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Intelligent materials
Intelligent Sensors H. Yamasaki (Editor) 9 1996 Elsevier Science B.V. All rights reserved.
39
Intelligent Materials Hiroaki YANAGIDA Department of Applied Chemistry, Faculty of Engineering, University of Tokyo, 73-1 Hongo, Bunkyo-ku, Tokyo, 113 JAPAN 1. Introduction: the background of intelligent materials development We often hear the term "intelligent material". Some international conferences on intelligent materials have already been held. While intelligent materials have become popular, the present author is afraid that very complicated materials are being developed because of the term "intelligent materials". He proposes that we keep in mind the original aim of R & D for intelligent materials [1], which is to solve the unfriendliness of technology to the public. Some recent advanced technology has led to technostress due to much too complicated control systems. Intelligent mechanisms involve self-diagnosis, self-adjustment, self-recovery, tuning (including recycling) capability, etc. These functions may be achieved by installing sensors and actuators within materials. If the structure is complicated, the material is no longer intelligent. One may believe the idea that the more complicated something is, the more advanced it is. This false recognition is sometimes called the "spaghetti syndrome", i.e. many electric wires tangling the object. Once technologies suffer these syndromes, they become increasingly complicated. We need intelligent materials to save complicated and unstable circuits. One of the important objectives for intelligent materials is to cure this syndrome. Another objective for intelligent materials is to develop technology that is friendly to the environment. Materials for technology must be designed to meet certain requirements: reasonable fabrication cost, high reliability during use, and capability for recycling. Improvement of the reliability has been tried by making the structure thicker. This, however uses many resources and energy and produces much waste. Even though one may make materials stronger and more durable, fractures may occur unnoticed. Increase in strength makes recycling more difficult. The materials break when undesired and do not break when desired. If we can obtain a certain signal prior to the fatal fracture, we may be able to avoid accidents. One may put strain gauges on materials or structures. Many gauges are needed to cover a large or long specimen. One may of course apply an acoustic emission method to detect the generation of cracks. The signal obtained, however, is usually very subtle and it is not always practical to install an acoustic emission apparatus in every application. These methods are complicated and may lead to the "spaghetti syndrome". The monitoring method must be very simple with distinct signals. One of the most promising ways to assure the reliability of materials is to install a serf-
40 diagnosis mechanism, where signals that warn of fractures must be very distinct, while the materials still resist stress. If materials could be made with such a selfdiagnostic mechanism, we could take action to avert disasters caused by material's failure. We could also avoid the unnecessary sacrifice of materials by replacing them prematurely lest they should fail. 2. The measure of intelligence-- Technological Wisdom Index The author proposes the following index to measure the merits of intelligence. MI = number of merit / ( number of component )n
(n>l)
Simpler structures with less components are considered to be more advanced. When there is addition of a sensor for an additional merit, MI decreases. The way to achieve higher values is integration of functional and structural materials. The following examples explain the index. 2.1. No necessity of electrical assistance Since most functional materials need computers and integrated circuits now, it may seem difficult to get a useful function without the assistance of electricity. The present author, however, considers the humidity adjustment of wood in old Japanese log storehouses an original intelligent mechanism. In comparison, the "spaghetti syndrome" needs humidity sensors, dehumidifiers, humidifiers, temperature sensors, heaters, coolers, many circuits, and so on. In addition, emergency dynamos and circuits are necessary to provide against accidents. The system becomes complicated and consumes much energy. One recent example is photochromic glass, where optical transmittance is automatically adjusted without electricity. This character may be achieved by installing an optical sensor and polarizer on ferroelectric ceramics. The degree of intelligence is much higher in photochromic glass, even though the response is slower than the ferroelectric device. Another example is the vibration damper already adopted for buildings which works even during electricity outage. Of course there are proposed dynamic damping mechanisms. We cannot expect that they work perfectly during very strong earthquakes. Electricity may eventually become out-of-date. 2.2. No additional sensors The present author has discovered the self-diagnosis function in CFGFRP, carbon fiber and glass fiber reinforced plastics, which are used as replacements for iron bars in concrete structures [2]. A typical example of the load-strain change of electrical resistance characteristic of the materials is shown in Figure 1. We can see a tremendous change in electrical resistance at the point corresponding with one where carbon fibers are broken before fatal fracture as shown around (A) in Figure 1. We can note a not-yet fatal fracture with a very distinct signal. This corresponds with a health examination. Residual increase of resistance observed when
41 unloaded, around (B) in Figure 1, shows a history of the specimens which have suffered damage close to fatal fracture. This method, therefore, also tells of past disease. Maintenance of large-scale structures, architecture or aircraft, is expected to be easier with this method. The material, CFGFRP, has intelligence to not fracture suddenly as structural material to diagnose present and past stress, and to foresee fatal fracture as functional material a sensor. There are many merits without the addition of complicated sensor systems. The method applied to check the damage of materials is very simple. Only a very conventional tester is needed. The number of components is not large because of integration of structural and functional materials. It is clear that the value of the wisdom index is high.
s!. Load
7-
.d
""~="
./" 6-
9 ~
-,L."-
./
s-
"='=" ' " ' ,
9
/ 0
0~ 4
"0 m 0 ,,,.I
// /
'; 2~
-
0 " 0
-
./.
