ADVANCED MATERIALS & PROCESSES | NOVEMBER 2026 30 Shape Memory and Super- elasticity: Advances in Science and Technology (SMJ) is the official journal of the International Organization on Shape Memory and Superelastic Technologies (SMST), an affiliate society of ASM International. The journal publishes original peer-reviewed papers that focus on shape memory materials research with contributions from materials science, experimental and theoretical mechanics, physics with cognizance of the chemistry, underlying phases, and crystallography. It also provides a forum for researchers, scientists, and engineers of varied disciplines to access information about shape memory materials. This article was taken from the September 2026 issue and was selected by Shape Memory Editor-in-Chief Huseyin Sehitoglu. SMJ is available through link.springer.com. For more information, visit asminternational.org/smst. September 2026 ADDITIVE MANUFACTURING OF SHAPE MEMORY ALLOYS: A REVIEW OF DATA GAPS AND OPPORTUNITIES Jamila Khanfri, Othmane Benafan, Peter E. Caltagirone, Sayed E. Saghaian, and Aaron P. Stebner Data and metadata from additively manufactured shape memory alloys (AM SMAs) were collected and utilized to illustrate trends and anomalies of current state-of- the-art additive manufacturing (AM) processes. Input parameters, output parameters, and properties were documented from six alloy families spanning nearly two decades of research and development: NiTi, NiMn, NiCo, FeMn, CuAl, and others. Data analyses revealed several key challenges and opportunities for advancing the field, including standardization of terminology, increased reporting of significant process parameters, and inclusion of more feedstock material information. These analyses demonstrate that improvements in these areas in future work can help ensure that reported results are easier to reproduce. Still, to date, microstructures and thermomechanical properties of SMAs have shown promising results, in some cases comparable with conventionally processed materials. This review documents some of these trends and opportunities while providing suggestions toward more data-centric reporting practices in AM SMA research. Furthermore, the dataset that was curated for this review can be analyzed in future investigations using data science approaches to further SMA alloy design and AM processes (Fig. 1). Fig. 1 — AM articles published per year across all SMA families (from 2006 to 2023). AM of (a) all SMA families, (b) NiTi-based SMAs, (c) NiCo- and NiMn-based alloys, and (d) CuAl-based and Fe-based alloys. Upward-pointing arrows indicate that additional publications exist but are not captured in this figure. (a) (b) (c) (d) SMJ HIGHLIGHTS
RkJQdWJsaXNoZXIy MTYyMzk3NQ==