Smart materials in cardiovascular implants: Shape memory alloys and shape memory polymers

2020 ◽  
Author(s):  
Heather Holman ◽  
Minoo Naozer Kavarana ◽  
Taufiek Konrad Rajab
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Shape Memory Polymers ◽  
Cardiovascular Implants

scholarly journals Biosmart Materials: Breaking New Ground in Dentistry

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Vijetha Badami ◽  
Bharat Ahuja
Keyword(s):  
Clinical Outcome ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Material Science ◽  
Piezoelectric Materials ◽  
Shape Memory Polymers ◽  
Strong Trend ◽  
Response To Change ◽  
As Stress

By definition and general agreement, smart materials are materials that have properties which may be altered in a controlled fashion by stimuli, such as stress, temperature, moisture, pH, and electric or magnetic fields. There are numerous types of smart materials, some of which are already common. Examples include piezoelectric materials, which produce a voltage when stress is applied or vice versa, shape memory alloys or shape memory polymers which are thermoresponsive, and pH sensitive polymers which swell or shrink as a response to change in pH. Thus, smart materials respond to stimuli by altering one or more of their properties. Smart behaviour occurs when a material can sense some stimulus from its environment and react to it in a useful, reliable, reproducible, and usually reversible manner. These properties have a beneficial application in various fields including dentistry. Shape memory alloys, zirconia, and smartseal are examples of materials exhibiting a smart behavior in dentistry. There is a strong trend in material science to develop and apply these intelligent materials. These materials would potentially allow new and groundbreaking dental therapies with a significantly enhanced clinical outcome of treatments.

Effects of Annealing on Microstructure and Martensitic Transition of Ni-Mn-Co-In Ferromagnetic Shape Memory Alloys

2011 ◽  
Vol 674 ◽  
pp. 171-175
Author(s):  
Katarzyna Bałdys ◽  
Grzegorz Dercz ◽  
Łukasz Madej
Keyword(s):  
Electron Microscopy ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Martensitic Transition ◽  
Magnetic Shape Memory ◽  
Ferromagnetic Shape Memory Alloys ◽  
Initial State ◽  
X Ray ◽  
Ferromagnetic Shape Memory

The ferromagnetic shape memory alloys (FSMA) are relatively the brand new smart materials group. The most interesting issue connected with FSMA is magnetic shape memory, which gives a possibility to achieve relatively high strain (over 8%) caused by magnetic field. In this paper the effect of annealing on the microstructure and martensitic transition on Ni-Mn-Co-In ferromagnetic shape memory alloy has been studied. The alloy was prepared by melting of 99,98% pure Ni, 99,98% pure Mn, 99,98% pure Co, 99,99% pure In. The chemical composition, its homogeneity and the alloy microstructure were characterized using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The phase composition was also studied by X-ray analysis. The transformation course and characteristic temperatures were determined by the use of differential scanning calorimetry (DSC) and magnetic balance techniques. The results show that Tc of the annealed sample was found to decrease with increasing the annealing temperature. The Ms and Af increases with increasing annealing temperatures and showed best results in 1173K. The studied alloy exhibits a martensitic transformation from a L21 austenite to a martensite phase with a 7-layer (14M) and 5-layer (10M) modulated structure. The lattice constants of the L21 (a0) structure determined by TEM and X-ray analysis in this alloy were a0=0,4866. The TEM observation exhibit that the studied alloy in initial state has bigger accumulations of 10M and 14M structures as opposed from the annealed state.

Adaptive Elastic SMA Elements for Damping Applications

2013 ◽  
Author(s):  
Alexander Czechowicz ◽  
Peter Dültgen ◽  
Sven Langbein
Keyword(s):  
Boundary Conditions ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Electrical Resistance ◽  
Thermal Activation ◽  
Hysteretic Behavior ◽  
Damping Function ◽  
Actual Shape ◽  
Elastic Elements

Shape memory alloys (SMA) are smart materials, which have two technical usable effects: While pseudoplastic SMA have the ability to change into a previously imprinted actual shape through the means of thermal activation, pseudoelastic SMA show a reversible mechanical elongation up to 8% at constant temperature. The transformation between the two possible material phases (austenite and martensite) shows a hysteretic behavior. As a result of these properties, SMA can be used as elastic elements with intrinsic damping function. Additionally the electrical resistance changes remarkably during the material deformation. These effects are presented in the publication in combination with potential for applications in different branches at varying boundary conditions. The focus of the presented research is concentrated on the application of elastic elements with adaptive damping function. As a proof for the potential considerations, an application example sums up this presentation.

