Evidence map›Paper›PMID 37273982›Full record

ArticleInternational journal of bioprinting2023

Evaluation of mechanical and biological properties of akermanite/poly-ether-ether- ketone composite fabricated by high- temperature laser powder bed fusion.

Zhiyuan Chen, Haoze Wang, Jin Su, Zixing Shu, Jiayi Hou, Peng Chen, Zhaoqing Li, Chunze Yan, Yusheng Shi

Abstract read
In one paragraph

Article in International journal of bioprinting, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Zhiyuan ChenState Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Haoze WangState Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Jin SuState Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Zixing ShuDepartment of Orthopedic Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Jiayi HouState Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Peng ChenState Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Zhaoqing LiWuhan Zeqing Technology Co. Ltd., Wuhan 430074, China.
Chunze YanState Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Yusheng ShiState Key Laboratory of Materials Processing and Die & Mould Technology, School of Materials Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-temperature laser bed powder fusion (HT-LPBF) technology is an ideal method for processing poly-ether-ether-ketone (PEEK) implants with personalized bionic structures, but the biological inertia of PEEK limits its medical applications. In this study, we evaluated the mechanical and biological properties of a novel akermanite (AKM)/PEEK composite for HT-LPBF. The results showed that tiny AKM particles are evenly attached to the surface of the PEEK particle. The delayed peak crystallization temperature and stable sintering window ensure the processing feasibility of the AKM/PEEK composites. The tensile strength and Young's modulus are in the range of 30.83-98.73 MPa and 2.27-3.71 GPa, respectively, which can match the properties of cancellous bones and meet their implanting requirement. The CCK-8 experiments demonstrated the biocompatibility of the composites and the good proliferation of bone marrow stromal cells. The dense hydroxyapatite network layer and petal-like hydroxyapatite demonstrates biological activity, indicating that the composite has a good potential in the orthopedics fields.

Indexed as

Additive manufacturingAkermanite/poly-ether-ether-ketone compositeBiological propertiesLaser powder bed fusionMechanical properties

Identifiers

PMID37273982
PMCPMC10236334

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.