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Simulation study demonstrates accurate biomass pyrolysis yield predictions across eight feedstocks, highlighting an accessible open-source modeling approach.
Pyrolysis is a leading route for valorizing lignocellulosic residues, yet detailed multi-step kinetic schemes have so far been deployed only in costly commercial simulators, limiting reproducibility. This work couples thermogravimetric (TGA) characterization with process simulation in the free, open-source simulator DWSIM to predict the pyrolysis product distribution of corn cob from Córdoba, Colombia. The lignocellulosic composition (hemicellulose 24.3 ± 2.9, cellulose 36.4 ± 3.0, lignin 39.3 ± 0.9 wt%) was obtained by deconvolving the derivative thermogravimetric (DTG) curve with a five-parameter asymmetric double sigmoidal (Asym2sig) function (R2 > 0.9996). Pseudocomponent activation energies from the Coats–Redfern method (154.2, 124.6, and 29.9 kJ/mol) calibrated the primary reactions of a 17-reaction Ranzi scheme, extended with 18 secondary gas-phase steam reforming reactions. Validated against eight lignocellulosic biomasses, the calibrated model yielded a consolidated R2 = 0.853 and average absolute deviation (AAD) = 9.8%, with char predictions most accurate (AAD = 8.9%). For corn cob, a bio-oil-optimized yield of 55.0 wt% was predicted at 500 °C, transitioning to a syngas-rich regime (51.0 wt% gas) at 750 °C. This constitutes the calibrated Ranzi-scheme implementation in DWSIM, offering an accessible, reproducible pathway for biomass pyrolysis modeling.
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Julio et al. (2026) studied this question.
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