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Thermodynamic equilibrium modeling of gasification for syngas production from carbonaceous feed containing the sulfur impurity

  • Mumtaj Shah , Sachin Meena , Prasenjit Mondal EMAIL logo and Ashutosh kumar
Published/Copyright: June 30, 2025

Abstract

The present study deals with modeling and simulating the gasification process for syngas production. Equilibrium modeling was done to study the product gas composition by changing the process parameters, viz., reaction temperature, equivalence ratio, and moisture content. Coal, wood waste, eucalyptus, pine, and oak were gasification feedstocks. System model equations have been solved using MATLAB software. The model is studied for the range of temperature (800–1400 K), moisture content (7–40 %), and equivalence ratio (0–1). The results of the simulation study were compared with the values in the literature. The results show that the model is entirely satisfactory for the equivalence ratio range of 0.15–0.35. The variation in operating conditions, i.e., equivalence ratio, temperature, moisture content, and the characteristics of carbonaceous feed material, greatly influences the exit gas composition. A carbonaceous feed with almost the same syngas composition can be used for the same gasification process without changing the parameters. Further, coal-derived syngas has different characteristics from the wood waste of oak, pine, and eucalyptus feedstocks. Under optimal conditions, H2 and CO concentrations reached 38  and 35 %, respectively. Increasing sulfur content by 2 % led to a 6 % reduction in CO yield, confirming its inhibitory effect on gasification efficiency.


Corresponding authors: Mumtaj Shah, Department of Chemical Engineering, King Khalid University, Abha 61411, Saudi Arabia, E-mail: ; and Prasenjit Mondal, Department of Chemical Engineering, Indian Institute of Technology Roorkee, Roorkee, India, E-mail:

Award Identifier / Grant number: RGP2/269/46

Acknowledgments

The authors express their gratitude to the Indian Institute of Technology Roorkee for providing the resources necessary to complete this work.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: Mumtaj Shah: Conceptualization, Methodology, Software Data Curation, Original draft Preparation and revision; Funding Acquisition. Ashutosh Kumar: Methodology and Formal Analysis; Writing – review & editing. Sachin Meena: Software Data Curation, Original draft Preparation and revision. Prasenjit Mondal: Resources; Methodology and Formal Analysis; Writing – review & editing

  4. Use of Large Language Models, AI and Machine Learning Tools: No tools were used to generate the text.

  5. Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

  6. Research funding: The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through the General Research Project under the grant number (RGP2/269/46).

  7. Data availability: Not applicable.

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Supplementary Material

This article contains supplementary material (https://doi.org/10.1515/ijcre-2025-0041).


Received: 2025-02-25
Accepted: 2025-06-14
Published Online: 2025-06-30

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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