RESUMO
The molecular generation task stands as a pivotal step in the domains of computational chemistry and drug discovery, aiming to computationally generate molecular structures for specific properties. In contrast to previous models that focused primarily on SMILES strings or molecular graphs, our model placed a special emphasis on the substructure information on molecules, enabling the model to learn richer chemical rules and structure features from fragments and chemical reaction information on molecules. To accomplish this, we fragmented the molecules to construct heterogeneous graph representations based on atom and fragment information. Then our model mapped the heterogeneous graph data into a latent vector space by using an encoder and employed a self-regressive generative model as a decoder for molecular generation. Additionally, we performed transfer learning on the model using a small set of ligand molecules known to be active against the target protein to generate molecules that bind better to the target protein. Experimental results demonstrate that our model is highly competitive with state-of-the-art models. It can generate valid and diverse molecules with favorable physicochemical properties and drug-likeness. Importantly, they produce novel molecules with high docking scores against the target proteins.
RESUMO
Exploring low-cost, high-activity, and structurally stable nonprecious metal electrocatalysts for sluggish oxygen evolution reaction (OER) is paramount for water electrolysis. Herein, we successfully prepare a novel Fe,Co-CeO2/CeF3@MXene heterostructure with Fe-Co dual active sites and oxygen vacancies for alkaline OER using an energy-free consumption co-deposition method. Impressively, Fe,Co-CeO2/CeF3@MXene achieves an ultralow overpotential of 192 mV and a long-term stability of 110 h at 10 mA cm-2 without structural changes, thereby outperforming the commercial IrO2 (345 mV). In addition, Fe,Co-CeO2/CeF3@MXene exhibits much superior activity (271 mV) and durability to IrO2 (385 mV) in the real seawater OER. Wind- and solar energy-assisted water electrolysis devices show their promising prospects for sustainable green hydrogen production. Characterization techniques and theoretical calculations reveal that the Fe,Co co-implanted CeO2/CeF3 heterostructure effectively degrades the energy barrier of the OER and optimizes the adsorption strength of *OH, *O, and *OOH intermediates. It exhibits the dual coupling mechanism of the adsorbed evolution and lattice oxygen mechanisms, which synergistically improves the OER performance. This work provides a facile and efficacious strategy for synthesizing a new class of heterostructures to achieve significant enhancement in the activity and stability of OER catalysts.
RESUMO
In the field of catalysis, the design and construction of nanomaterials is an efficient way to optimize the catalytic activity of catalysts. This study presents the synthesis of PtCu tripod nanocrystals with branching structures and high purity prepared using a simple hydrothermal method. The dendritic PtCu triangular nanocrystals were successfully synthesized by regulating the amount of I- ions to achieve different degrees of branching on PtCu nanocrystals, and the process was systematically studied and analyzed. Meanwhile, dumbbell nanocrystals of PtCu were successfully synthesized through slight adjustments to synthesis conditions. In electrochemical tests, the obtained dendritic PtCu triangular nanocrystals exhibited prominent electrocatalytic activity and long-term stability for ethylene glycol, methanol, and ethanol oxidation reactions due to the unique nanostructures as well as alloyed virtue, and were much better than commercial Pt/C. In addition, this study provides a general strategy for designing novel branched Pt-based nanomaterials with high electrocatalytic performance.
