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1. Advances in dynamically controlled catalytic reaction engineering

   https://doi.org/10.1039/d0re00330a  

   Armstrong, Cameron D. ; Teixeira, Andrew R. ( November 2020 , Reaction Chemistry & Engineering)

   null (Ed.)

   Transient reaction modulation has found its place in many branches of chemical reaction engineering over the past hundred years. Historically, catalytic reactions have been dominated by the impulse to reduce spatial and temporal perturbations in favor of steady, static systems due to their ease of operation and scalability. Transient reactor operation, however, has seen remarkable growth in the past few decades, where new operating regimes are being revealed to enhance catalytic reaction rates beyond the statically achievable limits classically described by thermodynamics and the Sabatier principle. These theoretical and experimental studies suggest that there exists a resonant frequency which coincides with its catalytic turnover that can be exploited and amplified for a given reaction to overcome classical barriers. This review discusses the evolution of thought from thermostatic (equilibrium), to thermodynamic (dynamic equilibrium), and finally dynamic (non-equilibrium) catalysis. Natural and forced dynamic oscillations are explored with periodic reactor operation of catalytic systems that modulate energetics and local concentrations through a multitude of approaches, and the challenges to unlock this new class of catalytic reaction engineering is discussed. 

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2. Power of stochastic kinetic models: From biological signaling and antibiotic activities to T cell activation and cancer initiation dynamics

   https://doi.org/10.1002/wcms.1612  

   Teimouri, Hamid ; Kolomeisky, Anatoly B. ( February 2022 , WIREs Computational Molecular Science)

   All chemical processes exhibit two main universal features. They are stochastic because chemical reactions might happen only after random successful collisions of reacting species, and they are dynamic because the amount of reactants and products change with time. Since biological processes rely heavily on specific chemical reactions, stochasticity and dynamics are also crucial features for all living systems. To understand the molecular mechanisms of chemical and biological processes, it is important to develop and apply theoretical methods that fully incorporate the randomness and dynamic nature of these systems. In recent years, there have been significant advances in formulating and exploring such theoretical methods. As an illustration of such developments, in this review, the recent applications of stochastic kinetic models for various biological processes are discussed. Specifically, we focus on applying these theoretical approaches to investigate the biological signaling, clearance of bacteria under antibiotics, T cells activation in the immune system, and cancer initiation dynamics. The main advantage of the presented stochastic kinetic models is that they generally can be solved analytically, allowing to clarify the underlying microscopic picture, as well as explain the existing experimental observations and make new testable predictions. This theoretical approach becomes a powerful tool in uncovering the molecular mechanisms of complex natural phenomena. 

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3. Controlling Polymer Material Structure during Reaction-Induced Phase Transitions

   https://doi.org/10.1021/accountsmr.3c00071  

   Hickey, Robert J. ( September 2023 , Accounts of Materials Research)

   Living systems are composed of a select number of biopolymers and minerals yet exhibit an immense diversity in materials properties. The wide-ranging characteristics, such as enhanced mechanical properties of skin and bone, or responsive optical properties derived from structural coloration, are a result of the multiscale, hierarchical structure of the materials. The fields of materials and polymer chemistry have leveraged equilibrium concepts in an effort to mimic the structure complex materials seen in nature. However, realizing the remarkable properties in natural systems requires moving beyond an equilibrium perspective. An alternative method to create materials with multiscale structures is to approach the issue from a kinetic perspective and utilize chemical processes to drive phase transitions. This Account features an active area of research in our group, reaction-induced phase transitions (RIPT), which uses chemical reactions such as polymerizations to induce structural changes in soft material systems. Depending on the type of phase transition (e.g., microphase versus macrophase separation), the resulting change in state will occur at different length scales (e.g., nm – μm), thus dictating the structure of the material. For example, the in situ formation of either a block copolymer or a homopolymer initially in a monomer mixture during a polymerization will drive nanoscale or macroscale transitions, respectively. Specifically, three different examples utilizing reaction-driven phase changes will be discussed: 1) in situ polymer grafting from block copolymers, 2) multiscale polymer nanocomposites, and 3) Lewis adduct-driven phase transitions. All three areas highlight how chemical changes via polymerizations or specific chemical binding result in phase transitions that lead to nanostructural and multiscale changes. Harnessing kinetic chemical processes to promote and control material structure, as opposed to organizing pre-synthesized molecules, polymers, or nanoparticles within a thermodynamic framework, is a growing area of interest. Trapping nonequilibrium states in polymer materials has been primarily focused from a polymer chain conformation viewpoint in which synthesized polymers are subjected to different thermal and processing conditions. The impact of reaction kinetics and polymerization rate on final polymer material structure is starting to be recognized as a new way to access different morphologies not available through thermodynamic means. Furthermore, kinetic control of polymer material structure is not specific to polymerizations and encompasses any chemical reaction that induce morphology transitions. Kinetically driven processes to dictate material structure directly impact a broad range of areas including separation membranes, biomolecular condensates, cell mobility, and the self-assembly of polymers and colloids. Advancing polymer material syntheses using kinetic principles such as RIPT opens new possibilities for dictating material structure and properties beyond what is currently available with traditional self-assembly techniques. 

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4. Single-Molecule Kinetic Analysis of Oxygenation of Co(II) Porphyrin at the Solution/Solid Interface

   https://doi.org/10.1021/acs.jpclett.2c01254  

   Johnson, Kristen N. ; Mazur, Ursula ; Hipps, K. W. ( June 2022 , The Journal of Physical Chemistry Letters)

   Kinetic analysis of surface reactions at the single molecule level is important for understanding the influence of the substrate and solvent on reaction dynamics and mechanisms, but it is difficult with current methods. Here we present a stochastic kinetic analysis of the oxygenation of cobalt octaethylporphyrin (CoOEP) at the solution/solid interface by monitoring fluctuations from equilibrium using scanning tunneling microscopy (STM) imaging. Image movies were used to monitor the oxygenated and deoxygenated state dwell times. The rate constants for CoOEP oxygenation are ka = 4.9×10-6 s-1∙torr-1 and kd = 0.018 s-1. This is the first use of stochastic dwell time analysis with STM to study a chemical reaction and the results suggest that it has great potential for application to a wide range of surface reactions. Expanding these stochastic studies to further systems is key to unlocking kinetic information for surface confined reactions at the molecular level -- especially at the solution/solid interface. 

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5. Trade-offs between number fluctuations and response in nonequilibrium chemical reaction networks

   https://doi.org/10.1063/5.0148662  

   Chun, Hyun-Myung ; Horowitz, Jordan M. ( May 2023 , The Journal of Chemical Physics)

   We study the response of chemical reaction networks driven far from equilibrium to logarithmic perturbations of reaction rates. The response of the mean number of a chemical species is observed to be quantitively limited by number fluctuations and the maximum thermodynamic driving force. We prove these trade-offs for linear chemical reaction networks and a class of nonlinear chemical reaction networks with a single chemical species. Numerical results for several model systems support the conclusion that these trade-offs continue to hold for a broad class of chemical reaction networks, though their precise form appears to sensitively depend on the deficiency of the network. 

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