Chemical composition and thermal processing parameters are used in a first-of-their-kind machine learning (ML) and batch Bayesian optimization (BBO) approach in an iterative fashion in the quaternary NiTiCuHf hightemperature shape memory alloy (HTSMA) composition space to minimize thermal hysteresis in a desired transformation temperature range. The first of three iterations exploited an existing SMA database of lower complexity alloys (binary and ternary) attempting to optimize quaternary NiCuTiHf chemistry and thermal processing for the given constraint and the objective. Alloy synthesis and characterization revealed that the initial ML model displays high error levels between the predicted and experimental values, indicating the need for high-fidelity data in the complex quaternary alloy design space for optimization. The second iteration used this conclusion to explore an expanded design space through tuning Gaussian process (GP) hyperparameters. Utilization of active learning enabled the enlargement of data present in the high-complexity space during the iterative process, improving model accuracy. The third iteration discovered NiTiCuHf HTSMAs with the lowest reported martensitic transformation thermal hysteresis with transformation temperatures between 250 degrees C and 350 degrees C to date without precious metals. The effects of optimized secondary heat treatments on the martensitic transformation characteristics were explored and compared to those achieved after the initial homogenization heat treatments to demonstrate the ability of the BBO framework to create optimal alloys with controlled chemistry and thermal processing. In Ni-rich compositions of the designed alloys, the secondary heat treatments suggested by the BBO framework resulted in significant increases in transformation temperatures, suggesting the formation of Ni-rich precipitates.

Refractory multi-principal element alloys (RMPEAs) have gained interest recently due to their superior properties at elevated temperatures, including outstanding yield and ultimate strengths, high thermal conductivity, and resistance to creep. RMPEAs can be designed to exhibit a wide range of properties by tailoring their composition. However, the vast chemical design space makes brute-force experimental screening inefficient and costly. In this work, we follow a closed-loop, iterative computational/experimental screening approach that combines computational alloy design methodologies with high-throughput synthesis and characterization tools to explore the vast RMPEAs space and design new RMPEAs that satisfy multiple objectives and constraints. In particular, we targeted compositions with yield strengths higher than 50 MPa at 2000 degrees C, W content of more than 30 at.% for high-temperature strength and operability up to 2000 degrees C, narrow solidification range for additive manufacturability, competitive ductility metrics, among other property constraints. We evaluated the mechanical properties and microstructure of 58 alloys designed in 5 batches, in both as-cast and homogenized conditions, synthesized using vacuum arc melting, utilizing scanning electron microscopy, X-ray diffraction, Vickers microhardness, nanoindentation, and high-temperature compression testing. Based on the microhardness screening experiments in each batch, the best-performing alloys were selected for scale-up. High-temperature compression at 1800 degrees C was performed in these alloys, demonstrating that the designed alloys exhibit up to five times higher yield strength than a pure tungsten benchmark. We conclude that W-containing RMPEAs designed in this study merit further consideration for next-generation structural materials for ultra-high temperature applications.

Interlocking metasurfaces (ILMs) are a newly developed joining technology that relies on arrays of interlocking features that transmit force and constrain motion between adjoining bodies in one or more directions. This study explores harnessing the shape memory effect (SME) in Nickel-Titanium shape memory alloys (NiTi SMAs) in structures fabricated using additive manufacturing (AM) to advance the development of active ILMs by creating unit cells that open or close at specific temperatures. The study encompasses designing and fabricating two distinct interlocking array configurations using near-equiatomic NiTi powder and the laser powder bed fusion (L-PBF) AM technique, following a previously developed AM process optimization framework to manufacture defect-free parts. To guide the design process, finite element analysis (FEA) was employed to predict strain values during engage-disengage cycles. The martensitic transformation characteristics of the ILMs were characterized. Thermomechanical testing revealed that the ILMs demonstrate high locking force once engaged, coupled with complete shape recovery and good cyclic stability. Digital image correlation (DIC) was also employed to validate the FEA predictions during the engage-disengage cycles. The results indicate that NiTi SMA-based ILMs can be designed and fabricated into complex shapes using L-PBF. By leveraging the SME, the functionality of an ILM can be improved upon. The combination of computational modeling, additive manufacturing, and thermomechanical and physical property characterization provides a framework for designing future ILMs out of active materials.

