Metal 3D Printing Techniques for Biomedical Applications

A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Biobased and Biodegradable Metals".

Deadline for manuscript submissions: 10 April 2026 | Viewed by 2019

Special Issue Editor


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Guest Editor
School of Mechanical and Aerospace Engineering, Queen’s University Belfast, University Road, Belfast BT7 1NN, Northern Ireland, UK
Interests: laser surface engineering; laser additive manufacturing; laser welding/joining for high-value manufacturing applications
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Special Issue Information

Dear Colleagues,

The world is facing significant challenges, including population growth, an ageing society, global warming, and a shift towards small-batch, customised manufacturing. Among these, the ageing population is driving demand for advanced medical implants. Metal implants, typically used for load-bearing functions, are a key category in biomedical applications.

Current manufacturing methods rely on traditional subtractive techniques, which limit the production of complex, patient-specific designs. Furthermore, conventional mass production contributes to material waste and CO2 emissions, contradicting sustainability goals. Metal 3D printing (M3DP) offers a transformative solution as an additive manufacturing technology, mitigating material waste, enabling powder recycling, and allowing the direct fabrication of customised implants from CAD models.

Various M3DP techniques have been developed, each with its own advantages. Powder-bed fusion (PBF) provides high precision and material flexibility, while directed energy deposition (DED) enables localised material addition. Binder-based methods utilise liquid binders to form green parts that require post-processing, and hybrid techniques combine mechanical bonding with CNC or laser shaping.

Despite these advancements, M3DP adoption in the medical device industry remains in its early stages. Further research is needed to optimise mechanical strength, corrosion and wear resistance, biocompatibility, bone integration, antibacterial properties, and long-term durability.

This Special Issue explores advancements in M3DP for biomedical applications, bridging materials science, additive manufacturing, and biomedical engineering.

Dr. Chi Wai Chan
Guest Editor

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Keywords

  • metal 3D printing (M3DP)
  • additive manufacturing
  • biomedical implants
  • customised implants
  • biocompatibility

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Published Papers (2 papers)

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Research

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25 pages, 9292 KB  
Article
Influence of Ball Burnishing Path Strategy on Surface Integrity and Performance of Laser-Cladded Inconel 718 Alloys
by Gustavo Fernandes, Andre Hatem, Anthony Roccisano, Mohammad Uddin, Colin Hall and Thomas Schlaefer
Metals 2025, 15(11), 1190; https://doi.org/10.3390/met15111190 - 26 Oct 2025
Viewed by 548
Abstract
This study investigates the influence of ball burnishing (BB) path strategies on the surface integrity and functional performance of laser-cladded Inconel 718. Three BB strategies—(1) BB-Longitudinal, (2) BB-Transverse, and (3) BB-Crosshatch—relative to the laser scan trajectory were evaluated and compared against ground surfaces [...] Read more.
This study investigates the influence of ball burnishing (BB) path strategies on the surface integrity and functional performance of laser-cladded Inconel 718. Three BB strategies—(1) BB-Longitudinal, (2) BB-Transverse, and (3) BB-Crosshatch—relative to the laser scan trajectory were evaluated and compared against ground surfaces as a baseline. Post-processing BB treatment were demonstrated to be effective in modifying the subsurface layer of the cladded Inconel 718 material, extending to depths of up to 100 µm, increasing dislocation density by over 2.5 times, and enhancing hardness from 260 HV5 (ground) to as high as 461 HV5. These microstructural improvements led to significant gains in corrosion and impact resistance, despite a rise in surface roughness from Ra 0.35 µm (ground) to up to 2.38 µm for BB-Longitudinal surfaces. Impact testing revealed up to 35% reduction in indentation volume, particularly with BB-Transverse and BB-Crosshatch strategies. Nonetheless, sliding wear tests did not confirm improvements in wear resistance, as wear depths exceeded the hardened layer and abrasive wear remained dominant. Electrochemical testing in 3.5 wt.% NaCl solution showed a positive shift in corrosion potential (Ecorr) exceeding 200 mV compared to the ground condition, indicating reduced corrosion susceptibility for BB-Longitudinal condition. Among the tested strategies, BB-Transverse offered the most balanced enhancements, highlighting the complex interplay between laser cladding heterogeneities and post-processing response in optimizing surface and mechanical properties of Inconel 718 claddings. Full article
(This article belongs to the Special Issue Metal 3D Printing Techniques for Biomedical Applications)
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Review

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29 pages, 8000 KB  
Review
Enhancing Biomedical Metal 3D Printing with AI and Nanomaterials Integration
by Jackie Liu, Jaison Jeevanandam and Michael K. Danquah
Metals 2025, 15(10), 1163; https://doi.org/10.3390/met15101163 - 21 Oct 2025
Cited by 1 | Viewed by 1109
Abstract
The integration of artificial intelligence (AI) with nanomaterials is rapidly transforming metal three-dimensional (3D) printing for biomedical applications due to their unprecedented precision, customization, and functionality. This article discusses the role of AI in optimizing design parameters, predicting material behaviors, and controlling additive [...] Read more.
The integration of artificial intelligence (AI) with nanomaterials is rapidly transforming metal three-dimensional (3D) printing for biomedical applications due to their unprecedented precision, customization, and functionality. This article discusses the role of AI in optimizing design parameters, predicting material behaviors, and controlling additive manufacturing processes for metal-based implants and prosthetics. Nanomaterials, particularly metallic nanoparticles, enhance the mechanical strength, biocompatibility, and functional properties of 3D-printed structures. AI-driven models, including machine learning (ML) and deep learning algorithms, are increasingly used to forecast print quality, detect defects in real-time, and reduce material waste. Moreover, data-driven design approaches enable patient-specific implant development and predictive modeling of biological responses. We highlight recent advancements in AI-guided material discovery through microstructure–property correlations and multi-scale simulation. Challenges such as data scarcity, standardization, and integration across interdisciplinary domains are also discussed, along with emerging solutions based on federated learning and the digital twinning approach. Further, the article emphasizes the importance of AI and nanomaterials to revolutionize metal 3D printing to fabricate smarter, safer, and effective biomedical devices. Future perspectives covering the need for robust datasets, explainable AI frameworks, and regulatory frameworks to ensure the clinical translation of AI-enhanced additive manufacturing technologies are discussed. Full article
(This article belongs to the Special Issue Metal 3D Printing Techniques for Biomedical Applications)
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