Shape Memory Alloys in Automotive Applications

Recent Advances in 4D-Printed Shape Memory Actuators

4D printing, which combines the design freedom of 3D printing with the responsiveness of smart materials, is revolutionizing the creation of active structures. These structures can change shape in response to external stimuli, paving the way for advancements in robotics, biomedicine, and beyond. However, a comprehensive review article highlighting recent advancements in 4D printed shape memory actuators (SMAAs) is lacking. This review explores the exciting potential of 4D printing for intelligent SMAAs. It examines the concept of shape memory and the materials used, like shape-memory polymers (SMPs), shape-memory alloys (SMAs), and shape-memory polymer composites (SMPCs). It then dives into compatible 3D printing techniques and design principles for achieving programmed shape changes. Different categories of 4D printed SMAAs are explored, showcasing their potential applications in diverse fields. The review concludes by discussing challenges and future directions, emphasizing the massive potential of 4D printing for creating the next generation of actuators, making it a valuable resource for researchers in the field.

Surface Treatment Strategies and Their Impact on the Material Behavior and Interfacial Adhesion Strength of Shape Memory Alloy NiTi Wire Integrated in Glass Fiber-Reinforced Polymer Laminate Structures

Over the past few decades, there has been a growing trend in designing multifunctional materials and integrating various functions into a single component structure without defects. This research addresses the contemporary demand for integrating multiple functions seamlessly into thermoplastic laminate structures. Focusing on NiTi-based shape memory alloys (SMAs), renowned for their potential in introducing functionalities like strain measurement and shape change, this study explores diverse surface treatments for SMA wires. Techniques such as thermal oxidation, plasma treatment, chemical activation, silanization, and adhesion promoter coatings are investigated. The integration of NiTi SMA into Glass Fiber-Reinforced Polymer (GFRP) laminates is pursued to enable multifunctional properties. The primary objective is to evaluate the influence of these surface treatments on surface characteristics, including roughness, phase changes, and mechanical properties. Microstructural, analytical, and in situ mechanical characterizations are conducted on both raw and treated SMA wires. The subsequent incorporation of SMA wires after characterization into GFRP laminates, utilizing hot-press technology, allows for the determination of interfacial adhesion strength through pull-out tensile tests.

Current Trends in Metallic Materials for Body Panels and Structural Members Used in the Automotive Industry

The development of lightweight and durable materials for car body panels and load-bearing elements in the automotive industry results from the constant desire to reduce fuel consumption without reducing vehicle performance. The investigations mainly concern the use of these alloys in the automotive industry, which is characterised by mass production series. Increasing the share of lightweight metals in the entire structure is part of the effort to reduce fuel consumption and carbon dioxide emissions into the atmosphere. Taking into account environmental sustainability aspects, metal sheets are easier to recycle than composite materials. At the same time, the last decade has seen an increase in work related to the plastic forming of sheets made of non-ferrous metal alloys. This article provides an up-to-date systematic overview of the basic applications of metallic materials in the automotive industry. The article focuses on the four largest groups of metallic materials: steels, aluminium alloys, titanium alloys, and magnesium alloys. The work draws attention to the limitations in the development of individual material groups and potential development trends of materials used for car body panels and other structural components.

Computational Modeling and Parametric Analysis of SMA Hybrid Composite Plates under Thermal Environment

This paper presents a coupled thermoelastic finite element formulation for static and dynamic analysis of composite laminated plates with embedded active shape memory alloy (SMA) wires, which accounts for both the phase transformation and the nonlinearity effects of SMA wires. The equations of motion are obtained by using Hamilton's principle and first-order shear deformation theory (FSDT). Furthermore, based on Brinson's one-dimensional phase transformation constitutive law, a novel coupled thermoelastic finite element model that enables analysis of the SMA hybrid composite (SMAHC) plate is developed. The accuracy and efficiency of the developed computational model for analysis of SMAHC plates are reinforced by comparing theoretical predictions with data available from the literature. The results of the numerical examples also show the ability of the proposed model to predict the thermal-mechanical behavior of SMAHC plates in accordance with SMA's hysteresis behavior. In addition, based on the proposed model, the influence of temperature as well as SMA volume fraction, pre-strain value, boundary condition and layup sequence on the static bending and free vibration behavior of the SMAHC plates is investigated in detail. The results of parametric analysis show that the variations of both static deflection and natural frequency of the SMAHC plate over temperature exhibit a nonmonotonic behavior.

