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A simulation study on enhancing sterilization efficiency in medical plastics through gamma radiation optimization

Gamma radiation is progressively emerging as an effective method to enhance the sterilization efficiency of medical plastics including Polyvinyl chloride (PVC). The parameters of the radiation facility will affect the efficiency of radiation sterilization. To investigate these effects, we simulate t...

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Autores principales: Yuan, Xin, Liu, Fang, Zhou, Hongchi, Liu, Bin, Li, Guanda, Yan, Peiguang, Li, Guoping, Luo, Xiaoru, Lyu, Xuefeng, Cheng, Jinxing, Niu, Fenglei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10660597/
https://www.ncbi.nlm.nih.gov/pubmed/37985894
http://dx.doi.org/10.1038/s41598-023-47771-9
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author Yuan, Xin
Liu, Fang
Zhou, Hongchi
Liu, Bin
Li, Guanda
Yan, Peiguang
Li, Guoping
Luo, Xiaoru
Lyu, Xuefeng
Cheng, Jinxing
Niu, Fenglei
author_facet Yuan, Xin
Liu, Fang
Zhou, Hongchi
Liu, Bin
Li, Guanda
Yan, Peiguang
Li, Guoping
Luo, Xiaoru
Lyu, Xuefeng
Cheng, Jinxing
Niu, Fenglei
author_sort Yuan, Xin
collection PubMed
description Gamma radiation is progressively emerging as an effective method to enhance the sterilization efficiency of medical plastics including Polyvinyl chloride (PVC). The parameters of the radiation facility will affect the efficiency of radiation sterilization. To investigate these effects, we simulate the gamma radiation sterilization performance of PVC material sample using Monte Carlo Method. The simulation results indicated that compared with the sterilization time of 20–90 min from high-temperature steam sterilization of medical waste, by optimizing the parameters of the model radiation facility, the radiation sterilization time can be reduced to 6.61 min. The optimized model facility parameters are as follows: the gamma photon energy is 1.25 MeV, the model space is 300 × 300 × 300 cm(3), the reflective layer material is concrete and its thickness is 8 cm, the PVC sample layer area is 100 × 100 cm(2), the distance between the radiation source and the PVC sample layer is 150 cm, the energy deposition in the bottom layer of the PVC sample layer is 1.31315 × 10(–6) MeV/g. This study offers a potentially feasible way for PVC sterilization, while also providing a crucial reference for the further promotion and application of radiation sterilization technology.
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spelling pubmed-106605972023-11-20 A simulation study on enhancing sterilization efficiency in medical plastics through gamma radiation optimization Yuan, Xin Liu, Fang Zhou, Hongchi Liu, Bin Li, Guanda Yan, Peiguang Li, Guoping Luo, Xiaoru Lyu, Xuefeng Cheng, Jinxing Niu, Fenglei Sci Rep Article Gamma radiation is progressively emerging as an effective method to enhance the sterilization efficiency of medical plastics including Polyvinyl chloride (PVC). The parameters of the radiation facility will affect the efficiency of radiation sterilization. To investigate these effects, we simulate the gamma radiation sterilization performance of PVC material sample using Monte Carlo Method. The simulation results indicated that compared with the sterilization time of 20–90 min from high-temperature steam sterilization of medical waste, by optimizing the parameters of the model radiation facility, the radiation sterilization time can be reduced to 6.61 min. The optimized model facility parameters are as follows: the gamma photon energy is 1.25 MeV, the model space is 300 × 300 × 300 cm(3), the reflective layer material is concrete and its thickness is 8 cm, the PVC sample layer area is 100 × 100 cm(2), the distance between the radiation source and the PVC sample layer is 150 cm, the energy deposition in the bottom layer of the PVC sample layer is 1.31315 × 10(–6) MeV/g. This study offers a potentially feasible way for PVC sterilization, while also providing a crucial reference for the further promotion and application of radiation sterilization technology. Nature Publishing Group UK 2023-11-20 /pmc/articles/PMC10660597/ /pubmed/37985894 http://dx.doi.org/10.1038/s41598-023-47771-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Yuan, Xin
Liu, Fang
Zhou, Hongchi
Liu, Bin
Li, Guanda
Yan, Peiguang
Li, Guoping
Luo, Xiaoru
Lyu, Xuefeng
Cheng, Jinxing
Niu, Fenglei
A simulation study on enhancing sterilization efficiency in medical plastics through gamma radiation optimization
title A simulation study on enhancing sterilization efficiency in medical plastics through gamma radiation optimization
title_full A simulation study on enhancing sterilization efficiency in medical plastics through gamma radiation optimization
title_fullStr A simulation study on enhancing sterilization efficiency in medical plastics through gamma radiation optimization
title_full_unstemmed A simulation study on enhancing sterilization efficiency in medical plastics through gamma radiation optimization
title_short A simulation study on enhancing sterilization efficiency in medical plastics through gamma radiation optimization
title_sort simulation study on enhancing sterilization efficiency in medical plastics through gamma radiation optimization
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10660597/
https://www.ncbi.nlm.nih.gov/pubmed/37985894
http://dx.doi.org/10.1038/s41598-023-47771-9
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