Fine grain growth of nickel electrodeposit: effect of applied magnetic field during deposition

The electrodeposition of nickel from a nickel sulphamate bath in the presence of a magnetic field applied at an angle of 45° to the cathode surface produces a nickel deposit with a fine grain structure. The sizes of grains vary from 17 to 25 nm. We have used scanning electron microscopy (SEM), scanning tunneling microscopy (STM) and X-ray diffraction (XRD) to characterize the surface morphology of the deposit. The SEM pictures show the formation of domain growth of nickel in which the nickel nanoparticles are mostly concentrated at domain boundaries while STM and XRD analysis show the existence of individual nanoparticles. From the chronopotentiometry studies during magnetoelectrolysis of nickel, we find a significant lowering of overpotential with time and large negative shift in electrode potential in the presence of a magnetic field. We believe from these results that magnetic field induced convection increases the mass transfer rate, reduces the concentration polarisation and leads to the growth of fine grain deposit. The large shift in electrode potential on the application of magnetic field is attributed to the field-induced shift in chemical potential of the ferromagnetic nickel electrode. We have used cyclic voltammetry (CV) to determine the roughness factor and steady state current-potential plots to study the hydrogen evolution reaction on the nickel-electrodeposited surface.     

Sobolev estimates for constructive uniform-grid FFT interpolatory approximations of spherical functions

The fast Fourier transform (FFT) based matrix-free ansatz interpolatory approximations of periodic functions are fundamental for efficient realization in several applications. In this work we design, analyze, and implement similar constructive interpolatory approximations of spherical functions, using samples of the unknown functions at the poles and at the uniform spherical-polar grid locations \(\left (\frac {j\pi }{N}, \frac {k \pi }{N}\right )\), for j=1,…,N?1, k=0,…,2N?1. The spherical matrix-free interpolation operator range space consists of a selective subspace of two dimensional trigonometric polynomials which are rich enough to contain all spherical polynomials of degree less than N. Using the \({\mathcal {O}}(N^{2})\) data, the spherical interpolatory approximation is efficiently constructed by applying the FFT techniques (in both azimuthal and latitudinal variables) with only \({\mathcal {O}}(N^{2} \log N)\) complexity. We describe the construction details using the FFT operators and provide complete convergence analysis of the interpolatory approximation in the Sobolev space framework that are well suited for quantification of various computer models. We prove that the rate of spectrally accurate convergence of the interpolatory approximations in Sobolev norms (of order zero and one) are similar (up to a log term) to that of the best approximation in the finite dimensional ansatz space. Efficient interpolatory quadratures on the sphere are important for several applications including radiation transport and wave propagation computer models. We use our matrix-free interpolatory approximations to construct robust FFT-based quadrature rules for a wide class of non-, mildly-, and strongly-oscillatory integrands on the sphere. We provide numerical experiments to demonstrate fast evaluation of the algorithm and various theoretical results presented in the article.     

Mechanisms with learning for stochastic multi-armed bandit problems

The multi-armed bandit (MAB) problem is a widely studied problem in machine learning literature in the context of online learning. In this article, our focus is on a specific class of problems namely stochastic MAB problems where the rewards are stochastic. In particular, we emphasize stochastic MAB problems with strategic agents. Dealing with strategic agents warrants the use of mechanism design principles in conjunction with online learning, and leads to non-trivial technical challenges. In this paper, we first provide three motivating problems arising from Internet advertising, crowdsourcing, and smart grids. Next, we provide an overview of stochastic MAB problems and key associated learning algorithms including upper confidence bound (UCB) based algorithms. We provide proofs of important results related to regret analysis of the above learning algorithms. Following this, we present mechanism design for stochastic MAB problems. With the classic example of sponsored search auctions as a backdrop, we bring out key insights in important issues such as regret lower bounds, exploration separated mechanisms, designing truthful mechanisms, UCB based mechanisms, and extension to multiple pull MAB problems. Finally we provide a bird’s eye view of recent results in the area and present a few issues that require immediate future attention.     

