[Elsevier] Advancing toxicology through new approach methodologies |
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Reward10points
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Coupling process-based models with machine learning for the prediction of soil carbon and nitrogen cycling
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Data-driven machine learning with SHAP for predicting multiple biochar properties from agricultural and forestry waste
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Template-free preparation of high-yield porous carbon nanosheets from low-cost sodium humate for supercapacitor electrodes
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Artificial neural network modeling for prediction and optimization of biochar yield and properties
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Biomass-derived 2D carbon architectures: soybean pod shell conversion into N,O-heteroatoms enriched nanosheets for high performance supercapacitors
