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Abstract Quantitative multi-image analysis (QMA) is the systematic extraction of new information and insight through the simultaneous analysis of multiple, related images. We present examples illustrating the potential for QMA to advance materials research in multi-image characterization, automatic feature identification, and discovery of novel processing-structure–property relationships. We conclude by discussing opportunities and challenges for continued advancement of QMA, including instrumentation development, uncertainty quantification, and automatic parsing of literature data. Graphical abstract 

The present work investigates fracture toughness, and actuation and mechanical fatigue crack growth responses of Ni50.3Ti29.7Hf20 HTSMAs across martensitic transformation with two different microstructures, one with H-phase nanoprecipitates and one without. H-phase precipitation is known to stabilize the actuation cycling response of NiTiHf HTSMAs and notably impacts transformation-induced plasticity. The fracture toughness tests performed reveal that precipitate-free NiTiHf has a higher fracture toughness and undergoes significantly more inelastic deformation than the one with the precipitates resulting in toughness enhancement, i.e., stable crack advance during fracture toughness experiments, which is not observed in the precipitated NiTiHf for the crack configuration and loading conditions tested. Furthermore, the precipitate free NiTiHf has higher actuation and mechanical fatigue crack growth resistance than the precipitation-hardened microstructure. This is attributed to plasticity buildup, which exacerbates the manifestation of retained martensite upon repeated transformations. The fatigue crack growth rates obtained from both actuation and mechanical fatigue experiments align to a single Paris Law Curve for the precipitation-hardened NiTiHf. This work aims to determine if unified Paris Law curves can be generated from mechanical and actuation fatigue experiments, irrespective of composition and microstructure, to estimate actuation fatigue crack growth rates, laborious and challenging to measure, from easier to detect mechanical fatigue crack growth rates. 

NiTiHf is a class of promising high-temperature shape memory alloys (SMAs) that find many applications. However, their complex martensitic microstructure and attendant thermomechanical properties are not well understood. In this work, we used solution-treated (precipitate-free) and aged (precipitate-bearing) Ni50.3Ti29.7Hf20 (at.%) SMAs as a model system. We observed that the presence of precipitates refines the martensite plates, reduces the number of martensite variants, and changes the orientation relationship between the martensite plates compared with the solution-treated counterpart. Furthermore, the aged samples exhibited higher transformation temperatures, narrower phase transformation temperature windows, improved thermal stability, and retained or even improved actuation strain. The improved thermomechanical properties observed in the aged samples are attributed in part to the reduction of the number of martensite variants and the change in martensite and twin interface characteristics, both of which are induced by the presence of precipitates. The findings of this study offer new information on the processing-property-microstructure relationship in NiTiHf-based SMAs. These insights can guide future materials design efforts, facilitating the development of advanced SMAs tailored for specific high-temperature applications. 

In this work, we developed three methods to map crystallographic variants of samples at the nanoscale by analyzing precession electron diffraction data using a high-temperature shape memory alloy and a VO2 thin film on sapphire as the model systems. The three methods are (I) a user-selecting-reference pattern approach, (II) an algorithm-selecting-reference-pattern approach, and (III) a k-means approach. In the first two approaches, Euclidean distance, Cosine, and Structural Similarity (SSIM) algorithms were assessed for the diffraction pattern similarity quantification. We demonstrated that the Euclidean distance and SSIM methods outperform the Cosine algorithm. We further revealed that the random noise in the diffraction data can dramatically affect similarity quantification. Denoising processes could improve the crystallographic mapping quality. With the three methods mentioned above, we were able to map the crystallographic variants in different materials systems, thus enabling fast variant number quantification and clear variant distribution visualization. The advantages and disadvantages of each approach are also discussed. We expect these methods to benefit researchers who work on martensitic materials, in which the variant information is critical to understand their properties and functionalities. 

NiTiHf high temperature shape memory alloys (HTSMAs) are being used in an ever-growing array of applications, specifically in the aerospace and automotive industries. One of the difficulties facing further implementation is ensuring the actuation fatigue lifetime is sufficiently long as to prevent the HTSMA components from being a limiting factor to the mean time between failures of a system. Another potential problem for widespread use is the deterioration of actuation stroke during lifetime, which can be problematic when attempting to have a high-fidelity repeatable design. One way of solving these issues is to optimize the microstructure through careful control of composition, processing, and heat treatments. Current research shows composition of large-scale productions is incredibly difficult to control, and small deviations in composition (~0.1 at.% Ni) can result in changes in transformation temperature by 50?C or more. Four NiTiHf compositions were investigated. The initial goal to simply extend the actuation fatigue lifetime and provide a stable actuation response morphed into determining material factors that influence the actuation response of partially cycled samples.