Hydrogen storage performance of lithium borohydride decorated activated hexagonal boron nitride nanocomposite for fuel cell applications

A safe and cost effective material for hydrogen storage is indispensable for developing hydrogen fuel cell technology to reach its greater heights. The present work deals with hydrogen storage performance of lithium borohydride decorated activated hexagonal boron nitride (LiBH₄@Ah-BN) nanocomposite. where a facile chemical impregnation method was adopted for the preparation of LiBH₄@Ah-BN nanocomposite. The prepared nanocomposite was subjected to various characterization techniques such as X-ray Diffraction (XRD), Micro-Raman Spectroscopy, Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM) with Energy Dispersive X-ray Spectroscopy (EDX), Brunauer–Emmett–Teller (BET) Studies, CHNS-Elemental Analysis and Thermo Gravimetric Analysis (TGA). From BET studies, it is confirmed that, there is an enhancement in the specific surface area of LiBH₄@Ah-BN nanocomposite (122 m²/g) compared to Ah-BN (70 m²/g). The hydrogen storage ability was examined using a Sieverts-like hydrogenation setup. An excellent hydrogen storage capacity of 2.3 wt% at 100 °C was noticed for LiBH₄@Ah-BN nanocomposite. The TGA study indicates the dehydrogenation profile of stored hydrogen in the range of 110–150 °C. The binding energy of stored hydrogen (0.31 eV) lies in recommended range of US-DOE 2020 targets for fuel cell applications. The present investigation demonstrates the preparation of LiBH₄@Ah-BN nanocomposite based hydrogen storage medium which has remarkable cycling stability and hydrogen storage capacity. Hence these desirable traits make LiBH₄@Ah-BN nanocomposite as a potential hydrogen storage candidate for fuel cell applications in near future.     

Environmental factors modify carbon nutritional patterns and niche overlap between Aspergillus flavus and Fusarium verticillioides strains from maize

This study examined the utilization patterns of key carbon sources (CS, 24: including key sugars, amino acids and fatty acids) in maize by strains of Aspergillus flavus and Fusarium verticillioides under different water activity (a_w, 0.87–0.98 a_w) and temperature (20–35 °C) values and compared the niche overlap indices (NOI) that estimate the in vitro CS utilization profiles [Wilson, M., Lindow, S.E., 1994. Coexistence among epiphytic bacterial populations mediated through nutritional resource partitioning. Applied and Environmental Microbiology 60, 4468–4477.]. The ability to grow in these key CS in minimal media was studied for 120 h in 12 h steps. The NOI was calculated for inter-species (F. verticillioides–A. flavus) and for intra-species (A. flavus–A. flavus) using CS utilization patterns over the range of interacting environmental conditions. 30 °C, over the whole a_w range examined, was found to be optimal for utilization of the maximum number of CS by A. flavus. In contrast, for F. verticillioides this was more so at 20 °C; 25 °C allowed a suboptimal usage of CS for both species. NOIs confirmed the nutritional dominance of A. flavus at 30 °C, especially at lower a_w levels and that of F. verticillioides at 20 °C, mainly at 0.95 a_w. In other conditions of a_w, based on CS utilization patterns, the data indicated that A. flavus and F. verticillioides occupied different ecological niches. The variability in nutritional sources utilization between A. flavus strains was not related to their ability to produce aflatoxins (AFs). This type of data helps to explain the nutritional dominance of fungal species and strains under different environmental conditions. This could be useful in trying to find appropriate natural biocontrol microorganisms to compete with these mycotoxigenic species.     

Complex regulation of the aflatoxin biosynthesis gene cluster of Aspergillus flavus in relation to various combinations of water activity and temperature

A microarray analysis was performed to study the effect of varying combinations of water activity and temperature on the activation of aflatoxin biosynthesis genes in Aspergillus flavus grown on YES medium. Generally A. flavus showed expression of the aflatoxin biosynthetic genes at all parameter combinations tested. Certain combinations of a_w and temperature, especially combinations which imposed stress on the fungus resulted in a significant reduction of the growth rate. At these conditions induction of the whole aflatoxin biosynthesis gene cluster occurred, however the produced aflatoxin B₁ was low. At all other combinations (25 °C/0.95 and 0.99; 30 °C/0.95 and 0.99; 35 °C/0.95 and 0.99) a reduced basal level of cluster gene expression occurred. At these combinations a high growth rate was obtained as well as high aflatoxin production. When single genes were compared, two groups with different expression profiles in relation to water activity/temperature combinations occurred. These two groups were co-ordinately localized within the aflatoxin gene cluster. The ratio of aflR/aflJ expression was correlated with increased aflatoxin biosynthesis.     

Temperature and water activity effects on growth and temporal deoxynivalenol production by two Argentinean strains of Fusarium graminearum on irradiated wheat grain

The ability of six strains of Pichia anomala, four strains of Pichia kluyveri and two strains of Hanseniaspora uvarum predominant during coffee processing to produce polygalacturonase (PG), pectin esterase (PE) and pectin lyase (PL) in yeast polygalacturonic acid medium (YPA) and in coffee broth (CB) was studied. For comparison, a reference strain of Kluyveromyces marxianus CCT 3172 isolated from cocoa and reported to produce high amount of PG was included.

