Investigation of combustion performance of tannery sewage sludge using thermokinetic analysis and prediction by artificial neural network

Khan, Arslan; Ali, Imtiaz; Farooq, Wasif; Naqvi, Salman Raza; Mehran, Muhammad Taqi; Shahid, Ameen; Liaquat, Rabia; Anjum, Muhammad Waqas; Naqvi, Muhammad

doi:10.1016/j.csite.2022.102586

Cited by 28 publications

(1 citation statement)

References 51 publications

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“…Khan et al 24 also used the machine learning method to predict the experimental results, and the results showed that the difference between the predicted hydrogen production of biomass sewage sludge and the actual hydrogen production was less than 2%. Khan et al 25 used kinetic knowledge to analyze the combustion behavior of tannery sewage sludge and employed an artificial neural network study to predict the thermal degradation behavior; the results showed a good agreement between the experimental values and the predicted values. Furthermore, the density functional theory (DFT) calculation method has been used to assist the study.…”

Section: Introductionmentioning

confidence: 99%

Analysis of gas product changes during pyrolysis of oily sludge based on density functional theory calculation

Wen¹,

Cheng

Liu

et al. 2023

Asia-Pacific J Chem Eng

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Oily sludge is a kind of harmful solid waste produced by the petroleum industry. It is the key point of research to understand the mechanism of gas product changes during the pyrolysis process. This study combined density functional theory (DFT) calculation with a pyrolysis experiment to explore the changes in pyrolytic gas products from oily sludge. The results of thermogravimetric–mass spectrometry (TG–MS) and gas chromatography–mass spectrometry (GC–MS) showed that the gas products below 400°C were dominated by long‐chain hydrocarbons, but with the increase of the treatment temperature, the long‐chain hydrocarbons will decrease. The results of kinetics and thermodynamics showed that there were five stages of pyrolysis of oily sludge, and the values of E, ΔH, and ΔG were increased with the increase of pyrolysis temperature. The DFT calculation revealed that there were delocalized π‐electrons at the fracture‐prone sites, and the electrons on the functional groups of the molecule were more easily excited. The results can provide ideas for the pyrolysis mechanism of oily sludge and theoretical support for the optimization of the pyrolysis process.

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Section: Introductionmentioning

confidence: 99%