1
-!
/
~ 0.5
1.0
1. 5
0 ......-.J 0 2.0
Strain/%
Figure 1. Load - Strain- &R-Characteristic of CFGFRP ( C= PAN-HMCF, R0--40~).
42 2.3. Simplicity of Structures 2.3.1. Thermistors A I ~ C (positive temperature coefficient) thermistor is a good example of intelligent material with a simple structure. From the viewpoint of heater performance, the IrI'C thermistor is more intelligent than the NTC (negative temperature coefficient) one. Figure 2 shows a comparison between a PTC thermistor and an NTC one. The resistivity of NTC thermistor decreases with temperature. An increase in temperature gives rise to an increase in electric current. This is positive feedback and difficult to control. When an NTC thermistor is used as a heating element, we have to add a temperature-control circuit. On the other hand, the I ~ C thermistor is a heater below the Curie Temperature (Tc), it is a critical temperature sensor, and it is a Switch since above the temperature the resistivity increases tremendously. It is multifunctional material. The structure is very simple and it is intelligent not because of the multifunctions but because of the self-adjusting mechanism. The temperature vs. resistivity characteristics give rise to a strong negative-feedback mechanism. We do not have to equip any electric circuits to control temperature.
|
i
i||
m
i
T
!
R
i
t
i
T-"~
(a) PTC
Figure 2. Two types of ceramic thermistors.
T--~
Co) NTC
43 2.3.2. Humidity sensor Some porous ceramic semiconductors work as a humidity sensor. The conductivity of the material increases with the adsorption of water vapor under humid conditions and decreases with the removal of adsorbed water molecules under dry conditions. Removal is, however, very slow at room temperature. In order that the water molecule adsorption sites remain fully active, one must frequently carry out a so-caged cleaning operation to remove the adsorbed water molecules at high temperature. During such cleaning treatments, the sensor cannot supply any information about current humidity. This is a disadvantage arising from the lack of a seE-recovery mechanism. The author's group has constructed a new type of ceramic humidity sensor [3]. This sensor, made of p / n contact, CuO p-type and ZnO n-type semiconductors, measures current across the interface required for electrolyzing water adsorbed around the contact points [4]. The adsorbed water is electrolyzed into gases. This means automatic cleaning. This has saved a circuit or treatment to remove water molecules adsorbed around the contact points, while the humidity sensor made of porous ceramic semiconductors cannot be operated without the treatment. The voltage-current characteristic changes with humidity, as shown in Figure 3.
FED C -I-'2 A
+1 E cO '= B L__ L_
-A
O
C D E F
--I
--2 ,
I --20
t
I, --10
,~
! 0
I
39~ 60%RH 80%RH 92%RH
_l
+ I0
.I
f
+20
V01tage/V Figure 3. Humidity-dependent voltage-current characteristic changes of an intelligent humidity sensor made by heterocontact between copper oxide and zinc oxide (All measurements were carried out at room temperature, RH = relative
hunud~ty).
44 In the CuO/ZnO heterocontact type of humidity sensor, the amount of water adsorption in the vicinity of the heterocontacts changes with humidity. This is also found for porous humidity sensors of the usual type with homophase contacts. Electron holes are injected by the p-type semiconductor electrode into the adsorbed water molecules, giving rise to protons in the adsorbed water. The positive charges from the protons are neutralized with negative charges injected by the n-type semiconductor electrode to liberate hydrogen gas. As a consequence, the adsorbed water is electrolyzed. During measurements, the cleaning process is always working, since the cleaning or self-recovery treatment is itself a working mechanism. If we look at the CuO/ZnO heterocontact from the viewpoint of humidity sensor performance compared with the porous ceramic type humidity sensor, we see more intelligence in the former. 2.4. Tuning capability There is the porous ceramic semiconductor type gas sensor using zinc or tin oxide. It is, however, very difficult to distinguish one gaseous species from another, for example, carbon monoxide from hydrogen. It has been proposed to use computers to judge different kinds of gaseous species. The computers memorizing how sensors react to each gaseous species evaluate the data from the sensors and give judgments. They need many sensors.
