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The application of green chemistry is critical for cultivating environmental responsibility and sustainable practices in pharmaceutical manufacturing. Process mass intensity (PMI) is a key metric that quantifies the resource efficiency of a manufacturing process, but determining what constitutes a successful PMI of a specific molecule is challenging. A recent approach correlated molecular features to a crowdsourced definition of molecular complexity to determine PMI targets. While recent machine learning tools show promise in predicting molecular complexity, a more extensive application could significantly optimize manufacturing processes. To this end, we refine and expand upon the SMART-PMI tool by Sheridan et al. to create an open-source model and application. Our solution emphasizes explainability and parsimony to facilitate a nuanced understanding of prediction and ensure informed decision-making. The resulting model uses four descriptors-the heteroatom count, stereocenter count, unique topological torsion, and connectivity index chi4n-to compute molecular complexity with a comparable 82.6% predictive accuracy and 0.349 RMSE. We develop a corresponding app that takes in structured data files (SDF) to rapidly quantify molecular complexity and provide a PMI target that can be used to drive process development activities. By integrating machine learning explainability and open-source accessibility, we provide flexible tools to advance the field of green chemistry and sustainable pharmaceutical manufacturing., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

The increasing energy demand and related environmental issues have drawn great attention worldwide, thus necessitating the development of sustainable technologies to preserve the ecosystems for future generations. Electrocatalysts for energy-conversion reactions such as the hydrogen evolution reaction (HER), nitrogen reduction reaction (NRR), and carbon dioxide reduction reaction (CO 2 RR) are at the heart of these renewable energy technologies, but they suffer from sluggish kinetics due to the multistep electron and mass transfer. State-of-the-art catalysts are thus highly desired to boost the conversion efficiencies, which are still inadequate. Recently, as a typical transition metal dichalcogenide, molybdenum disulfide (MoS 2 ) with unique physicochemical properties has been verified as a promising material for catalyzing key electrochemical reactions ( i.e. , HER, NRR, and CO 2 RR), presenting excellent performances. Therefore, in this review, we give insight into the structure and synthetic strategies of MoS 2 . Recent advances in MoS 2 -based materials for the three key electrochemical reactions are briefly summarized. Open challenges and perspectives of MoS 2 -based electrocatalysts toward HER, NRR, and CO 2 RR are also outlined.

Recently, hollow nanofibers could be fabricated by coaxis electrospinning method or template method. However, they are limited to applications because of the hardship in actual preparation. In this work, hollow γ-Al 2 O 3 nanofibers with loofah-like skins were first fabricated by using a single spinneret during electrospinning. These intriguing nanofibers were explored as new Pt supports with excellently sinter-resistant performance up to 500 °C, attributed to the unique loofah-like surface of γ-Al 2 O 3 nanofibers and the strong metal-support interactions between Pt and γ-Al 2 O 3 . When applied in the catalytic reduction of p-nitrophenol, the Pt/γ-Al 2 O 3 calcined at 500 °C exhibited 4-times higher reaction rate constant (6.8 s -1 ·mg -1 ) over free Pt nanocrystals.

Graphene sheets, a flexible 2D material with excellent absorptive capacity, have great potential as absorbing materials. However, this material has always suffered from irreversible aggregation and thus loses the abundant active sites and large surface area. In this paper, large-scale graphene oxide (GO) sheets were cut and reduced to tiny reduced graphene oxide (RGO) sheets by a cell-break sonicator, for producing numerous defects, which are the center of chemisorption. Furthermore, sodium titanate nanowires functioned as a framework to help to disperse the tiny RGO sheets uniformly. And, in turn, the flexible tiny RGO sheets glued robust nanowires into a free-standing membrane. This novel composite membrane exhibited an ultra-high decoloration efficiency of 99.8% of rhodamine B in a continuous flow mode, and an outstanding absorptive capability of 1.30 × 10 -2 mol g -1 correlated to RGO content in batch reaction, which is about two orders of magnitude higher than other reported graphene-based absorbents. In addition, an efficient and feasible method without any heat treatment for regenerating the membrane is illustrated, and the recycled membrane retains superior decoloration efficiency. The excellent absorptive performance indicates the framework-based disperse strategy has great potential for the construction and application of defect-rich graphene.