Arsenate Anion-π Interactions on Amine-Modified Polydivinylbenzene in Aqueous Systems: Experimental and Theoretical Investigation.

Anion-π interactions aiding in the adsorption of anions in the solution phase, though challenging to quantify, have attracted a lot of attention in supramolecular chemistry. We present the design of a polymer adsorbent that quantifies the adsorption of arsenate ions experimentally by optimizing anion-π interactions in a purely aqueous system and use density functional theory to compare these results with theoretical data. Arsenate anions are removed from water by amine-functionalized polydivinylbenzene using the comonomer 1-vinyl-1,2,4-triazole, which was cross-linked with divinylbenzene via radical polymerization in a hydrothermal procedure.

Partial oxidation of methane to methanol on boron nitride at near critical acetonitrile.

Direct catalytic conversion of methane to methanol with O has been a fundamental challenge in unlocking abundant natural gas supplies. Metal-free methane conversion with 17% methanol yield based on the limiting reagent O at 275 °C was achieved with near supercritical acetonitrile in the presence of boron nitride. Reaction temperature, catalyst loading, dwell time, methane-oxygen molar ratio, and solvent-oxygen molar ratios were identified as critical factors controlling methane activation and the methanol yield.

Role of catalytic nitrile decomposition in tricopper complex mediated direct partial oxidation of methane to methanol.

Synthetic homogeneous system known to date performing methane to methanol conversion using O as terminal oxidant is unique and based on copper complex with piperazine-based ligand (CuL in Fig. 1) in a medium of acetonitrile. Prior work have shown that in order to achieve catalytic turnover, hydrogen peroxide is needed to regenerate the active site.

Trends in Solid Adsorbent Materials Development for CO Capture.

A recent report from the United Nations has warned about the excessive CO emissions and the necessity of making efforts to keep the increase in global temperature below 2 °C. Current CO capture technologies are inadequate for reaching that goal, and effective mitigation strategies must be pursued. In this work, we summarize trends in materials development for CO adsorption with focus on recent studies.

Energy-Geometry Dependency of Molecular Structures: A Multistep Machine Learning Approach.

There is growing interest in estimating quantum observables while circumventing expensive computational overhead for facile in silico materials screening. Machine learning (ML) methods are implemented to perform such calculations in shorter times. Here, we introduce a multistep method based on machine learning algorithms to estimate total energy on the basis of spatial coordinates and charges for various chemical structures, including organic molecules, inorganic molecules, and ions.

Synthesis of Large Mesoporous-Macroporous and High Pore Volume, Mixed Crystallographic Phase Manganese Oxide, MnO/MnO Sponge.

The controlled synthesis of mixed crystallographic phase MnO/MnO sponge material by varying heating rates and isothermal segments provides valuable information about the morphological and physical properties of the obtained sample. The well-characterized MnO/MnO sponge and applicability of difference in reactivity of H and CO desorbed during the synthesis provide new developments in the synthesis of metal oxide materials with unique morphological and surface properties. We report the preparation of a MnO/MnO sponge using a metal nitrate salt, water, and Dextran, a biopolymer consisting of glucose monomers.

Machine Learning Using Combined Structural and Chemical Descriptors for Prediction of Methane Adsorption Performance of Metal Organic Frameworks (MOFs).

Using molecular simulation for adsorbent screening is computationally expensive and thus prohibitive to materials discovery. Machine learning (ML) algorithms trained on fundamental material properties can potentially provide quick and accurate methods for screening purposes. Prior efforts have focused on structural descriptors for use with ML.

Photocatalytic Water Splitting-The Untamed Dream: A Review of Recent Advances.

Photocatalytic water splitting using sunlight is a promising technology capable of providing high energy yield without pollutant byproducts. Herein, we review various aspects of this technology including chemical reactions, physiochemical conditions and photocatalyst types such as metal oxides, sulfides, nitrides, nanocomposites, and doped materials followed by recent advances in computational modeling of photoactive materials. As the best-known catalyst for photocatalytic hydrogen and oxygen evolution, TiO₂ is discussed in a separate section, along with its challenges such as the wide band gap, large overpotential for hydrogen evolution, and rapid recombination of produced electron-hole pairs.