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The influence of the functionalization of polystyrene and graphene oxide composites on the flammability characteristics: modeling with artificial intelligence tools

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Abstract

This paper tackles the influence of the functionalization of polystyrene and graphene oxide (GO) composites on the flammability characteristics. A microscale combustion calorimeter (MCC) was used to experimentally determine the heat release capacity (HRC), the specific heat release rate (HRR) and the total heat released (THR). Neural models were designed that correlate the THR with a number of parameters related to the composition and type of flame retardant used, the heating rate, the amount of residue, the HRC, the peak heat release rate (PHRR), the temperature at the peak pyrolysis rate (TPHRR) and the time elapsed until the occurrence of the peak heat release rate (Time). The best results in the training, validation and testing stages were achieved with the neural model with 9 neurons in the input layer, 40 neurons in the hidden layer and one neuron in the output layer. This model was incorporated into an optimization procedure, based on a genetic algorithm, to establish the values of the input parameters used in the training of the neural networks, in order to generate a minimum THR value, which is the output parameter. Since the synthesis of polystyrene particles with different GO concentrations is costly, this research helps to reduce the number of experimental tests and allows to determine the best GO concentration by means of neural models and genetic algorithms.

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Acknowledgements

This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS/CCCDI—UEFISCDI, Project Number PN-III-P2-2.1-PED-2021-3156, within PNCDI III.

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Authors and Affiliations

  1. Fire Officers Faculty, Police Academy “Alexandru Ioan Cuza”, 3 Morarilor Street, Sector 2, 022451, Bucharest, Romania

    Ion Anghel, Dana Maria Preda & Ioana-Emilia Şofran

  2. Faculty of Chemical Engineering and Environmental Protection “Cristofor Simionescu”, Department of Chemical Engineering, Gheorghe Asachi Technical University of Iasi, Bd. Mangeron 73, 700050, Iași, Romania

    Catălin Lisa & Silvia Curteanu

  3. Faculty of Physics, “Babes-Bolyai” University, Mihail Kogălniceanu 1, 400084, Cluj-Napoca, Romania

    Monica Baia & Lucian Baia

  4. Laboratory of Optical Processes in Nanostructured Materials, National Institute of Materials Physics, P.O. Box MG-7, R077125, Bucharest, Romania

    Malvina Stroe, Mirela Paraschiv & Mihaela Baibarac

  5. Department of Chemical Engineering, Faculty of Chemistry and Chemical Engineering, “Babes-Bolyai” University, Arany Janos 11, 400028, Cluj-Napoca, Romania

    Virginia Danciu & Liviu Cosmin Cotet

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  1. Ion Anghel
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  2. Catălin Lisa
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  3. Silvia Curteanu
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  12. Lucian Baia
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Correspondence to Catălin Lisa.

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Anghel, I., Lisa, C., Curteanu, S. et al. The influence of the functionalization of polystyrene and graphene oxide composites on the flammability characteristics: modeling with artificial intelligence tools. J Therm Anal Calorim 149, 2805–2824 (2024). https://doi.org/10.1007/s10973-023-12869-9

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