Modeling Smart Materials Using Hysteretic Recurrent Neural Networks

2009 ◽  
Author(s):  
Arun Veeramani ◽  
John Crews ◽  
Gregory D. Buckner
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Real Time Control ◽  
Ferromagnetic Shape Memory Alloys ◽  
Two Phase ◽  
Time Control ◽  
Novel Approach ◽  
Three Phase ◽  
Ferromagnetic Shape Memory

This paper describes a novel approach to modeling hysteresis using a Hysteretic Recurrent Neural Network (HRNN). The HRNN utilizes weighted recurrent neurons, each composed of conjoined sigmoid activation functions to capture the directional dependencies typical of hysteretic smart materials (piezoelectrics, ferromagnetic, shape memory alloys, etc.) Network weights are included on the output layer to facilitate training and provide statistical model information such as phase fraction probabilities. This paper demonstrates HRNN-based modeling of two- and three-phase transformations in hysteretic materials (shape memory alloys) with experimental validation. A two-phase network is constructed to model the displacement characteristics of a shape memory alloy (SMA) wire under constant stress. To capture the more general thermo-mechanical behavior of SMAs, a three-phase HRNN model (which accounts for detwinned Martensite, twinned Martensite, and Austensite phases) is developed and experimentally validated. The HRNN modeling approach described in this paper readily lends itself to other hysteretic materials and may be used for developing real-time control algorithms.

Shape memory alloy–actuated prestressed composites with application to morphing automotive fender skirts

2018 ◽  
Vol 30 (3) ◽  
pp. 479-494 ◽  
Author(s):  
Venkata Siva C Chillara ◽  
Leon M Headings ◽  
Ryohei Tsuruta ◽  
Eiji Itakura ◽  
Umesh Gandhi ◽  
...  
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Design Procedure ◽  
Building Blocks ◽  
Smart Composite ◽  
Thermally Induced ◽  
One Dimensional ◽  
Flat Shape

This work presents smart laminated composites that enable morphing vehicle structures. Morphing panels can be effective for drag reduction, for example, adaptive fender skirts. Mechanical prestress provides tailored curvature in composites without the drawbacks of thermally induced residual stress. When driven by smart materials such as shape memory alloys, mechanically-prestressed composites can serve as building blocks for morphing structures. An analytical energy-based model is presented to calculate the curved shape of a composite as a function of force applied by an embedded actuator. Shape transition is modeled by providing the actuation force as an input to a one-dimensional thermomechanical constitutive model of a shape memory alloy wire. A design procedure, based on the analytical model, is presented for morphing fender skirts comprising radially configured smart composite elements. A half-scale fender skirt for a compact passenger car is designed, fabricated, and tested. The demonstrator has a domed unactuated shape and morphs to a flat shape when actuated using shape memory alloys. Rapid actuation is demonstrated by coupling shape memory alloys with integrated quick-release latches; the latches reduce actuation time by 95%. The demonstrator is 62% lighter than an equivalent dome-shaped steel fender skirt.

Smart materials: Properties, design and mechatronic applications

2016 ◽  
Vol 233 (4) ◽  
pp. 734-762 ◽  
Author(s):  
A Spaggiari ◽  
D Castagnetti ◽  
N Golinelli ◽  
E Dragoni ◽  
G Scirè Mammano
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Piezoelectric Materials ◽  
Magnetorheological Fluids ◽  
Research Perspective ◽  
Active Devices ◽  
Complete Survey ◽  
Basic Equations ◽  
Commercial Applications

This paper describes the properties and the engineering applications of the smart materials, especially in the mechatronics field. Even though there are several smart materials which all are very interesting from the research perspective, we decide to focus the work on just three of them. The adopted criterion privileges the most promising technologies in terms of commercial applications available on the market, namely: magnetorheological fluids, shape memory alloys and piezoelectric materials. Many semi-active devices such as dampers or brakes or clutches, based on magnetorheological fluids are commercially available; in addition, we can trace several applications of piezo actuators and shape memory-based devices, especially in the field of micro actuations. The work describes the physics behind these three materials and it gives some basic equations to dimension a system based on one of these technologies. The work helps the designer in a first feasibility study for the applications of one of these smart materials inside an industrial context. Moreover, the paper shows a complete survey of the applications of magnetorheological fluids, piezoelectric devices and shape memory alloys that have hit the market, considering industrial, biomedical, civil and automotive field.

