Electric vehicles (EVs) have been garnering wide attention over conventional fossil fuel-based vehicles due to the serious concerns of environmental pollution and crude oil depletion. In this article, we have conducted a systematic literature survey to explore the battery raw material supply chain, material processing, and the economy behind the commodity price appreciation. We present significant areas of concern, including resource reserves, supply, demand, geographical distribution, battery reuse, and recycling industries. Furthermore, details of the battery supply chain and its associated steps are illustrated. The authors believe the presented study will be an information cornerstone in boosting manufacturing and understanding the key components and materials required to facilitate EV battery production. Further, this study discusses the major industries, and their policies and global market share in each material category.

This paper describes a method for developing a novel, low-cost, hand-held electronic nose (E-Nose) for black tea flavor estimation using metal-oxide-semiconductor gas sensors. In this research, a first-level experimentation has been conducted with a computer-assisted-technology-based system for sensor selection and validation. In the second level, a novel hand-held E-Nose is designed and developed for generation of tea aroma, capturing the response patterns and signal processing in a microcontroller (PIC 18F45K22) for tea flavor grading. The results of the first-level experimentation provide the sensor selection, where only four out of 12 sensors were selected based on their performance. Moreover, the classification network was predetermined for implementation in the microcontroller. Experiments conducted on the developed hand-held E-Nose show the classification on eight different grades of tea (each with ten samples) varying from 70% to 100%, revealing an average classification efficiency of 90%. The repeatability of the system was also found to be 80%. The developed system also overcomes the problem of heating the tea sample, since the volatile organic compounds of tea are generated due to the emitted heat of the sensors in the proposed system.