Transformation In Shape Memory Alloys Research Articles

Ultra-low stress-hysteresis and huge superelasticity in NiMn-based shape memory microwire

Hysteresis related to first-order phase transformation in shape memory alloys, which is the macroscopic manifestation of energy dissipation, is detrimental to the precise control of actuation and causes structural and functional fatigue of components. It is of vital importance to explore high-performance shape memory alloys with low stress-hysteresis, large superelasticity, and wide temperature range operation in practical applications. Here, we have developed a Ni-Mn-Fe-In shape memory microwire, exhibiting an ultra-low stress-hysteresis and huge tensile superelasticity in a wide temperature range. The microwire shows a smooth surface and a single crystal structure (with ⟨001⟩A-oriented along the axial direction of microwire), and the microstructure of the microwire contains austenite matrix and sparsely distributed precipitates with an average size of 20–80 nm, all of which may be beneficial to obtain low hysteresis and large strains in the microwire. As a result, the microwire exhibits a minimum stress-hysteresis of as low as 8.5 MPa (with overall strain of 15.3%) and corresponding energy dissipation as low as 1.44 MJ/m3. The microwire always shows a low stress-hysteresis (less than 24 MPa) and low energy dissipation (less than 2.86 MJ/m3) above room temperature. The microwire shows a huge superelasticity with recoverable strains higher than 15% in the wide temperature range from 218 to 418 K. Together with the advantages of easy fabrication and no post-processing required, this microwire shows a tremendous potential for cyclic actuators and energy conversion devices under multi-field coupling.

Effect of short heat treatment on mechanical properties and shape memory properties of Cu–Al–Ni shape memory alloy

Abstract The transformation of shape-memory alloys to high-temperature shape-memory alloys can be achieved through either the addition of alloying elements or heat treatment. However, heat treatment is more effective in improving the properties of the alloys. This research paper explores the impact of annealing on the mechanical and shape memory properties of Cu–Al–Ni shape memory alloys. The alloys were first cast, homogenized, and then machined before being aged at temperatures of 250, 300, and 350°C, and finally air-cooled. The results showed an increase in transformation temperature and recovery strain, as well as shape memory effect, and a decrease in hardness. Moreover, there was an increase in yield stress and strain. In conclusion, aging was found to improve the shape memory properties and mechanical properties better than thermomechanical treatment and some alloying elements.

Thermomechanical response and elastocaloric effect of shape memory alloy wires

Refrigeration technologies based on the elastocaloric effect of shape memory alloys (SMAs) have attracted much interest in recent years. To seek for schemes that can improve the temperature span and efficiency of elastocaloric devices, this work explores more practical loading conditions (between adiabatic and isothermal) of SMAs. To account for the smoothness of the martensite phase transformation of SMAs, a general polynomial form of hardening-like function is adopted in the phenomenological multi-physics coupling framework. The modeling framework is further calibrated by measurements of the thermomechanical responses of pre-trained Ni–Ti wires. Due to the hardening-like function, the martensitic volume fraction cannot be explicitly expressed. Accordingly, a new numerical scheme is also presented in this work. Moreover, an empirical function of the maximum transformation strain is proposed based on the experimental observation, which improves the capability of the model to capture experimental data. This work aims to provide a paradigm from material characterization to theoretical modeling and numerical simulation, and then to elastocaloric cooling performance analysis of SMAs.

Microstructural mechanisms of hysteresis and transformation width in NiTi alloy from molecular dynamics simulations

Martensitic transformations in shape memory alloys are often accompanied by thermal hysteresis, and engineering this property is of prime scientific interest. The martensitic transformation can be characterized as thermoelastic, where the extent of the transformation is determined by a balance between thermodynamic driving force and stored elastic energy. Here we used molecular dynamics simulations of the NiTi alloy to explore hysteresis-inducing mechanisms and thermoelastic behavior by progressively increasing microstructural constraints from single crystals to bi-crystals to polycrystals. In defect-free single crystals, the austenite-martensite interface moves unimpeded with a high velocity. In bi-crystals, grain boundaries act as significant obstacles to the transformation and produce hysteresis by requiring additional nucleation events. In polycrystals, the transformation is further limited by the thermoelastic balance. The stored elastic energy can be converted to mechanisms of non-elastic strain accommodation, which also produce hysteresis. We further demonstrated that the thermoelastic behavior can be controlled by adjusting microstructural constraints.

