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Efficient and selective oxidative dehydrogenation (ODH) catalysts are crucial to advance the production of valuable petrochemicals. In this study, we leverage the power of machine learning to predict dehydrogenation (DH) product yield and unravel the factors influencing the product distribution. A comprehensive data set obtained from experiments conducted in a fixed-bed reactor under varying temperatures, feed ratios (O 2 / n -butane), and metal oxide loadings (Ni, Fe, Co, Bi, Mo, W, Zn, and Mn) on an aluminum oxide support served as the basis for model development. Three supervised machine learning models, Boosted Tree (BT), Extreme Gradient Boosting Linear (XGBL), and Support Vector Machine Radial (SVMR), were evaluated. The ensemble technique of the three models showed remarkable accuracy, with an RMSE of 1.65 and MAE of 1.14 on the test data set, and it demonstrated robust generalization capabilities by capturing 87% of the variation in DH yield. In the feature importance analysis of the selected models, Mo, Co, Ni, and W emerged as critical factors influencing the DH yield. The practical significance of these findings lies in their potential to revolutionize catalysis research and industrial applications. The ability of the ensemble model to predict DH yields opens new avenues for optimizing DH products and designing more advanced catalysts. By providing essential insights into the influential variables governing the ODH reactions, researchers can make informed decisions to achieve higher yields and efficiencies., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

The thermochemical conversion of CO 2 into methanol, a process known for its selectivity, often encounters a significant obstacle: the reverse water gas reaction. This problem emerges due to the demanding high temperatures and pressures, causing instability in catalytic performance. Recent endeavours have focused on innovatively designing catalysts capable of withstanding such conditions. Given the costliness of experimental approaches, a theoretical framework has emerged as a promising avenue for addressing the challenges in methanol production. It has been reported that transition metals, especially Pd, provide ideal binding sites for CO 2 molecules and hydrogen atoms, facilitating their interactions and subsequent conversion to methanol. In the geometric single-atom form, their surface enables precise control over the reaction pathways and enhances the selectivity towards methanol. In our study, we employed density functional theory (DFT) to explore the conversion of CO 2 to CH 3 OH on Pd 1 -Cu(111) and Pd 1 -Ag(111) single-atom alloy (SAA) catalysts. Our investigation involved mapping out the complex reaction pathways of CO 2 hydrogenation to CH 3 OH using microkinetic reaction modelling and mechanisms. We examined three distinct pathways: the COOH* formation pathway, the HCOO* formation pathway, and the dissociation of CO 2 * to CO* pathway. This comprehensive analysis encompassed the determination of adsorption energies for all reactants, transition states, and resultant products. Additionally, we investigated the thermodynamic and kinetic profiles of individual reaction steps. Our findings emphasised the essential role of the Pd single atom in enhancing the activation of CO 2 , highlighting the key mechanism underlying this catalytic process. The favoured route for methanol generation on the Pd 1 -Ag(111) single-atom alloy (SAA) surface unfolds as follows: CO 2 * progresses through a series of transformations, transitioning successively into HCOO*, HCOOH*, H 2 COOH*, CH 2 O*, and CH 2 OH*, terminating in the formation of CH 3 OH*, due to lower activation energies and higher rate constants.

An iron-based SBA-16 mesoporous silica (ferrisilicate) with a large surface area and three-dimensional (3D) pores is explored as a potential insulin delivery vehicle with improved encapsulation and loading efficiency. Fe was incorporated into a framework of ferrisilicate using the isomorphous substitution technique for direct synthesis. Fe 3+ species were identified using diffuse reflectance spectroscopy. The large surface area (804 m 2 /g), cubic pores (3.2 nm) and insulin loading were characterized using XRD, BET surface area, FTIR and TEM analyses. For pH sensitivity, the ferrisilicate was wrapped with polyethylene glycol (MW = 400 Daltons) (PEG). For comparison, Fe (10 wt%) was impregnated on a Korea Advanced Institute of Science and Technology Number 6 (KIT-6) sieve and Mesocellular Silica Foam (MSU-F). Insulin loading was optimized, and its release mechanism was studied using the dialysis membrane technique (MWCO = 14,000 Da) at physiological pH = 7.4, 6.8 and 1.2. The kinetics of the drug's release was studied using different structured/insulin nanoformulations, including Santa Barbara Amorphous materials (SBA-15, SBA-16), MSU-F, ultra-large-pore FDU-12 (ULPFDU-12) and ferrisilicates. A different insulin adsorption times (0.08-1 h), insulin/ferrisilicate ratios (0.125-1.0) and drug release rates at different pH were examined using the Korsmeyer-Peppas model. The rate of drug release and the diffusion mechanisms were obtained based on the release constant (k) and release exponent (n). The cytotoxicity of the nanoformulation was evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay using human foreskin fibroblast (HFF-1) cells. A low cytotoxicity was observed for this nanoformulation starting at the highest concentrations used, namely, 400 and 800 μg. The hypoglycemic activity of insulin/ferrisilicate/PEG on acute administration in Wistar rats was studied using doses of 2, 5 and 10 mg/kg body weight. The developed facile ferrisilicate/PEG nanoformulation showed a high insulin encapsulation and loading capacity with pH-sensitive insulin release for potential delivery through the oral route.

