No abstract

Over the last few decades, the development of the electronic nose (E-nose) for detection and quantification of dangerous and odorless gases, such as methane (CH4) and carbon monoxide (CO), using an array of SnO2 gas sensors has attracted considerable attention. This paper addresses sensor cross sensitivity by developing a classifier and estimator using an artificial neural network (ANN) and least squares regression (LSR), respectively. Initially, the ANN was implemented using a feedforward pattern recognition algorithm to learn the collective behavior of an array as the signature of a particular gas. In the second phase, the classified gas was quantified by minimizing the mean square error using LSR. The combined approach produced 98.7% recognition probability, with 95.5 and 94.4% estimated gas concentration accuracies for CH4 and CO, respectively. The classifier and estimator parameters were deployed in a remote microcontroller for the actualization of a wireless E-nose system.

No abstract

Separators are a vital component to ensure the safety of lithium-ion batteries. However, the commercial separators employed in lithium ion batteries are inefficient due to their low porosity. In the present study, a simple electrospinning technique is adopted to prepare highly porous polyacrylonitrile (PAN)-based membranes with a higher concentration of lithium aluminum titanium phosphate (LATP) ceramic particles, as a viable alternative to the commercialized separators used in lithium ion batteries. The effect of the LATP particles on the morphology of the porous membranes is demonstrated through Field emission scattering electron microscopy. X-ray diffraction and Fourier transform infrared spectra studies suitably demonstrate the mixing of PAN and LATP particles in the polymer matrix. PAN with 30 wt% LATP (P-L30) exhibits an enhanced porosity of 90% and is more thermally stable, with the highest electrolyte uptake among all the prepared membranes. Due to better electrolyte uptake, the P-L30 membrane demonstrates an improved ionic conductivity of 1.7 mS/cm. A coin cell prepared with a P-L30 membrane and a LiFePO4 cathode demonstrates the highest discharge capacity of 158 mAh/g at 0.5C rate. The coin cell with the P-L30 membrane also displays good cycling stability by retaining 87% of the initial discharge capacity after 200 cycles of charging and discharging at 0.5C rate.

No abstract