Mechanical properties of refractory high entropy alloys (RHEAs) at ultra-high temperatures (>1,100°C) are reviewed. Deformation behavior and strengthening mechanisms of select compositions are discussed. The limited number of studies portray remarkable mechanical properties of newly developed RHEA compositions at temperatures beyond the melting point of commercial Ni-based superalloys. Yet, the lack of quasi-static tensile deformation data and application relevant creep deformation data indicates RHEAs are still far from being reliable alternatives to Ni-based superalloys as high temperature structural materials. Future studies should concentrate on tensile deformation and creep of these new alloys systems at very high temperatures.

Shape memory alloys (SMAs) have been demonstrated as effective phase change materials (PCMs) for thermal energy storage (TES) applications. NiTi and NiTiHf SMAs have shown high TES performance, as quantified by PCM figure of merit (FOM) but their use in applications requiring narrow operation temperature windows is limited by large overall phase transformation ranges (OTR). This work investigates NiTiCu SMAs as PCMs with high FOM and low OTR. A full-factorial design of experiments is used to examine 24 NiTiCu compositions. The compositions were fabricated using vacuum arc melting and their phase transformation and thermophysical properties were characterized using calorimetry, thermal diffusivity, and density measurements. The NiTiCu compositions spanned martensitic transformation temperatures between -22 and 84 °C and exhibited greater FOM (250–1050 106J2K−1s−1m−4), compared to traditional PCMs (typically <100 106J2K−1s−1m−4), with major benefits associated with higher density and higher thermal conductivity values. In addition, the NiTiCu compositions in this study show ultra-low OTR (12–20 °C) compared to NiTi and NiTiHf SMAs (>50 °C), enabling utility in narrow operating temperature windows. Thermal cycling was also performed revealing extreme stability of martensitic transformation with only 0.04 °C shift in transformation temperatures after 80 thermal cycles, which is the lowest reported to date in SMA literature.

Additive Manufacturing (AM) has quickly emerged as a promising technology to manufacture Shape Memory Alloy (SMA)-based components of complex geometries. 3D-printed High Temperature SMAs (HT-SMAs) components can enable applications that demand operating temperatures well beyond conventional NiTi SMAs. Here, a detailed printability assessment of NiTiHf HT-SMAs fabricated using laser powder bed fusion (LPBF) AM is conducted for the first time. Specifically, the regions associated with lack of fusion, keyholing, and balling regimes are quantitatively classified through an efficient printability assessment framework. Nearly porosity-free specimens are achieved from the predicted good printable region. The effects of key processing parameters (laser power, scanning speed, and hatch spacing) on the microstructure variation and phase transformation characteristics are studied systematically. A positive correlation is observed between the transformation temperatures and volumetric energy density (EV). Beyond a critical EV of 100 J/mm3, the transformation temperatures become insensitive to further increases in EV. At identical or similar energy density levels, the individual change of laser power, scanning speed, or hatch spacing alters the transformation behavior to a certain extent. It is hypothesized that to a large extent, this behavior is due to the effects that processing conditions have on the differential evaporation of Ni from the melt pool. A model connecting thermal histories, scanning strategy and chemistry changes is found to be consistent with this hypothesis. It is shown that the transformation temperatures in AM NiTiHf HT-SMAs can be varied over a range of more than 160 °C by controlling Ni evaporation through altering processing parameters.

