## 5 Conclusions  
This study developed stoichiometric models that involve correction factors for the reaction equilibrium constant. The developed models focus on reducing errors, predicting tar content, and applying steam reforming reactions. Six stoichiometric models (M1-M6) with four-factor models (A-D) and equilibrium constants (\(K_{3}^{*}\)-\(K_{6}^{*}\)) were developed in this study, resulting in 24 model combinations with the following details. * All models can predict the composition of the producer gas with an RMSE of less than 3.5%. * All models can predict the concentration of tar (C\({}_{6}\)H\({}_{6}\)) in gas producers through using steam reforming reactions in the modeling process. * Only three models (M1D, M2C, and M3C) out of 24 models showed high accuracy in predicting CO, CO\({}_{2}\), H\({}_{2}\), and N\({}_{2}\) gas concentration. * Model M2C can be further used to develop empirical correlations that include H/C, O/C, and N/C. * The empirical correlation models have power function equations that include biomass content and gasification operating parameters (H/C, O/C, N/C, ER, and T) as the input variables. * The empirical correlations estimated the composition of CO, CO\({}_{2}\), CH\({}_{4}\), H\({}_{2}\), and tar content (C\({}_{6}\)H\({}_{6}\)), LHV, and CGE with R\({}^{2}\) of prediction of each composition was 0.9815, 0.9931, 0.9960, 0.9354, 0.8634, 0.9950, and 0.8423, respectively. These results confirmed that the inclusion of H/C, O/C, and N/C into the models makes the models more reliable. The empirical correlations developed in this study will be beneficial for identifying the most appropriate biomass to be a gasifier, designing gasification operating parameters, and predicting the resulting producer gas and tar composition, LHV, and CGE values. **Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app14135880/s1](https://www.mdpi.com/article/10.3390/app14135880/s1)]([https://www.mdpi.com/article/10.3390/app14135880/s1](https://www.mdpi.com/article/10.3390/app14135880/s1)), Table S1: The operational gasification parameters of each biomass and the yield of producer gas to develop modified stoichiometric models with correction factors and the new function for reaction equilibrium constant; Table S2: Sampel operating conditions and experimental data sets for validation and testing model accuracy from literature. Figure 9: Simulation Prediction of CGE (%) as a function of (**a**) ER and T at H/C = 1.691; O/C = 0.821, N/C = 0.0198; (**b**) H/C and O/C at N/C = 0.0198, ER = 0.331, T = 1321 K.  
**Author Contributions:** All the authors have contributed substantially to the review studies. Conceptualization, P.S., L.O.N. and N.P. ; methodology, P.S., L.O.N. and N.P. ; data curation, P.S. and N.P., writing--original draft preparation, P.S. and N.P. ; writing--review and editing, P.S., S.S.M., N.P. and L.O.N. ; software, P.S. ; validation, P.S., N.P. and L.O.N. ; formal analysis, S.S.M., P.S., N.P. and L.O.N. ; supervision, S.S.M., N.P. and L.O.N. All authors have read and agreed to the published version of the manuscript. **Funding:** This research work was supported by the Institut Teknologi PLN Jakarta. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** Data are not share publicly available; the data may be made available on request from the corresponding author. **Acknowledgments:** The authors would like to acknowledge Institut Teknologi PLN Jakarta for financially supporting this research. **Conflicts of Interest:** The authors declare no conflict of interest. * (20) [PERSON]; [PERSON]; [PERSON] Development of a Semi-Empirical Equilibrium Model for Downdraft Gasification Systems. _Energy_**2017**, _130_, 86-98. [CrossRef]
* (21) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A Robust Numerical Model for Characterizing the Syngas Composition in a Downdraft Gasification Process. _Comptes Rendus Chim._**2016**, _19_, 441-449.