A comprehensive neural network model for predicting flash point of oxygenated fuels using a functional group approach

Aljaman, Baqer; Ahmed, Usama; Zahid, Umer; Reddy, V. Mahendra; Sarathy, S. Mani; Jameel, Abdul Gani Abdul

doi:10.1016/j.fuel.2022.123428

Cited by 16 publications

(17 citation statements)

References 31 publications

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“…Analysis of these functional groups indicates the thermal decomposition reactions occurring during pyrolysis, and this information could help optimize gasifier conditions such that high-value gases could be obtained while minimizing emissions. The functional groups present in a fuel often dictate its properties, − and the evolved groups dictate the propensity to form soot. ,, The IR band assignments for the aforementioned functional groups are provided in Table including the selected wavenumber for each functional group.…”

Section: Resultsmentioning

confidence: 99%

Pyrolysis and Oxidation of Waste Tire Oil: Analysis of Evolved Gases

et al. 2022

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Valorization of waste such as waste tires offers a way to manage and reduce urban waste while deriving economic benefits. The rubber portion of waste tires has high potential to produce pyrolysis fuels that can be used for energy production or further upgraded for use as blend fuel with diesel. In the preset work, waste tire oil (WTO) was produced from the pyrolysis of waste tires in an electric heating furnace at 500–550 °C in the absence of oxygen. Pyrolysis (in nitrogen) and oxidation (in air) of the obtained WTO sample were then performed in a thermogravimetric (TG) furnace that was connected to a Fourier transform infrared cell where the evolved gases were analyzed. The WTO sample was heated up to 800 °C in the TG furnace where the temperature of the sample was ramped up at three heating rates, namely, 5, 10, and 20 °C/min. The TG mass loss and differential thermogravimetric mass loss plots were used to analyze the thermal degradation pathways. Kinetic analysis was performed using the distributed activation energy model to estimate the activation energies along the various stages of the reaction. The pollutant gases, namely, CO 2 , CO, NO, and H 2 O, formed during WTO oxidation were evaluated by means of the characteristic infrared absorbance. The functional groups evolved during pyrolysis, namely, alkanes, alkenes, aromatics, and carbonyl groups, were also analyzed. The obtained information can be used for the better design of gasifiers and combustors, to ensure the formation of high-value gaseous products while reducing the emissions. The utilization of waste tires by producing pyrolysis oils thus offers a way of tackling the menace of waste tires while acting as a potential energy source.

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Section: Resultsmentioning

confidence: 99%

Pyrolysis and Oxidation of Waste Tire Oil: Analysis of Evolved Gases

et al. 2022

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“…At present, high-precision prediction models for various basic properties, such as the boiling point, density, and flash point, have been developed. − Although the QSPR method has a good fitting effect, it is cumbersome and difficult to associate with the SOL method. In recent years, the method of using functional groups to predict the molecular properties has been increasingly favored by researchers. − The functional groups method fully combines the advantages of the simplicity and directness of the GC method and the accuracy of the QSPR method in the structural description and describes the molecular structure by setting limited functional groups that can be directly described on the molecular structural features. Abdul Jameel et al constructed the calculation models for the flash point and cetane number by introducing two special functional groups: molecular weight and branching index on chain. , The property prediction model based on the artificial neural network (ANN) functional groups method fully retains the advantages of the high fitting accuracy of the ANN method and the interpretability between the structure and properties of the functional group method.…”

