Enhancing Biomedical Metal 3D Printing with AI and Nanomaterials Integration

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Enhancing Biomedical Metal 3D Printing with AI and Nanomaterials Integration

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Enhancing Biomedical Metal 3D Printing with AI and Nanomaterials Integration

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

21002 - Nano-processes (applications on nano-scale); (biomaterials to be 2.9)

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Metals

ISSN

2075-4701

e-ISSN

2075-4701

Svazek periodika

15

Číslo periodika v rámci svazku

10

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

29

Strana od-do

"Article Number 1163"

Kód UT WoS článku

001601991000001

EID výsledku v databázi Scopus

2-s2.0-105020195267