Martensitic transformation temperatures and other transformation characteristics are extremely sensitive to composition and microstructural features in shape memory alloys (SMAs), particularly in well-known NiTi based SMAs. Because of this sensitivity, it is challenging to synthesize NiTi based SMAs with the same transformation characteristics and thermomechanical properties repeatedly; making qualification and certification of these materials difficult. The present study analyses variations in actuation fatigue properties of four batches of Ni50.3Ti29.7Hf20 (at.%) high temperature SMA (HTSMA), with similar fabrication methods, through microstructural observations, thermal and compositional studies, thermomechanical testing and tensile actuation fatigue experiments. Small differences in the Ni content and volume fraction of non-metallic inclusions of different batches are found to alter the transformation temperatures and actuation fatigue properties significantly. In general, it is observed that higher Ni content and volume fraction of non-metallic inclusions shorten the fatigue life. The results presented in this study draw attention to the difficulties associated with the fabrication of a target NiTiHf HTSMA composition with desired mechanical and shape memory properties, while also presenting a methodology to screen different batches of the alloy for superior actuation fatigue response using conventional microstructural, thermal and mechanical characterization.

Laser-powder bed fusion (L-PBF) additive manufacturing (AM) presents excellent potential to fabricate geometrically complex structures with tailored microstructures and compositions from nickel titanium shape memory alloys (NiTi SMAs). The effect of common L-PBF process parameters, such as laser power, scanning speed, and hatch spacing, have been reported in many literature studies. However, one important factor that has not been investigated is the laser scan strategy, or the path that the laser follows within each layer. This is a particularly important factor to investigate in the case of NiTi SMAs that tend to be more sensitive to thermal histories than other commercial AM materials. For example, even slight variations in thermal history might exhibit notable influence on transformation behavior due to composition changes resulting from differential evaporation of nickel. The current work presents a first investigation on such effects of 12 laser scan strategy on the fabrication outcome of additively manufactured Ni-rich NiTi SMAs. The extent of warping deformation and surface morphology of fabricated parts with different scan strategies were found to show notable differences. Some phase transformation variations among different scan strategies were also identified in as-fabricated and solution heat treated conditions, although these variations were not as pronounced as variations in warping due to residual stresses and surface morphology. This study guides the selection of scan strategies such that build failures due to excessive warping and poor surface morphology are minimized. It also provides additional flexibility in controlling mechanical properties and phase transformation behavior of this relatively difficult-to-process class of materials.

Laser powder bed fusion is a promising additive manufacturing technique for the fabrication of NiTi shape memory alloy parts with complex geometries that are otherwise difficult to fabricate through traditional processing methods. The technique is particularly attractive for the biomedical applications of NiTi shape memory alloys, such as stents, implants, and dental and surgical devices, where primarily the superelastic effect is exploited. However, few additively manufactured NiTi parts have been reported to exhibit superelasticity under tension in the as-printed condition, without a post-fabrication heat treatment, due to either persistent porosity formation or brittleness from oxidation during printing, or both. In this study, NiTi parts were fabricated using laser powder bed fusion and consistently exhibited room temperature tensile superelasticity up to 6% in the as-printed condition, almost twice the maximum reported value in the literature. This was achieved by eliminating porosity and cracks through the use of optimized processing parameters, carefully tailoring the evaporation of Ni from a Ni-rich NiTi powder feedstock, and controlling the printing chamber oxygen content. Crystallographic texture analysis demonstrated that the as-printed NiTi parts had a strong preferential texture for superelasticity, a factor that needs to be carefully considered when complex shaped parts are to be subjected to combined loadings. Transmission electron microscopy investigations revealed the presence of nano-sized oxide particles and Ni-rich precipitates in the as-printed parts, which play a role in the improved superelasticity by suppressing inelastic accommodation mechanisms for martensitic transformation.

