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A visible-light induced metal-free approach was described for the hydroxyalkylation of 2H-benzothiazoles with alcohols by using selectfluor as the oxidant. A variety of 2H-benzothiazoles and alcohols could be tolerated, providing a mild and simple method for the synthesis of C2-hydroxyalkylated 2H-benzothiazoles in moderate to good yields. Besides, ethers were also compatible in this reaction, leading to corresponding C2 ether-substituted 2H-benzothiazoles with high regioselectivity. 相似文献
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Maohuai Wang Lingyan Kong Prof. Dr. Xiaoqing Lu Prof. Dr. Chi-Man Lawrence Wu 《ChemSusChem》2022,15(3):e202101674
CO2 capture and separation by using charge-modulated adsorbent materials is a promising strategy to reduce CO2 emissions. Herein, three TM-HAB (TM=Co, Ni, and Cu; HAB=hexa-aminobenzene) metal-organic frameworks (MOFs) were evaluated as charge-modulated CO2 capture and separation materials by using density functional theory and grand canonical Monte Carlo simulations. The results showed that each TM-HAB presented a high electrical conductivity and structural stability when injecting charges. The CO2 adsorption energy increased from 0.211 to 2.091 eV on Co-HAB, 0.262 to 2.119 eV on Ni-HAB, and 0.904 to 2.803 eV on Cu-HAB, respectively, with the increase in charge state from 0.0 to 3.0 e−. Co-HAB and Ni-HAB were better charge-modulated CO2 capture materials with less structure deformation based on energy decomposition analyses. The kinetic process demonstrated that considerably low energy consumptions of 0.911 and 1.589 GJ ton−1 CO2 were observed for a complete adsorption–desorption cycle on Co-HAB and Ni-HAB. All charged MOFs, especially Co-HAB and Ni-HAB, exhibited higher CO2 adsorption energies and adsorption capacities than those of H2, N2, and CH4, thereby exhibiting high CO2 selectivities. Interaction analysis confirmed that the injecting charges had a more pronounced enhancement in the coulombic interactions between CO2 and MOFs. The results of this work highlight Co-HAB and Ni-HAB as promising charge-modulated CO2 capture and separation materials with controllable CO2 capture, high selectivity, and low energy consumption. 相似文献
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Dr. Joyjit Chattoraj Dr. Brahim Hamadicharef Dr. Jian Feng Kong Mohan Kashyap Pargi Yingzhi Zeng Dr. Chee Kok Poh Dr. Luwei Chen Dr. Fei Gao Dr. Teck Leong Tan 《ChemCatChem》2022,14(16):e202200355
Machine learning (ML) has widespread applications in catalyst discovery and reaction optimization. We present a theory-guided machine learning framework to evaluate the carbon monoxide (CO) conversion performance of noble metal catalysts in water-gas shift (WGS) reaction. Our study is based on an open source WGS dataset, which we modify significantly to be consistent with the chemical reaction principles. We apply state-of-the-art ML models including artificial neural networks, extreme gradient boosting to predict CO conversion percentage. These models show superior regression performance than the previously reported results in the literature. We further generalize the existing data structure by including physical, chemical and surface chemistry properties as fingerprint features that rationalize the importance of all the input features for CO conversion. We noticed that purely data-driven ML models frequently violate the thermodynamic equilibrium principle and predict unphysical CO conversion percentage. We address these two problems by developing a custom loss function and an additional activation function in our neural networks architecture. Our proposed theory-guided ML model displays high accuracy (R2 score is 0.95 and root mean square error is 6.87) and physically robust predictions. The model also opens up promising possibilities to improve CO conversion percentage, which were previously unexplored in experiments. 相似文献
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Shuyue Dong Jiaojiao Xia Hexin Zhu Xiangning Du Yang Gu Prof. Qian Liu Yonglan Luo Prof. Qingquan Kong Dr. Haoran Guo Prof. Tingshuai Li Prof. Enrico Traversa 《ChemCatChem》2022,14(17):e202200458
Electrochemical synthesis of ammonia via nitrogen reduction reaction is a rational route to save energy and relieve pollution compared to the traditional Haber-Bosch process. In this report, ZrO2 nanosphere derived from thermolysis of Zr-based biphenyl-4,4′-dicarboxylic acid MOFs (ZrO2/C) as a non-noble metal catalyst with large specific surface area and porous structure is proposed to fix nitrogen to ammonia at ambient conditions. Such catalyst achieves Faradaic efficiency of 11.86 % and a NH3 yield rate of 10.72 μg h−1 mg−1cat. at −0.6 V vs. the reversible hydrogen electrode in 0.1 M Na2SO4. First-principles calculations confirm the alternating reaction at the catalyst surface. 相似文献
210.
Fanhui Kong Dr. Jie Chen Xiangquan Qin Chuanfei Liu Dr. Yiping Jiang Dr. Li Ma Prof. Huifang Xu Prof. Shengying Li Prof. Zhiqi Cong 《ChemCatChem》2022,14(24):e202201151
Herein, we describe an environmentally benign enzymatic approach for the preparation of indigoid from indole derivatives. A series of beneficial P450BM3 mutants were obtained using a stepwise approach involving site-directed, random, and combinatory hot-site mutations. Using H2O2 as the terminal oxidant and N-(ω-imidazolyl)-hexanoyl-L-phenylalanine as a co-catalyst, the quadruple-mutant F87G/T268V/F77I/E140D efficiently catalyzed the 3-hydroxylation of indole and subsequent autooxidation to indigo with higher efficiency than the flavin-containing monooxygenase, PTDH-mFMO, which was the best oxidizing enzyme for indigo synthesis reported to date. Following this procedure, 12 indigoid compounds were prepared using indole derivatives with various substituents as starting materials with moderate to high isolated yields (31.3–79.5 %). The catalytic efficiencies (kcat/Km) of the beneficial mutants for typical indole substrates ranged from 182–2849 mM−1 ⋅ min−1, almost 2- to 712-fold higher than those of the reported P450 enzymes. This study provides a new enzymatic approach for the biosynthesis of indigoid dyes from indole derivatives. 相似文献