A high-throughput framework for pile-up correction in high-speed nanoindentation maps
Accurate mapping of mechanical properties across extensive areas in heterogeneous materials is essential for understanding phase-specific contributions to strength and hardness. High-speed nanoindentation mapping enables their x-y spatial mapping through a fast and dense grid of indents. However, ac...
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Elsevier
2025-03-01
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| Series: | Materials & Design |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0264127525001285 |
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| author | Edoardo Rossi Daniele Duranti Saqib Rashid Michal Zitek Rostislav Daniel Marco Sebastiani |
| author_facet | Edoardo Rossi Daniele Duranti Saqib Rashid Michal Zitek Rostislav Daniel Marco Sebastiani |
| author_sort | Edoardo Rossi |
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| description | Accurate mapping of mechanical properties across extensive areas in heterogeneous materials is essential for understanding phase-specific contributions to strength and hardness. High-speed nanoindentation mapping enables their x-y spatial mapping through a fast and dense grid of indents. However, accurate measurements are complicated by pile-up, the plastic displacement of material laterally and vertically around an indent, causing hardness and modulus overestimation, especially in materials with varying phase compliance. Traditional correction methods rely on time-consuming, localized Atomic Force Microscopy measurements, which are impractical for large-area mapping. This study presents a fast and semi-automated solution using High-speed nanoindentation mapping-induced surface roughness changes Sa, quantifiable by optical profilometry, with machine learning to correct pile-up over extensive areas selectively. By correlating these roughness changes with the Atomic Force Microscopy-measured pile-up height, we derived universal calibration functions for a wide range of bulk materials and thin films, validated through Finite Element Modeling. Applied to a benchmark cobalt-based, chromium-tungsten alloy, the method uses unsupervised clustering to identify piling-up phases in the cobalt matrix while excluding the hard carbides. This approach reduced the hardness and modulus errors by up to 7 %, uniquely enabling accurate phase-specific property mapping in high-speed nanoindentation, advancing the mechanical microscopy frontier. |
| format | Article |
| id | doaj-art-3a49aed5b0474b439f2080a68aeeb484 |
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| issn | 0264-1275 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
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| series | Materials & Design |
| spelling | doaj-art-3a49aed5b0474b439f2080a68aeeb4842025-08-20T02:00:42ZengElsevierMaterials & Design0264-12752025-03-0125111370810.1016/j.matdes.2025.113708A high-throughput framework for pile-up correction in high-speed nanoindentation mapsEdoardo Rossi0Daniele Duranti1Saqib Rashid2Michal Zitek3Rostislav Daniel4Marco Sebastiani5Università degli Studi Roma Tre, Department of Civil, Computer Science and Aeronautical Technologies Engineering, Via Vito Volterra, 62, Rome 00146, Italy; Consorzio Interuniversitario Nazionale per la Scienza e Tecnologia dei Materiali (INSTM), Via Giuseppe Giusti 9, Florence 50121, Italy; Corresponding authors at: Università degli Studi Roma Tre, Department of Civil, Computer Science and Aeronautical Technologies Engineering, Via Vito Volterra, 62, Rome 00146, Italy.Università degli Studi Roma Tre, Department of Civil, Computer Science and Aeronautical Technologies Engineering, Via Vito Volterra, 62, Rome 00146, ItalyUniversità degli Studi Roma Tre, Department of Civil, Computer Science and Aeronautical Technologies Engineering, Via Vito Volterra, 62, Rome 00146, ItalyMontanuniversität Leoben, Department of Materials Science, Franz-Josef-Straße 18, Leoben 8700, AustriaMontanuniversität Leoben, Department of Materials Science, Franz-Josef-Straße 18, Leoben 8700, AustriaUniversità degli Studi Roma Tre, Department of Civil, Computer Science and Aeronautical Technologies Engineering, Via Vito Volterra, 62, Rome 00146, Italy; Consorzio Interuniversitario Nazionale per la Scienza e Tecnologia dei Materiali (INSTM), Via Giuseppe Giusti 9, Florence 50121, Italy; Corresponding authors at: Università degli Studi Roma Tre, Department of Civil, Computer Science and Aeronautical Technologies Engineering, Via Vito Volterra, 62, Rome 00146, Italy.Accurate mapping of mechanical properties across extensive areas in heterogeneous materials is essential for understanding phase-specific contributions to strength and hardness. High-speed nanoindentation mapping enables their x-y spatial mapping through a fast and dense grid of indents. However, accurate measurements are complicated by pile-up, the plastic displacement of material laterally and vertically around an indent, causing hardness and modulus overestimation, especially in materials with varying phase compliance. Traditional correction methods rely on time-consuming, localized Atomic Force Microscopy measurements, which are impractical for large-area mapping. This study presents a fast and semi-automated solution using High-speed nanoindentation mapping-induced surface roughness changes Sa, quantifiable by optical profilometry, with machine learning to correct pile-up over extensive areas selectively. By correlating these roughness changes with the Atomic Force Microscopy-measured pile-up height, we derived universal calibration functions for a wide range of bulk materials and thin films, validated through Finite Element Modeling. Applied to a benchmark cobalt-based, chromium-tungsten alloy, the method uses unsupervised clustering to identify piling-up phases in the cobalt matrix while excluding the hard carbides. This approach reduced the hardness and modulus errors by up to 7 %, uniquely enabling accurate phase-specific property mapping in high-speed nanoindentation, advancing the mechanical microscopy frontier.http://www.sciencedirect.com/science/article/pii/S0264127525001285Mechanical property mappingNanoindentationPile-upMachine learning |
| spellingShingle | Edoardo Rossi Daniele Duranti Saqib Rashid Michal Zitek Rostislav Daniel Marco Sebastiani A high-throughput framework for pile-up correction in high-speed nanoindentation maps Materials & Design Mechanical property mapping Nanoindentation Pile-up Machine learning |
| title | A high-throughput framework for pile-up correction in high-speed nanoindentation maps |
| title_full | A high-throughput framework for pile-up correction in high-speed nanoindentation maps |
| title_fullStr | A high-throughput framework for pile-up correction in high-speed nanoindentation maps |
| title_full_unstemmed | A high-throughput framework for pile-up correction in high-speed nanoindentation maps |
| title_short | A high-throughput framework for pile-up correction in high-speed nanoindentation maps |
| title_sort | high throughput framework for pile up correction in high speed nanoindentation maps |
| topic | Mechanical property mapping Nanoindentation Pile-up Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S0264127525001285 |
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