Laser powder bed fusion (L-PBF) additive manufacturing (AM) is an effective method of fabricating nickel-titanium (NiTi) shape memory alloys (SMAs) with complex geometries, unique functional properties, and tailored material compositions. However, with the increase of Ni content in NiTi powder feedstock, the ability to produce high-quality parts is notably reduced due to the emergence of macroscopic defects such as warpage, elevated edge/corner, delamination, and excessive surface roughness. This study explores the printability of a nickel-rich NiTi powder, where printability refers to the ability to fabricate macro-defect-free parts. Specifically, single track experiments were first conducted to select key processing parameter settings for cubic specimen fabrication. Machine learning classification techniques were implemented to predict the printable space. The reliability of the predicted printable space was verified by further cubic specimens fabrication, and the relationship between processing parameters and potential macro-defect modes was investigated. Results indicated that laser power was critical to the printability of high Ni content NiTi powder. In the low laser power setting (P < 100 W), the printable space was relatively wider with delamination as the main macro-defect mode. In the sub-high laser power condition (100 W <= P <= 200 W), the printable space was narrowed to a low hatch spacing region with macro-defects of warpage, elevated edge/corner, and delamination happened at different scanning speeds and hatch spacing combinations. The rough surface defect emerged when further increasing the laser power (P > 200 W), leading to a further narrowed printable space.

One of the obstacles to the deployment of shape memory alloys (SMAs) in solid-state actuation is the low efficiency and functional instability due to the transformation thermal hysteresis and large temperature ranges during martensitic phase transformation. Numerous studies have been conducted in an effort to minimize the thermal hysteresis and transformation temperature range of SMAs through ternary and quaternary alloying of known binary alloy systems, such as NiTi, and considerable success has been achieved. However, and crucially, the alloys discovered so far have failed to maintain a narrow hysteresis under applied stress. In the present study, an AI-enabled materials discovery framework was successfully used to identify both SMA chemistries and the associated thermo-mechanical processing steps that result in narrow transformation hysteresis and transformation range under an applied stress. The major elements of the proposed workflow are described in detail and its materials-agnostic character makes it widely applicable to other alloy discovery challenges. Using this framework, and without relying on subsequent experimental exploratory analysis, an SMA composition, i.e. Ni32Ti47Cu21 (at. %), was predicted and confirmed to have the narrowest thermal hysteresis and transformation range under stress achieved thus far for a NiTi-based SMA. Furthermore, the alloy was shown to exhibit excellent cyclic stability and actuation strain. The methodology and the dataset introduced here can be extended to design novel SMAs with other target functions.

The actuation fatigue performance of a Ni-rich Ni50.3Ti29.7Zr20 (at.%) high temperature shape memory alloy (HTSMA) was evaluated and compared to previous results for Ni50.3Ti29.7Hf20 HTSMA. The shape memory properties of these alloys are known to improve significantly after proper aging heat treatments. Yet, their widespread implementation in high temperature applications requires a thorough characterization and a detailed understanding of their actuation fatigue performance. Consequently, actuation fatigue tests were performed by thermal cycling the NiTiZr alloy under constant loads from 200 to 500 MPa until failure. The results revealed that NiTiZr exhibits a shorter fatigue life with lower recoverable strain levels than a comparable NiTiHf alloy at all applied stress levels and the difference in fatigue life between the two alloys became more distinct with increasing stress. Building upon the extensive research on the microstructure, mechanical and functional behaviors of NiTiHf and NiTiZr HTSMAs during the last decade, this work is the first fundamental study that directly compares actuation fatigue behaviors of Ni-rich NiTiZr and NiTiHf alloys.

Laser Powder Bed Fusion (L-PBF) was utilized to fabricate fully dense, near-equiatomic (Ni50.1Ti49.9) and Ni-rich NiTi (Ni50.8Ti49.2) shape memory alloy (SMA) parts which exhibited tensile ductility up to 16%, shape memory strain of 6%, and tensile superelasticity up to 4%. Annealing heat treatments marginally improved the superelasticity of the as-fabricated Ni-rich NiTi parts due to the formation of a small volume fraction of Ni4Ti3 precipitates. The selection of optimum processing parameters that yielded fully dense parts was guided by a process optimization framework based on a computationally inexpensive analytical model used to predict the melt pool dimensions. The framework also included single-track experiments to validate the model predictions and a criterion for the maximum allowable hatch spacing to prevent the formation of lack of fusion porosity. This framework allowed for constructing L-PBF processing maps for the present NiTi SMAs and revealed that fully dense parts could be printed over a wide range of process parameters. By controlling the L-PBF process parameters, in particular laser power, laser scan speed, and volumetric energy density, in the processing space that result in fully dense parts, it was demonstrated systematically that the composition of the printed parts could be precisely changed by controlling the evaporation of Ni. The flexibility of parameter selection to print defect-free NiTi SMAs and composition control by preferential evaporation of Ni opens the possibility to print functional NiTi SMA parts or devices without post-processing.