Evolution of Structure and Properties of Nickel-Enriched NiTi Shape Memory Alloy Subjected to Bi-Axial Deformation

The effect of a promising method of performing a thermomechanical treatment which provides the nanocrystalline structure formation in bulk NiTi shape memory alloy samples and a corresponding improvement to their properties was studied in the present work. The bi-axial severe plastic deformation of Ti-50.7at.%Ni alloy was carried out on the MaxStrain module of the Gleeble system at 350 and 330 °C with accumulated true strains of e = 6.6-9.5. The obtained structure and its mechanical and functional properties and martensitic transformations were studied using DSC, X-ray diffractometry, and TEM. A nanocrystalline structure with a grain/subgrain size of below 80 nm was formed in bulk nickel-enriched NiTi alloy after the MaxStrain deformation at 330 °C with e = 9.5. The application of MaxStrain leads to the formation of a nanocrystalline structure that is characterized by the appearance of a nano-sized grains and subgrains with equiaxed and elongated shapes and a high free dislocation density. After the MaxStrain deformation at 330 °C with e = 9.5 was performed, the completely nanocrystalline structure with the grain/subgrain size of below 80 nm was formed in bulk nickel-enriched NiTi alloy for the first time. The resulting structure provides a total recoverable strain of 12%, which exceeds the highest values that have been reported for bulk nickel-enriched NiTi samples.

Microwave versus Conventional Sintering of NiTi Alloys Processed by Mechanical Alloying

The present study shows a comparison between two sintering processes, microwave and conventional sintering, for the manufacture of NiTi porous specimens starting from powder mixtures of nickel and titanium hydrogenation-dehydrogenation (HDH) milled by mechanical alloying for a short time (25 min). The samples were sintered at 850 °C for 15 min and 120 min, respectively. Both samples exhibited porosity, and the pore size results are within the range of the human bone. The NiTi intermetallic compound (B2, R-phase, and B19') was detected in both sintered samples through X-ray diffraction (XRD) and electron backscattering diffraction (EBSD) on scanning electron microscopic (SEM). Two-step phase transformation occurred in both sintering processes with cooling and heating, the latter occurring with an overlap of the peaks, according to the differential scanning calorimetry (DSC) results. From scanning electron microscopy/electron backscatter diffraction, the R-phase and B2/B19' were detected in microwave and conventional sintering, respectively. The instrumented ultramicrohardness results show the highest elastic work values for the conventionally sintered sample. It was observed throughout this investigation that using mechanical alloying (MA) powders enabled, in both sintering processes, good results, such as intermetallic formation and densification in the range for biomedical applications.

Review of Neural Network Modeling of Shape Memory Alloys

Shape memory materials are smart materials that stand out because of several remarkable properties, including their shape memory effect. Shape memory alloys (SMAs) are largely used members of this family and have been innovatively employed in various fields, such as sensors, actuators, robotics, aerospace, civil engineering, and medicine. Many conventional, unconventional, experimental, and numerical methods have been used to study the properties of SMAs, their models, and their different applications. These materials exhibit nonlinear behavior. This fact complicates the use of traditional methods, such as the finite element method, and increases the computing time necessary to adequately model their different possible shapes and usages. Therefore, a promising solution is to develop new methodological approaches based on artificial intelligence (AI) that aims at efficient computation time and accurate results. AI has recently demonstrated some success in efficiently modeling SMA features with machine- and deep-learning methods. Notably, artificial neural networks (ANNs), a subsection of deep learning, have been applied to characterize SMAs. The present review highlights the importance of AI in SMA modeling and introduces the deep connection between ANNs and SMAs in the medical, robotic, engineering, and automation fields. After summarizing the general characteristics of ANNs and SMAs, we analyze various ANN types used for modeling the properties of SMAs according to their shapes, e.g., a wire as an actuator, a wire with a spring bias, wire systems, magnetic and porous materials, bars and rings, and reinforced concrete beams. The description focuses on the techniques used for NN architectures and learning.

