Abstract Before the 1990s, the fact that almost all enzymes had an optimal temperature (Topt) above which catalytic activity declined was explained by thermal denaturation. However, since then it has been demonstrated for many enzymes that activity declines above Topt in the absence of measurable denaturation. Two main models have been proposed to explain this: the Inactivation Equilibrium Model proposed by Daniel and Danson, and the Macromolecular Rate hypothesis put forth by the Arcus group. Comparisons of these two models have, until now, used activity vs T data sets from a limited number of enzymes, with relatively few k(T) measurements. We present here a meta-analysis of 260 published data sets from 27 enzymes and 5 multienzyme metabolic processes. First, we note that fits for kcat vs T data sets give thermodynamic and activation parameters related specifically to the catalytic step; data sets with a more complex independent variable (e.g., kcat/Km, Vmax/Km, v0, enzyme activity) yield fitted parameters that could characterize catalysis, substrate binding, or both. Additionally, for both models, the fitted activation parameters display enthalpy/entropy compensation (ΔH‡ vs ΔS‡ plots are strictly linear, with R2 > 0.98) that is found to be “apparent”, i.e., statistical rather than thermodynamic. We also conclude that for symmetric activity vs T curves, the fits from the two models are equally good. However, for asymmetric activity vs T curves, the Inactivation Equilibrium Model yields significantly better fits. This problem was addressed recently by the Arcus group, which presented a “two-state” modification of their MMRt model with six adjustable parameters, which can fit asymmetric k vs T peaks. This compares with the Inactivation Equilibrium model which has four adjustable parameters.
Abstract Microkinetic modeling (MKM) is a pivotal computational tool that bridges potential energy surfaces and catalytic activity, while descriptor-based MKM enables rational catalyst design through computational methods. However, the use of descriptors requires repeated MKM calculations across numerous conditions, increasing the overall cost by orders of magnitude and imposing stringent demands on solver stability. To address these challenges, we herein report a robust and efficient Sampling-Expansion Approach (SEA) for accelerated descriptor-based MKM, which is incorporated into our in-house developed multiscale kinetic modeling platform (MuKiP). SEA maximizes computational efficiency by strategically controlling the solving strategy, leveraging converged solutions as initial guesses, and employing a parallel computing framework. Compared with conventional approaches, SEA achieves significantly higher efficiency and reduces reliance on solver stability, thereby exhibiting strong robustness. The application of the proposed method and framework is expected to substantially accelerate the rational design of catalysts.
Abstract Controlling product selectivity in homogeneous electrocatalytic CO2 reduction remains a significant challenge, often requiring complicated catalyst redesigning. Herein, we identify and validate a cobalt-hydride intermediate that governs the selectivity switch for CO2 reduction to either formate or synthesis gas (syngas), a mixture of H2 and CO, for a cobalt 2-diisopropylphosphinothiolate complex (CoPS) upon modifying the concentration of the proton donor, water, without altering the catalyst structure. At low water concentrations (0.01 M), CoPS achieves up to 90% faradaic efficiency for formate production, whereas at higher water concentrations (0.5 M), syngas is favored. Spectroscopic characterization techniques reveal the formation of a rate-limiting cobalt-hydride, with density functional theory calculations predicting a hydricity value of 44.3 kcal/mol, which coincides with the thermodynamic threshold of CO2 to formate interconversion in acetonitrile, positioning this intermediate at the thermodynamic boundary of the two reaction pathways. Electrochemical and mechanistic studies reveal that the concentration of the proton donor drives the competition between hydride transfer to CO2 (formate pathway) and protonation (hydrogen evolution pathway). These findings establish the local proton environment as a practical switch between catalytic pathways and underscore the mechanistic insights into the associated CO2 reduction reaction, highlighting broad applicability for tunable selectivity in homogeneous catalysis.
Abstract Atomically dispersed metal catalysts demonstrate significant catalytic potential, though achieving precise structural elucidation and electronic modulation remains a key challenge. Herein, we report the synthesis and characterization of three isostructural, semiconducting heterometallic titanium-oxo clusters, Ti14M2(μ3-O)13(μ2-O)8(H2O)(C6H5CO2)18(Nfm)3 (designated as Ti14M2, where M2 = CoNi, Co2, or Ni2), serving as molecularly precise model systems for dual single-atom catalysts. Distinct electronic interaction between the heterometallic Co and Ni sites in Ti14CoNi modulates the local charge distribution, lowering the charge density at Ni while elevating it at Co. In photocatalytic CO2 reduction reaction (CO2RR), Ti14CoNi exhibits high performance, ranking among the best catalysts, surpassing Ti14Co2 and Ti14Ni2, as well as many state-of-the-art solid-state Ni, Fe, Cu, and Co single atom catalysts. Notably, Ti14CoNi retains activity even when using simulated flue gas as the CO2 source. Experimental and DFT studies reveal that Ni acts as the primary catalytic site for CO2RR in Ti14CoNi, with *COOH formation as the rate-determining step, while the lowered Ni valence state enhances CO2 activation and suppresses H2 evolution. The dual-metal strategy improves CO2RR efficiency and provides a thermodynamically favorable pathway for CO production. Our findings establish molecular metal-oxo clusters as atomically precise dual single atom catalysts and offer valuable insights for developing efficient CO2RR catalysts of the next generation.
Abstract Industrial ammonia synthesis relies heavily on the energy-intensive Haber-Bosch process with substantial CO2 emissions, which stimulates the quest for environmentally friendly alternatives. Recently, electrocatalytic reduction of waste inorganic nitrogen oxide (NOx) species, such as NO3−, NO2−, and NO, has sprouted as a promising route for ambient ammonia synthesis by utilizing advanced electrocatalysts. In particular, single-atom alloys (SAAs), as an innovative class of catalytic materials, not only inherit the merits of single-atom catalysts like high-atom utilization efficiency but also possess a multimetallic alloy effect, opening a broad prospect in electrocatalytic NOx reduction reaction (NOxRR) to ammonia. This review summarizes recent advancements in the utilization of SAAs for electrocatalytic NOxRR to ammonia. An overview of potential reaction pathways and their distinctions in NOxRR, alloying effect, associated in situ characterization techniques, and density functional theory (DFT) calculations is introduced, followed by discussing several bottom-up/top-down synthetic methods and characterization techniques for various SAAs. Subsequently, their electrocatalytic applications for NOxRR to ammonia are exemplified and discussed in detail. Lastly, potential research challenges in this field are delineated to amplify their contribution in accomplishing a neutral carbon footprint.
