Beyond Reduction Cocatalysts: Critical Role of Metal Cocatalysts in Photocatalytic Oxidation of Methane with Water**

Environmentally sustainable and selective conversion of methane to valuable chemicals under ambient conditions is pivotal for the development of next-generation photocatalytic technology. However, due to the lack of microscopic knowledge about non-thermal methane conversion, controlling and modulating photocatalytic oxidation processes driven by photogenerated holes remain a challenge. Here, we report novel function of metal cocatalysts to accept photogenerated holes and dominate selectivity of methane oxidation, which is clearly beyond the conventional concept in photocatalysis that the metal cocatalysts loaded on the surfaces of semiconductor photocatalysts mostly capture photogenerated electrons and dominate reduction reactions exclusively. The novel photocatalytic role of metal cocatalysts was verified by operando molecular spectroscopy combined with real-time mass spectrometry for metal-loaded Ga₂O₃ model photocatalysts under methane and water vapor at ambient temperature and pressure. Our concept of metal cocatalysts that work as active sites for both photocatalytic oxidation and reduction provides a new understanding of photocatalysis and a solid basis for controlling non-thermal redox reactions by metal-cocatalyst engineering.     

Dual Lewis Acid-Base Sites Regulate Silver-Copper Bimetallic Oxide Nanowires for Highly Selective Photoreduction of Carbon Dioxide to Methane

Highly selective photoreduction of CO₂ to valuable hydrocarbons is of great importance to achieving a carbon-neutral society. Precisely manipulating the formation of the Metal₁⋅⋅⋅C=O⋅⋅⋅Metal₂ (M₁⋅⋅⋅C=O⋅⋅⋅M₂) intermediate on the photocatalyst interface is the most critical step for regulating selectivity, while still a significant challenge. Herein, inspired by the polar electronic structure feature of CO₂ molecule, we propose a strategy whereby the Lewis acid-base dual sites confined in a bimetallic catalyst surface are conducive to forming a M₁⋅⋅⋅C=O⋅⋅⋅M₂ intermediate precisely, which can promote selectivity to hydrocarbon formation. Employing the Ag₂Cu₂O₃ nanowires with abundant Cu⋅⋅⋅Ag Lewis acid-base dual sites on the preferred exposed {110} surface as a model catalyst, 100 % selectivity toward photoreduction of CO₂ into CH₄ has been achieved. Subsequent surface-quenching experiments and density functional theory (DFT) calculations verify that the Cu⋅⋅⋅Ag Lewis acid-base dual sites do play a vital role in regulating the M₁⋅⋅⋅C=O⋅⋅⋅M₂ intermediate formation that is considered to be prone to convert CO₂ into hydrocarbons. This study reports a highly selective CO₂ photocatalyst, which was designed on the basis of a newly proposed theory for precise regulation of reaction intermediates. Our findings will stimulate further research on dual-site catalyst design for CO₂ reduction to hydrocarbons.     

预测金属有机骨架甲烷和氢气输送能力的迁移学习建模

基于深度神经网络(DNN)和迁移学习(TL),使用少量数据建立TL模型,精准预测了金属有机骨架(MOFs)的甲烷和氢气输送性能.首先,使用8414个MOFs在298 K/65 bar～298 K/5.8 bar(1 bar=0.1 MPa)条件下的甲烷输送数据训练一个决定系数(R²)为0.973的DNN[源任务(ST)模型].随后,将ST模型的部分参数冻结,使用100个MOFs在233 K/65 bar～358 K/5.8 bar条件下的甲烷输送数据和100个MOFs在198 K/100 bar～298 K/5 bar条件下的氢气输送数据分别微调ST模型,进行TL建模.结果表明,两个TL模型的R²分别为0.968和0.945,均高于其它5个传统的ML模型.所开发的TL模型在预测小数据集时具有高精度与高稳定性.最后,使用排列特征重要度方法来计算描述符重要度,明确了模型之间的“知识”共享情况,并在此基础上探讨了重要描述符和输送能力之间的关系.     