Shape Memory Alloy-Polymer Composites: Static and Fatigue Pullout Strength under Thermo-Mechanical Loading

This work was carried out within the context of an R&D project on morphable polymer matrix composites (PMC), actuated by shape memory alloys (SMA), to be used for active aerodynamic systems in automotives. Critical issues for SMA–polymer integration are analyzed that are mostly related to the limited strength of metal–polymer interfaces. To this aim, materials with suitable thermo-mechanical properties were first selected to avoid premature activation of SMA elements during polymer setting as well as to avoid polymer damage during thermal activation of SMAs. Nonstandard samples were manufactured for both static and fatigue pullout tests under thermo-mechanical loading, which are made of SMA wires embedded in cylindrical resin blocks. Fully coupled thermo-mechanical simulations, including a special constitutive model for SMAs, were also carried out to analyze the stress and temperature distribution in the SMA–polymer samples as obtained from the application of both mechanical loads and thermal activation of the SMA wires. The results highlighted the severe effects of SMA thermal activation on adhesion strength due to the large recovery forces and to the temperature increase at the metal–polymer interface. Samples exhibit a nominal pullout stress of around 940 MPa under static mechanical load, and a marked reduction to 280 MPa was captured under simultaneous application of thermal and mechanical loads. Furthermore, fatigue run-out of 5000 cycles was achieved, under the combination of thermal activation and mechanical loads, at a nominal stress of around 200 MPa. These results represent the main design limitations of SMA/PMC systems in terms of maximum allowable stresses during both static and cyclic actuation.

Mechanical and Microstructural Characterization of Ultrasonic Welded NiTiCu Shape Memory Alloy Wires to Silver-Coated Copper Ferrules

The aim of this study was to investigate the mechanical behavior, and the microstructure of NiTiCu shape memory alloy wires joined with silver-coated copper ferrules via ultrasonic spot welding. Therefore, the electrical resistance was measured during tensile testing, and the joints were analyzed by scanning electron microscopy. Energy-dispersive X-ray spectroscopy has determined the compounds of the developed welding zones. Furthermore, the influence of the ultrasonic welding on the transition temperatures of the NiTiCu wires was examined via differential scanning calorimetry. Tensile tests have shown that the ultimate tensile strengths of the joints reached almost 100% of that of the base material. An additional heat treatment rebuilt the typical shape memory alloy behavior after the ultrasonic welding process detwinned the martensitic wires. In addition, the B19′ structure of the welding zone and the ultrasonic spot-welding process did not affect the transition temperatures of the shape memory alloy.

Vision based supervised restricted Boltzmann machine helps to actuate novel shape memory alloy accurately

Extraordinary shape recovery capabilities of shape memory alloys (SMAs) have made them a crucial building block for the development of next-generation soft robotic systems and associated cognitive robotic controllers. In this study we desired to determine whether combining video data analysis techniques with machine learning techniques could develop a computer vision based predictive system to accurately predict force generated by the movement of a SMA body that is capable of a multi-point actuation performance. We identified that rapid video capture of the bending movements of a SMA body while undergoing external electrical excitements and adapting that characterisation using computer vision approach into a machine learning model, can accurately predict the amount of actuation force generated by the body. This is a fundamental area for achieving a superior control of the actuation of SMA bodies. We demonstrate that a supervised machine learning framework trained with Restricted Boltzmann Machine (RBM) inspired features extracted from 45,000 digital thermal infrared video frames captured during excitement of various SMA shapes, is capable to estimate and predict force and stress with 93% global accuracy with very low false negatives and high level of predictive generalisation.

A Review of SMA-Based Actuators for Bidirectional Rotational Motion: Application to Origami Robots

Shape memory alloys (SMAs) are a group of metallic alloys capable of sustaining large inelastic strains that can be recovered when subjected to a specific process between two distinct phases. Regarding their unique and outstanding properties, SMAs have drawn considerable attention in various domains and recently became appropriate candidates for origami robots, that require bi-directional rotational motion actuation with limited operational space. However, longitudinal motion-driven actuators are frequently investigated and commonly mentioned, whereas studies in SMA-based rotational motion actuation is still very limited in the literature. This work provides a review of different research efforts related to SMA-based actuators for bi-directional rotational motion (BRM), thus provides a survey and classification of current approaches and design tools that can be applied to origami robots in order to achieve shape-changing. For this purpose, analytical tools for description of actuator behaviour are presented, followed by characterisation and performance prediction. Afterward, the actuators’ design methods, sensing, and controlling strategies are discussed. Finally, open challenges are discussed.

