Evolution of Electron Channelling Contrast Imaging of Plastic Deformation Induced by Berkovich Nanoindentation in Ferrite Steel
Notice bibliographique
Résumé
Strain field characterization is critical for understanding plastic deformation in electrical and structural materials [1]. Electron Channelling Contrast Imaging (ECCI) and Electron Backscattered Diffraction (EBSD) methods can be used in a Scanning Electron Microscope (SEM) to study near-surface strain fields with nanoscale spatial resolution, a broad field of view, and statistically accurate data on a bulk sample [2]. In this work, we used the novel approach correlative ECCI to evaluate the microstructures and deformation evolution in a ferrite 1010 steel sample after nanoindentation. This technique uses the Bloch wave theorem to study the contrast obtained from lattice crystal defects in samples, including dislocations, twins, grain boundaries, and stacking faults [1]. ECCI measurements were made in the SEM SU 8000 from Hitachi with an accelerating voltage of 5kV. A solid-state Backscatter Electron (PD-BSE) detector was used to capture the contrast caused by crystal defects through electron channelling techniques [3], with EBSD measurements done with the SEM SU8230 from Hitachi at acceleration voltage of 15 kV. Geometrically Necessary Dislocations (GNDs) were identified using a cross-correlation-based EBSD with high angular resolution [4] and a Burgers vector of 2.48 nm. The average GNDs density was then calculated with the ATEX software. To extract the mechanical properties of the ferrite sample, experimental nanoindentation were carried out with the Hysitron system, while simulations were carried out using Finite Element Method in ABAQUS software, both with a load of 7500 µN. Figure 1a shows the average surface roughness of 13.76 ± 0.31 μm measured by zygo-profilometer. This determines the surface topology of the ferrite sample, to ensure a flat, smooth, and perpendicular surface to the nano indenter. The formation of equiaxed grains were observe in the microstructure of the 1010 ferrite sample, as shown in the ECCI image fig. 1b. The area of the nanoindentation 6 x 6 matrix is shown in the ECCI image in fig. 1c. Each indent shows up as an equilateral triangle located either inside a grain, at a grain boundary, or near a triple junction. It was observed that the channelling contrast varied across grains and around each indent. The variation in BSE intensity surrounding each indent was caused by local strain fields and the presence of deformation after indentation, as shown in fig. 1d. Figure 2a shows the histogram plot that was obtained through the EBSD orientation map on the sample, which gives an average of GND density of 8.13 x 1014 m-2. The load-displacement curve in figure 2b depicts the maximum indentation depth of 0.42 µm, reached at 7500 µN. An average hardness 2.39 ± 0.34 GPa was obtained, while 205.60 ± 9.72, and 207.00 GPa were obtained as the Young’s modulus for the experimental and computational analyses, respectively. Based on the strain field size measured from the ECCI image, the yield strength is aimed to be calculated in the future. Furthermore, materials from the indented surface would be removed using the ion milling surface preparation process. This would allow the evaluation of the microstructures and to know the magnitude of the plastic deformation induced at the maximum depth of the indents. (a) Surface topography obtained by zygo-profilometer, (b) ECCI image of the microstructure before nanoindentation, (c) ECCI image of the microstructure after nanoindentation, and (d) ECCI image on one of the indents. (a) Histogram showing GND distributions obtained from the EBSD map, (b) Experimental and simulated load-displacement curve for the ferrite steel.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».