High-Throughput Study on the Influence of Carbon on the Shape Memory Effect in an Additively Manufactured Fe–Mn–Si–Cr Alloy Using In Situ Alloying

Jonas Schmidt, Marten Grube, Anastasiya Toenjes · Springer Science and Business Media LLC · 2025

This study explores how varying carbon content in a Fe-Mn-Si-Cr alloy affects its shape memory properties through different heat treatments.

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Plain English summary

This research examines how carbon influences the mechanical and functional properties of a specific alloy made using additive manufacturing. The study involved adjusting the carbon content during the manufacturing process and analyzing the resulting alloys after various heat treatments. The findings indicate that the carbon content and heat treatments significantly affect the alloy's microstructure and properties.

Why this matters

Understanding how to manipulate the properties of shape memory alloys can lead to advancements in various applications, particularly in manufacturing where tailored material properties are crucial. This research could enhance the performance of materials used in industries that require specific mechanical characteristics.

Key findings

  • Carbon content was varied from 0.06 wt.-% to 0.23 wt.-%.
  • Higher carbon content increased the volume fraction of precipitates.
  • Mechanical properties were tunable based on carbon content and heat treatments.
  • The highest mechanical strength was achieved through direct ageing.
  • The highest recovery strain of up to 80% was observed with 0.06 wt.-% carbon after solution annealing and ageing.

What's new

The study introduces a nanoparticle dispersion-based in situ re-alloying approach to modify carbon content during additive manufacturing.

Limitations

The abstract does not provide details on the specific applications of the findings or the broader implications for industry.

Commercial context

The research is still in the laboratory phase and has not yet been demonstrated in commercial applications.

Publication

Publisher
Springer Science and Business Media LLC
Publication date
October 17, 2025
Research type
Paper
License
https://creativecommons.org/licenses/by/4.0

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Method note: Summaries and ratings on this page are generated by AI from the abstract only. Read the original paper for full context. · Model: gpt-4o-mini-2024-07-18