The rhodium oxide (Rh₂O₃) doping effect on the activity and stability of nickel catalysts supported over yttria-stabilized zirconia was examined in dry reforming of methane (DRM) by using a tubular reactor, operated at 800 °C. The catalysts were characterized by using several techniques including nitrogen physisorption, X-ray diffraction, transmission electron microscopy, H₂-temperature programmed reduction, CO₂-temperature programmed Desorption, and temperature gravimetric analysis (TGA). The morphology of Ni-YZr was not affected by the addition of Rh₂O₃. However, it facilitated the activation of the catalysts and reduced the catalyst’s surface basicity. The addition of 4.0 wt.% Rh₂O₃ gave the optimum conversions of CH₄ and CO₂ of ~89% and ~92%, respectively. Furthermore, the incorporation of Rh₂O₃, in the range of 0.0–4.0 wt.% loading, enhanced DRM and decreased the impact of reverse water gas shift, as inferred by the thermodynamics analysis. TGA revealed that the addition of Rh₂O₃ diminished the carbon formation on the spent catalysts, and hence, boosted the stability, owing to the potential of rhodium for carbon oxidation through gasification reactions. The 4.0 wt.% Rh₂O₃ loading gave a 12.5% weight loss of carbon. The TEM images displayed filamentous carbon, confirming the TGA results.

Due to the large versatility in organic semiconductors, selecting a suitable (organic semiconductor) material for photodetectors is a challenging task. Integrating computer science and artificial intelligence with conventional methods in optimization and material synthesis can guide experimental researchers to develop, design, predict and discover high-performance materials for photodetectors. To find high-performance organic semiconductor materials for photodetectors, it is crucial to establish a relationship between photovoltaic properties and chemical structures before performing synthetic procedures in laboratories. Moreover, the fast prediction of energy levels is desirable for designing better organic semiconductor photodetectors. Herein, we first collected large sets of data containing photovoltaic properties of organic semiconductor photodetectors reported in the literature. In addition, molecular descriptors that make it easy and fast to predict the required properties were used to train machine learning models. Power conversion efficiency and energy levels were also predicted. Multiple models were trained using experimental data. The light gradient boosting machine (LGBM) regression model and Hist gradient booting regression model are the best models. The best models were further tuned to achieve better prediction ability. The reliability of our designed approach was further verified by mining the photovoltaic database to search for new building units. The results revealed that good consistency is obtained between experimental outcomes and model predictions, indicating that machine learning is a powerful approach to predict the properties of photodetectors, which can facilitate their rapid development in various fields.

This study concerns the role of activated carbon (AC) from palm raceme as a support material for the enhancement of lipase-catalyzed reactions in an aqueous solution, with deep eutectic solvent (DES) as a co-solvent. The effects of carbonization temperature, impregnation ratio, and carbonization time on lipase activity were studied. The activities of Amano lipase from Burkholderia cepacia (AML) and lipase from the porcine pancreas (PPL) were used to investigate the optimum conditions for AC preparation. The results showed that AC has more interaction with PPL and effectively provides greater enzymatic activity compared with AML. The optimum treatment conditions of AC samples that yield the highest enzymatic activity were 0.5 (NaOH (g)/palm raceme (g)), 150 min, and a carbonization temperature of 400 °C. DES was prepared from alanine/sodium hydroxide and used with AC for the further enhancement of enzymatic activity. Kinetic studies demonstrated that the activity of PPL was enhanced with the immobilization of AC in a DES medium.