Modeling the material behavior of heterogeneous materials considering a two‐scale FE–FFT‐based simulation framework

AbstractIn various engineering applications, components subjected to high mechanical or multi‐physical loads such as thermal, thermo‐mechanical, or electro‐thermal loads are predominantly made of metals or composites. These materials are characterized by polycrystalline or multi‐phase microstructures which determine the overall material response. However, since the microscopic material behavior is directly related to the distribution, size, and morphology of the individual grains or phase constituents, precise predictions of the macroscopic material response require simulations of the microstructural behavior. Hence, this work considers a two‐scale finite element (FE) and fast Fourier transform (FFT)‐based simulation framework, which is an efficient alternative to the classical method for the simulation of periodic unit cells. Assuming scale separation, the macroscopic and microscopic boundary value problems are first solved individually and subsequently linked by performing a scale transition in terms of averaging the macroscopic quantities over the corresponding local fields. While the macroscopic solution is computed by means of the finite element method, the microscopic boundary value problem, which is embedded as a periodic unit cell in each macroscopic integration point, is solved using an FFT‐based simulation method. In general, these microscopic simulations allow to model grain‐scale phenomena such as martensitic phase transformation or plastic deformation caused by dislocation glide which can be observed in polycrystalline materials. In this work, we present a two‐scale FE–FFT‐based model to capture the martensitic phase transformations in shape memory alloys. In order to demonstrate the applicability of the model, a numerical example is given.

Design and Evaluation of Smart Textile Actuator with Chain Structure.

Textiles composed of fibers can have their mechanical properties adjusted by changing the arrangement of the fibers, such as strength and flexibility. Particularly, in the case of smart textiles incorporating active materials, various deformations could be created based on fiber patterns that determine the directivity of active materials. In this study, we design a smart fiber-based textile actuator with a chain structure and evaluate its actuation characteristics. Smart fiber composed of shape memory alloy (SMA) generates deformation when the electric current is applied, causing the phase transformation of SMA. We fabricated the smart chain column and evaluated its actuating mechanism based on the size of the chain and the number of rows. In addition, a crochet textile actuator was designed using interlooping smart chains and developed into a soft gripper that can grab objects. With experimental verifications, this study provides an investigation of the relationship between the chain actuator's deformation, actuating force, actuator temperature, and strain. The results of this study are expected to be relevant to textile applications, wearable devices, and other technical fields that require coordination with the human body. Additionally, it is expected that it can be utilized to configure a system capable of flexible operation by combining rigid elements such as batteries and sensors with textiles.

Extremely stable stress-induced martensitic transformation at the nanoscale during superelastic cycling of Ni51Mn28Ga21 shape memory alloy

Superelasticity from the stress-induced martensitic transformation in shape memory alloys (SMA) and its study at the nanoscale has a fundamental and technological relevance. However, strong size effects at the micro and nanoscale have been reported in several shape memory alloys, showing, in some cases, higher critical stress and damping, in comparison with the same alloys at the macroscopic scale. In the present work, the stress-induced martensitic transformation in Ni51Mn28Ga21 (at%) SMA is studied, at zero magnetic field, running superelastic nano-compression tests on micropillars of 1 μm in diameter, milled by focused ion beam on [001] oriented single crystals. Here, we demonstrate that such micropillars exhibit a fully reversible stress-induced martensitic transformation during a nano-compression cycle, with an extremely stable hysteretic superelastic behavior. In addition, long-term superelastic nano-compression cycling, above five thousand tests, was performed on these micropillars, revealing outstanding stability of the superelastic behavior at the nanoscale. Finally, these Ni51Mn28Ga21 micropillars showed ultra-high strength, up to 1.4 GPa, while exhibiting a good reproducible superelastic behavior, and evidencing a noticeable size effect on the stress-induced martensite strength at the micro/nanoscale. This size-effect should mitigate the degradation during martensite nucleation and growing, being at the origin of the good superelastic cycling behavior. The present results open the door to further studies and new potential applications of this family of magnetic SMA in small-scale devices.

A data-driven approach for plasticity using history surrogates: Theory and application in the context of truss structures

Data-driven methods and algorithms show immense potential for future advancements in the modeling and simulation of complex mechanical systems. However, in order to actually exploit this potential, the methods must be extended to consider inelastic and path-dependent material behavior—a step that appears more complex than in conventional material modeling, where this can be achieved with the help of additional, mostly internal, history variables. The effect of such history variables must thereby be transferred to the data-driven framework. This is achieved in the present paper by defining an appropriate history surrogate as well as a so-called propagator. The history surrogate contains tangible quantities that represent the backward path–uniquely in the ideal case–and enrich the conventional database entries of matching pairs of stresses and strains. The propagator defines the update of the history surrogate from one discrete time step to another. As a major advantage, the newly developed method retains the structures of the data-driven algorithm for elastic material behavior and therefore allows a rather straightforward extension of preexisting program codes. Thus, for instance, heterogeneous problems in which purely elastic and elastoplastic materials are present can be solved without further significant coding effort. Furthermore, several material classes covering different inelastic phenomena such as plasticity with isotropic and kinematic hardening as well as phase transformations in shape memory alloys can be considered in our framework.

