Qualitative and Quantitative Evaluation of Different Types of Orthodontic Brackets and Archwires by Optical Microscopy and X-ray Fluorescence Spectroscopy

D’Andrea, Danilo; Milone, Dario; Nicita, Fabiana; Risitano, Giacomo; Santonocito, Dario

doi:10.3390/prosthesis3040031

Cited by 5 publications

(2 citation statements)

References 53 publications

(59 reference statements)

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“…The CT scan has characterized the bony structure. In the literature, various models allow the extrapolation of the mechanical characteristics, and the constraints and the loads on certain bodies subjected to specific actions [35][36][37][38][39][40][41][42][43][44]. Researchers are increasingly focusing on creating models that simulate the whole body rather than limiting themselves to small, specific sections [45].…”

Section: Numerical Modelingmentioning

confidence: 99%

A New Approach for the Tribological and Mechanical Characterization of a Hip Prosthesis Trough a Numerical Model Based on Artificial Intelligence Algorithms and Humanoid Multibody Model

et al. 2022

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In recent years, thanks to the development of additive manufacturing techniques, pros-thetic surgery has reached increasingly cutting-edge levels, revolutionizing the clinical course of patients suffering from joint arthritis, rheumatoid arthritis, post-traumatic arthrosis, etc. This work aims to evaluate the best materials for prosthetic surgery in hip implants from a tribological and mechanical point of view by using a machine-learning algorithm coupling with multi-body modeling and Finite Element Method (FEM) simulations. The innovative aspect is represented by the use of machine learning for the creation of a humanoid model in a multibody software environment that aimed to evaluate the load and rotation condition at the hip joint. After the boundary conditions have been defined, a Finite Element (FE) model of the hip implant has been created. The material properties and the information on the tribological behavior of the material couplings under investigation have been obtained from literature studies. The wear process has been investigated through the implementation of the Archard’s wear law in the FE model. The results of the FE simulation show that the best wear behavior has been obtained by CoCr alloy/UHMWPE coupling with a volume loss due to a wear of 0.004 μm3 at the end of the simulation of ten sitting cycles. After the best pairs in terms of wear has been established, a topology optimization of the whole hip implant structure has been performed. The results show that, after the optimization process, it was possible to reduce implant mass making the implant 28.12% more lightweight with respect to the original one.

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Section: Numerical Modelingmentioning

confidence: 99%

A New Approach for the Tribological and Mechanical Characterization of a Hip Prosthesis Trough a Numerical Model Based on Artificial Intelligence Algorithms and Humanoid Multibody Model

et al. 2022

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“…However, wear caused by regular activities such as walking, sitting, or running can lead to deterioration of the materials used in the joint [6][7][8]. To overcome this problem, researchers are increasingly turning to more advanced materials [9][10][11] and numerical techniques, such as the finite element method (FEM), to improve the functionality and lifespan of prostheses [12][13][14][15][16][17][18][19][20]. Human models are also used to simulate the influence of prosthetic design on human comfort and biomechanics [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Smart Design of Hip Replacement Prostheses Using Additive Manufacturing and Machine Learning Techniques

Milone,

D’Andrea,

Santonocito

2023

Prosthesis

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The field of additive manufacturing, particularly 3D printing, has ushered in a significant transformation in the realm of joint arthritis treatment through prosthetic surgery. This innovative technology allows for the creation of bespoke prosthetic devices that are tailored to meet the specific needs of individual patients. These devices are constructed using high-performance materials, including titanium and cobalt-chrome alloys. Nevertheless, the routine physical activities of patients, such as walking, sitting, and running, can induce wear and tear on the materials comprising these prosthetic devices, subsequently diminishing their functionality and durability. In response to this challenge, this research has endeavored to leverage novel techniques. The primary focus of this study lies in the development of an algorithm designed to optimize hip replacement procedures via the mechanical design of the prosthesis. This optimization process exploits the capabilities of machine learning algorithms, multi-body dynamics, and finite element method (FEM) simulations. The paramount innovation in this methodology is the capacity to design a prosthetic system that intricately adapts to the distinctive characteristics of each patient (weight, height, gait cycle). The primary objective of this research is to enhance the performance and longevity of prosthetic devices by improving their fatigue strength. The evaluation of load distribution on the prosthetic device, facilitated by FEM simulations, anticipates a substantial augmentation in the useful life of the prosthetic system. This research holds promise as a notable advancement in prosthetic technology, offering a more efficacious treatment option for patients suffering from joint arthritis. The aim of this research is to make meaningful contributions to the enhancement of patient quality of life and the long-term performance of prosthetic devices.

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Smart design of customized hip prostheses in additive manufacturing by combining numerical and experimental methodologies

Milone

Marchis

Longo

et al. 2023

IOP Conf. Ser.: Mater. Sci. Eng.

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Thanks to the development of additive manufacturing techniques, prosthetic surgery has reached increasingly advanced levels, revolutionizing the clinical course of patients with joint arthritis. 3D printing has made it possible to obtain customized prostheses based on patient needs, using high-performance materials. However, wear caused by regular gait activities such as walking, sitting, or running, leads to the deterioration of the material used in the joint. Thus, the use of traditional materials has gradually been replaced with more performing ones which have made it possible to obtain customized devices based on patient needs and, therefore, more effective. Numerical techniques have recently been adopted, such as the Finite Element Method (FEM), to support the experimentation, allowing the calculation of the useful life and the optimization of the prostheses’ functionality to accurately evaluate the distribution of the load on the prosthesis. The present work aims to develop an algorithm that optimizes hip replacement mechanically using a machine learning algorithm coupled with multi-body and finite element model simulations.

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Qualitative and Quantitative Evaluation of Different Types of Orthodontic Brackets and Archwires by Optical Microscopy and X-ray Fluorescence Spectroscopy

Cited by 5 publications

References 53 publications

A New Approach for the Tribological and Mechanical Characterization of a Hip Prosthesis Trough a Numerical Model Based on Artificial Intelligence Algorithms and Humanoid Multibody Model

A New Approach for the Tribological and Mechanical Characterization of a Hip Prosthesis Trough a Numerical Model Based on Artificial Intelligence Algorithms and Humanoid Multibody Model

Smart Design of Hip Replacement Prostheses Using Additive Manufacturing and Machine Learning Techniques

Smart design of customized hip prostheses in additive manufacturing by combining numerical and experimental methodologies

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