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Hybrid evolutionary machine learning framework optimizing biochar production in biomass pyrolysis | Synapse
March 3, 2026
Open Access
Hybrid evolutionary machine learning framework optimizing biochar production in biomass pyrolysis
DC
Deivid Campos
Universidade Federal de Juiz de Fora
RE
Ricardo Ervilha
Universidade Federal de Juiz de Fora
MB
Matteo Bodini
University of Milan
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Key Points
Biochar yield optimization is achieved through a novel hybrid machine learning framework, driving efficiency in biomass conversion.
A study found that using this method can increase biochar production by up to 20% compared to traditional techniques.
Analysis of biomass pyrolysis data revealed that the optimized parameters significantly enhance yield outcomes.
This work highlights the potential of integrating machine learning and evolutionary algorithms for sustainable bioenergy solutions.
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Campos et al. (Tue,) studied this question.
synapsesocial.com/papers/69a76206c6e9836116a301ce
https://doi.org/https://doi.org/10.1016/j.fuproc.2026.108419