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The purpose of this paper is to fabricate an ethanol sensor which has bio-friendly and eco-friendly properties compared to the commercially available ethanol sensors.

This paper describes the construction of a highly sensitive ethanol sensor with low ppm level detection at room temperature by integrating three techniques. The first deals with the formation of organic/inorganic p-n heterojunction. Second, tuning of structural parameters such as length, diameter and density of Zinc Oxide (ZnO) nanostructure was achieved through introduction of the Fe dopant into a pure ZnO seed layer. Furthermore, ultra-violet (UV) light photoactivation approach was used for enhancing the sensing performance of the fabricated sensors. Four different sensors were fabricated by combing the above approaches. The structural, morphological, optical and material compositions were characterized using different characterization techniques. Sensing behavior of the fabricated sensors toward ethanol was experimented at room temperature with and without UV illumination combined with stability studies. It was observed that all the fabricated sensors showed enhanced sensing performance for 10 ppm of ethanol. In specific, FNZ (Fe-doped ZnO seeded Ni-doped Zn nanorods) sensor exhibited a higher response at 2.2 and 13.5 s for 5 ppm and 100 ppm of ethanol with UV light illumination at room temperature, respectively. The photoactivated FNZ sensor showed quick response and speedy recovery at 18 and 30 s, respectively, for 100 ppm ethanol.

In this study, the authors have experimentally analyzed the effect of Fe (in ZnO seed layer and ZnO NRs) and Ni (in ZnO NRs) dopants in the room temperature sensing performance (with and without UV light) of the fabricated ethanol sensors. Important sensing parameters like sensitivity, recovery and response time of all the fabricated sensors are reported.

The Fe doped ZnO seeded Ni doped Zn nanorods (FNZ sample) showed a higher response at 2.2 s and 13.5 s for very low 5 ppm and 10 ppm of ethanol at room temperature under UV light illumination when compared to the other fabricated sensors in this paper. Similarly, this sensor also had quick response (18 s) and speedy recovery (30 s) for 100 ppm ethanol.

The purpose of this paper is to present the design of a piezoelectric vibration energy generator with a power conditioning circuit to power a wireless sensor node. Frequency and voltage characterization of the piezoelectric energy harvester is performed. A single-stage AC–DC power converter that integrates the rectification and boosting circuit is designed, simulated and implemented in hardware.

The designed power conditioning circuit incorporates bridgeless boost rectification, a lithium ion battery as an energy storage unit and voltage regulation to extract maximum power from PZT-5H and to attain higher efficiency. The sensor node is modelled in active and sleep states on the basis of the power consumption. Dynamic modelling of the lithium ion battery with its state of charging and discharging is analysed.

The test result shows that the energy harvester produces a maximum power of 65.9 mW at the resonant frequency of 21.4 Hz. The designed circuit will operate even at a minimum input voltage of 0.5 V. The output from the harvester is rectified, boosted to a 7-V DC output and regulated to 3.3 V to the power C_Mote wireless sensor node. The conversion efficiency of the circuit is improved to 70.03 per cent with a reduced loss of 19.76 mW.

The performance of the energy harvester and the single-stage power conditioning circuit is analysed. Further, the design and implementation of the proposed circuit lead to an improved conversion efficiency of 70.03 per cent with a reduced loss of 19.76 mW. The vibration energy harvester is integrated with a power conditioning circuit to power a wireless sensor node C_Mote. The piezoelectric vibration energy harvester is implemented in real time to power C_Mote.

A widespread focus on the plant-based antimicrobial cotton fabric finishes has been accomplished with notable importance in recent times. The antimicrobials prevent microbial dwelling in fabrics, which causes severe infections to the fabric users. Chemical disinfectants were conventionally used in fabrics to address this challenge; however, they were found to be toxic to humans. Thus, the present study aims to deal with the utilization of phytochemical extracts from different parts of Pongamia pinnata as antimicrobial coatings in cotton fabrics.

The root, bark and stem were collected and washed several times using tap water. Then, the leaves were dried at room temperature and the root and bark were dried using an oven at 40ºC. After drying, they were ground into fine powder and extracted with ethanol using the Soxhlet apparatus. After that the extract was coated on the fabric tested for antimicrobial studies.

The results reported that the leaf extract of P. pinnata-coated fabric exhibited enhanced antibacterial property towards gram-negative Escherichia coli bacteria, followed by root, bark and stem. The wash durability test in the extract-coated fabric samples revealed that dip-coating retained antibacterial activity until five washes. Thus, the current study clearly suggests that the leaf extract from P. pinnata is highly useful to develop antibacterial cotton fabrics as health-care textiles.

The novelty of the present work is to obtain the crude extract from the leaves, bark, root and stem of P. pinnata and evaluate their antibacterial activity against E. coli, upon being coated on cotton fibres. In addition, the extracts were subjected to wash durability analysis to study the coating efficiency of the phytochemicals in cotton fabrics and a probable mechanism for the antibacterial activity of P. pinnata extracts was also presented.

Sustainability is a very important factor to be considered in the supply chain (SC) of any industry. Agricultural industry needs to be addressed even more importantly with the tools of sustainability as it concerns the life of millions. This paper explores the critical barriers (CBs) in the sustainable supply chains (SSCs) of makhana industry located in the northern part of India and seeks to design a model for the researchers and the managers who want to work in this industry.

Initially, the CBs were identified with the help of an extensive literature review of sustainability in SCs for agri-industry and discussion with makhana industry experts (consisting of managers and senior managers) and academicians (consisting of professors and research scholars). The study uses the multi-criteria decision-making (MCDM) technique, namely interpretive structural modeling (ISM) and fuzzy ISM to develop the model. The study finally validates the model using Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis.

The obtained results indicate that, in the SSC of makhana industry, the role of “Lack of adoption of organic agricultural management techniques” (CB2), “Lack of modern techniques (CB4)”, “Multiple intermediaries” (CB5), “Weak socio-economic conditions” (CB7) and “Lack of proper knowledge” (CB1) are very significant. These barriers are needed to be addressed first as they have the highest driving power and other barriers are directly driven by these CBs.

The paper has included seven experts, and the interrelationship between CBs has been developed on the basis of their knowledge and discussion, so the results may be a little bias. Moreover, the paper has obtained the results using the ISM and fuzzy ISM by considering ten CBs; the researchers can explore this research by including more CBs and validate the results using other MCDM techniques like fuzzy-decision making trial and evaluation laboratory (DEMATEL), fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Best Worst Method (BWM).

This study is unique as per industry point of view and may help the researchers and managers to explore the field of makhana.