Evaluating the Free Energies of Solvation and Electronic Structures of Lithium‐Ion Battery Electrolytes

Adaptive biasing force molecular dynamics simulations and density functional theory calculations were performed to understand the interaction of Li⁺ with pure carbonates and ethylene carbonate (EC)‐based binary mixtures. The most favorable Li carbonate cluster configurations obtained from molecular dynamics simulations were subjected to detailed structural and thermochemistry calculations on the basis of the M06‐2X/6‐311++G(d,p) level of theory. We report the ranking of these electrolytes on the basis of the free energies of Li‐ion solvation in carbonates and EC‐based mixtures. A strong local tetrahedral order involving four carbonates around the Li⁺ was seen in the first solvation shell. Thermochemistry calculations revealed that the enthalpy of solvation and the Gibbs free energy of solvation of the Li⁺ ion with carbonates are negative and suggested the ion–carbonate complexation process to be exothermic and spontaneous. Natural bond orbital analysis indicated that Li⁺ interacts with the lone pairs of electrons on the carbonyl oxygen atom in the primary solvation sphere. These interactions lead to an increase in the carbonyl (C=O) bond lengths, as evidenced by a redshift in the vibrational frequencies [ν(C=O)] and a decrease in the electron density values at the C=O bond critical points in the primary solvation sphere. Quantum theory of atoms in molecules, localized molecular orbital energy decomposition analysis (LMO‐EDA), and noncovalent interaction plots revealed the electrostatic nature of the Li⁺ ion interactions with the carbonyl oxygen atoms in these complexes. On the basis of LMO‐EDA, the strongest attractive interaction in these complexes was found to be the electrostatic interaction followed by polarization, dispersion, and exchange interactions. Overall, our calculations predicted EC and a binary mixture of EC/dimethyl carbonate to be appropriate electrolytes for Li‐ion batteries, which complies with experiments and other theoretical results.     

Surface Charge‐Transfer Doping of Graphene Nanoflakes Containing Double‐Vacancy (5‐8‐5) and Stone–Wales (55‐77) Defects through Molecular Adsorption

The adsorption of six electron donor–acceptor (D/A) organic molecules on various sizes of graphene nanoflakes (GNFs) containing two common defects, double‐vacancy (5‐8‐5) and Stone–Wales (55‐77), are investigated by means of ab initio DFT [M06‐2X(‐D3)/cc‐pVDZ]. Different D/A molecules adsorb on a defect graphene (DG) surface with binding energies (ΔE_b) of about ?12 to ?28 kcal mol^?1. The ΔE_b values for adsorption of molecules on the Stone–Wales GNF surface are higher than those on the double vacancy GNF surface. Moreover, binding energies increase by about 10 % with an increase in surface size. The nature of cooperative weak interactions is analyzed based on quantum theory of atoms in molecules, noncovalent interactions plot, and natural bond order analyses, and the dominant interaction is compared for different molecules. Electron density population analysis is used to explain the n‐ and p‐type character of defect graphene nanoflakes (DGNFs) and also the change in electronic properties and reactivity parameters of DGNFs upon adsorption of different molecules and with increasing DGNF size. Results indicate that the HOMO–LUMO energy gap (E_g) of DGNFs decreases upon adsorption of molecules. However, by increasing the size of DGNFs, the E_g and chemical hardness of all complexes decrease and the electrophilicity index increases. Furthermore, the values of the chemical potential of acceptor–DGNF complexes decrease with increasing size, whereas those of donor–DGNF complexes increase.     

Effect of flame thickness variation on the mass burning rate of premixed counterflow flames with an oscillating strain rate

The mass-based stretch rate is used to study the response of premixed axisymmetric counterflow flames subject to an oscillating strain rate. Integral analysis is used to estimate the mass burning rate of the oscillating counterflow flames. From this study it can be concluded that the flame responds in a nonlinear manner. With an increase of the applied strain frequencies, it is found that unsteady stretch effects arising due to flame thickness variations become significant and the mass-based stretch rate is able to capture these nonlinear effects. The inclusion of these unsteady stretch effects in the mass-based stretch helps the integral analysis to predict the mass-burning rate of oscillating flames more accurately.     

