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Related Experiment Video

Updated: Mar 9, 2026

Fast Pyrolysis of Biomass Residues in a Twin-screw Mixing Reactor
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Innovative model-optimized machine learning for high-accuracy predicting and exploring nitrogen transformation in

Xinran Zhou1, Zhenting Zha1, Bowen Li1

  • 1School of Mechanical Engineering, Hefei University of Technology, Hefei, Anhui 230009, China; Institute of Thermo-Fluid Equipment and Energy Saving & Environmental Protection Engineering, Hefei University of Technology, Hefei, Anhui 230009, China.

Bioresource Technology
|March 7, 2026
PubMed
Summary

This study introduces the Pyro-SPIN model to predict and optimize nitrogen migration during biomass pyrolysis, crucial for reducing harmful nitrogen oxides (NOx) emissions from waste-to-fuel processes.

Keywords:
Biomass pyrolysisMachine learningModel optimizationNitrogen migration

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On-line Analysis of Nitrogen Containing Compounds in Complex Hydrocarbon Matrixes
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Area of Science:

  • Biomass thermochemical conversion
  • Environmental engineering
  • Computational chemistry

Background:

  • Producing zero-carbon fuels from biomass pyrolysis requires minimizing nitrogen oxides (NOx) emissions.
  • Controlling nitrogen behavior during pyrolysis is key to source reduction.
  • Traditional methods struggle to analyze complex nitrogen migration pathways.

Purpose of the Study:

  • To develop a predictive model for nitrogen migration during biomass pyrolysis.
  • To optimize pyrolysis conditions for reduced NOx formation.
  • To offer a novel approach for understanding and controlling elemental behavior in biomass conversion.

Main Methods:

  • Development of the Pyro-SPIN (Source Parameter-based Integrated Nitrogen Migration) model.
  • Synergistic analysis of model predictions with experimental data.
  • Machine learning techniques including chain modeling and multi-output joint training.

Main Results:

  • Temperature, nitrogen content, and oxygen content are primary factors influencing nitrogen migration.
  • Optimized conditions (particle size <200 μm, temp <500°C, duration <60 min, slow heating) favor nitrogen enrichment in solid char.
  • The model achieved mass conservation and improved prediction consistency.

Conclusions:

  • The Pyro-SPIN model accurately predicts and optimizes nitrogen migration pathways in biomass pyrolysis.
  • This approach offers a new method for understanding and controlling NOx formation at the source.
  • The developed strategies can be applied to other elements in biomass thermochemical conversion.