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Waterless sterilization of clinical solid waste using supercritical carbon dioxide: fungal spores inactivation mechanisms, optimization and artificial neural network models

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Abstract

Clinical solid waste contains pathogenic microorganisms and therefore requires effective sterilization prior to safe handling and disposal. This work deals with the inactivation of Aspergillus niger, Aspergillus terreus var. terreus and Penicillium simplicissimum spores in clinical solid waste using supercritical carbon dioxide (SC-CO2) as a waterless sterilization technology. The artificial neural network (ANN) approach was used to study the behavior of the fungal spores for the pressure, temperature, time and initial fungal spore concentrations. The optimal operating parameters were 35 MPa, 35 °C, 100-min treatment time with 6 log10 spores g−1: the predicted and experimental results were 5.48 and 5.96 logs of A. niger, 5.56 and 5.96 logs of A. terreus var. terreus, 5.84 and 5.99 log reduction of P. simplicissimum. ANN analysis revealed that temperature, time and initial concentrations showed a greater influence on the inactivation of the fungal spore’s inactivation. Inactivation results from destructing the cell wall, as evidenced by the lack of growth of fungi in the culture medium, indicating complete inactivation of the fungal spores. The findings of the present study would be useful in implementing the sustainable utilization of clinical solid waste materials.

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Acknowledgements

The authors acknowledge the Master Thesis of Efaq Ali Noman (Identification of fungi isolated from clinical waste and inactivation of fungal spores by using supercritical carbon dioxide), which the manuscript is derived from the thesis. The authors confirm that there is no third-party material in the manuscript. The authors would like to thank UTHM for supporting this research through Tier 1 (H743).

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EN: methodology investigation and manuscript draft. AA: conceptualization, supervision, writing—review and editing. SS: writing—review and editing. MSH: writing—review and editing. RMSRM: writing—review and editing. NNNAR: conceptualization, supervision, writing—review and editing. MOAK: writing—conceptualization, supervision, writing—review and editing.

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Correspondence to Adel Ali Al-Gheethi, Spilimbergo Sara or Radin Maya Saphira Radin Mohamed.

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Noman, E.A., Al-Gheethi, A.A., Sara, S. et al. Waterless sterilization of clinical solid waste using supercritical carbon dioxide: fungal spores inactivation mechanisms, optimization and artificial neural network models. Biomass Conv. Bioref. 13, 13573–13589 (2023). https://doi.org/10.1007/s13399-022-02931-1

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  • DOI: https://doi.org/10.1007/s13399-022-02931-1

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