Conversion of biomass to biochar using top‐lit updraft technology: a review

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The importance of carbonizing teak seed waste lies in unlocking its untapped potential for sustainable resource transformation while achieving waste management and converting the waste to more valuable products. This study investigates the production and characterization of teak‐seed biochar employing a top‐lit updraft reactor. The process parameters include a carbonization time of 2 h and a peak temperature of 379 °C, resulting in a substantial yield of 42%. Elemental analysis reveals the biochar's composition, consisting of 77.20% carbon and 18.79% potassium, positioning it as a valuable resource with versatile applications. The Fourier transform infrared (FTIR) analysis showcases a rich variety of functional groups within the biochar, including alcohols, carboxylic and phenolic groups, amides, and various hydrocarbon structures, signifying its multifaceted potential for applications like the adsorption of aqueous pollutants, soil stabilization, and enhanced ion‐exchange capacity. Textural assessments emphasize its noteworthy surface area (Brunauer, Emmett, and Teller (BET) analysis: 190.05 m2g−1; Langmuir: 1664.35 m2g−1), micropore volume (0.069 cm3g−1), and total pore volume (0.097 cm3/g−1), primarily characterized by mesoporous attributes (pore diameter: 2.153 nm), rendering it suitable for various applications. Scanning electron microscopy (SEM) analysis of surface morphology reveals a rough texture embellished with various‐sized and shaped particles, distinguished by their silvery, shiny appearance, which is attributed to the biochar's elemental composition, particularly the presence of potassium. These findings underline the promising potential of teak seed biochar across multiple applications, including agriculture, wastewater treatment, and environmental remediation.

Unlocking the potential of teak seed waste: carbonization for sustainable resource transformation

Adeniyi,

Iwuozor,

Ezzat

et al. 2023

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Biochar‐based catalysts derived from biomass waste: production, characterization, and application for liquid biofuel synthesis

Nguyen,

Sharma,

Rowinski

et al. 2024

Among the feasible options for valorizing lignocellulosic biomass into value‐added products, biochar is considered to be extremely appealing and it could be applied easily in several established thermochemical processes. Biochar possesses a large surface area due to its porous nature, which permits easy use in various applications, including catalytic biofuel production. This work summarizes research on biochar generation processes, its critical physicochemical properties, and factors that influence them. Important studies adopting biochar catalysts for liquid biofuel production are critically reviewed, and the reaction mechanisms and biofuel yield are analyzed. Finally, challenges in the use of biochar‐based catalysts for biofuel production are presented, together with possible solutions. In general, this current work aims to provide the critical characteristics of biochar as a potential catalyst to biofuel synthesis toward sustainable bioenergy production.

Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy

Nguyen,

Sharma,

Ağbulut

et al. 2024

Biochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine‐learning‐based forecasts, optimization, and feature selection are critical for improving biomass management techniques. In this research, we explore the influences of these techniques on the accurate forecasting of biochar yield and properties for a range of biomass sources. We emphasize the importance of the interpretability of a model, as this improves human comprehension and trust in ML predictions. Sensitivity analysis is shown to be an effective technique for finding crucial biomass characteristics that influence the synthesis of biochar. Precision prognostics have far‐reaching ramifications, influencing industries such as biomass logistics, conversion technologies, and the successful use of biomass as renewable energy. These advances can make a substantial contribution to a greener future and can encourage the development of a circular biobased economy. This work emphasizes the importance of using sophisticated data‐driven methodologies such as ML in biochar synthesis, to usher in ecologically friendly energy solutions. These breakthroughs hold the key to a more sustainable and environmentally friendly future.