{"title":"Multiscale residual stress analysis and microstructure characterization of Ti-grade 2 implant fabricated by adaptive tool path-driven SPIF process","authors":"Arun Sharma , Parnika Shrivastava , Aniket Nagargoje , Amrut Mulay","doi":"10.1016/j.matchar.2025.114861","DOIUrl":null,"url":null,"abstract":"<div><div>Single Point Incremental Forming of titanium alloys for biomedical implants presents a unique challenge in balancing geometrical accuracy with the control of residual stresses. The proposed methodology introduces a novel curvature-driven adaptive toolpath for incremental forming, overcoming the limitations of conventional constant depth spiral and existing adaptive strategies. Unlike STL-based adaptive methods that rely on volumetric error correction by adding slices between consecutive layers, this approach optimizes the toolpath by removing redundant slices. By adjusting slice, the process assigns density values according to local curvature fluctuations thus creating more efficient forming while reducing forming time. Electron Backscatter Diffraction is utilized to measure the evolution of microstructure through an evaluation of misorientation distribution, deformation twinning and geometrically necessary dislocation density. X-ray diffraction technology and micro-scale residual stress measurement techniques are used to measure macro and micro residual stress fields in the produced implants. The present work correlates the tool path strategies with the observed residual stress distribution along with microstructural characteristics which uncovered the underlying deformation mechanism in implants formed by SPIF. Results highlight that adaptive tool path-driven SPIF process led to decreased amounts of residual stress while creating more uniform stress patterns within Ti-Grade 2 implants. The implant formed with adaptive tool path resulted in higher homogeneity in stress distribution with lower localized strain concentrations in comparison to those formed with conventional tool paths. In addition, microstructural characteristics denoted more uniform plastic deformation across the formed implant. The study demonstrates that the modifications in SPIF tool path bring superior results in product quality. Achieving desired residual stress states and microstructural characteristics becomes possible through SPIF which delivers improved dimensional accuracy and reliability of the formed Ti-Grade 2 implants.</div></div>","PeriodicalId":18727,"journal":{"name":"Materials Characterization","volume":"222 ","pages":"Article 114861"},"PeriodicalIF":4.8000,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Characterization","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1044580325001500","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, CHARACTERIZATION & TESTING","Score":null,"Total":0}
引用次数: 0
Abstract
Single Point Incremental Forming of titanium alloys for biomedical implants presents a unique challenge in balancing geometrical accuracy with the control of residual stresses. The proposed methodology introduces a novel curvature-driven adaptive toolpath for incremental forming, overcoming the limitations of conventional constant depth spiral and existing adaptive strategies. Unlike STL-based adaptive methods that rely on volumetric error correction by adding slices between consecutive layers, this approach optimizes the toolpath by removing redundant slices. By adjusting slice, the process assigns density values according to local curvature fluctuations thus creating more efficient forming while reducing forming time. Electron Backscatter Diffraction is utilized to measure the evolution of microstructure through an evaluation of misorientation distribution, deformation twinning and geometrically necessary dislocation density. X-ray diffraction technology and micro-scale residual stress measurement techniques are used to measure macro and micro residual stress fields in the produced implants. The present work correlates the tool path strategies with the observed residual stress distribution along with microstructural characteristics which uncovered the underlying deformation mechanism in implants formed by SPIF. Results highlight that adaptive tool path-driven SPIF process led to decreased amounts of residual stress while creating more uniform stress patterns within Ti-Grade 2 implants. The implant formed with adaptive tool path resulted in higher homogeneity in stress distribution with lower localized strain concentrations in comparison to those formed with conventional tool paths. In addition, microstructural characteristics denoted more uniform plastic deformation across the formed implant. The study demonstrates that the modifications in SPIF tool path bring superior results in product quality. Achieving desired residual stress states and microstructural characteristics becomes possible through SPIF which delivers improved dimensional accuracy and reliability of the formed Ti-Grade 2 implants.
期刊介绍:
Materials Characterization features original articles and state-of-the-art reviews on theoretical and practical aspects of the structure and behaviour of materials.
The Journal focuses on all characterization techniques, including all forms of microscopy (light, electron, acoustic, etc.,) and analysis (especially microanalysis and surface analytical techniques). Developments in both this wide range of techniques and their application to the quantification of the microstructure of materials are essential facets of the Journal.
The Journal provides the Materials Scientist/Engineer with up-to-date information on many types of materials with an underlying theme of explaining the behavior of materials using novel approaches. Materials covered by the journal include:
Metals & Alloys
Ceramics
Nanomaterials
Biomedical materials
Optical materials
Composites
Natural Materials.