Correlation between crystallinity index, skin depth, and optical phonon vibration for enhancing Ni²⁺ removal using AC/CaCO₃–clay composite

The water problem caused by Ni²⁺ contamination has attracted attention as it causes environmental damage. AC/CaCO₃ adsorbent composited with clay, combined in the ratio of 1:1 as S1 and 1:2 as S2, using the sol–gel method, has been conducted. The adsorption was implemented under environmental conditions (natural sunlight and no stirring) and monitored using an IoT-based monitoring system, which provides a novel approach for real-time observation of the adsorption process. After 24 h of continuous monitoring via the IoT system, we found that S2 (0.5 g) adsorbed up to 93.35% of Ni²⁺ ions, with an adsorption capacity of 3.72 mg/g at the optimal pH and temperature of 2.6 and 27 °C, respectively. The results of sample characterization found that the performance of the adsorbent was related to a decrease in the crystallinity index (Xc), shallowing skin depth (Pd), optical phonon vibration (Δ(LO-TO)) broadening, surface area, pore volume, and pore diameter enlargement. In addition, kinetic models (pseudo-first-order, pseudo-second-order, and intraparticle diffusion) and isothermal models (Langmuir, Freundlich, and Temkin) were used. The results showed that the pseudo-first-order and the Freundlich models best fit the experiments, with R² = 0.9434 and 0.99918 for S2, respectively. Finally, S2 shows promising potential to become a cost-effective material due to the negligible cost of raw materials, effective, and efficient material for adsorbing Ni²⁺ ion contamination from wastewater through analysis of material properties that support adsorption and real-time monitoring based on IoT.