Energy utilization of agricultural waste: Machine learning prediction and pyrolysis transformation.

The rapid screening of agricultural waste materials for capacitor preparation holds significant importance in comprehending the relationship between material properties and enhancing experimental efficiency. In this study, we developed two machine learning models to predict electrode material characteristics using 2997 data points extracted from 235 articles. The identification and influence of key features on prediction indices provide a theoretical foundation for subsequent practical preparation. Through regression analysis and index evaluation, corn straw emerged as the optimal material for capacitor preparation, leading us to propose a one-step activation and two-step modification approach to convert corn straw into porous biochar. By modifying biochar with Co(NO3)2·6H2O, the maximum electrode capacitance of porous carbon reached 732.6 F/g. Furthermore, the electrode exhibited exceptional cycle stability with a remaining capacitance of 96 % after 5000 cycles. The prepared symmetric capacitor demonstrated pseudocapacitance behavior with a capacitance of 183.15 F/g at a current density of 1.0 A/g, power density of 22 kW/kg, and energy density of 9.03 Wh/kg. Considering the increasing annual output of corn straw and its superior industrial application prospects compared to acid-, base-, or precious metal-based alternatives due to their cost-effectiveness and environmental friendliness, these findings highlight the potential practical value in utilizing modified corn straw biochar as an efficient energy storage electrode material.

Insight into the soil aggregate-mediated restoration mechanism of degraded black soil via biochar addition: Emphasizing the driving role of core microbial communities and nutrient cycling.

Soil microbial communities are responsive to biochar application. However, few studies have investigated the synergistic effects of biochar application in the restoration of degraded black soil, especially soil aggregate-mediated microbial community changes that improve soil quality. From the perspective of soil aggregates, this study explored the potential microbial driving mechanism of biochar (derived from soybean straw) addition in black soil restoration in Northeast China. The results showed that biochar significantly improved the soil organic carbon, cation exchange capacity and water content, which play crucial roles in aggregate stability. The addition of biochar also significantly increased the concentration of the bacterial community in mega-aggregates (ME; 0.25-2 mm) compared with micro-aggregates (MI; <0.25 mm). Microbial co-occurrence networks analysis showed that biochar enhanced microbial interactions in terms of the number of links and modularity, particularly in ME. 16 S rRNA sequencing predicted that the expression of genes related to carbon (rbcL, acsA, gltS, aclB, and mcrA) and nitrogen (nifH and amoA) transformation increased after the addition of biochar. Furthermore, the functional microbes involved in carbon fixation (Firmicutes and Bacteroidetes) and nitrification (Proteobacteria) were significantly enriched and are the key regulators of carbon and nitrogen kinetics. Structural equation model (SEM) analysis further showed that the application of biochar promoted soil aggregates to positively regulate the abundance of soil nutrient conversion-related microorganisms, thereby increasing soil nutrient content and enzyme activities. These results provide new insights into the mechanisms of soil restoration through biochar addition.