Typically, the development of materials is intimately tied to the concurrent development of manufacturing technologies especially suitable to that material. In the case of metal additive manufacturing (AM), in contrast, the alloys typically used a feedstock were originally developed having other traditional manufacturing technologies in mind. Since metal AM processes involve fundamentally different physics, it is common to encounter many challenges when processing these materials such as high susceptibility to defects and microstructure inconsistencies. Recent research directions call for developing new materials and alloys specifically for AM. This poses a new and significant challenge: how can we determine the optimal processing recipes for an alloy not previously investigated. This is a typically time-consuming and expensive endeavor and, in this work, we propose an efficient framework to efficiently and effectively determine the processing parameter window of a given alloy considered as potential feedstock for AM. The framework integrates design of experiments, physics-based simulation, uncertainty analysis and fabrication and characterization in order to determine the bounding region in the manufacturing space resulting in near full density, defect-free parts. The proposed framework is developed aiming at maximizing its efficiency, accessibility and practicality. We validate the proposed framework and demonstrate its robustness using three model materials, two of which have not been previously reported.

In the present study, Ni95Nb5 (wt. %) alloy samples are additively manufactured using selective laser melting (SLM) as a surrogate for Ni-based superalloys. Near porosity-free samples are fabricated utilizing a simple analytical model to predict melt pool dimensions, guide process parameter selection, and determine the defect free printability map in the process parameter space. Ni95Nb5 mechanical testing specimens displayed consistent yield strengths (similar to 600 MPa) and ultimate tensile strengths (similar to 750 MPa) across a range of process parameters. These results show that with the proper selection of process parameters, SLM can produce parts with consistent mechanical properties in a wide process parameter space in simple alloying systems.

Motivated by the recent advancements demonstrating the effectiveness of NiTi shape memory alloys (SMAs) as high figure of merit (FOM) phase change materials (PCMs) for thermal management and storage, NiTiHf SMAs were explored as candidate solid-solid PCMs with high temperature capability. Differential scanning calorimetry and Archimedes' method were used to determine the transformation temperatures, thermal hysteresis, enthalpy of transformation, and density of several different NiTiHf SMAs with varying compositions. Ni50.3Ti29.7Hf20 (at. %) demonstrated a high transformation enthalpy of 32.5 J/g, a relatively low thermal hysteresis of 31°C and a thermal conductivity of 11.19 Wm−1K−1 in the austenite phase. In general, NiTiHf SMAs exhibited FOM values an order of magnitude higher than traditional PCMs and up to about 120 % higher than the FOM value measured in binary NiTi SMAs. The clear trends relating transformation temperatures, transformation enthalpy, and thermal hysteresis to composition presented here provide for tunability of NiTiHf SMAs to specific thermal energy storage applications through composition control. High FOM values combined with transformation temperatures surpassing 500°C allows NiTiHf alloys to populate previously empty regions of FOM vs. transformation temperature property space for high FOM PCMs.

This study reports the use of Additively Manufactured nitinol as a high-performance metallic solid-solid phase change material. Compared to standard phase change materials, which offer point solutions, it's shown here that latent heat, thermal conductivity, and transformation temperature can be tuned in additively manufactured nitinol by adjusting the chemistry, processing parameters, and heat treatment. Leveraging these results, a 28% reduction in peak temperature during a simulated transient electronic application is demonstrated. It's anticipated that these perennial results, combined with future optimization efforts, will encourage new phase change material development and architecture designs.