Analysis and design of bistable and thermally reversible metamaterials inspired by shape-memory alloys

In this work, we study lattice structures that exhibit a bistable behavior, i. e., they can snap from one stable state to another, and are also completely reversible, capable of reverting back to its original state through a heat treatment. We design this behavior by constructing lattice structures using networks of nonlinear springs that display tension–compression asymmetry and have different thermal expansion coefficients. The mismatch in the thermal expansion coefficients induces residual stresses in the springs which results in the lattice structure exhibiting bistability at low temperatures and monostability at high temperatures. This behavior mimics the crystallographic phase transformations of shape memory alloys, but here artificially introduced in a structural lattice. By analyzing a representative unit cell, we quantify the effect that the stiffness and the thermal expansion coefficient of the springs have on the stability of the structural lattice. In addition, for simple 2D lattices, using the concept of universal unfoldings of singularity theory, we perform a perturbation analysis to identify the key variables of the structure where controlling defects is important, as they lead to drastic changes in the bifurcation behavior of the lattice. Finally, we verify numerically our analytical predictions in both 2D and 3D simulations using continuation techniques. The examples proposed confirm that the bistable and reversible features of the unit cell carry on to the macroscale, opening the route for the design of lattice structures for energy absorption applications that can heal with a heat treatment.

Isothermal martensitic transformation in Ti-Ni-Cu-Co shape memory alloy: Insight from a thermally activated kinetic model

Recently the isothermal martensitic transformation in shape memory alloys (SMAs) has been reported in many literatures, and several models have been proposed to interpret the isothermal and athermal kinetics. However, the underlying mechanisms remain inadequately understood. In this work, the isothermal transformation from B2 to B19 is confirmed in Ti-Ni-Cu-Co melt-spun ribbons at the temperature range between Ms and Mf. It reaches a saturation point at every isothermal temperature Tiso, and the saturation points correspond to the f−T curve at the cooling rate of 0.5 K/min. The experimental results indicate that the isothermal accumulation of martensite is a relaxation process from the transient state to the thermoelastic balance one. A thermally activated kinetic model is developed in this study to characterize the isothermal and athermal kinetics. The model is able to estimate the evolution of martensite volume fraction under any temperature path T(t) and it agrees with the experimental results well. According to the model, the effects of elastic energy, nucleation density, and activation energy on the kinetics are investigated. Among those, a small nucleation density ni as well as a large activation energy Q will result in a significant isothermal transition. In this work, the slighter isothermal effects originate from the higher value of ni. As for the non-stoichiometric SMAs, the higher value of Q is responsible for the accumulation of martensite at the isothermal process. Accordingly, the present work provides a novel view from a kinetic model to understand the isothermal martensitic transformation in SMAs.

Actuation response of typical biased shape memory alloy wire under variable electric heating rates: Experimental investigation and modeling

Electric heating is commonly used to induce the inverse martensitic transformation in shape memory alloy (SMA) wire actuators. Different actuation responses can be achieved when adjusting the heating currents. In this study, typical biased NiTi SMA wire actuators were tested under the heating currents of 1.5 A, 3 A, 4 A, and 5 A. It was found that SMA wire actuators under three typical biases (dead weight, linear spring, dead weight & linear spring) behaved differently as the heating current increased. Moreover, under dead weight bias and mixed bias, high heating currents tended to cause dynamic responses during actuation. The maximum inertia load induced by dynamic responses was 2.65 times as much as the static load. In contrast, the actuation response under linear spring bias was relatively steady. A model based on the SMA constitutive equation and the dynamic equation was also established, which was capable of simulating the dynamic actuation responses of SMA wire actuators under high electric heating rates.

Interface propagation and energy dissipation in Shape Memory Alloys

Recent experiments showed that the macroscopic interface propagation of the martensitic phase transformation in Shape Memory Alloys (SMAs) includes unstable microstructure evolution in the macroscopic diffuse interfacial zone (with nucleation, branching, merging and/or annihilation of numerous small domains), releasing the stored energy of the diffuse interface. In this paper, with a one-dimensional Cahn-Hilliard model, a quantitative relation between the energy dissipation and the interfacial properties (interface energy and interface thickness) is revealed: the energy dissipation is governed by the energy barrier caused by the diffuse interface. The relation is verifiable with existing experiments. It can also help understand the interfacial effect on the material's fatigue failure and provide a hint to search for low-hysteresis SMAs: weak first-order phase transformation implies weak energy dissipation (low hysteresis).

