Intelligent Molecular Identification for High Performance Organosulfide Capture Using Active Machine Learning Algorithm

Machine learning and computer-aided approaches significantly accelerate molecular design and discovery in scientific and industrial fields increasingly relying on data science for efficiency. The typical method used is supervised learning which needs huge datasets. Semi-supervised machine learning approaches are effective to train unlabeled data with improved modeling performance, whereas they are limited by the accumulation of prediction errors. Here, to screen solvents for removal of methyl mercaptan, a type of organosulfur impurities in natural gas, we constructed a computational framework by integrating molecular similarity search and active learning methods, namely, molecular active selection machine learning (MASML). This new model framework identifies the optimal molecules set by molecular similarity search and iterative addition to the training dataset. Among all 126,068 compounds in the initial dataset, 3 molecules were identified to be promising for methyl mercaptan (MeSH) capture, including benzylamine (BZA), p-methoxybenzylamine (PZM), and N,N-diethyltrimethylenediamine (DEAPA). Further experiments confirmed the effectiveness of our modeling framework in efficient molecular design and identification for capturing methyl mercaptan, in which DEAPA presents a Henry\u27s law constant 89.4% lower than that of methyl diethanolamine (MDEA)

Complete Hydrodesulfurization of Dibenzothiophene via Direct Desulfurization Pathway over Mesoporous TiO₂-Supported NiMo Catalyst Incorporated with Potassium

Mesoporous TiO2 containing different potassium content was prepared from potassium titanate by mediating the pH value of the ion exchange, which was used as catalytic support to load NiMo for hydrodesulfurization of dibenzothiophene. The as-prepared samples were characterized by X-ray diffraction, N2 physical adsorption/desorption, temperature-programmed reduction, scanning electron microscope/energy dispersive X-ray mapping analysis, high resolution transmission electron microscopy, and pyridine-adsorbed Fourier transform infrared spectroscopy. The characterization results showed that NiO and MoO3 were well dispersed on mesoporous TiO2 with varying potassium content. A crystal NiMoO4 phase was formed on the TiO2 with relatively high potassium content, which could decrease the reduction temperature of oxidized active species. The evaluation results from the hydrodesulfurization displayed that as the potassium content of the catalyst increased, the dibenzothiophene conversion firstly increased and then slightly decreased when potassium content exceeded 6.41 wt %. By contrast, the direct desulfurization selectivity could continuously increase along with the potassium content of catalyst. Furthermore, the change in direct desulfurization selectivity of a TiO2-supported NiMo catalyst was independent of the reaction condition. The mesoporous TiO2-supported NiMo catalyst incorporated with potassium could have near both 100% of dibenzothiophene and 100% of direct desulfurization selectivity. According to the structure–performance relationship discussion, the incorporation of potassium species could benefit the formation of more sulfided active species on mesoporous TiO2. Moreover, excessive free potassium species may poison the active sites of the hydrogenation pathway. Both factors determined the characteristics of complete hydrodesulfurization of dibenzothiophene via a direct desulfurization pathway for potassium-incorporated mesoporous TiO2 supported NiMo catalysts

Water Intrusion–Extrusion in Metal Azolate Frameworks and Pressure-Induced Supramolecular Isomerism

Revealing the pressure-induced structure evolution of porous materials is fundamentally important for the development of a HLS (porous heterogeneous lyophobic system). Herein, a series of metal azolate frameworks (MAFs) were synthesized via regulating template concentrations and applied in the {MAF + water} HLS to unveil structure–property relationships and understand pressure-induced structure changes. The quasi-static mechanical measurements indicate that the MAF-5 and MAF-6 samples exhibit intrusion pressures of 93.53 and 48.69 MPa, intrusion volumes of 0.14 and 0.55 mL/g, and intrusion energies of 22.54 and 27.73 J/g, respectively. After high-pressure water intrusion, the MAF-5/MAF-6 mixed composite synthesized under a template concentration of 0.38 vol % undergoes phase transfer to a new structure of MAF-32, while other samples evolve into the consistent structure of MAF-5. Rietveld refinement confirmed the distinct coordination modes between Zn and 2-ethylimidazolate in MAF-5 and MAF-6, and realized the pressure-induced positional changes of the ethyl group on the imidazole ring. The present study highlights the structural evolution of MAFs in response to high-pressure water intrusion and offers insights into the rational design of HLSs and tuning the topological structures of porous coordination polymers in potential applications