Chameekara T. Wanniarachchi , Arun Arjunan , Ahmad Baroutaji , Manpreet Singh
{"title":"3D打印定制硬度匹配的超生物材料,具有接近零的auxecity,用于承重组织修复","authors":"Chameekara T. Wanniarachchi , Arun Arjunan , Ahmad Baroutaji , Manpreet Singh","doi":"10.1016/j.bprint.2023.e00292","DOIUrl":null,"url":null,"abstract":"<div><p>The evolution of meta-biomaterials has opened up exciting new opportunities for mass personalisation of biomedical devices. This research paper details the development of a CoCrMo meta-biomaterial structure that facilitates personalised stiffness-matching while also exhibiting near-zero auxeticity. Using laser powder bed fusion, the porous architecture of the meta-biomaterial was characterised, showing potential for near-zero Poisson's ratio. The study also introduces a novel surrogate model that can predict the porosity (<span><math><mrow><mi>φ</mi></mrow></math></span>), yield strength (<span><math><mrow><msub><mi>σ</mi><mi>y</mi></msub></mrow></math></span>), elastic modulus (<span><math><mrow><mi>E</mi></mrow></math></span>), and negative Poisson's ratio (<span><math><mrow><mo>−</mo><mi>υ</mi></mrow></math></span>) of the meta-biomaterial, which was achieved through prototype testing and numerical modelling. The model was then used to inform a multi-criteria desirability objective, revealing an optimum near-zero <span><math><mrow><mo>−</mo><mi>υ</mi></mrow></math></span> of −0.037, with a targeted stiffness of 17.21 GPa. Parametric analysis of the meta-biomaterial showed that it exhibited <span><math><mrow><mo>−</mo><mi>υ</mi></mrow></math></span>, <span><math><mrow><mi>φ</mi></mrow></math></span>, <span><math><mrow><msub><mi>σ</mi><mi>y</mi></msub></mrow></math></span> and <span><math><mrow><mi>E</mi></mrow></math></span> values ranging from −0.02 to −0.08, 73.63–81.38%, 41–64 MPa, and 9.46–20.6 GPa, respectively. In this study, a surrogate model was developed for the purpose of generating personalised scenarios for the production of bone scaffolds. By utilising this model, it was possible to achieve near-zero <span><math><mrow><mo>−</mo><mi>υ</mi></mrow></math></span> and targeted stiffness personalisation. This breakthrough has significant implications for the field of bone tissue engineering and could pave the way for improved patient outcomes. The presented methodology is a powerful tool for the development of biomaterials and biomedical devices that can be 3D printed on demand for load-bearing tissue reconstruction. It has the potential to facilitate the creation of highly tailored and effective treatments for various conditions and injuries, ultimately enhancing patient outcomes.</p></div>","PeriodicalId":72406,"journal":{"name":"","volume":"33 ","pages":"Article e00292"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"3D printing customised stiffness-matched meta-biomaterial with near-zero auxeticity for load-bearing tissue repair\",\"authors\":\"Chameekara T. Wanniarachchi , Arun Arjunan , Ahmad Baroutaji , Manpreet Singh\",\"doi\":\"10.1016/j.bprint.2023.e00292\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The evolution of meta-biomaterials has opened up exciting new opportunities for mass personalisation of biomedical devices. This research paper details the development of a CoCrMo meta-biomaterial structure that facilitates personalised stiffness-matching while also exhibiting near-zero auxeticity. Using laser powder bed fusion, the porous architecture of the meta-biomaterial was characterised, showing potential for near-zero Poisson's ratio. The study also introduces a novel surrogate model that can predict the porosity (<span><math><mrow><mi>φ</mi></mrow></math></span>), yield strength (<span><math><mrow><msub><mi>σ</mi><mi>y</mi></msub></mrow></math></span>), elastic modulus (<span><math><mrow><mi>E</mi></mrow></math></span>), and negative Poisson's ratio (<span><math><mrow><mo>−</mo><mi>υ</mi></mrow></math></span>) of the meta-biomaterial, which was achieved through prototype testing and numerical modelling. The model was then used to inform a multi-criteria desirability objective, revealing an optimum near-zero <span><math><mrow><mo>−</mo><mi>υ</mi></mrow></math></span> of −0.037, with a targeted stiffness of 17.21 GPa. Parametric analysis of the meta-biomaterial showed that it exhibited <span><math><mrow><mo>−</mo><mi>υ</mi></mrow></math></span>, <span><math><mrow><mi>φ</mi></mrow></math></span>, <span><math><mrow><msub><mi>σ</mi><mi>y</mi></msub></mrow></math></span> and <span><math><mrow><mi>E</mi></mrow></math></span> values ranging from −0.02 to −0.08, 73.63–81.38%, 41–64 MPa, and 9.46–20.6 GPa, respectively. In this study, a surrogate model was developed for the purpose of generating personalised scenarios for the production of bone scaffolds. By utilising this model, it was possible to achieve near-zero <span><math><mrow><mo>−</mo><mi>υ</mi></mrow></math></span> and targeted stiffness personalisation. This breakthrough has significant implications for the field of bone tissue engineering and could pave the way for improved patient outcomes. The presented methodology is a powerful tool for the development of biomaterials and biomedical devices that can be 3D printed on demand for load-bearing tissue reconstruction. It has the potential to facilitate the creation of highly tailored and effective treatments for various conditions and injuries, ultimately enhancing patient outcomes.</p></div>\",\"PeriodicalId\":72406,\"journal\":{\"name\":\"\",\"volume\":\"33 \",\"pages\":\"Article e00292\"},\"PeriodicalIF\":0.0,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2405886623000350\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/6/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405886623000350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/6/19 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
3D printing customised stiffness-matched meta-biomaterial with near-zero auxeticity for load-bearing tissue repair
The evolution of meta-biomaterials has opened up exciting new opportunities for mass personalisation of biomedical devices. This research paper details the development of a CoCrMo meta-biomaterial structure that facilitates personalised stiffness-matching while also exhibiting near-zero auxeticity. Using laser powder bed fusion, the porous architecture of the meta-biomaterial was characterised, showing potential for near-zero Poisson's ratio. The study also introduces a novel surrogate model that can predict the porosity (), yield strength (), elastic modulus (), and negative Poisson's ratio () of the meta-biomaterial, which was achieved through prototype testing and numerical modelling. The model was then used to inform a multi-criteria desirability objective, revealing an optimum near-zero of −0.037, with a targeted stiffness of 17.21 GPa. Parametric analysis of the meta-biomaterial showed that it exhibited , , and values ranging from −0.02 to −0.08, 73.63–81.38%, 41–64 MPa, and 9.46–20.6 GPa, respectively. In this study, a surrogate model was developed for the purpose of generating personalised scenarios for the production of bone scaffolds. By utilising this model, it was possible to achieve near-zero and targeted stiffness personalisation. This breakthrough has significant implications for the field of bone tissue engineering and could pave the way for improved patient outcomes. The presented methodology is a powerful tool for the development of biomaterials and biomedical devices that can be 3D printed on demand for load-bearing tissue reconstruction. It has the potential to facilitate the creation of highly tailored and effective treatments for various conditions and injuries, ultimately enhancing patient outcomes.