Facile Synthesis of Regenerative Framework Adsorbent for Organic Dyes: Experimental and Artificial Neural Modeling Studies

Abstract

The primary challenge in the design and synthesis of materials having higher affinity, rapid uptake, and superior adsorption capacity is to achieve the balance between performance and economy for real-world application. The present study unfolded the synthesis of a regenerative framework adsorbent employing greener condition, that shows excellent performance with an ultrahigh adsorption capacity and 99 % removal efficiency for a range of water polluting contaminants, i. e., organic dyes of industrial importance. A pseudo-second-order kinetics model shows a favorable fit for the adsorption process. The maximum adsorption capacity calculated by the Langmuir isotherm was found to be highest among many reports in the minimum concentration range, which directly indicates its outstanding efficiency even at lower contaminant concentration. The framework has good reusability and remarkable adsorption performance after being used for several repeated cycles. Consequently, the adsorption behavior of real effluent sample is also investigated using the current system. Additionally, artificial intelligence based on artificial neural network modeling has been executed successfully to estimate and model process parameters of dye removal by adsorption technique which results in mutual correlation between labbased techniques and neural based modeling for solving environmental concerns.

Recent Advancements and Developments in the Biological Importance of Pyrimido[4,5‐b]Quinoline Scaffolds

“…In addition to these specific areas, the future of research on PQ-heterocycle hybrids is also likely to be influenced by advances in other fields such as computational chemistry and artificial intelligence. [90,91] These tools can be used to accelerate the design and discovery of new PQ-heterocycle hybrids and to predict their biological activities. Particularly, the future perspectives for research on PQ-heterocycle hybrids are very promising.…”

“…This will ultimately lead to the development of new and effective drugs for the treatment of a variety of diseases. In addition to these specific areas, the future of research on PQ‐heterocycle hybrids is also likely to be influenced by advances in other fields such as computational chemistry and artificial intelligence [90,91] . These tools can be used to accelerate the design and discovery of new PQ‐heterocycle hybrids and to predict their biological activities.…”