Electrochemical Reversible Reforming between Ethylamine and Acetonitrile on Heterostructured Pd-Ni(OH)2 Nanosheets

Rational design of electrocatalysts is essential to achieve desirable performance of electrochemical synthesis process. Heterostructured catalysts have thus attracted widespread attention due to their multifunctional intrinsic properties, and diverse catalytic applications with corresponding outstanding activities. Here, we report an in situ restoration strategy for the synthesis of ultrathin Pd-Ni(OH)₂ nanosheets. Such Pd-Ni(OH)₂ nanosheets exhibit excellent activity and selectivity towards reversible electrochemical reforming of ethylamine and acetonitrile. In the acetonitrile reduction process, Pd acts as reaction center, while Ni(OH)₂ provide proton hydrogen through promoting the dissociation of water. Also ethylamine oxidation process can be achieved on the surface of the heterostructured nanosheets with abundant Ni(II) defects. More importantly, an electrolytic cell driven by solar cells was successfully constructed to realize ethylamine-acetonitrile reversible reforming. This work demonstrates the importance of heterostructure engineering in the rational synthesis of multifunctional catalysts towards electrochemical synthesis of fine chemicals.     

Structure- and Data-Driven Protein Engineering of Transaminases for Improving Activity and Stereoselectivity

Amine transaminases (ATAs) are powerful biocatalysts for the stereoselective synthesis of chiral amines. Machine learning provides a promising approach for protein engineering, but activity prediction models for ATAs remain elusive due to the difficulty of obtaining high-quality training data. Thus, we first created variants of the ATA from Ruegeria sp. (3FCR) with improved catalytic activity (up to 2000-fold) as well as reversed stereoselectivity by a structure-dependent rational design and collected a high-quality dataset in this process. Subsequently, we designed a modified one-hot code to describe steric and electronic effects of substrates and residues within ATAs. Finally, we built a gradient boosting regression tree predictor for catalytic activity and stereoselectivity, and applied this for the data-driven design of optimized variants which then showed improved activity (up to 3-fold compared to the best variants previously identified). We also demonstrated that the model can predict the catalytic activity for ATA variants of another origin by retraining with a small set of additional data.     

Effect of Fluorocarbon Side Chain on the Microphase Morphology and Rheological Behavior of Thermoplastic Polyurethanes

Chinese Journal of Polymer Science - Fluorinated diols (FDO) with dangling chain were introduced into polyether urethanes (PEUs) as chain extender in order to achieve internal plasticization. Based...