Role of Intramolecular Aromatic π–π Interactions in the Self‐Assembly of Di‐l‐Phenylalanine Dipeptide Driven by Intermolecular Interactions: Effect of Alanine Substitution

Although the role of intermolecular aromatic π–π interactions in the self‐assembly of di‐l ‐phenylalanine (l ‐Phe‐l ‐Phe, FF), a peptide that is known for hierarchical structure, is well established, the influence of intramolecular π–π interactions on the morphology of the self‐assembled structure of FF has not been studied. Herein, the role of intramolecular aromatic π–π interactions is investigated for FF and analogous alanine (Ala)‐containing dipeptides, namely, l ‐Phe‐l ‐Ala (FA) and l ‐Ala‐l ‐Phe (AF). The results reveal that these dipeptides not only form self‐assemblies, but also exhibit remarkable differences in structural morphology. The morphological differences between FF and the analogues indicate the importance of intramolecular π–π interactions, and the structural difference between FA and AF demonstrates the crucial role of the nature of intramolecular side‐chain interactions (aromatic–aliphatic or aliphatic–aromatic), in addition to intermolecular interactions, in deciding the final morphology of the self‐assembled structure. The current results emphasise that intramolecular aromatic π–π interaction may not be essential to induce self‐assembly in smaller peptides, and π (aromatic)–alkyl or alkyl–π (aromatic) interactions may be sufficient. This work also illustrates the versatility of aromatic and a combination of aromatic and aliphatic residues in dipeptides in the formation of structurally diverse self‐assembled structures.     

Molybdenum Incorporated Strontium-Iron and Strontium-Cobalt (SrBMoO3−δ; B=Fe & Co) Perovskites: Preparation and Their Application on Oxidation of Iso-Eugenol into Vanillin

SrBO_3−δ (B=Fe & Co) type perovskite oxides and their 25 % molybdenum doped counterparts, SrFe_0.75Mo_0.25O_3−δ (SFMO) and SrCo_0.75Mo_0.25O_3−δ (SFCO) are synthesized by the conventional solid-state method and systematically characterized using Fourier transfer infrared spectroscopy, powder X-ray diffraction, thermo-gravimetric analysis, nitrogen sorption, and temperature-programmed reduction. The powder X-ray diffraction patterns and FTIR spectral analysis evident the formation of the pure cubic phase and the doping of molybdenum into the perovskite crystal lattice. The variable oxidation states of iron and cobalt and the formation of oxygen vacancies are apparent from the TPR-H₂ and TGA curves, respectively. All of the samples have a lower surface area than porous materials, which is typical of the bulk oxide character. The iron-based perovskite demonstrated superior activity to the cobalt-based one for the oxidation of iso-eugenol to 4-hydroxy-3-methoxybenzaldehyde (vanillin) when employing aqueous H₂O₂ as the oxidant. The maximum conversion of 73 % with 63 % selectivity for vanillin was obtained within 1.5 h at 60 °C over the SFMO catalyst. The catalytic conversion was almost similar upon re-use of the catalyst.     

Harnessing the Structure-Performance Relationships in Designing Non-Fused Ring Acceptors for Organic Solar Cells

The prerequisite for commercially viable organic solar cells (OSC) is to reduce the efficiency-stability-cost gap. Therefore, the cost of organic materials should be reduced by minimizing the synthetic steps, yet maintaining the molecular planarity and efficiencies achieved by the fused ring acceptors (FRA). In this respect, developing non-fused ring acceptors (NFRA) with suitable functionalization to favor conformational planarity and effective molecular packing is beneficial and cost-effective. Presently, the power conversion efficiency (PCE) for NFRAs is around 16 %, yet lower than the 19 % achieved for FRAs. Despite their potential, a thorough understanding of the effective structural design of NFRAs is necessary for developing efficient OSCs. This article pays special attention to the molecular design concept for NFRAs developed in the last years and analyzed the approach toward materials design and efficiency improvement, an important step toward technological application.