• Energy Research
• 2021-2025close

AbstractMicrowave (MW)‐assisted catalytic pyrolysis represents a promising method for transforming petroleum‐based plastic waste into valuable chemicals, offering a pathway towards more sustainable circular economy. In this study, catalytic pyrolysis of low‐density polyethylene (LDPE) was conducted under MW irradiation. The influence of various catalyst types (HZSM‐5, Ga/ZSM‐5, Ga/Ni/ZSM‐5, Ga/Co/ZSM‐5, and Ga/Cu/ZSM‐5) on product yield and distribution was examined. The results revealed that the Ga/ZSM‐5 catalyst yielded the maximum liquid oil, approximately 41%. Ga/Ni/ZSM‐5 performed excellently in the production of long‐chain olefins, constituting about 27% of the liquid fraction. However, Ga/Co/ZSM‐5 led to the production of heavy pyrolysis oil containing nearly 25% long‐chain paraffins, rendering it unsuitable for producing high‐value chemicals. Conversely, the Ga/Cu/ZSM‐5 catalyst yielded an aromatic‐rich pyrolysis oil, with benzene derivatives constituting approximately 90% of the liquid oil fraction, thus proving to be a suitable catalyst for the intended application. The liquid product distribution was compared with a petroleum assay by SimDist, and this suggested that utilizing the HZSM‐5 catalyst could yield an 86.4% naphtha fraction. The study also revealed that the Ga/Cu/ZSM‐5 catalyst generated the largest amounts of hydrogen and syngas, as determined by a MicroGC analysis of the gas products. This catalyst also exhibited the maximum coke deposition (1.35%) postreaction, which was attributed to its high aromatic hydrocarbon content in the pyrolysis oil and maximal hydrogen release. A comparison of fresh and spent catalyst properties was conducted to gain insights into catalyst activity and to correlate the effects of metal doping on product distribution. These findings underscore the potential of MW‐assisted catalytic pyrolysis, particularly with the Ga/Cu/ZSM‐5 catalyst, for the efficient conversion of plastic waste into valuable chemicals, thereby contributing to sustainable resource utilization and environmental conservation.

AbstractMicrowave (MW)‐assisted catalytic pyrolysis represents a promising method for transforming petroleum‐based plastic waste into valuable chemicals, offering a pathway towards more sustainable circular economy. In this study, catalytic pyrolysis of low‐density polyethylene (LDPE) was conducted under MW irradiation. The influence of various catalyst types (HZSM‐5, Ga/ZSM‐5, Ga/Ni/ZSM‐5, Ga/Co/ZSM‐5, and Ga/Cu/ZSM‐5) on product yield and distribution was examined. The results revealed that the Ga/ZSM‐5 catalyst yielded the maximum liquid oil, approximately 41%. Ga/Ni/ZSM‐5 performed excellently in the production of long‐chain olefins, constituting about 27% of the liquid fraction. However, Ga/Co/ZSM‐5 led to the production of heavy pyrolysis oil containing nearly 25% long‐chain paraffins, rendering it unsuitable for producing high‐value chemicals. Conversely, the Ga/Cu/ZSM‐5 catalyst yielded an aromatic‐rich pyrolysis oil, with benzene derivatives constituting approximately 90% of the liquid oil fraction, thus proving to be a suitable catalyst for the intended application. The liquid product distribution was compared with a petroleum assay by SimDist, and this suggested that utilizing the HZSM‐5 catalyst could yield an 86.4% naphtha fraction. The study also revealed that the Ga/Cu/ZSM‐5 catalyst generated the largest amounts of hydrogen and syngas, as determined by a MicroGC analysis of the gas products. This catalyst also exhibited the maximum coke deposition (1.35%) postreaction, which was attributed to its high aromatic hydrocarbon content in the pyrolysis oil and maximal hydrogen release. A comparison of fresh and spent catalyst properties was conducted to gain insights into catalyst activity and to correlate the effects of metal doping on product distribution. These findings underscore the potential of MW‐assisted catalytic pyrolysis, particularly with the Ga/Cu/ZSM‐5 catalyst, for the efficient conversion of plastic waste into valuable chemicals, thereby contributing to sustainable resource utilization and environmental conservation.

