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Updated: Jun 25, 2025

Quantitative Hardness Measurement by Instrumented AFM-indentation
Published on: November 22, 2016
Microhardness Variation with Indentation Depth for Body-Centered Cubic Steels Pertinent to Grain Size and Ferrite
Anye Xu1, Xuding Song1, Min Ye1
1Key Laboratory of Road Construction Technology and Equipment, Ministry of Education, Chang'an University, Xi'an 710064, China.
This study proposes a new model to predict microhardness in steels based on indentation depth, grain size, and ferrite content. The model accurately forecasts hardness variations and scatter, enhancing non-destructive testing reliability.
Area of Science:
- Materials Science
- Mechanical Engineering
- Metallurgy
Background:
- The Nix-Gao model is standard for analyzing indentation size effects in microhardness testing.
- Understanding microhardness variation is crucial for non-destructive material characterization.
- Steel microstructure significantly influences mechanical properties like hardness.
Purpose of the Study:
- To develop an analytical model predicting microhardness-to-mac rohardness ratio based on indentation depth.
- To link the characteristic indentation depth parameter to microstructural features like grain size and ferrite volume fraction.
- To incorporate normal distribution theory for accounting for measurement scatter in hardness testing.
Main Methods:
- Analysis of microhardness measurements on 10 body-centered cubic steels with varying microstructures.
- Development of an analytical relationship between microhardness ratio and indentation depth.
- Linking characteristic indentation depth to grain size and ferrite volume fraction using two distinct methods.
- Incorporation of normal distribution theory to model measurement variability.
Main Results:
- A reliable analytical model was developed to predict microhardness variation with indentation depth.
- The model demonstrates 96% reliability in its predictions.
- The characteristic indentation depth was successfully correlated with microstructural parameters.
- The model effectively accounts for scatter in hardness measurements due to material heterogeneity and testing errors.
Conclusions:
- The proposed model offers an effective method for predicting microhardness in steels across various indentation depths.
- The model enhances the accuracy and reliability of non-destructive microhardness testing.
- Explicitly linking microstructural features to indentation behavior improves material characterization capabilities.
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