Enhancing Biomedical Metal 3D Printing with AI and Nanomaterials Integration
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023752%3A_____%2F25%3A43921697" target="_blank" >RIV/00023752:_____/25:43921697 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/2075-4701/15/10/1163" target="_blank" >https://www.mdpi.com/2075-4701/15/10/1163</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/met15101163" target="_blank" >10.3390/met15101163</a>
Alternative languages
Result language
angličtina
Original language name
Enhancing Biomedical Metal 3D Printing with AI and Nanomaterials Integration
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
21002 - Nano-processes (applications on nano-scale); (biomaterials to be 2.9)
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Metals
ISSN
2075-4701
e-ISSN
2075-4701
Volume of the periodical
15
Issue of the periodical within the volume
10
Country of publishing house
CH - SWITZERLAND
Number of pages
29
Pages from-to
"Article Number 1163"
UT code for WoS article
001601991000001
EID of the result in the Scopus database
2-s2.0-105020195267