Water and wastewater treatment applications stand to benefit immensely from the design and development of new materials based on silica nanoparticles and their derivatives. Nanosilica possesses unique properties, including low toxicity, chemical inertness, and excellent biocompatibility, and can be developed from a variety of sustainable precursor materials. Herein, we provide an account of the recent advances in the synthesis and utilization of nanosilica for wastewater treatment. This review covers key physicochemical aspects of several nanosilica materials and a variety of nanotechnology-enabled wastewater treatment techniques such as adsorption, separation membranes, and antimicrobial applications. It also discusses the prospective design and tuning options for nanosilica production, such as size control, morphological tuning, and surface functionalization. Informative discussions on nanosilica production from agricultural wastes have been offered, with a focus on the synthesis methodologies and pretreatment requirements for biomass precursors. The characterization of the different physicochemical features of nanosilica materials using critical surface analysis methods is discussed. Bio-hybrid nanosilica materials have also been highlighted to emphasize the critical relevance of environmental sustainability in wastewater treatment. To guarantee the thoroughness of the review, insights into nanosilica regeneration and reuse are provided. Overall, it is envisaged that this work's insights and views will inspire unique and efficient nanosilica material design and development with robust properties for water and wastewater treatment applications., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

n -pentane catalytic cracking was studied over a series of MFI zeolites with varying SiO 2 /Al 2 O 3 ratios (30, 80, 280, 500, and 1500) using a fixed-bed reactor operated at temperature 550-650 °C. Other MFI zeolites (SiO 2 /Al 2 O 3 = 280) with various crystal morphology and size (such as large crystal and nano size) were also synthesized and tested for n -pentane cracking. The effects of MFI zeolite modification with ammonia and phosphorus on its physiochemical properties and catalytic activity were investigated. Among the parent MFI zeolites, MFI (280) demonstrated high selectivity (51%) towards light olefins (C 3 = /C 2 = = 0.7) at 650 °C with undesired C 1 -C 4 alkanes (38%). Surface modified MFI (280) zeolites of different crystal size and morphology showed improvement towards propylene selectivity by suppressing undesired reactions. Phosphorous-modified MFI zeolite with a large crystal size was found to improve light olefin selectivity (52.2%) with C 3 = /C 2 = = ∼1.3 and reduce undesired C 1 -C 4 alkanes (8%) formation due to suppressed strong acidic sites. The characterization and evaluation results for the modified MFI (280) revealed that the incorporation of phosphorous created moderate acidic sites, which were stabilized by some non-framework aluminum species, thereby leading to suppressing the formation of undesired C 1 -C 4 alkanes with improved light olefins selectivity., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)

Dexamethasone (Dex) is used in drug regimen for treatment of Coronavirus disease (COVID-19). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) fusion and entry into the cell occurs at pH 5.5. In our present study, we have identified a green, cheap clay based halloysite (Hal) nanoformulation with release capability of Dex at such interactive pH condition. 30%ZnFe 2 O 4 /Hal and 30%NiFe 2 O 4 /Hal were prepared by one-pot synthesis technique. Dex (5% wt/wt) was functionalized over both nanocomposites. Finally, polyethylene glycol (PEG) was coated over ZnFe 2 O 4 /Hal/Dex and NiFe 2 O 4 /Hal/Dex nanocomposite using lyophilization technique (0.08 μl/mg of nanocarrier). The release ability of Dex was studied under pulmonary infection and normal pH conditions (pH = 5.6 and 7.4). The characterization study using X-ray diffraction (XRD) and UV-visible diffuse reflectance (DRS) spectra confirmed the presence of spinel ferrites over Hal. Nitrogen adsorption isotherm showed the surface area of ZnFe 2 O 4 /Hal (75 m 2 /g), pore volume (0.27 cm 3 /g) with average pore size (14.5 nm). Scanning electron microscope/Energy dispersive spectroscopy (SEM-EDS) and Transmission electron microscopy analysis revealed a textural change in halloysite tubular type indicating drug adsorption and PEG adhesion. DRS spectra indicated an intergrowth of zinc ferrite nanoparticles on the halloysite nanotubes. Interestingly, ZnFe 2 O 4 /Hal/Dex/PEG exhibited a high Dex release ability (17.5%, 168 h) at pH = 5.6 relevant to SARS-CoV-2 fusion entry into the cell pH condition of 5.5. Comparatively, the nanocomposite showed a less Dex release (<5%) release for 168 h at neutral pH = 7.4. The drug release kinetics were studied and the obtained data were fitted for the release constant and release exponent, using the Korsmeyer-Peppas model. To test the compatibility of our nanocomposites, we performed the cell viability assay (MTT) using HEK293 cells. Our results showed that at 0.3 mg/ml, Dex-loaded nanocomposite had a statistically significant improvement in cell viability compared to Dex alone. These results suggest that our nanocomposite has prevented the toxic effect of Dex and has huge potential to act as pulmonary drug delivery system for targeted lung infection therapeutics., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 Elsevier B.V. All rights reserved.)