Energy material - the role of silicotungstic acid and fly ash in sulfonated poly (ether sulfone) composites for PEMFC applications

The composite polymer electrolyte membranes were prepared from sulfonated poly (ether sulfone) (SPES), silicotungstic acid (STA) and fly ash (FA). Post sulfonation process was adopted to synthesize SPES using sulphuric and chlorosulfonic acid. The prepared electrolyte membranes were examined by water uptake capacity, swelling ratio, ion-exchange ability, proton conductivity, thermal stability and electrochemical performance for evaluating the pertinence of these membranes in fuel cell applications. As such the pristine membrane restricts with the proton conductivity of 0.042?S cm^?1 at 30?°C and 0.060?S cm^?1 at 90?°C while the polymer composite membrane, SP-STA-FA-10 reveals the maximum conductivity of 0.054?S cm^?1 at 30?°C and 0.073?S cm^?1 at 90?°C. It also exhibits good thermal stability than that of the pure membrane. The membrane electrode assemblies (MEAs) have been successfully developed from SPES as well as SP-STA-FA-10 membranes and their electrochemical performance were studied the wide range of current density. Herein, the composite membranes derived from SPES, STA and FA can be viable candidates for fuel cell applications.     

Electronic,redox, and optical property prediction of organic π-conjugated molecules through a hierarchy of machine learning approaches

Accelerating the development of π-conjugated molecules for applications such as energy generation and storage, catalysis, sensing, pharmaceuticals, and (semi)conducting technologies requires rapid and accurate evaluation of the electronic, redox, or optical properties. While high-throughput computational screening has proven to be a tremendous aid in this regard, machine learning (ML) and other data-driven methods can further enable orders of magnitude reduction in time while at the same time providing dramatic increases in the chemical space that is explored. However, the lack of benchmark datasets containing the electronic, redox, and optical properties that characterize the diverse, known chemical space of organic π-conjugated molecules limits ML model development. Here, we present a curated dataset containing 25k molecules with density functional theory (DFT) and time-dependent DFT (TDDFT) evaluated properties that include frontier molecular orbitals, ionization energies, relaxation energies, and low-lying optical excitation energies. Using the dataset, we train a hierarchy of ML models, ranging from classical models such as ridge regression to sophisticated graph neural networks, with molecular SMILES representation as input. We observe that graph neural networks augmented with contextual information allow for significantly better predictions across a wide array of properties. Our best-performing models also provide an uncertainty quantification for the predictions. To democratize access to the data and trained models, an interactive web platform has been developed and deployed.

A hierarchical series of machine learning models are developed to provide robust predictions of the electronic, redox, and optical properties of π-conjugated molecules.     

Growth and microhardness studies of melt-grown lead (II) chloride single crystals

In the present work, lead (II) chloride material is purified by directional solidification and single crystals of PbCl₂ are grown by vertical Bridgman technique employing double zone furnace. The growth conditions and the problems overcome are discussed. The grown crystals of pure and K₊-doped crystals are cleaved and subjected to microindentation tests. The validity of Kick's relation is checked, the value of K₁ the standard hardness number and n the work-hardening coefficient are discussed. The microhardness behaviour of pure and K⁺-doped lead(II) chloride have been compared.     

Growth and characterization of mercurous chloride single crystals

Mercurous chloride was purified by repeated sublimation using multichamber distillation column. Single crystals were grown by Physical Vapour Transport technique. During the process of purification of the material, very interesting habit modifications like dendrites and needles were observed. Vickers hardness tests were carried out on the (110) plane of the crystal for different orientations of the indentor. The shape of the impressions for different orientations of the indentor reveals the non-cubic structure of the plane. No structural phase transition in mercurous chloride was observed in calorimetry and optical studies.     

Perfect Domination Polynomial of Homogeneous Caterpillar Graphs and of Full Binary Trees

Mathematical Notes - Let $$G=(V,E)$$ be a simple graph of order $$n$$ . A set $$S \subseteq V(G)$$ is a perfect dominating set of a graph $$G$$ if every vertex $$v\in V(G)-S$$ is adjacent to...     

On the perturbation of the H-bonding interaction in ethylene glycol clusters upon hydration

Ab initio and density functional methods have been employed to study the structure, stability, and spectral properties of various ethylene glycol (EG(m)) and ethylene glycol-water (EG(m)W(n)) (m = 1-3, n = 1-4) clusters. The effective fragment potential (EFP) approach was used to explore various possible EG(m)W(n) clusters. Calculated interaction energies of EG(m)W(n) clusters confirm that the hydrogen-bonding interaction between EG molecules is perturbed by the presence of water molecules and vice versa. Further, energy decomposition analysis shows that both electrostatic and polarization interactions predominantly contribute to the stability of these clusters. It was found from the same analysis that ethylene glycol-water interaction is predominant over the ethylene glycol-ethylene glycol and water-water interactions. Overall, the results clearly illustrate that the presence of water disrupts the ethylene glycol-ethylene glycol hydrogen bonds.     

Octadecyl maleamic acid salt as a microreactor for its copolymerization reaction with butyl acrylate in aqueous medium

The hydrogelator, octadecyl maleamic acid salt (ODMAS), has been shown to perform as a microreactor in copolymerization reaction with butyl acrylate in aqueous medium thereby providing functionalized latex. The evidence for occurrence of controlled polymerization reaction inside the microreactor is drawn from the composition and the polydispersity index of the copolymers. The copolymers generated under microreactor conditions or in other words, from emulsion phase provided by the hydrogelator exhibit significant incorporation of ODMAS with narrow polydispersity index. For example, a copolymer with ODMAS as high as 0.62 m and polydispersity index at 1.39 could be achieved. On the contrary, the solution copolymerization reactions in THF resulted in low yield of polymers with molecular weight at 10(3) order and polydispersity index in range of 2.53-2.91. The particle size distribution of the latexes remains almost invariant at 74 +/- 4 nm, over the concentration range of 0.12-0.62m with standard deviation (sigma) of 0.12-0.22. The surface area/molecule of ODMAS on the latex particle has been estimated to be 0.21 nm(2)/molecule. The polymerized latexes exhibit zeta potential at 64 +/- 3 mV and surface tension in range of 42.8-47.9 mN m(-)(1) respectively. This is indicative of coverage of latex with ODMAS.     

Asymmetric reduction of alkyl 2-oxo-4-arylbutanoates and -but-3-enoates by Candida parapsilosis ATCC 7330: assignment of the absolute configuration of ethyl 2-hydroxy-4-(p-methylphenyl)but-3-enoate by H NMR

Enantioselective bioreduction of alkyl 2-oxo-4-arylbutanoates and 2-oxo-4-arylbut-3-enoates mediated by Candida parapsilosis ATCC 7330 resulted in the formation of the corresponding (S)-2-hydroxy compounds in high enantiomeric excesses (93–99%) and good isolated yields (58–71%). The absolute configuration of enantiomerically pure ethyl 2-hydroxy-4-(p-methylphenyl)but-3-enoate obtained by the reduction of the corresponding keto ester was assigned by ¹H NMR using Mosher’s method.