Machine Learning Application, Isotherm Modelling and Adsorption Kinetics for the Removal of Chromium (VI) using Carissa Carandas| Chapter 1 | Research Aspects in Chemical and Materials Sciences Vol. 5

 The basic goal concerning this study is to scrutinize and predict the capacity of cheap bio-sorbent Carissa carandas in eliminating chromium from industrial waste water utilizing analytical methods and machine learning methods such as Radial Basis Function Neural Networks. The adsorption method has been widely used to separate ingot ions in bulk for many age, and it is well known to scientists. The adsorption capacity of Carissa carandas for the evacuation of Cr(VI) ions from local industrial wastewater was examined in this paper as an application to physical-time wastewater situation using differing analytical mechanisms such as Atomic Adsorption Spectroscopy (AAS), Scanning Electron Microscope (SEM), Fourier Transform Infrared Spectroscopy (FTIR) and X-ray dissemination (XRD). In this paper, we proposed machine learning located radial footing function neural network, that is used to model the obtained exploratory results to estimate the percentage expulsion of Cr(VI) for different obscure metal ion concentrations.The adsorption of Cr(VI) from local industrial waste water by Carissa carandas groomed by chemical system, it was treated accompanying the standard test procedures, resolved using Langmuir, Freundlich isotherms and Pseudo-first and second order energetic models. Adsorbent dose, initial adsorbate aggregation, pH, and contact time all had an affect the percentage of adsorption. According to the research's verdicts, Carissa carandas was able to adsorb hexavalent chromium to a maximum of 96% at 5 ppm, 120 record, 1 g/L of adsorbent dose, pH = 5, and 95.81% utilizing ANN for the same parameters. The Carissa carandas are widespread and freely accessible in many locales, thus the results concerning this research will be economically and effectively advantageous for the health of the sea and land environments.

Author(s) Details:

GopiKrishna Pasam,
Engineering Department, University of Technology and Applied Sciences (UTAS), Ibra, Oman.

P. Sirisha,
Department of Chemistry, St. Peter’s Institute of Higher Education and Research (Deemed to be University), Avadi, Chennai, Tamil Nadu - 600 054, India.

Sayeeda Sultana,
Department of Chemistry, St. Peter’s Institute of Higher Education and Research (Deemed to be University), Avadi, Chennai, Tamil Nadu - 600 054, India.

Please see the link here: https://stm.bookpi.org/RACMS-V5/article/view/8894