Ordering-induced Elinvar effect over a wide temperature range in a spinodal decomposition titanium alloy

Temperature-independent elastic modulus is termed as Elinvar effect, which is available by tuning the continuous spin transition of ferromagnetic alloys via composition optimization and the first-order martensitic transformation of shape memory alloys via plastic deformation. However, these reversible mechanisms are restricted generally in a narrow temperature range of less than 300 K. Here reports, by tuning a spinodal decomposition in a Ti-Nb-based titanium alloy via aging treatment, both the Elinvar effect in a wide temperature range of about 500 K and a high strength-to-modulus ratio of about 1.5% can be obtained by a continuous and reversible crystal ordering mechanism. The results demonstrate that the alloy aged at 723 K for 4 h has a nanoscale plate-like modulated β+α" two-phase microstructure and its elastic modulus keeps almost constant from 100 to 600 K. Synchrotron and in-situ X-ray diffraction measurements reveal that the crystal ordering parameter of the α" phase increases linearly with temperature from 0.88 at 133 K to 0.97 at 523 K but its volume fraction keeps a constant of about 33.8%. This suggests that the continuous ordering of the α" phase toward the high modulus α phase induces a positive modulus-temperature relation to balance the negative relation of the elastically stable β phase. The aged alloy exhibits a high yield strength of 1200 MPa, good ductility of 16% and a high elastic admissible strain of 1.5%. Our results provide a novel strategy to extend the Elinvar temperature range and enhance the strength by tuning the crystal ordering of decomposition alloys.

Indentation-induced martensitic transformation in SMAs: Insights from phase-field simulations

Direct experimental characterization of indentation-induced martensitic microstructures in pseudoelastic shape memory alloys (SMAs) is not possible, and thus there is a lack of evidence and understanding regarding the microstructure pattern and related features. To fill this gap, in this work we employ the phase-field method to provide a detailed and systematic analysis of martensitic phase transformation during nanoindentation. A recently-developed finite-element-based computational model is used for this purpose, and a campaign of large-scale 3D simulations is carried out. First, the orientation-dependent indentation response in CuAlNi (a widely studied SMA) is examined. A detailed investigation of the predicted microstructures reveals several interesting features, some of them are consistent with theoretical predictions and some can be (to some extent) justified by experiments other than micro/nanoindentation. The results also highlight the key role of finite-deformation effects and elastic anisotropy of the phases on the model predictions. Next, a detailed study of indentation-induced martensitic transformation in NiTiPd (a potential low-hysteresis SMA) with varying Pd content is carried out. In terms of hysteresis, the results demonstrate the prevailing effect of the transformation volume change over phase compatibility in the conditions imposed by nanoindentation and emphasize on the dominant role of the interfacial energy at small scales. Results of such scope have not been reported so far.

Phase-field method based simulation of martensitic transformation in porous alloys

Porous materials, characterized by the presence of interconnected pores, exhibit the properties different from their bulk counterparts. One of properties of interest is that the pores can influence the martensitic transformation in shape memory alloys (SMAs), which directly affects the material's shape memory effect and mechanical properties. The martensitic transformation is accompanied by the formation of different martensitic variants, which determine the overall morphology, distribution, and self-accommodation effect of the transformed regions. Previous experimental studies have shown that the presence of pores, particularly at the metal-air interface, can significantly affect the martensitic variant structure, leading to its thinning. This thinning effect has been found to be able to improve the damping performance of the alloy. Experimental observations have indicated that no relief of martensitic variants was found around the metal-air interface, but non-transformed regions were observed. These observations suggest that the metal-air interface in porous materials is not a free surface and plays a crucial role in influencing the martensitic transformation. To further investigate the effect of martensitic variant self-accommodation on different constrained interfaces in porous materials, a three-dimensional phase-field model based on the time dependent Ginzburg-Landau (TDGL) function is proposed in this study. The phase-field model can give a comprehensive understanding of the evolution of martensitic variants and their interaction with the constrained interfaces. Remarkably, the simulation results accord well with the experimental findings, demonstrating the presence of fine martensitic variants near the metal-air interface. The simulations under different interface constraint conditions reveal that increasing the specific surface area of porous materials is an effective strategy to obtain a more refined martensitic variant structure. The system’s total energy is minimized by reducing the strain energy, which leads to the formation of a greater number of fine martensitic variants. This finding suggests that controlling the specific surface area of porous materials can be a promising approach to tailoring the mechanical properties of SMAs for specific applications. In conclusion, the presence of metal-air interface in porous material significantly influences the evolution of the martensitic transformation in SMA. Experimental observations show that the introduction of pore can modify the martensitic variant structure, resulting in improved damping performance. The proposed phase-field model successfully captures the behavior of martensitic variants near constrained interface. The simulation results emphasize the importance of specific surface area in obtaining fine martensitic variant structures. These findings contribute to a more in-depth understanding of the role of porous materials in shaping the properties of SMAs and provide a valuable insight into their design and application in various fields.

