Details

Autor(en) / Beteiligte

• Schneider-Maunoury, C.
• Albayda, A.
• Bartier, O.
• Weiss, L.
• Mauvoisin, G.
• Hernot, X.
• Laheurte, P.

Titel

On the use of instrumented indentation to characterize the mechanical properties of functionally graded binary alloys manufactured by additive manufacturing

Ist Teil von

• Materials today communications, 2020-12, Vol.25, p.101451, Article 101451

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2020

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• •A Ti-xNb FGM (where x=0, 26, 48, 75 and 100%) was builded by CLAD® additive manufacturing process.•The Young’s modulus and the work hardening law of each part of the FGM was obtained from instrumented indentation.•A good correlation between the mechanical properties obtained from tensile test and indentation was obtained.•For all compositions of the Ti-Nb FGM, Young’s Modulus values obtained from IIT are consistent with results from literature. The mechanical properties of a Ti-xNb functionally graded material (FGM) created by using an additive manufacturing process (CLAD®) were obtained using a spherical instrumented indentation test (IIT). The aim of this paper is to demonstrate the great suitability of the indentation test coupled with FGM for not only obtaining the hardness of a material, but also obtaining other mechanical properties such as Young’s modulus, yield stress and the work-hardening exponent for heterogeneous materials. In the first step, results obtained from the instrumented indentation test were compared with those obtained from the tensile test for the same materials. These results show that these two tests highlight a similar evolution in the mechanical properties. In the second step, and after validating the efficiency of the IIT in obtaining mechanical properties, the FGM Ti-xNb was successfully identified using only IIT. This paper demonstrates that the different mechanical properties of all the compositions of a phase diagram can be measured very easily and quickly while minimizing the number of samples.