Digestate-derived carbonized char and activated carbon: Application perspective

Biochar-based polymeric film as sustainable and efficient sorptive phase for preconcentration of steroid hormones in environmental waters and wastewaters

BACKGROUND

The environmental impact of sample preparation should be minimized through simplification of the procedures and the use of natural, renewable and/or reusable materials. In such scenario, thin-film microextraction fulfils the former criteria, as it enables few steps and miniaturization, thus small amount of extraction phase. At the same time, the use of sorbents such as biochars obtained from biomass waste is even more promoted due to their availability at low cost and increased life-cycle in a circular economy vision. However, it is not always easy to combine these criteria in sample preparation.

RESULTS

A thin film microextraction was developed for the determination of steroids in aqueous samples, entailing a membrane made of cellulose triacetate and a wood-derived biochar (Nuchar®) as carbon precursor. Different characterization techniques showed the successful preparation, whereas the sorption kinetics experiments demonstrated that biochar is responsible for the extraction with the polymer acting as a smart support. After a study about membranes' composition in terms of biochar amounts (4 %, 10 %, 16 % wt) and type of synthesis set up, the ceramic 3D-mold was selected, achieving reproducible and ready-to-use membranes with composition fixed as 10 %. Different elution conditions, viz. type and time of agitation, type, composition and volume of eluent, were evaluated. The final microextraction followed by HPLC-MS/MS quantification was successfully validated in river and wastewater treatment plant effluent samples in terms of accuracy (R% 64-123 %, RSD<19 % in river; R% 61-118 %, RSD <18 % in effluent, n = 4), sensitivity (MQLs 0.2-8.5 ng L-1) and robustness.

SIGNIFICANCE

This novel biochar-based polymeric film proved to be a valid and sustainable sorbent, in terms of extraction capability, ease of preparation and greenness. By comparison with literature and the greenness evaluation with the most recent metric tools, this method expands the potential applicability of the thin-film microextraction and opens up innovative scenarios for sustainable procedures entailing the use of biochars entrapped in bio-polymers.

Machine learning applications for biochar studies: A mini-review

Biochar is a promising carbon sink whose application can assist in reducing carbon emissions. Development of this technology currently relies on experimental trials, which are time-consuming and labor-intensive. Machine learning (ML) technology presents a potential solution for streamlining this process. This review summarizes the current research on ML's applications in biochar production, characterization, and applications. It briefly explains commonly used machine learning algorithms and discusses prospects and challenges. A hybrid model that combines ML with mechanism-based analysis could be a future trend, addressing the ML's black-box nature. While biochar studies have adopted ML technology, current works mostly use lab-scale data for model training. Further work is needed to develop ML models based on pilot or industrial-scale data to realize the use of ML techniques for the field application of biochar.