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Design of (TiHfZr)(NiCoCu) High-Entropy Shape Memory Alloys: From Firstov's Experiments to Data-Driven Approach

Article dans une revue avec comité de lecture
Auteur
PELTIER, Laurent
178323 Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux [LEM3]
THIERCELIN, Léo
178323 Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux [LEM3]
ccMERAGHNI, Fodil
178323 Laboratoire d'Etude des Microstructures et de Mécanique des Matériaux [LEM3]

URI
http://hdl.handle.net/10985/26181
DOI
10.1007/s40830-025-00532-1
Date
2025-03
Journal
Shape Memory and Superelasticity

Résumé

This paper deals with the design of (TiHfZr)(NiCoCu) high-entropy and high-temperature shape memory alloys (HE-HT-SMAs). It explains the chronology and the progress of this design starting from the experimental work of Georgi Firstov initiated in the 2015s until the advent of data-driven alloy approaches. A state-of-the-art (TiHfZr)(NiCoCu) HE-HT-SMA family is presented and enriched by a database used as input for a data-driven approach. The paper then focuses on the comparison of martensitic transformation temperatures provided by: (i) the experimental work of Firstov et al. started in 2015, (ii) other recent experimental studies and, (iii) those predicted by two numerical approaches. The first approach consists of a linear regression model proposed by Peltier et al., while the second one is proposed and enriched by Thiercelin et al. using a data-driven technique (random forest regression). The results from the data-driven approach yield accurate predictions that align with the experimental data from both the literature and previous studies. Thus demonstrating the importance of physics-informed, inspired techniques to optimize the design of future alloys, in particular HE-HT-SMAs.

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LEM3_SMST_2025_MERAGHNI.pdf
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Documents liés

Visualiser des documents liés par titre, auteur, créateur et sujet.

  • Physics-informed machine learning prediction of the martensitic transformation temperature for the design of “NiTi-like” high entropy shape memory alloys 
    Article dans une revue avec comité de lecture
    THIERCELIN, Léo; PELTIER, Laurent; ccMERAGHNI, Foudil (Elsevier BV, 2024-01)
    The present study proposes a physics-informed machine learning (PIML) algorithm-based approach aimed at predicting the martensitic transformation temperature (Ms) for the design of “NiTi-like” high entropy shape memory ...
  • Thermally-activated hardening recovery in viscoplastic materials with kinematic hardening at high temperatures 
    Article dans une revue avec comité de lecture
    THIERCELIN, Léo; PRAUD, Francis; ccMERAGHNI, Fodil; FLEURY, Eric (ELSEVIER, 2023-05)
    In this work, a new constitutive model is proposed to describe the thermally-activated hardening recovery mechanism in metallic materials. This model takes up the concept of hardening recovery variable, which is extended ...
  • Microstructural and experimental analysis of strain rate effect for short glass fiber reinforced polypropylene 
    Conférence invitée
    ACHOUR-RENAULT, Nadia; ccMERAGHNI, Fodil; PELTIER, Laurent; ccFITOUSSI, Joseph (2015)
    The scope of this work is to provide a microstructural description and an experimental analysis of the strain rate effect on short glass fiber reinforced polypropylene.
  • Damage Evaluation in Woven Glass Reinforced Polyamide 6.6/6 Composites Using Ultrasound Phase-Shift Analysis and X-ray Tomography 
    Article dans une revue avec comité de lecture
    POMAREDE, Pascal; ccMERAGHNI, Fodil; PELTIER, Laurent; DELALANDE, Stéphane; DECLERCQ, Nico Felicien (Springer Verlag, 2018)
    The paper proposes a new experimental methodology, based on ultrasonic measurements, that aims at evaluating the anisotropic damage in woven semi-crystalline polymer composites through new damage indicators. Due to their ...
  • Martensite Transformation and Superelasticity at High Temperature of (TiHfZr)74(NbTa)26 High-Entropy Shape Memory Alloy 
    Article dans une revue avec comité de lecture
    PELTIER, Laurent; ccBERVEILLER, Sophie; ccMERAGHNI, Fodil; LOHMULLER, Paul; LAHEURTE, Pascal (Springer Science and Business Media LLC, 2021)
    In this work, a (TiHfZr)(NbTa) 26 (%at) high-entropy quinary alloy has been developed especially for high-temperature superelastic applications and studied over a large range of temperatures. The mechanical properties of ...

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