Shape memory alloys (SMAs) have been getting much attention by many researchers in a variety of application areas due to their unique properties of superelasticity (SE) and shape memory effect (SME). They have the ability to recover large inelastic deformations upon heating (SME) and stress removal (SE). In recent years, structural engineers have been dealing with these smart materials to incorporate into civil engineering applications such as rebar in the reinforcement of concrete structures, repairing, retrofitting, base isolation system, dampers for vibrational control, etc. To overcome and mitigate the possible seismic risk of the structure under consideration, understanding the material characteristics of SMAs under various loading conditions is one of the critical steps. In this study, the mechanical properties of two popular SE SMAs, i.e. copper-aluminum-manganese (Cu-Al-Mn) and nickel-titanium (Ni-Ti), were investigated in detail. Moreover, the mechanical properties of the conventional rebar steel were also identified for comparison purposes. Room temperature monotonic and incremental cyclic tests were applied on dog-bone shaped Steel, Cu-Al-Mn and Ni-Ti tensile coupon specimens the obtain and compare their mechanical characteristics. The results showed that Cu-Al-Mn and Ni-Ti materials exhibited a significant re-centering ability upon unloading with negligible and comparable residual deformations whereas the Steel experienced higher permanent plastic deformations with almost 3% recovery at the same amount of deformation. In addition, the decrease in the amount of dissipated energy for Cu-Al-Mn and Ni-Ti for consecutive cyclic motion is much less than conventional steel. Test results were also evaluated in terms of cyclic performance of materials, residual strain, recovery capacity, dissipated energy and equivalent viscous damping. Experimental outcomes highlighted the potential usage of SMAs in seismic applications and supply basis information for continued research.

The effects of constant load thermal cycles (training) on the thermomechanical behavior of nano-precipitation strengthened Ni50.3Ti29.7Hf20 (NiTiHf) and Ni50.3Ti29.7Zr20 (NiTiZr) high temperature shape memory alloys (HTSMAs) were compared. Thermomechanical properties were determined as a function of the number of training cycles, which consisted of up to 2000 isobaric thermal cycles at 300 MPa, between lower and upper cycle temperatures of 35 and 300 degrees C, respectively. In addition, the stability of the trained alloys was determined after exposure to thermal treatments at temperatures above the upper cycle training temperature. Training at 300 MPa significantly improved the actuation strain capability of the NiTiHf HTSMA at low stresses (i.e., 50 MPa) and resulted in a two-way shape memory strain (TWSMS) up to 1.9%, but essentially had no effect on the 300 MPa response. Training had less notable benefits in the case of the NiTiZr, producing negligible TWSMS, and resulting in a decrease in actuation strain capability at 300 MPa with repeated cycling. The benefits of training to the NiTiHf HTSMA were maintained after aging at 400 degrees C but were lost after exposure to 500 degrees C and above. Since training was not notably beneficial to the NiTiZr alloy and resulted in a loss in strain capability at 300 MPa, the high temperature annealing treatment actually recovered strain capability in the alloy under high stresses. The superior TWSM response of the NiTiHf HTSMA as compared to the NiTiZr, was attributed to the higher melting temperature, and thus the lower homologous operating temperature of the former, when both alloys were tested over the same temperature range.

Shape memory alloys (SMAs) have been utilized as an alternative to conventional materials for seismic retrofit applications in the last two decades. The effectiveness of SMAs to provide further improvement in seismic behavior of structures was demonstrated satisfactorily. Three 2/3-scaled, one-bay and one-storey substandard RC frames were constructed to represent the seismically vulnerable buildings with several deficiencies. The first RC frame was tested as a reference specimen under quasi-static reversed cyclic loading, which caused flexural plastic hinges at the column ends. Then, the rest of the two RC frames were upgraded with superelastic copper–aluminum–manganese (CuAlMn) alloy bars and conventional steel bars with the aim of enhancing seismic performance of substandard RC frames. The upgrading materials were attached to the RC frames through a retrofitting mechanism to provide tension-only retrofitting bars. Hence, the RC frame retrofitted by conventional steel bars was exposed to residual displacements after they yielded. The SMA-upgraded frame showed flag shaped hysteresis curve due to its superelastic behavior and caused considerable reduction in the residual displacement of RC frames.