Mohd. Zafar

This study investigates chromium removal onto modified maghemite nanoparticles in batch experiments based on a central composite design. The effect of modified maghemite nanoparticles on the adsorptive removal of chromium was quantitatively elucidated by fitting the experimental data using artificial neural network (ANN) and adaptive neuro-fuzzy interference system (ANFIS) modeling approaches. The ANN and ANFIS models, relating the inputs, i.e., pH, adsorbent dose, and initial chromium concentration to the output, i.e., chromium removal efficiency (RE), were developed by comparing the predicted value with that of the experimental values. The RE of chromium ranged from 49.58% to 92.72% under the influence of varying pH (i.e., 2.6–9.4) and adsorbent dose, i.e., 0.8 g/L to 9.2 g/L. The developed ANN model fits the experimental data exceptionally well with correlation coefficients of 1.000 and 0.997 for training and testing, respectively. In addition, the Pearson’s Chi-square measure (χ²) of 0.0004 and 0.0673 for the ANN and ANFIS models, respectively, indicated the superiority of ANN over ANFIS. However, a small discrepancy in the predictability of the ANFIS model was observed owing to the fuzzy rule-based complexity and overtraining of data. Thus, the developed models can be used for the online prediction of RE onto synthesized maghemite nanoparticles with different sets of input parameters and it can also predict the operational errors in the system.

The dynamics of microbial growth and poly(3-hydroxybutyrate) [P(3HB)] production in growth/ non-growth phases of Azhohydromonas lata MTCC 2311 were studied using a maintenance-energy-dependent mathematical model. The values of calculated model kinetic parameters were: m s1 = 0.0005 h-1, k = 0.0965, µmax = 0.25 h-1 for glucose; m s1 = 0.003 h-1, k = 0.1229, µmax = 0.27 h-1 for fructose; and m s1 = 0.0076 h-1, k = 0.0694, µmax = 0.25 h-1 for sucrose. The experimental data of biomass growth, substrate consumption, and P(3HB) production on different carbon substrates were mathematically fitted using non-linear least square optimization technique and similar trends, but different levels were observed at varying initial carbon substrate concentration. Further, on the basis of substrate assimilation potential, cane molasses was used as an inexpensive and renewable carbon source for P(3HB) production. Besides, the physico-chemical, thermal, and material properties of synthesized P(3HB) were determined which reveal its suitability in various applications.