The present work discusses the development and application of a machine-learning-based model to predict the enthalpy of combustion of various oxygenated fuels of interest. A detailed dataset containing 207 pure compounds and 38 surrogate fuels has been prepared, representing various chemical classes, namely paraffins, olefins, naphthenes, aromatics, alcohols, ethers, ketones, and aldehydes. The dataset was subsequently used for constructing an artificial neural network (ANN) model with 14 input layers, 26 hidden layers, and 1 output layer for predicting the enthalpy of combustion for various oxygenated fuels. The ANN model was trained using the collected dataset, validated, and finally tested to verify its accuracy in predicting the enthalpy of combustion. The results for various oxygenated fuels are discussed, especially in terms of the influence of different functional groups in shaping the enthalpy of combustion values. In predicting the enthalpy of combustion, 96.3% accuracy was achieved using the ANN model. The developed model can be successfully employed to predict the enthalpies of neat compounds and mixtures as the obtained percentage error of 4.2 is within the vicinity of experimental uncertainty.

The present work discusses the development and application of a machine-learning-based model to predict the enthalpy of combustion of various oxygenated fuels of interest. A detailed dataset containing 207 pure compounds and 38 surrogate fuels has been prepared, representing various chemical classes, namely paraffins, olefins, naphthenes, aromatics, alcohols, ethers, ketones, and aldehydes. The dataset was subsequently used for constructing an artificial neural network (ANN) model with 14 input layers, 26 hidden layers, and 1 output layer for predicting the enthalpy of combustion for various oxygenated fuels. The ANN model was trained using the collected dataset, validated, and finally tested to verify its accuracy in predicting the enthalpy of combustion. The results for various oxygenated fuels are discussed, especially in terms of the influence of different functional groups in shaping the enthalpy of combustion values. In predicting the enthalpy of combustion, 96.3% accuracy was achieved using the ANN model. The developed model can be successfully employed to predict the enthalpies of neat compounds and mixtures as the obtained percentage error of 4.2 is within the vicinity of experimental uncertainty.

This study has been dedicated towards the conversion of plastics to methanol and hydrogen. The base design (case 1) represents the conventional design for producing syngas via steam gasification of waste plastics followed by CO2 and H₂S removal. The syngas then processed in the methanol synthesis reactor to produce methanol, whereas, the remaining unconverted gases are processed in water gas shift reactors to produce hydrogen. On the other hand, an alternative design (case 2) has been also developed with an aim to increase the H2 and methanol production, which integrates the plastic gasification and the methane reforming units to utilize the high energy stream from gasification unit to heat up the feed stream of reforming unit. Both the cases have been techno-economically compared to evaluate the process feasibility. The comparative analysis revealed that case 2 outperforms the case 1 in terms of both process efficiency and economics.

This study has been dedicated towards the conversion of plastics to methanol and hydrogen. The base design (case 1) represents the conventional design for producing syngas via steam gasification of waste plastics followed by CO2 and H₂S removal. The syngas then processed in the methanol synthesis reactor to produce methanol, whereas, the remaining unconverted gases are processed in water gas shift reactors to produce hydrogen. On the other hand, an alternative design (case 2) has been also developed with an aim to increase the H2 and methanol production, which integrates the plastic gasification and the methane reforming units to utilize the high energy stream from gasification unit to heat up the feed stream of reforming unit. Both the cases have been techno-economically compared to evaluate the process feasibility. The comparative analysis revealed that case 2 outperforms the case 1 in terms of both process efficiency and economics.

The torrefaction of lignocellulose biomass was conducted to produce biochar with properties compatible with coal. Two lignocellulose biomasses, pearl millet (PM) and walnut shell (WS), were torrefied at different process temperatures (230-300 °C), residence times (30-90 min), and different compositional biomass blends to improve the characteristics of the biochar product. The resulting biochar product exhibited favorable changes in their properties. The pure biomasses and their blends obtained a high biochar yield (41-91%). The gross calorific value (GCV) ranged from 22 to 27 MJ/kg, showing an increase of 22-59% compared to the raw biomass. The torrefaction temperature had the most notable effect on the biochar quantity and quality. The biochar samples obtained from the torrefaction of different blends showed a higher GCV and other physicochemical characteristics than the pure biomasses. Scanning electron microscopy showed that these products might also be used for other applications.