a framework for techno-economic analysis and life cycle assessment for both closed- and open-loop chemical recycling. Rigorous application of these process analysis tools will be required to enable impactful solutions for the plastics waste problem.