Bayesian Optimization-guided Discovery of High-performance Methane Combustion Catalysts based on Multi-component PtPd@CeZrOx Core–Shell Nanospheres

Formula regulation of multi-component catalysts by manual search is undoubtedly a time-consuming task, which has severely impeded the development efficiency of high-performance catalysts. In this work, PtPd@CeZrO_x core–shell nanospheres, as a successful case study, is explicitly demonstrated how Bayesian optimization (BO) accelerates the discovery of methane combustion catalysts with the optimal formula ratio (the Pt/Pd mole ratio ranges from 1/2.33–1/9.09, and Ce/Zr from 1/0.22–1/0.35), which directly results in a lower conversion temperature (T₅₀ approaching to 330 °C) than ones reported hitherto. Consequently, the best sample obtained could be efficiently developed after two rounds of iterations, containing only 18 experiments in all that is far less than the common human workload via the traditional trial-and-error search for optimal compositions. Further, this BO-based machine learning strategy can be straightforward extended to serve the autonomous discovery in multi-component material systems, for other desired properties, showing promising opportunities to practical applications in future.     

Hydrogen-Deuterium Isotope Exchange of Methane via Non-redox Palladium Catalysis

Under mild conditions, Pd(II) catalysts coordinated to tridentate NHC-amidate-ether ligand successfully activated the carbon-hydrogen bond to facilitate the hydrogen/deuterium isotope exchange on methane. The structural features and catalytic behavior suggested an intriguing non-redox catalytic system derived from the amidate nitrogen. As the amidate nitrogen acts as an internal base, the metal center was able to maintain the oxidation state throughout the reaction. Accordingly, the catalytic system demonstrated its reactivity and stability during the H/D exchange on methane resulting in a high degree of deuterium conversions (44 %) and turnover number (346) under low temperature conditions.     

Lithium Promotes Acetylide Formation on MgO During Methane Coupling Under Non-Oxidative Conditions

A prototypical material for the oxidative coupling of methane (OCM) is Li/MgO, for which Li is known to be essential as a dopant to obtain high C₂ selectivities. Herein, Li/MgO is demonstrated to be an effective catalyst for non-oxidative coupling of methane (NOCM). Moreover, the presence of Li is shown to favor the formation of magnesium acetylide (MgC₂), while pure MgO promotes coke formation as evidenced by solid-state ¹³C NMR, thus indicating that Li promotes C−C bond formation. Metadynamic simulations of the carbon mobility in MgC₂ and Li₂C₂ at the density functional theory (DFT) level show that carbon easily diffuses as a C₂ unit at 1000 °C. These insights suggest that the enhanced C₂ selectivity for Li-doped MgO is related to the formation of Li and Mg acetylides.     

预处理条件对Mo/HZSM-5和Mo-Zn/HZSM-5甲烷芳构化性能的影响

甲烷无氧芳构化 ,具有选择性高、技术简单及产物易分离等特点 ,已引起人们的广泛关注 [1,2 ] .Mo/HZSM- 5是芳构化的良好催化剂 ,为了探讨预处理条件对反应的影响 ,我们对不同预处理条件下的 Mo/HZSM- 5及 Zn改性的 Mo/HZSM- 5催化剂上的甲烷无氧芳构化反应进行了研究 ,并以热重法对催化剂的稳定性进行了表征 .1实验部分1 .1原料和试剂钼酸铵 ( A.R.级 ) ,乙酸锌 ( A.R.级 ) ,铵型ZSM- 5分子筛 (硅铝比为 5 0～ 70 ) .1 .2催化剂制备铵型 ZSM- 5分子筛于 81 3K、空气气氛下焙烧3h,即成 HZSM- 5分子筛 .以一定浓度的钼酸铵溶液…