Accelerating Charge Separation and CO2 Photoreduction in Aqueous Phase under Visible Light with Ru Nanoparticles Loaded on Ga-Doped NiTiO3 in a Batch Photoreactor.

Titanate perovskite (ATiO3) semiconductors show prospects of being active photocatalysts in the conversion of CO2 to chemical fuels such as methanol (CH3OH) in the aqueous phase. Some of the challenges in using ATiO3 are limited light-harvesting capability, rapid bulk charge recombination, and the low density of catalytic sites participating in CO2 reduction. To address these challenges, Ga-doped NiTiO3 (GNTO) photocatalysts in which Ga ions substitute for Ti ions in the crystal lattice to form electron trap states and oxygen vacancies have been synthesized in this work. The synthesized GNTO was then loaded with Ru nanoparticles to accelerate charge separation and enable excellent CO2 photoreduction activity under visible light. CO2 photoreduction was conducted in a batch photoreactor charged with a 0.1 M NaHCO3 aqueous solution at room temperature and a 3.5 bar pressure using a 1.0 wt % Ru-GNTO photocatalyst to yield methanol at a rate of 84.45 µmol g-1 h-1. A small amount of methane was produced as a side product at 21.35 µmol g-1 h-1, which is also a fuel molecule. We attribute this high catalytic activity toward CO2 photoreduction to a synergistic combination of our novel heterostructured 1.0 wt % Ru-GNTO photocatalyst and the implementation of a pressurized photoreactor. This work demonstrates an effective strategy for metal doping with active nanospecies functionality to improve the performance of ATiO3 photocatalysts in valorizing CO2 to solar fuels.

O-Vacancy Mediated Partially Inverted Ferrospinels for Enhanced Activity in the Sulfuric Acid Decomposition for Hydrogen Production.

Understanding the characterization of a tailored Co3O4 spinel with Fe3+ doping poses a challenge due to the surface state complexity in bifunctional catalysts with higher cation diversity. Doping with secondary metal results in a double spinel structure (a hybrid of normal and inverted spinels). This enhances the catalytic properties by generating more active oxygen vacancies. The cobalt-rich (FeCo2O4) hybrid spinel and iron-rich (CoFe2O4) inverted spinel are synthesized using a wet impregnation method, supported over oxidized SiC (SiC-Pretrt) for an improved metal-support interaction. FeCo2O4 on pretreated SiC exhibits the highest catalytic activity (90% conversion at 1173 K) and stability (over 100 h) in sulfuric acid decomposition of the iodine-sulfur process for hydrogen production. This improved performance is attributed to the high electronegativity of Co3+, oxygen vacancies, and strong metal-support interaction. The high electronegativity of Co3+ weakens the S-O bond in M-S-O, enhancing the catalytic activity of the spinels. These results are further corroborated by detailed characterization and density functional theory calculations.

Multiobjective Bayesian Optimization Framework for the Synthesis of Methanol from Syngas Using Interpretable Gaussian Process Models.

Methanol production has gained considerable interest on the laboratory and industrial scale as it is a renewable fuel and an excellent hydrogen energy storehouse. The formation of synthesis gas (CO/H2) and the conversion of synthesis gas to methanol are the two basic catalytic processes used in methanol production. Machine learning (ML) approaches have recently emerged as powerful tools in reaction informatics. Inspired by these, we employ Gaussian process regression (GPR) to the model conversion of carbon monoxide (CO) and selectivity of the methanol product using data sets obtained from experimental investigations to capture uncertainty in prediction values. The results indicate that the proposed GPR model can accurately predict CO conversion and methanol selectivity as compared to other ML models. Further, the factors that influence the predictions are identified from the best GPR model employing "Shapley Additive exPlanations" (SHAP). After interpretation, the essential input features are found to be the inlet mole fraction of CO (Y(CO, in)) and the net inlet flow rate (Fin(nL/min)) for our best prediction GPR models, irrespective of our data sets. These interpretable models are employed for Bayesian optimization in a weighted multiobjective framework to obtain the optimal operating points, namely, maximization of both selectivity and conversion.

SO3 decomposition over silica-modified ß-SiC supported CuFe2O4 catalyst: characterization, performance, and atomistic insights.

