Search

Catalytic conversion of biomass or biomass-derived intermediate to value-added chemicals is important for both biomass waste management and production of industrially important chemicals. Oxidation of 5-hydroximethyl furfural (HMF) is considered one of the most important biomass conversion processes, which resulted in many value-added products such as 2,5-diformylfuran (DFF), 2,5-furandicarboxylic acid (FDCA), 5-hydroxymethyl-2-furancarboxylic acid (HMFCA), and 5-formyl-2-furancarboxylic acid (FFCA). In this study, the three morphologies of CdS catalyst (nanorod, nanosheet, and nanosphere) with two different crystalline structures are synthesized and characterized by SEM, TEM, and XRD analysis. The oxidation of HMF to FFCA is performed using the synthesized catalysts in the presence of different solvents and oxidizing agents. We find that CdS nanorod provides the selective oxidation of HMF to FFCA in the presence of dimethyl sulfoxide solvent and tert-butyl hydrogen peroxide oxidizing agent. The density functional theory (DFT) simulations are carried out to explain the catalytic activity of the CdS catalyst for oxidation of HMF to FFCA. The DFT simulations show that CdS is an excellent catalyst for binding HMF on the CdS surface. Our findings provide the way of effective oxidation of biomass into value-added products using the cheap CdS catalyst.

Polybetaines have received widespread attention due to their smart response properties and structures which resemble biological polymers like peptides and DNA. However, few studies have focused on the controlled synthesis and self-assembly of hydrophobically modified polybetaines due to the difficulty of synthesizing these materials. We report the first molecular weight-controlled synthesis of hydrophobically modified polycarboxybetaines (HMPCB). Poly(dodecyl grafted aminocrotonate -methacrylic acid) (P(DACRO-MAA)) was synthesized via the reversible addition-fragmentation chain-transfer (RAFT) polymerization approach. The two different tautomers of the monomer were also successfully identified and separated via thin layer chromatography (TLC) and column chromatography, making it possible to obtain pure polycarboxybetaine via RAFT synthesis. Both the successfully separated enamine form of the monomer and the resulting polycarboxybetaine were confirmed via FTIR and NMR. The polycarboxybetaine was found to have a low polydispersity (PDI) of 1.214, and its molecular weight was determined as 70590 g/mol via gel permeation chromatography (GPC) measurements. Spherical, rodlike, and fractal assembled structures for the P(DACRO-MAA) were observed with pH change using TEM, zeta sizer, and dynamic light scattering (DLS). The unique self-assembled structures of HMPCB synthesized via RAFT provide an opportunity to understand fundamental polymer science and can be engineered for broad applications.

The ability to estimate the force field parameters of materials is critical for calculating the properties of materials using molecular dynamics (MD) simulations. The density functional theory and empirical methods are used to calculate the force field parameters. These force filed parameters must be tuned in order to accurately capture the properties of materials using MD simulations. For performing MD simulations in ionic liquid systems, we tuned the force field parameters using Machine Learning techniques. We have specifically provided an example for tuning partial charges derived from the general Amber force field (GAFF) parameters for ionic liquids (ILs). We have performed equilibrium MD simulations with various partial charges at varied temperatures and pressures, and we obtained density of ILs at each temperature and pressure. We then use this MD simulation data to train several ML models to predict partial charges based on the experimental features of ILs. We employ several renowned techniques such as LASSO, Elastic Net, Partial Least Squares Regression, and Random Forest along with two stacked models using Mean Stacking and Linear Stacking. The predictions from our ML-based models follow the experimental data closely with the stacked models displaying the best overall predictive performance. The prediction model presented here is general and could be used to tune the force field parameters for a wide variety of application systems.

Photocatalytic water splitting is a promising path for generating hydrogen which will decrease the dependency on conventional fossil fuels to generate power and provides an environmentally benign way to store solar energy. Designing photocatalysts is one of the key challenges in making photocatalytic water splitting efficient and economically viable. Heterojunction formation using different functional materials in a single photo-catalyst has the potential of broadening light harvesting properties, improving chemical stability, enhancing the photoexcited charge separation, and thus boosting water splitting efficiency. This article gives an overview on the heterojunction strategy for improving photocatalytic water splitting performance. Recent developments in different visible light-responsive heterojunction systems are discussed for metal oxide–metal oxide and metal oxide–non-metal oxide heterojunctions. Along with experimental observation and the proposed charge separation mechanism, synthesis techniques of heterojunction materials are also included in this article. In addition to recent progress in the heterojunction-based photocatalytic system, this review article also provides future directions for photocatalytic water splitting.

Water splitting is an important technique to store solar energy in the simple form of chemical energy, such as hydrogen. Strontium titanate (SrTiO3) is one of the most promising photocatalysts to produce hydrogen gas from water splitting. In this research, an electrospinning technique in combination with sol-gel method was developed to synthesize 3D porous SrTiO3 nanostructures. Different crystallite sizes of SrTiO3-nanofibers (STO-NFs) were produced by varying the synthesis parameters including precursor concentration and calcination temperature. The synthesized nanofibers were characterized using DSC, TGA, XRD, SEM, and TEM. The crystallite size of STO-NFs decreases with increasing precursor concentration (3.03–15.78 vol.%) and gradually increases as the calcination temperature increases within the range of 600–800 °C. The photocatalytic activity of different STO-NFs (based on crystallite size) was also evaluated by the amount of H2 production from water splitting under UV irradiation. The H2 evolution study demonstrated that the photocatalytic activity of the STO-NFs strongly depends on the crystallite size of the nanofibers, precursor concentration, and calcination temperature. The H2 production rate increases with increasing crystallite size and temperature, whereas it decreases with increasing precursor concentration. The photocatalytic performance of the STO-NFs was also compared with the commercial SrTiO3 nanoparticles (STO-NPs) after Pt addition as a cocatalyst, where the synthesized nanofibers showed 2 times higher H2 production rate (1.14 mmol/g-h) than that of the nanoparticles. This synthesis technique provides a good example to produce other inorganic photocatalytic 3D porous structure materials.