Photoluminescent biocomposite films of chitosan based on styrylbenzothiazolium-g-cellulose nanocrystal for anti-counterfeiting applications

In the present investigation, novel photoluminescent and transparent biocomposite films based on chitosan reinforced with styrylbenzothiazolium-g-cellulose nanocrystal for anti-counterfeiting applications were successfully prepared by casting solvent. Three novel styrylbenzothiazolium derivatives were synthesized by Knoevenagel condensation and characterized by FTIR, ¹H, ¹³C NMR and photoluminescence analysis. These photochromic compounds have been used to functionalize cellulose nanocrystal and the resulting fluorescent photonic materials were characterized by FTIR, ¹³C-CP/MAS NMR as well as photoluminescent analysis to confirm the successful grafting. It can be concluded that the addition of 5 wt% of fluorescent modified CNC to chitosan matrix increase the photoluminescent properties as well as improved the mechanical properties of the Cs/CNC-dye biocomposite films. These photoluminescent biocomposite film hold promising applicative value in anti-counterfeiting material in large-scale.

Analysis of One-Dimensional Ivshin-Pence Shape Memory Alloy Constitutive Model for Sensitivity and Uncertainty

Shape memory alloys (SMAs) are classified as smart materials due to their capacity to display shape memory effect and pseudoelasticity with changing temperature and loading conditions. The thermomechanical behavior of SMAs has been simulated by several constitutive models that adopted microscopic thermodynamic or macroscopic phenomenological approaches. The Ivshin–Pence model is one of the most popular SMA macroscopic phenomenological constitutive models. The construction of the model requires involvement of parameters that possess inherent uncertainty. Under varying operating temperatures and loading conditions, the uncertainty in these parameters propagates and, therefore, affects the predictive power of the model. The propagation of uncertainty while using this model in real-life applications can result in performance discrepancies or failure at extreme conditions. In this study, we employed a probabilistic approach to perform the sensitivity and uncertainty analysis of the Ivshin–Pence model. Sobol and extended Fourier Amplitude Sensitivity Testing (eFAST) methods were used to perform the sensitivity analysis for simulated isothermal loading/unloading at various operating temperatures. It is evident that the model’s prediction of the SMA stress–strain curves varies due to the change in operating temperature and loading condition. The average and stress-dependent sensitivity indices present the most influential parameters at several temperatures.

Application of Virtual Reality for Learning the Material Properties of Shape Memory Alloys

A shape memory alloy (SMA) is an alloy which can eliminate deformation at lower temperatures and restore its original shape upon heating. SMAs have been receiving considerable attention in the research field of materials science, and their applications include robotics, automotive, aerospace, and biomedical industries. Observing the SMA’s shaping and restoration processes is important for understanding its working principles and applications. However, the transformation of its crystal structure with temperature can only be seen using special equipment, such as a transmission electron microscope (TEM), which is an expensive apparatus and the operation requires professional skills. In this study, a teaching module is designed using virtual reality (VR) technology and research results of an SMA to show its shape memory properties, shaping and restoration processes, as well as the real-life applications in an immersive and interactive way. A teaching experiment has been conducted to analyze students’ learning effectiveness using the teaching module (the experimental group) compared with that of using real SMA materials as the teaching aids (the control group). Two classes of students in the Department of Materials Science (one as the experimental group and the other as the control group) were selected as the samples by convenience sampling from a university in North Taiwan. The experimental group contained 52 students and the control group contained 70 students. A nonequivalent pretest-posttest design was adopted to explore whether the two groups had a significant difference in learning effectiveness. The experimental results reveal that the teaching module can improve the learning effectiveness significantly (p = 0.001), and the questionnaire results also show that a majority of the students had positive attitudes about the teaching module. They believed that it could increase their learning motivation and help them understand the properties and applications of the SMA.

Car Soundproof Improvement through an SMA Adaptive System

The work at hand focuses on an adaptive system aimed at improving the soundproof performance of car door seals at specific regimes (cruise), without interfering with the conventional opening and closing operations. The idea addresses the necessity of increasing seal effectiveness, jeopardized by aerodynamic actions that strengthen as the speed increases, generating a growing pressure difference between the internal and the external field in the direction of opening the door, and then deteriorating the acoustic insulation. An original expansion mechanism driven by a shape memory alloy (SMA) wire was integrated within the seal cavity to reduce that effect. The smart material was activated (heated) by using the Joule effect; its compactness contributed to the realization of a highly-integrable and modular system (expanding cells). In this paper, the system development process is described together with the verification and validation activity, aimed at proving the functionality of the realized device. Starting from industrial requirements, a suitable solution was identified by considering the basic phenomenon principle and the allowable design parameters. The envisaged system was designed and its executive digital mock-up (CAD, computer-aided design) was released. Prototyping and laboratory tests showed the reliability of the developed numerical models and validated the associated predictions. Finally, the system was integrated within the reference car. To demonstrate the insulation effect, the experimental campaign was carried out in an anechoic room, achieving significant results on the concept value.