Sintering regimes and resulting microstructure and properties of binder jet 3D printed Ni-Mn-Ga magnetic shape memory alloys
Source abstract
Abstract
Binder jet 3D printing was used to produce magnetic shape memory alloy samples with densities increasing from 45% to 99% with increasing sintering temperature from 1000 °C to 1100 °C for 2 h. Within this temperature range, the sintering mechanisms, microstructural evolution, phase transformation and magnetic behavior were investigated and categorized in three different sintering regimes. X-ray diffraction showed that the pre-alloyed ball-milled Ni 49.7Mn 30Ga 20.3 powder has the austenite phase, however, twinned 14 M modulated martensite is present over the entire sintering temperature range with an increasing formation of martensite twins with temperature. At the low temperature sintering regime (<1020 °C), solid-state sintering results in densities of ∼45%, consistent composition, phase transformation, Curie temperature and magnetization. In the medium temperature sintering regime (1020 °C–1080 °C), solid-state sintering with grain boundary diffusion leads to densities up to ∼80% and otherwise similar properties as the low temperature regime. In the high temperature sintering regime (1090 °C–1100 °C), liquid phase sintering is dominant leading to densities up to ∼99% but due to segregation at the grain boundaries, broadening of transformation temperatures and lower saturation magnetization. In conclusion, binder jet 3D printing of Ni-Mn-Ga alloys show potential to enable functional, complex-shaped elements, and intentional porosity might allow these polycrystals to exhibit the magnetic field induced strain by reducing constraints between neighboring grains.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Shape Memory Alloy Transformations · Advanced Memory and Neural Computing · Magnetic and transport properties of perovskites and related materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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