Artificial intelligence (AI) applications in adsorption of heavy metals using modified biochar

The process of removal of heavy metals is important due to their toxic effects on living organisms and undesirable anthropogenic effects. Conventional methods possess many irreconcilable disadvantages pertaining to cost and efficiency. As a result, the usage of biochar, which is produced as a by-product of biomass pyrolysis, has gained sizable traction in recent times for the removal of heavy metals. This review elucidates some widely recognized harmful heavy metals and their removal using biochar. It also highlights and compares the variety of feedstock available for preparation of biochar, pyrolysis variables involved and efficiency of biochar. Various adsorption ki-netics and isotherms are also discussed along with the process of desorption to recycle biochar for reuse as adsor-bent. Furthermore, this review elucidates the advancements in remediation of heavy metals using biochar by emphasizing the importance and advantages in the usage of machine learning (ML) and artificial intelligence (AI) for the optimization of adsorption variables and biochar feedstock properties. The usage of AI and ML is cost and time-effective and allows an interdisciplinary approach to remove heavy metals by biochar. (c) 2021 Published by Elsevier B.V.

Automated summary

The use of biochar for heavy metal removal has gained traction in recent years due to its cost-effectiveness and efficiency compared to conventional methods. Research shows that utilizing biochar for the removal of harmful heavy metals is an effective method, with the type and preparation process of biochar also affecting the removal efficiency.