Initial screening of PG activity using YPA medium showed that K. marxianus CCT 3172, P. anomala S16 and P. kluyveri S13Y4 had the strongest activity. Enzymatic assays showed that the four yeast species secreted PG, but none of the yeasts investigated was found to produce PE or PL. P. anomala S16 and P. kluyveri S13Y4 were found to produce higher amounts of PG when grown in CB than in YPA. When K. marxianus CCT 3172, P. anomala S16 and P. kluyveri S13Y4 were grown in YPA broth adjusted to pH of 3.0–8.0 and incubated at temperatures of 15–40 °C, the three yeast species secreted the highest amount of PG at pH 6.0 and at 30 °C. For PG secreted by K. marxianus CCT 3172 and P. anomala S16, the optimum pH and temperature for the enzymatic activity were 5.5 and 40 °C, respectively. On the other hand, PG produced by P. kluyveri S13Y4 showed the highest activity at pH 5.0 and 50 °C.

Significant differences in the extracellular activity of PG were found between the yeasts species as well as between strains within same species. High amounts of PG were produced by two strains of P. anomala and P. kluyveri. It is therefore likely that strains of those two species may be involved in the degradation of pectin during coffee fermentation.     

Alloy formation at the tetrapod core/arm interface

The nature of the interfacial structure between the core and the arms of a tetrapod quantum dot (QD) formed during the heteroepitaxial growth of a ZnS arm onto a CdSe core is not well understood but can be analyzed through the use of high-frequency electron paramagnetic resonance (HF-EPR) spectroscopy. The spectroscopic resolution at high frequency allows the presence of unique crystal fields reflecting interfacial alloying to be analyzed by incorporating Mn(II) ions as a dopant into the QD to act as an intentional EPR active spectroscopic probe. In addition, the HF-EPR can spectroscopically observe the presence of ion vacancies that are anticipated to form at the heteroepitaxial interface to accommodate structural mismatch. The HF-EPR spectra for Mn(II) are extremely sensitive to perturbations of the microenvironment due to changes in the crystal field. The HF-EPR spectra of Mn(II) in a CdSe (core)/ZnS (arm) tetrapod exhibiting wurtzite symmetry for both core and interface of the tetrapod provide clear evidence of heteroalloying at the core-arm interface and formation of intrinsic dislocations at grain boundaries. The formation of the interfacial alloy and grain boundaries reflects short-range ion migration at the heteroepitaxial layer to reduce strain energy due to the 12% lattice mismatch between the wurtzite lattices of CdSe and ZnS.     

Multi-objective optimization of process parameters in Electro-Discharge Diamond Face Grinding based on ANN-NSGA-II hybrid technique

The effective study of hybrid machining processes (HMPs), in terms of modeling and optimization has always been a challenge to the researchers. The combined approach of Artificial Neural Network (ANN) and Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) has attracted attention of researchers for modeling and optimization of the complex machining processes. In this paper, a hybrid machining process of Electrical Discharge Face Grinding (EDFG) and Diamond Face Grinding (DFG) named as Electrical Discharge Diamond face Grinding (EDDFG) have been studied using a hybrid methodology of ANN-NSGA-II. In this study, ANN has been used for modeling while NSGA-II is used to optimize the control parameters of the EDDFG process. For observations of input-output relations, the experiments were conducted on a self developed face grinding setup, which is attached with the ram of EDM machine. During experimentation, the wheel speed, pulse current, pulse on-time and duty factor are taken as input parameters while output parameters are material removal rate (MRR) and average surface roughness (R_a). The results have shown that the developed ANN model is capable to predict the output responses within the acceptable limit for a given set of input parameters. It has also been found that hybrid approach of ANN-NSGA-II gives a set of optimal solutions for getting appropriate value of outputs with multiple objectives.     

Investigation of multiple process parameters in abrasive water jet machining of tiles

This paper discusses the optimization of an abrasive water jet machining process with multiple characteristics, using the Taguchi orthogonal array and grey relational analysis (GRA). The machining process variables, such as mesh size, nozzle diameter, abrasive flow rate, water pressure, stand-off distance, and feed rate, were optimized with respect to multiple performance characteristics, namely, the surface roughness and the kerf angle. Experiments were performed using an L₁₈ orthogonal array, and the optimum machining process variables were determined, using GRA. Analysis of variance was used to identify the most significant factor in the machining performance. A confirmatory test was performed to verify the improvement of the performance characteristics. The microstructure of the machined surfaces was also examined by scanning electron microscopy and atomic force microscopy. The results showed that the surface roughness and kerf angle were minimized under optimal machining conditions.     

Supply chain risk assessment during new product development: a group decision making approach using numeric and linguistic data

Companies strive to minimise supply chain related risks during new product development as any glitch while developing new products can lead to considerable delay in product launch with severe financial implications. However, many organisations face difficulty in properly assessing the vulnerabilities of their globally dispersed supply chains during the product development stage as no suitable procedure for that purpose seems to be readily available in the literature. The present research is an attempt to fulfil this requirement. A step-by-step approach for supply chain risk assessment during new product development, involving group decision making, is suggested. This approach can use both numeric and linguistic data and helps in determining vulnerability scores for various sub-systems and for each supplier of the most vulnerable sub-system. This is followed by failure mode effect analysis (FMEA) which helps prioritise failure modes of vulnerable suppliers and thus create specific control plans to mitigate supply related failures. Using this approach, organisations can devise control plans to alleviate the supplier related risks during new product development. Although, the methodology is illustrated through an application in aircraft manufacturing, it can also be used in other discrete and process manufacturing industries.