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In the May issue of Chem Catalysis, Mathison et al. discuss a strategy that leverages biocatalysis and electrocatalysis to decarbonize the production of adiponitrile, a building block of nylon 6,6. High-throughput combinatorial electrosynthesis and machine learning expedited the exploration of the parameter space and the identification of optimal reaction conditions. 

We report the tethering of flame-retardant additives like 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) to the backbone of a polyamide throughtrans-3-hexenedioic acid, a bioadvantaged derivative of muconic acid. 

The decarbonization of chemical manufacturing is a multifaceted challenge that requires technologies able to selectively convert CO2-sequestering feedstocks using renewable energy. The electrochemical conversion of biomass-derived platform chemicals is well-positioned to address this need. However, the electroactivity of biobased molecules that carry multiple redox centers remains challenging to predict and control. For instance, cis,cis-muconic acid, a conjugated dicarboxylic acid, is electrohydrogenated to trans-3-hexenedioic acid (t3HDA) with excellent yield and stereoselectivity while free energy calculations predict mixtures of 2- and 3-hexenedioic acids. To decipher this discrepancy, we studied the electrohydrogenation of C4 and C6 unsaturated acids, diacids, and their esters, and tied the observed product distributions to the electronic structure of the parent molecules. We show that the electrohydrogenation of the three isomers of muconic acid proceeds through a hydrogenating proton-coupled electron transfer (PCET) in the α position of the carboxylic acids and invariably yields t3HDA as the sole product. The selectivity can be explained by the electron-withdrawing effect of the carboxylic acid groups and the resulting perturbation of the local electron density that promotes the 2,5-hydrogenation over the thermodynamically-preferred 2,3-hydrogenation. This electronic perturbation is reflected in the computed Fukui indices, which can serve as local reactivity descriptors to predict product distributions not captured by calculated reaction thermochemistry. In addition to predicting the electroactivity of other unsaturated acids, this approach can provide insights into homogeneous electrochemical processes that may coexist with surface-mediated electrocatalytic transformations. 

The structural versatility and vibrant surface chemistry of carbon materials offer tremendous opportunities for tailoring the catalytic performance of supported metal nanoparticles through the modulation of interfacial metal-support interactions (MSI). MSI’s geometric and structural effects are well documented for these materials. However, other potential support effects such as electronic metal-carbon interactions remain poorly understood. Such limitations are tied to constraints intrinsic to commonly available carbon materials such as activated carbon (e.g., microporosity) and the top-down approach that is often used for their synthesis. Nonetheless, it is crucial to understand the interplay between the structure, properties, and performance of carbon-supported metal catalysts to take steps toward rationalizing their design. The present study investigates promising and scalable bottom-up synthesis approaches, namely hydrothermal carbonization (HTC) and evaporation-induced self-assembly (EISA), that offer great flexibility for controlling the carbon structure. The opportunities and limitations of the methods are discussed with a particular focus on harnessing the power of oxygen functionalities. A remarkable production yield of 32.8% was achieved for mesoporous carbons synthesized via EISA. Moreover, these carbon materials present similar external surface areas of 316 ± 19 m2/g and average pore sizes of 10.0 ± 0.1 nm while offering flexibility to control the oxygen concentration in the range of 5–26 wt%. This study provides the cornerstone for future investigations of metal-carbon support interactions and the rational design of these catalysts.