The sulfur-iodine (S-I) thermochemical water-splitting cycle is one of the potential ways to produce hydrogen on a large scale. CuFe2O4 was dispersed over modified silica or treated ß-SiC and untreated ß-SiC using the wet impregnation method for SO3 decomposition, which is the most endothermic reaction of the S-I cycle. Various state-of-the-art techniques such as XRD, FT-IR, BET, XPS, TEM, HR-TEM, FESEM-EDS and elemental mapping were employed to characterize both the synthesized catalysts. CuFe2O4 catalyst supported on silica-modified ß-SiC resulted in enhanced catalytic activity and stability due to better metal-support interaction. In order to get a better insight into the reaction mechanism over this bimetallic catalyst, the first principles based simulation under the framework of density functional theory was performed. We have found that the presence of Cu gives rise to an improved charge localization at the O-vacancy site alongside favourable reaction kinetics, which results in an enhanced catalytic activity for the CuFe2O4 nano-cluster compared to that of a single metallic catalyst containing Fe2O3 nano-cluster.

Techno-economic analysis of ethanol production from lignocellulosic biomass-a comparison of fermentation, thermo catalytic, and chemocatalytic technologies.

Bioethanol produced from 2nd generation biomass comprising of agricultural residues and forest wastes is a viable alternate fuel. Besides fermentation and biomass gasification to syngas and its further conversion to ethanol, a direct chemocatalytic conversion of lignocellulosic biomass into ethanol is being investigated as a viable route which avoids the emission of greenhouse gases. In this work, a detailed configuration of chemocatalytic route is simulated and optimized for minimizing the cost of ethanol production. The economic feasibility of ethanol production through the chemocatalytic pathway is analyzed. The techno-economic analysis is conducted in terms of ethanol selectivity and ethanol production cost. The obtained results show that biomass feedstock and catalyst have major contributions to the production cost. The proposed route is found to be giving a lower ethanol selling price as compared to the well-researched routes of biomass fermentation to ethanol and biomass gasification followed by syngas conversion to ethanol.

Catalytic Conversion of Glucose into Levulinic Acid Using 2-Phenyl-2-Imidazoline Based Ionic Liquid Catalyst.

Levulinic acid (LA) is an industrially important product that can be catalytically valorized into important value-added chemicals. In this study, hydrothermal conversion of glucose into levulinic acid was attempted using Brønsted acidic ionic liquid catalyst synthesized using 2-phenyl-2-imidazoline, and 2-phenyl-2-imidazoline-based ionic liquid catalyst used in this study was synthesized in the laboratory using different anions (NO3, H2PO4, and Cl) and characterized using 1H NMR, TGA, and FT-IR spectroscopic techniques. The activity trend of the Brønsted acidic ionic liquid catalysts synthesized in the laboratory was found in the following order: [C4SO3HPhim][Cl] > [C4SO3HPhim][NO3] > [C4SO3HPhim][H2PO4]. A maximum 63% yield of the levulinic acid was obtained with 98% glucose conversion at 180 °C and 3 h reaction time using [C4SO3HPhim][Cl] ionic liquid catalyst. The effect of different reaction conditions such as reaction time, temperature, ionic liquid catalyst structures, catalyst amount, and solvents on the LA yield were investigated. Reusability of [C4SO3HPhim][Cl] catalyst up to four cycles was observed. This study demonstrates the potential of the 2-phenyl-2-imidazoline-based ionic liquid for the conversion of glucose into the important platform chemical levulinic acid.

Effectiveness of reactive oxygen species generated from rGO/CdS QD heterostructure for photodegradation and disinfection of pollutants in waste water.

The present study investigates the role of reactive oxygen species (ROS) generated on surface of nanophotocatalyst in wastewater treatment discharged from exponentially growing industries. A facile synthetic route is presented to produce reduced graphene oxide/CdS quantum dot (rGO/CdS QD) heterostructure by monowave-assisted solvothermal method where room temperature ionic liquid 1-ethyl-3-methylimidazolium thiocyanate serves as a "green" precursor. The prepared photocatalyst was tested for: (1) photodegradation performance against various cationic dyes, anionic dyes, and antibiotics as model organic water pollutants; and (2) disinfection performance against gram-positive S. aureus and gram-negative E. coli bacterial strains as pathogenic water pollutants. The negative surface charge of rGO/CdS QD precisely attracted the cationic dye molecules to its surface and degraded the dyes at a higher rate. Moreover, excellent antibacterial activity of rGO/CdS QD were observed against S. aureus and E. coli with a minimum inhibitory concentration of 16 µg ml-1 and 32 µg ml-1, respectively. A plausible mechanism of the photocatalytic activity suggested that ROS with strong oxidizing ability reacts with the organic pollutants to mineralize them into CO2, H2O or some other small molecules, and reacts with pathogens to damage the macromolecules like proteins, lipids, DNA, etc in the bacterial cells. Among all the surface generated ROS, hydroxyl radicals was found to be the main contributor in the photodegradation and disinfection mechanism.

NSAIDs as potential treatment option for preventing amyloid ß toxicity in Alzheimer's disease: an investigation by docking, molecular dynamics, and DFT studies.

