Evidence map›Paper›PMID 37512747›Full record

ArticleMicromachines2023

Superelastic NiTi Functional Components by High-Precision Laser Powder Bed Fusion Process: The Critical Roles of Energy Density and Minimal Feature Size.

Shuo Qu, Liqiang Wang, Junhao Ding, Jin Fu, Shiming Gao, Qingping Ma, Hui Liu, Mingwang Fu, Yang Lu, Xu Song

Abstract read
In one paragraph

Article in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Shuo QuDepartment of Mechanical and Automation Engineering, Chinese University of Hong Kong, Shatin, Hong Kong, China.ORCID 0000-0001-7152-5806
Liqiang WangDepartment of Mechanical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.
Junhao DingDepartment of Mechanical and Automation Engineering, Chinese University of Hong Kong, Shatin, Hong Kong, China.ORCID 0000-0001-8643-7518
Jin FuDepartment of Mechanical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
Shiming GaoDepartment of Mechanical and Automation Engineering, Chinese University of Hong Kong, Shatin, Hong Kong, China.
Qingping MaDepartment of Mechanical and Automation Engineering, Chinese University of Hong Kong, Shatin, Hong Kong, China.ORCID 0000-0002-4425-1464
Hui LiuDepartment of Mechanical and Automation Engineering, Chinese University of Hong Kong, Shatin, Hong Kong, China.
Mingwang FuDepartment of Mechanical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
Yang LuDepartment of Mechanical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.
Xu SongDepartment of Mechanical and Automation Engineering, Chinese University of Hong Kong, Shatin, Hong Kong, China.ORCID 0000-0001-9811-9883

Funding

City University of Hong Kong Project No. 7020008Innovation and Technology Fund of the Government of the Hong Kong Special Administrative Region Project No. ITS/008/19the Changsha Municipal Science and Technology Bureau Project No. kh2201035the collaborative research fund of the research grants council of Hong Kong C4074-22GFthe Shun Hing Institute of Advanced Engineering, The Chinese University of Hong Kong Project No. RNE-p2-21
6 · The paper itself

Abstract

Additive manufacturing (AM) was recently developed for building intricate devices in many fields. Especially for laser powder bed fusion (LPBF), its high-precision manufacturing capability and adjustable process parameters are involved in tailoring the performance of functional components. NiTi is well-known as smart material utilized widely in biomedical fields thanks to its unique superelastic and shape-memory performance. However, the properties of NiTi are extremely sensitive to material microstructure, which is mainly determined by process parameters in LPBF. In this work, we choose a unique NiTi intricate component: a robotic cannula tip, in which material superelasticity is a crucial requirement as the optimal object. First, the process window was confirmed by printing thin walls and bulk structures. Then, for optimizing parameters precisely, a Gyroid-type sheet triply periodic minimal-surface (G-TPMS) structure was proposed as the standard test sample. Finally, we verified that when the wall thickness of the G-TPMS structure is smaller than 130 μm, the optimal energy density changes from 167 J/m

Indexed as

3D printingenergy densitylaser powder bed fusionmechanical testingNiTi alloyrobotic cannulaTPMS lattice

Identifiers

PMID37512747
PMCPMC10383407

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Registered trials

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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.