Future machine learning strategies for materials process optimization will likely replace human capital-intensive artisan research with autonomous and/or accelerated approaches. Such automation enables accelerated multimodal characterization that simultaneously minimizes human errors, lowers costs, enhances statistical sampling, and allows scientists to allocate their time to critical thinking instead of repetitive manual tasks. Previous acceleration efforts to synthesize and evaluate materials have often employed elaborate robotic self-driving laboratories or used specialized strategies that are difficult to generalize. Herein we describe an implemented workflow for accelerating the multimodal characterization of a combinatorial set of 915 electroplated Ni and Ni–Fe thin films resulting in a data cube with over 160,000 individual data files. Our acceleration strategies do not require manufacturing-scale resources and are thus amenable to typical materials research facilities in academic, government, or commercial laboratories. The workflow demonstrated the acceleration of six characterization modalities: optical microscopy, laser profilometry, X-ray diffraction, X-ray fluorescence, nanoindentation, and tribological (friction and wear) testing, each with speedup factors ranging from 13–46x. In addition, automated data upload to a repository using FAIR data principles was accelerated by 64x.
Magnetostrictive Co77Fe23 films are fully suspended to produce free-standing, clamped-clamped, microbeam resonators. A negative or positive shift in the resonant frequency is observed for magnetic fields applied parallel or perpendicular to the length of the beam, respectively, confirming the magnetoelastic nature of the shift. Notably, the resonance shifts linearly with higher-bias fields oriented perpendicular to the beam's length. Domain imaging elucidates the distinction in the reversal processes along the easy and hard axes. Together, these results suggest that through modification of the magnetic anisotropy, the frequency shift and angular dependence can be tuned, producing highly magnetic-field-sensitive resonators.
The ability to track nuclear material is a challenge for resiliency of complex systems, e.g., harsh environments. RF tags, frequently used in national security applications, cannot be used for technological, operational, or safety reasons. Magnetic Smart Tags (MaST) is a novel tag technology based on magnetoelastic sensing that circumvents these issues. This technology is enabled by a new, cost-effective, batch manufacturing electrochemical deposition (ECD) process. This new advancement in fabrication enables multi-frequency tags capable of providing millions of possible codes for tag identification unlike existing theft deterrent tags that can convey only a single bit of information. Magnetostrictive 70% Co: 30% Fe was developed as the base alloy comprising the magnetoelastic resonator transduction element. Saturation magnetostriction, λS, has been externally measured by the Naval Research Laboratory to be as high as 78 ppm. Description of a novel MEMS variable capacitive test structure is described for future measurements of this parameter.
Recent studies have shown the potential for nanocrystalline metals to possess excellent fatigue resistance compared to their coarse-grained counterparts. Although the mechanical properties of nanocrystalline metals are believed to be particularly susceptible to material defects, a systematic study of the effects of geometric discontinuities on their fatigue performance has not yet been performed. In the present work, nanocrystalline Ni–40 wt%Fe containing both intrinsic and extrinsic defects were tested in tension–tension fatigue. The defects were found to dramatically reduce the fatigue resistance, which was attributed to the relatively high notch sensitivity in the nanocrystalline material. Microstructural analysis within the crack-initiation zones underneath the defects revealed cyclically-induced abnormal grain growth (AGG) as a predominant deformation and crack initiation mechanism during high-cycle fatigue. Furthermore, the onset of AGG and the ensuing fracture is likely accelerated by the stress concentrations, resulting in the reduced fatigue resistance compared to the relatively defect-free counterparts.