Aggregation of amyloid beta (Aß) protein considered as one of contributors in development of Alzheimer's disease (AD). Several investigations have identified the importance of non-steroidal anti-inflammatory drugs (NSAIDs) as Aß aggregation inhibitors. Here, we have examined the binding interactions of 24 NSAIDs belonging to eight different classes, with Aß fibrils by exploiting docking and molecular dynamics studies. Minimum energy conformation of the docked NSAIDs were further optimized by density functional theory (DFT) employing Becke's three-parameter hybrid model, Lee-Yang-Parr (B3LYP) correlation functional method. DFT-based global reactivity descriptors, such as electron affinity, hardness, softness, chemical potential, electronegativity, and electrophilicity index were calculated to inspect the expediency of these descriptors for understanding the reactive nature and sites of the molecules. Few selected NSAID-Aß fibrils complexes were subjected to molecular dynamics simulation to illustrate the stability of these complexes and the most prominent interactions during the simulated trajectory. All of the NSAIDs exhibited potential activity against Aß fibrils in terms of predicted binding affinity. Sulindac was found to be the most active compound underscoring the contribution of indene methylene substitution, whereas acetaminophen was observed as least active NSAID. General structural requirements for interaction of NSAIDs with Aß fibril include: aryl/heteroaryl aromatic moiety connected through a linker of 1-2 atoms to a distal aromatic group. Considering these structural requirements and electronic features, new potent agents can be designed and developed as potential Aß fibril inhibitors for the treatment of AD.

An investigation on biosorption of nitrate from water by chitosan based organic-inorganic hybrid biocomposites.

In this study, three types of crosslinked organic-inorganic hybrid biocomposites, such as chitosan/bentonite, chitosan/titanium oxide, and chitosan/alumina (ChBT, ChTi, and ChAl respectively) were prepared and utilized for the removal of nitrate from water by batch biosorption experiments. Effects of crosslinker dose, initial nitrate concentration, contact time, initial pH of the nitrate solution, biosorbent dose, temperature, and the presence of competitive ions on adsorption capacities were investigated. Actual adsorption capacities of ChBT, ChTi, and ChAl at a crosslinker to chitosan solution ratio of 1:40 were 35.68 and 43.62, and 45.38mg/g as nitrate respectively. The actual adsorption capacities decreased with increase in crosslinker dose. Adsorption equilibrium isotherm models data were well fitted to the linear Freundlich isotherm model. Thermodynamic parameters indicate that adsorption process was spontaneous and endothermic. The adsorption process was better described by a pseudo-second-order equation. The results show that chitosan based organic-inorganic biocomposites were effective, low cost, and reusable for the removal of nitrate from water.

Synergistic effect of chloro and sulphonic acid groups on the hydrolysis of microcrystalline cellulose under benign conditions.

The hydrolysis of cellulose catalysed by ionic liquid (IL) immobilized on chloromethyl vinyl benzene (CMVB) with different IL/CMVB ratio was carried out in water as a solvent. The influence of process variables like IL/CMVB ratio in catalyst, temperature and time were investigated in a batch reactor. It was found that 40% IL/CMVB catalyst afforded maximum%TRS and glucose yield 58.5 and 47.9% respectively at 160 °C in 6h reaction time. This can be attributed to the synergistic effect of chloro and sulfonic groups, to dissolve the cellulose by breaking the intra and inter molecular hydrogen bonds and cleave the ß-1, 4 glycosidic bonds respectively. The catalysts synthesized in the laboratory were characterized by FTIR, CHNS and TGA. The catalyst can be recovered three times without any significant loss in activity and characterized by FTIR to show the peaks of chloro and sulfonic groups in the recovered catalyst.

Hydrolysis of microcrystalline cellulose using functionalized Bronsted acidic ionic liquids - A comparative study.

Cellulose conversion to platform chemicals is required to meet the demands of increasing population and modernization of the world. Hydrolysis of microcrystalline cellulose was studied with SO3H, COOH and OH functionalized imidazole based ionic liquid using 1-butyl-3-methylimidazolium chloride [BMIM]Cl as a solvent. The influence of temperature, time, acidity of ionic liquids and catalyst loading was studied on hydrolysis reaction. The maximum %TRS yield 85%, was obtained at 100°C and 90min with 0.2g of SO3H functionalized ionic liquid. UV-vis spectroscopy using 4-nitro aniline as an indicator was performed to find out the Hammett function of ionic liquid and acidity trends are as follows: SO3H>COOH>OH. Density functional theory (DFT) calculations were performed to optimize the ionic liquid and their conjugate bases at B3LYP 6-311G++ (d, p) level using Gaussian 09 program. Theoretical findings are in agreement with the experimental results.