Poor wound healing affects millions of people globally, resulting in increased mortality rates and associated expenses. The three major complications associated with wounds are: (i) the lack of an appropriate environment to enable the cell migration, proliferation, and angiogenesis; (ii) the microbial infection; (iii) unstable and protracted inflammation. Unfortunately, existing therapeutic methods have not solved these primary problems completely, and, thus, they have an inadequate medical accomplishment. Over the years, the integration of the remarkable properties of nanomaterials into wound healing has produced significant results. Nanomaterials can stimulate numerous cellular and molecular processes that aid in the wound microenvironment via antimicrobial, anti-inflammatory, and angiogenic effects, possibly changing the milieu from nonhealing to healing. The present article highlights the mechanism and pathophysiology of wound healing. Further, it discusses the current findings concerning the prospects and challenges of nanomaterial usage in the management of chronic wounds.

Nowadays, biochar is being studied to a great degree because of its potential for carbon sequestration, soil improvement, climate change mitigation, catalysis, wastewater treatment, energy storage, and waste management. The present review emphasizes on the utilization of biochar and biochar-based nanocomposites to play a key role in decontaminating dyes from wastewater. Numerous trials are underway to synthesize functionalized, surface engineered biochar-based nanocomposites that can sufficiently remove dye-contaminated wastewater. The removal of dyes from wastewater via natural and modified biochar follows numerous mechanisms such as precipitation, surface complexation, ion exchange, cation–π interactions, and electrostatic attraction. Further, biochar production and modification promote good adsorption capacity for dye removal owing to the properties tailored from the production stage and linked with specific adsorption mechanisms such as hydrophobic and electrostatic interactions. Meanwhile, a framework for artificial neural networking and machine learning to model the dye removal efficiency of biochar from wastewater is proposed even though such studies are still in their infancy stage. The present review article recommends that smart technologies for modelling and forecasting the potential of such modification of biochar should be included for their proper applications.