Experimental and theoretical validation of the solid-state heat storage device using the latent heat of martensitic transformation in shape memory alloy

Experimental and theoretical validation of the solid-state heat storage device using the latent heat of martensitic transformation in shape memory alloy

Effect of Ultrasound on the Austenite Transformation of Shape Memory Alloys

Effect of Ultrasound on the Austenite Transformation of Shape Memory Alloys

Numerical study of a double-effect elastocaloric cooling system powered by low-grade heat

• A double-effect heat-driven elastocaloric cooling cycle was proposed. • The double-effect eC cycle can harvest low-grade heat at 120 to 160 °C. • Driving temperature difference is used to design the transition temperature of SMAs. • COP of the double-effect eC cycle is three times better than single-effect eC cycle. Elastocaloric cooling technology is a novel solid-state cooling technology based on the latent heat associated with martensitic phase transformation in shape-memory alloys. Heat-driven elastocaloric cooling cycle could harvest low-grade thermal energy other than consuming electric power, and was proposed as a new direction in this field. To improve the heat-to-cooling efficiency of heat-driven elastocaloric cooling systems, a double-effect elastocaloric cooling cycle with two beds of actuator shape-memory alloys and two beds of refrigerant super-elastic alloys is proposed in this study. The double-effect cycle utilizes the input heat two times and thus provides improved efficiency. Numerical simulations are carried out to study the characteristics of the phase transformation in both the actuators and refrigerants. The impact of phase transition temperatures of the actuator alloys, the heat source temperature, and the operating parameters on the phase transformation and cooling performance of the system is investigated. If the phase transition temperatures are properly designed, the double-effect heat-driven elastocaloric cooling system is three times more efficient than the baseline single-effect heat-driven elastocaloric cooling system.

Molecular dynamics simulations of austenite-martensite interface migration in NiTi alloy

The mechanism of austenite-martensite interface migration is a key component in understanding the phase transformations in shape memory alloys. It is also intimately tied to their observed hysteresis. Molecular dynamics simulations offer a unique capability to study phase transformations in detail, however, their associated timescales prevent the observation of interface formation via nucleation and growth near the transformation temperature. To address this challenge, we present a simulation methodology in which steady-state austenite-martensite interfaces are allowed to form close to equilibrium. The resulting structures contain well-defined interfaces which can be perturbed from equilibrium to study their migration. In NiTi specifically, the austenite-martensite interfaces are semicoherent, made up of terrace planes separated by structural disconnections. The disconnections advance via kink pairs and provide an atomic-scale mechanism for interface migration. The methodology and results presented here provide a foundation toward further leveraging molecular dynamics simulations to better understand how the atomic-scale structure of austenite-martensite interfaces impacts macroscopic properties such as hysteresis in shape memory alloys.

Asymmetric Airfoil Morphing via Deep Reinforcement Learning.

Morphing aircraft are capable of modifying their geometry configurations according to different flight conditions to improve their performance, such as by increasing the lift-to-drag ratio or reducing their fuel consumption. In this article, we focus on the airfoil morphing of wings and propose a novel morphing control method for an asymmetric deformable airfoil based on deep reinforcement learning approaches. Firstly, we develop an asymmetric airfoil shaped using piece-wise Bézier curves and modeled by shape memory alloys. Resistive heating is adopted to actuate the shape memory alloys and realize the airfoil morphing. With regard to the hysteresis characteristics exhibited in the phase transformation of shape memory alloys, we construct a second-order Markov decision process for the morphing procedure to formulate a reinforcement learning environment with hysteresis properties explicitly considered. Subsequently, we learn the morphing policy based on deep reinforcement learning techniques where the accurate information of the system model is unavailable. Lastly, we conduct simulations to demonstrate the benefits brought by our learning implementations and validate the morphing performance of the proposed method. The simulation results show that the proposed method provides an average 29.8% performance improvement over traditional methods.