A 2D Graph-Based Generative Approach For Exploring Transition States Using Diffusion Model

The exploration of transition state (TS) geometries is crucial for elucidating chemical reaction mechanisms and modeling their kinetics. In recent years, machine learning (ML) models have shown remarkable performance in TS geometry prediction. However, they require 3D geometries of reactants and products that can be challenging to determine. To tackle this, we introduce TSDiff, a novel ML model based on the stochastic diffusion method, which generates the 3D geometry of the TS from a 2D graph composed of molecular connectivity. Despite of this simple input, TSDiff generated TS geometries with high accuracy, outperforming existing ML models that utilize geometric information. Moreover, the generative model approach enabled the sampling of various valid TS conformations, even though only a single conformation for each reaction was used in training. Consequently, TSDiff also found more favorable reaction pathways with lower barrier heights than those in the reference database. We anticipate that this approach will be useful for exploring complex reactions that require the consideration of multiple TS conformations

Perovskite Nano-Powder and Nano-Film Catalysts in Mineralization of Aqueous Organic Contaminants through Solar Simulated Radiation

Water contamination with various contaminants, including organic species, is a global concern. Reclamation through safe, economic and technically feasible methods is imperative. Two perovskites, zinc titanate (ZnTiO3) and manganese titanate (MnTiO3), mixed with TiO2 phases, were prepared as nano-powders and nano-films. The materials were characterized and used as catalysts in photodegradation of aqueous methylene blue, a hazardous model contaminant, using solar simulated radiation. The effects of various reaction conditions on the photodegradation were examined. The kinetics indicated the suitability of using the process at various contaminant concentrations and catalyst loadings. Both powder and film catalysts completely removed the contaminant in less than 6 h. Powder and film forms of the MnTiO3 mixture were more efficient than their ZnTiO3 counterparts. In both perovskite mixtures, the films exhibited higher catalytic efficiency than the powders. The film materials exhibited high catalytic efficiency in both the continuous flow and batch processes. Water contaminated with various methylene blue concentrations can be treated by the film catalysts that can be recovered and reused with no technical difficulties. The results open new horizons for larger-scale water purification processes