{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Jiao P"],"funding":["NIBIB NIH HHS","National Key Research and Development Program of China","Zhejiang University","National Institute of Biomedical Imaging and Bioengineering","National Science Foundation"],"pagination":["2991-3001"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11744508"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["17(2)"],"pubmed_abstract":["Current limitations in implant design often lead to trade-offs between minimally invasive surgery and achieving the desired post-implantation functionality. Here, we present an artificial intelligence inverse design paradigm for creating deployable implants as planar and tubular thermal mechanical metamaterials (thermo-metamaterials). These thermo-metamaterial implants exhibit tunable mechanical properties and volume change in response to temperature changes, enabling minimally invasive and personalized surgery. We begin by generating a large database of corrugated thermo-metamaterials with various cell structures and bending stiffnesses. An artificial intelligence inverse design model is subsequently developed by integrating an evolutionary algorithm with a neural network. This model allo"],"journal":["ACS applied materials & interfaces"],"pubmed_title":["Artificial Intelligence-Guided Inverse Design of Deployable Thermo-Metamaterial Implants."],"pmcid":["PMC11744508"],"funding_grant_id":["2023YFC3008100","1R21EB034457-01A1","R21 EB034457","CMMI-2235494"],"pubmed_authors":["Wu Z","Agarwal N","Jang D","Jiao P","Zhang C","Alavi AH","Wang J","Meng W"],"additional_accession":[]},"is_claimable":false,"name":"Artificial Intelligence-Guided Inverse Design of Deployable Thermo-Metamaterial Implants.","description":"Current limitations in implant design often lead to trade-offs between minimally invasive surgery and achieving the desired post-implantation functionality. Here, we present an artificial intelligence inverse design paradigm for creating deployable implants as planar and tubular thermal mechanical metamaterials (thermo-metamaterials). These thermo-metamaterial implants exhibit tunable mechanical properties and volume change in response to temperature changes, enabling minimally invasive and personalized surgery. We begin by generating a large database of corrugated thermo-metamaterials with various cell structures and bending stiffnesses. An artificial intelligence inverse design model is subsequently developed by integrating an evolutionary algorithm with a neural network. This model allo","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Jan","modification":"2025-04-21T16:46:45.032Z","creation":"2025-04-05T09:31:00.63Z"},"accession":"S-EPMC11744508","cross_references":{"pubmed":["39746033"],"doi":["10.1021/acsami.4c17625"]}}