Combined Tribological and Bactericidal Effect of Nanodiamonds as a Potential Lubricant for Artificial Joints.

ACS Appl Mater Interfaces

Department of Biomedical Engineering , Stony Brook University, Stony Brook , New York 11749 , United States.

Published: November 2019

AI Article Synopsis

  • Artificial joints, like knee and hip implants, often fail due to high friction and wear, leading to inflammation and infections.
  • Researchers propose a solution using nanodiamond (ND) particles to improve the friction and wear behavior of ultrasound molecular weight polyethylene (UHMWPE) and titanium, which mimic the artificial joint interface.
  • The introduction of NDs not only enhances lubrication and reduces wear but also shows excellent biocompatibility with bone cells and antibacterial properties against common infection strains, making them a promising option for improving artificial joint performance through injection.

Article Abstract

The artificial joints, for example, knee and hip implants, are widely used for the treatment of degenerative joint diseases and trauma. The current most common material choice for clinically used implants is the combination of polymer-on-metal structures. Unfortunately, these joints often suffer from high friction and wear, leading to associated inflammation and infection and ultimate failure of the artificial joints. Here, we propose an alternative solution to this tribologically induced failure of the joint materials. We demonstrate that the friction and wear behavior of ultrahigh-molecular-weight polyethylene (UHMWPE) and titanium tribopair, used to mimic the artificial joint interface, can be improved by introducing nanodiamond (ND) particles in the sliding contact. Characterization of the wear track using energy-dispersive spectroscopy and Raman spectroscopy revealed that the tribofilm formed from embedded NDs during sliding significantly suppressed the wear of the UHMWPE surface. In addition to the improved lubrication characteristics, NDs exhibit high biocompatibility with the bone cells and promising antibacterial properties against , the most common strain associated with artificial joint infection. These results indicate that NDs can be used as a promising nontoxic human-body lubricant with antiwear and antibacterial features, thus demonstrating their great potential to treat artificial joint complications through intra-articular injection.

Download full-text PDF

Source
http://dx.doi.org/10.1021/acsami.9b14904DOI Listing

Publication Analysis

Top Keywords

artificial joints
12
artificial joint
12
friction wear
8
artificial
6
joint
5
combined tribological
4
tribological bactericidal
4
bactericidal nanodiamonds
4
nanodiamonds potential
4
potential lubricant
4

Similar Publications

Reversible Isomerization of Stiff-Stilbene by an Oriented External Electric Field.

J Am Chem Soc

January 2025

Key Laboratory for Advanced Materials, Feringa Nobel Prize Scientist Joint Research Center, Frontiers Science Center for Materiobiology and Dynamic Chemistry, Institute of Fine Chemicals, School of Chemistry and Molecular Engineering, East China University of Science and Technology, Shanghai 200237, P. R. China.

Understanding and effectively controlling molecular conformational changes are essential for developing responsive and dynamic molecular systems. Here, we report that an oriented external electric field (OEEF) is an effective catalyst for the cis-trans isomerization of stiff-stilbene, a key component of overcrowded alkene-based rotary motors. This reversible isomerization occurs under ambient conditions, is free from side reactions, and has been verified using ultraperformance liquid chromatography and UV-vis absorption spectroscopy.

View Article and Find Full Text PDF

Novel Design on Knee Exoskeleton with Compliant Actuator for Post-Stroke Rehabilitation.

Sensors (Basel)

December 2024

Institute of Robotics, Autonomous System and Sensing, School of Electronic and Electrical Engineering, University of Leeds, Leeds LS2 9JT, UK.

Knee joint disorders pose a significant and growing challenge to global healthcare systems. Recent advancements in robotics, sensing technologies, and artificial intelligence have driven the development of robot-assisted therapies, reducing the physical burden on therapists and improving rehabilitation outcomes. This study presents a novel knee exoskeleton designed for safe and adaptive rehabilitation, specifically targeting bed-bound stroke patients to enable early intervention.

View Article and Find Full Text PDF

Design, Development, and Testing of Machine Learning Models to Estimate Properties of Friction Stir Welded Joints.

Materials (Basel)

December 2024

Department of Mechanical Engineering Technology, College of Applied Industrial Technology, Jazan University, Jazan 45142, Saudi Arabia.

This paper estimates friction stir welded joints' ultimate tensile strength (UTS) and hardness using six supervised machine learning models (viz., linear regression, support vector regression, decision tree regression, random forest regression, K-nearest neighbour, and artificial neural network). Tool traverse speed, tool rotational speed, pin diameter, shoulder diameter, tool offset, and tool tilt are the six input parameters in the 200 datasets for training and testing the models.

View Article and Find Full Text PDF

This article presents a new parametric method for shaping flat transverse frame structural systems supporting thin-walled roofs made of flat sheets folded unidirectionally and transformed elastically to various shell forms. The parameterization was limited to one independent variable, that is the stiffness of the support joints. For different discrete values of simulated stiffness, the surface areas of the cross sections of the tensile and compressed elements and the section modulus of the bending elements were calculated so as to obtain the optimized work of the frame and its elements in the assumed load environment.

View Article and Find Full Text PDF

As the global economy expands, waterway transportation has become increasingly crucial to the logistics sector. This growth presents both significant challenges and opportunities for enhancing the accuracy of ship detection and tracking through the application of artificial intelligence. This article introduces a multi-object tracking system designed for unmanned aerial vehicles (UAVs), utilizing the YOLOv7 and Deep SORT algorithms for detection and tracking, respectively.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!