Phenomenological Models of Solid State Actuators for Network Based System Modelling

2014 ◽  
Author(s):  
Johannes Ziske ◽  
Fabian Ehle ◽  
Holger Neubert
Keyword(s):  
Solid State ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Magnetic Flux Density ◽  
System Modelling ◽  
Magnetic Shape Memory ◽  
Magnetic Shape Memory Alloys ◽  
Design And Optimization ◽  
Highly Nonlinear

Smart materials, such as thermal or magnetic shape memory alloys, provide interesting characteristics for new solid state actuators. However, their behavior is highly nonlinear and determined by strong hysteresis effects. This complex behavior must be adequately considered in simulation models which can be applied for efficient actuator design and optimization. We present a new phenomenological lumped element model for magnetic shape memory alloys (MSM). The model takes into account the two-dimensional hysteresis of the magnetic field induced strain as a function of both the compressive stress and the magnetic flux density. It is implemented in Modelica. The model bases on measured limiting hysteresis surfaces which are material specific. An extended Tellinen hysteresis modeling approach is used to calculate inner hysteresis trajectories in between the limiting surfaces. The developed model provides sufficient accuracy with low computational effort compared to finite element models. Thus, it is well suited for system design and optimization based on network models. This is demonstrated with exemplary models of MSM based actuators. System models and simulation results are shown and evaluated for different topologies.

Novel Behavior in Smart Polymeric Materials: Stress Memory and its Potential Applications

2016 ◽  
Vol 97 ◽  
pp. 93-99
Author(s):  
Jin Lian Hu ◽  
Harishkumar Narayana
Keyword(s):  
Magnetic Field ◽  
Shape Memory ◽  
Smart Materials ◽  
Shape Memory Polymers ◽  
Polymeric Materials ◽  
External Stimulus ◽  
Artificial Muscles ◽  
Recovery Stress ◽  
Stress Memory ◽  
Potential Applications

Materials, structures and systems, responsive to an external stimulus are smart and adaptive to our human demands. Among smart materials, polymers with shape memory effect are at the forefront of research leading to comprehensive publications and wide applications. In this paper, we extend the concept of shape memory polymers to stress memory ones, which have been discovered recently. Like shape memory, stress memory represents a phenomenon where the stress in a polymer can be programmed, stored and retrieved reversibly with an external stimulus such as temperature and magnetic field. Stress memory may be mistaken as the recovery stress which was studied quite broadly. Our further investigation also reveals that stress memory is quite different from recovery stress containing multi-components including elastic and viscoelastic forces in addition to possible memory stress. Stress memory could be used into applications such as sensors, pressure garments, massage devices, electronic skins and artificial muscles. The current revelation of stress memory potentials is emanated from an authentic application of memory fibres, films, and foams in the smart compression devices for the management of chronic and therapeutic disorders.

scholarly journals Development of Smart Textile Materials with Shape Memory Alloys for Application in Protective Clothing

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 689 ◽  
Author(s):  
Grażyna Bartkowiak ◽  
Anna Dąbrowska ◽  
Agnieszka Greszta
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Protective Clothing ◽  
Radiant Heat ◽  
Textile Material ◽  
Material System ◽  
Molten Metals ◽  
Textile Materials ◽  
Smart Textile

The latest directions of research on the design of protective clothing concern the implementation of smart materials, in order to increase its protective performance. This paper presents results on the resistance to thermal factors such as flames, radiant heat, and molten metals, which were obtained for the developed smart textile material with shape memory alloys (SMAs). The laboratory tests performed indicated that the application of the designed SMA elements in the selected textile material system caused more than a twofold increase in the resistance to radiant heat (RHTI24 = 224 s) with an increase of thickness of 13 mm (sample located vertically with a load), while in the case of tests on the resistance to flames, it was equal to 41 mm (sample located vertically without a load) and in the case of tests on the resistance to molten metal, it was 17 mm (sample located horizontally).

Deployable Process Analysis of Packaged SMP Sandwich Beam

2010 ◽  
Vol 123-125 ◽  
pp. 943-946 ◽  
Author(s):  
Zheng Fa Li ◽  
Zheng Dao Wang
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Sandwich Structure ◽  
Shape Recovery ◽  
Process Analysis ◽  
Sandwich Beam ◽  
Shape Memory Polymers ◽  
Recovery Stress ◽  
Recovery Response

Shape memory polymers own many advantages compared with traditional shape memory alloys or ceramics. In order to improve their shape recovery stress and realize a stable recovery response during the deployable process, the structure of SMP sandwich beam composed of two metallic skin and one SMP core is considered. The recovery behaviors of pure SMP and SMP beams reinforced by one-layer metallic skin are also discussed for comparison. The results confirm that the deployable properties of SMP matrix can be significantly improved by using sandwich structure.

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