Intelligent Material Systems: Application of Functional Materials

1998 ◽  
Vol 51 (8) ◽  
pp. 505-521 ◽  
Author(s):  
Junji Tani ◽  
Toshiyuki Takagi ◽  
Jinhao Qiu

This article presents a review of recent important developments in the field of intelligent material systems. Intelligent material systems, sometimes referred to as smart materials, can adjust their behavior to changes of external or internal parameters analogously to biological systems. In these systems, sensors, actuators and controllers are seamlessly integrated with structural materials at the macroscopic or mesoscopic level. In general, sensors and actuators are made of functional materials and fluids such as piezoelectric materials, magnetostrictive materials, shape memory alloys, polymer hydrogels, electro- and magneto-rheological fluids and so on. This article is specifically focused on the application of piezoelectric materials, magnetostrictive materials and shape memory alloys to intelligent material systems used to control the deformation, vibration and fracture of composite materials and structures. This review article contains 188 references.

Author(s):  
A Spaggiari ◽  
D Castagnetti ◽  
N Golinelli ◽  
E Dragoni ◽  
G Scirè Mammano

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.


1991 ◽  
Vol 246 ◽  
Author(s):  
L. McD. Schetky

AbstractAdaptive structures, also called Intelligent or smart materials, refers to the various materials systems which automatically or remotely alter their dynamic characteristics or their geometry to meet their Intended performance. By integrating the sensors and actuators Into the structural system, typically a composite materials, control of shape, vibration and acoustic behavior an be effected. In addition to active control, passive control of system damping can be achieved in these structures. The sensors employed include piezoelectric ceramics, piezoelectric polymer films, ferroelectrics, and fiber optics. For producing the stress induced changes in dynamic characteristics of a composite the actuators are either embedded within the composite or are surface mounted. In general, the piezoelectric type actuator Is used where small strains at high frequencies are appropriate, while shape memory actuators are used when high forces and strains at lower frequencies are required. Static damping, modulus shift effect on acoustic radiation, and strain energy shift of modal response and acoustic radiation of composite materials with embedded shape memory actuators will be discussed. The constitutive equations for shape memory alloys will be described and how these are used in the design of adaptive composite structuresThe term smart materials seems to have become a part of the engineering vocabulary with variants such as Intelligent materials, and their application in adaptive structures. Smart materials consist of a structural component such as a composite such as fiber reenforced resin, with distributed sensors and actuators and a microprocessor. In response to changing external or Internal conditions these materials can change their properties to more effectively perform their function. The external conditions may be environment such as light or heat, loads, vibration or the need to change the geometry or shape of the structure to cope with changing service conditions. Internal conditions may be delamination in a composite, fatigue cracks in a metallic or nonmetallic structure, or other forms of Incipient failure.In reviewing papers presented in the past several years at conferences on smart/adaptive structures one would see a dominant number on various aspects of space structures such as mirrors. antennas, robotics booms and satellite docking. In these areas the control of vibration or the precise control of motion are most often the specific subject addressed. Much of the ongoing research is on control theory and the design of algorithms to define the sensor-actuator-microprocessor Integration. Of concern in this paper Is the actuator itself which, in response to commands from the microprocessor, produces strains and forces in the structure to modify Its acoustic or vibratory response or alter Its shape. These actuators are broadly of two types: low to medium force, low strain, high frequency systems, typically a piezoceramic such as PZT, or a high force, high strain, low frequency actuator which is most likely to be a shape memory alloy element.


2009 ◽  
Vol 6 (4) ◽  
pp. 219-227 ◽  
Author(s):  
T. Grund ◽  
C. Megnin ◽  
J. Barth ◽  
M. Kohl

Polymer based microvalves offer outstanding properties for biomedical and life science applications. They can be produced cost efficiently by batch fabrication methods. Further, by adapting the polymer material, custom-tailored properties of the valve are possible. For mechanically active microvalves, actuation with smart materials like shape memory alloys is highly attractive due to their high work output per volume and favorable scaling behavior. For the integration of such smart materials, fabrication process incompatibilities between the actuator material and the polymer target system need to be avoided. This can be achieved by novel transfer bonding technologies being optimized for batch fabrication. These technologies are demonstrated for polymer microvalves actuated by a shape memory alloy but they can also be applied to other functional materials and structures.


2005 ◽  
Vol 888 ◽  
Author(s):  
K. Jai Ganesh ◽  
Arunya Suresh

ABSTRACTShape Memory Alloys (SMAs) are versatile functional materials with an I.Q of their own. This class of SMART Materials exhibit unique properties like superelasticity and shape memory effect (SME) which have made them suitable for potential applications. Although Ni-Ti SMAs have attracted attention ever since their inception in 1962, Cu based SMAs due to their ease in fabrication, cost effectiveness and high temperature properties are gaining immense popularity. This research aimed at the fabrication of Cu-14 Al-3.5 Ni (wt %) Shape Memory Alloy by a simple cost effective route and its characterization to correlate its structure and properties. The alloy of desired composition was melted in an Electric Resistance Furnace at 1473 K and cast in a metallic mould. Homogenization was carried out at 1123 K for twenty four hours followed by analysis of chemical composition by Optical Emission Spectroscopy. Transformation temperatures of the alloy were determined using Differential Scanning Calorimetry. Heat treatment operations were carried out at 1273 K for one hour followed by quenching in different media. Optical and SEM micrographs were taken at various magnifications and the formation of self accommodating martensite was observed which was further confirmed by X-Ray Diffraction technique. Further improvements in the mechanical properties of the alloy by quaternary additions of Mn and Ti have been cited. Finally, SME was observed in a rolled strip of the alloy, thus concreting the obtained results.


2018 ◽  
Vol 8 (10) ◽  
pp. 1928 ◽  
Author(s):  
Jung Sohn ◽  
Gi-Woo Kim ◽  
Seung-Bok Choi

Over the last two decades, smart materials have received significant attention over a broad range of engineering applications because of their unique and inherent characteristics for actuating and sensing aspects. In this review article, recent research works on various robots, medical devices and rehabilitation mechanisms whose main functions are activated by smart materials are introduced and discussed. Among many smart materials, electro-rheological fluids, magneto-rheological fluids, and shape memory alloys are considered since there are mostly appropriate application candidates for the robot and medical devices. Many different types of robots proposed to date, such as parallel planar robots, are investigated focusing on design configuration and operating principles. In addition, specific mechanism and operating principles of medical devices and rehabilitation systems are introduced and commented in terms of practical realization.


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Vijetha Badami ◽  
Bharat Ahuja

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.


2011 ◽  
Vol 674 ◽  
pp. 171-175
Author(s):  
Katarzyna Bałdys ◽  
Grzegorz Dercz ◽  
Łukasz Madej

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.


2008 ◽  
Vol 14 (S3) ◽  
pp. 85-86
Author(s):  
R.M.S. Martins ◽  
A. Mücklich ◽  
N. Schell ◽  
R.J.C. Silva ◽  
K.K. Mahesh ◽  
...  

Ni-Ti Shape Memory Alloys (SMAs) have been attracting attention as smart materials because they can work as sensors and actuators at the same time. Miniaturization of mechanical devices is evolving toward sub-micron dimensions raising important questions in the properties of Ni-Ti films. In thin films it is essential to investigate the microstructure to understand the origin of the thickness limit. The design of functionally graded films has also been considered but for their successful development it is important to characterize the variations in crystalline structure.


Author(s):  
Alexander Czechowicz ◽  
Peter Dültgen ◽  
Sven Langbein

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.


Author(s):  
Arun Veeramani ◽  
John Crews ◽  
Gregory D. Buckner

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.


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