Section: Introductionmentioning

confidence: 99%

“…Abdul Jameel et al constructed the calculation models for the flash point and cetane number by introducing two special functional groups: molecular weight and branching index on chain. 39,40 The property prediction model based on the artificial neural network (ANN) functional groups method fully retains the advantages of the high fitting accuracy of the ANN method and the interpretability between the structure and properties of the functional group method. What is more, rational functional groups can be generated by combining structural increments with the similar physical structure meaning, which provides an idea of how to construct a prediction method for the physicochemical properties of molecules in petroleum based on the extended SOL method.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, the method of using functional groups to predict the molecular properties has been increasingly favored by researchers. − The functional groups method fully combines the advantages of the simplicity and directness of the GC method and the accuracy of the QSPR method in the structural description and describes the molecular structure by setting limited functional groups that can be directly described on the molecular structural features. Abdul Jameel et al constructed the calculation models for the flash point and cetane number by introducing two special functional groups: molecular weight and branching index on chain. , The property prediction model based on the artificial neural network (ANN) functional groups method fully retains the advantages of the high fitting accuracy of the ANN method and the interpretability between the structure and properties of the functional group method. What is more, rational functional groups can be generated by combining structural increments with the similar physical structure meaning, which provides an idea of how to construct a prediction method for the physicochemical properties of molecules in petroleum based on the extended SOL method.…”

Section: Introductionmentioning

confidence: 99%

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Predicting the Physicochemical Properties of Molecules in Petroleum Based on Structural Increments

Hou

Qin

et al. 2023

Ind. Eng. Chem. Res.

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The structure-oriented lumping (SOL) method has been widely applied to molecular-level modeling and optimization in the refining industry. Calculating the physicochemical properties of products obtained by the SOL models can effectively guide the evaluation of product quality and optimization of the process. In this study, the SOL method was improved by extending the structural increments from 22 to 38 to describe the molecules in petroleum more accurately. According to the basic law that the properties and structures of molecules are inseparable, the structural increments with similar physical meanings were combined into a functional group to reduce the dimension to 11 characteristic parameters to describe the molecular structure, and a property prediction method that can be combined with the molecularlevel refining models based on the optimized SOL method was constructed. In addition, the accuracy of the selection and definition of the 11 functional groups was verified by analyzing and discussing the effects of functional groups on the properties, which, in turn, ensured the accuracy of the property prediction models. Compared with other property prediction methods, this method can be combined with the SOL method to provide reliable predictions of the boiling point, critical temperature, critical volume, critical pressure, density, cetane number, motor octane number, and research octane number of molecules.

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“…Storage and transportation of all conventionally used high energy density fuels have the potential to cause unintended fire and explosion. , Liquid hydrocarbons which are typically used as fuels combust in the vapor phase, and the heat feedback from the flame is able to vaporize enough fuel to self-sustain the combustion. − Therefore, the typical way to extinguish a flame is to remove the oxygen source (air) from the flame front. Alternatively, room temperature ionic liquids (RTIL) are a special class of hydrocarbons having extremely low vapor pressures, which on thermal decomposition produces oxidation resistant species. − Owing to these characteristics, RTILs are usually nonflammable and are often used as flame-retardant components in various materials for energy storage and conversion. − …”

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confidence: 99%

Electrochemical Modulation of the Flammability of Ionic Liquid Fuels

et al. 2023

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Flammability and combustion of high energy density liquid propellants are controlled by their volatility. We demonstrate a new concept through which the volatility of a high energy density ionic liquid propellant can be dynamically manipulated enabling one to (a) store a thermally insensitive oxidation resistant nonflammable fuel, (b) generate flammable vapor phase species electrochemically by applying a direct-current voltage bias, and (c) extinguish its flame by removing the voltage bias, which stops its volatilization. We show that a thermally stable imidazolium-based energy dense ionic liquid can be made flammable or nonflammable simply by application or withdrawal of a direct-current bias. This cycle can be repeated as often as desired. The estimated energy penalty of the electrochemical activation process is only ∼4% of the total energy release. This approach presents a paradigm shift, offering the potential to make a "safe fuel" or alternatively a simple electrochemically driven fuel metering scheme.

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A comprehensive neural network model for predicting flash point of oxygenated fuels using a functional group approach

Cited by 16 publications

References 31 publications

Pyrolysis and Oxidation of Waste Tire Oil: Analysis of Evolved Gases

Pyrolysis and Oxidation of Waste Tire Oil: Analysis of Evolved Gases

Predicting the Physicochemical Properties of Molecules in Petroleum Based on Structural Increments

Electrochemical Modulation of the Flammability of Ionic Liquid Fuels

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