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Related Concept Videos

Abrasion Resistance of Concrete01:23

Abrasion Resistance of Concrete

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Abrasion resistance is an essential characteristic of concrete that determines its durability and longevity under various wear conditions. Concrete surfaces are vulnerable to different types of abrasion. For instance, surfaces may wear down due to the constant movement of vehicles or be eroded by solids carried in water, as seen in concrete canal linings. Specific tests are conducted to measure the abrasion resistance of concrete.
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Related Experiment Video

Updated: Nov 9, 2025

Mimicking and Measuring Occlusal Erosive Tooth Wear with the "Rub&Roll" and Non-contact Profilometry
08:47

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Three-Dimensional Surface Texture Characterization of In Situ Simulated Erosive Tooth Wear.

A T Hara1, D Elkington-Stauss2, P S Ungar2

  • 1Indiana University School of Dentistry, Indianapolis, IN, USA.

Journal of Dental Research
|April 15, 2021
PubMed
Summary
This summary is machine-generated.

This study shows fractal complexity (Asfc) and arithmetical mean height (Sa) can detect and differentiate erosive tooth wear (ETW) severity. Asfc also monitors severe ETW progression, unlike anisotropy (Str).

Keywords:
aciddental abrasiondental erosiondietenamelsaliva

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Area of Science:

  • Dental Biomaterials
  • Oral Health Research
  • Surface Metrology

Background:

  • Erosive tooth wear (ETW) is a growing concern in oral health.
  • Accurate detection and differentiation of ETW lesions are crucial for effective management.
  • Current methods for assessing ETW may lack sensitivity in differentiating early or varying severities.

Purpose of the Study:

  • To evaluate the efficacy of 3D surface texture analysis in detecting and differentiating simulated erosive tooth wear (ETW) lesions.
  • To validate an in situ ETW simulation model using human enamel specimens.
  • To compare the performance of fractal complexity (Asfc), arithmetical mean height (Sa), and texture aspect ratio (Str) in characterizing ETW.

Main Methods:

  • An in situ crossover study involving 20 participants simulating ETW using three protocols: severe (lemon juice), moderate (grapefruit juice), and control (water).
  • Human enamel specimens were analyzed using white-light scanning confocal profilometry at baseline, 7, and 14 days.
  • 3D surface texture parameters, including Asfc, Sa, and Str, were calculated and statistically analyzed.

Main Results:

  • Asfc and Sa successfully differentiated ETW severity (none < moderate < severe) and detected changes over time.
  • Asfc and Sa showed high positive correlation (r=0.89), indicating similar sensitivity to ETW.
  • Surface loss increased with ETW severity, validating the simulation model, while Str did not effectively characterize ETW.
  • Asfc demonstrated potential in monitoring the progression of severe ETW lesions.

Conclusions:

  • 3D surface texture parameters, specifically Asfc and Sa, are effective tools for detecting and differentiating erosive tooth wear severity.
  • Asfc shows promise for monitoring the progression of severe erosive tooth wear.
  • Anisotropy (Str) is not a reliable parameter for characterizing ETW in this context.