2.0
v
.1,,q
.g..q
o
1.5 I
1.0
0.0
0
1.0
2.0
Appliedvoltage (V )
Figure 4. The relation between gas sensitivity and the forward applied voltage in CuO/ZnO heterocontact. Gas concentrations are 8000 ppm. Measuring temperature is 260 ~
45 The p / n contact humidity sensor also works as a very selective carbon monoxide gas sensor [5]. The sensitivity changes with the bias applied across the p / n contact, as shown in Figure 4. Selectivity and sensitivity for carbon monoxide gas is maximum when the CuO side is positively biased at about 0.5 volt. Although sensitivity decreases above the bias, selectivity becomes uniform for all kinds of flammable gaseous species. This effect constitutes a "tuning". Sometimes we need to change the behavior or characteristics of materials from the outside. We may call this "tuning" the device. It avoids having to employ a large number of different components. The material with tuning capability achieves a high value in wisdom index. The present author proposes that the intelligent mechanisms are classified into two levels. Self-diagnosis, self-recovery and self-adjustment belong to primary intelligence. Tuning capability to control these primary intelligent mechanisms as we want should be called advanced intelligence. 3. Conclusion Intelligent materials are required to make technology friendly for the environment and people. The intelligent mechanisms, such as self-diagnosis, selfrecovery, self-adjustment and tuning capability for saving complexity and/or recycling must be achieved by simple methodology. The author proposes the technological wisdom index to measure the merits of intelligence and has shown typical cases. References 1.
2. 3. 4. 5.
K. Yamayoshi and H. Yanagida, Chemistry Today, 1992 [5] (1992) 13; H. Yanagida, Intelligent Materials, 2 [1] (1992) 6, 1st International Conference on Intelligent Materials, March 23-25, 1992 Oiso, Japan; H. Yanagida, Symposium of University of Tokyo, Jan. 28, 1992; H. Yanagida, Electronic Ceramics, 22 [5] (1991) 5; H. Yanagida, Lecture. U. S. - India - Japan Joint Symposium upon Electronic Ceramics, Jan. 16, 1989, Pune, India; H. Yanagida, Angewandte Chemie, 100 [10] (1988) 1443. N. Muto, H. Yanagida, M. Miyayama, T. Nakatsuji, M. Sugita and Y. Ohtsuka, J. Ceram. Soc. Jpn., 100 [4] (1992) 585. K. Kawakami and H. Yanagida, Yogyo Kyokaishi, 87 (1979) 112. Y. Nakamura, M. Ikejiri, M. Miyayama, K. Koumoto and H. Yanagida, Nippon Kagaku Kaishi, 1985 (1985) 1154. Y. Nakamura, T, Tsurutani, M. Miyayama, O. Okada, K. Koumoto and H. Yanagida, Nippon Kagaku Kaishi, 1987 (1987) 477.
39
Intelligent Materials Hiroaki YANAGIDA Department of Applied Chemistry, Faculty of Engineering, University of Tokyo, 73-1 Hongo, Bunkyo-ku, Tokyo, 113 JAPAN 1. Introduction: the background of intelligent materials development We often hear the term "intelligent material". Some international conferences on intelligent materials have already been held. While intelligent materials have become popular, the present author is afraid that very complicated materials are being developed because of the term "intelligent materials". He proposes that we keep in mind the original aim of R & D for intelligent materials [1], which is to solve the unfriendliness of technology to the public. Some recent advanced technology has led to technostress due to much too complicated control systems. Intelligent mechanisms involve self-diagnosis, self-adjustment, self-recovery, tuning (including recycling) capability, etc. These functions may be achieved by installing sensors and actuators within materials. If the structure is complicated, the material is no longer intelligent. One may believe the idea that the more complicated something is, the more advanced it is. This false recognition is sometimes called the "spaghetti syndrome", i.e. many electric wires tangling the object. Once technologies suffer these syndromes, they become increasingly complicated. We need intelligent materials to save complicated and unstable circuits. One of the important objectives for intelligent materials is to cure this syndrome. Another objective for intelligent materials is to develop technology that is friendly to the environment. Materials for technology must be designed to meet certain requirements: reasonable fabrication cost, high reliability during use, and capability for recycling. Improvement of the reliability has been tried by making the structure thicker. This, however uses many resources and energy and produces much waste. Even though one may make materials stronger and more durable, fractures may occur unnoticed. Increase in strength makes recycling more difficult. The materials break when undesired and do not break when desired. If we can obtain a certain signal prior to the fatal fracture, we may be able to avoid accidents. One may put strain gauges on materials or structures. Many gauges are needed to cover a large or long specimen. One may of course apply an acoustic emission method to detect the generation of cracks. The signal obtained, however, is usually very subtle and it is not always practical to install an acoustic emission apparatus in every application. These methods are complicated and may lead to the "spaghetti syndrome". The monitoring method must be very simple with distinct signals. One of the most promising ways to assure the reliability of materials is to install a serf-
40 diagnosis mechanism, where signals that warn of fractures must be very distinct, while the materials still resist stress. If materials could be made with such a selfdiagnostic mechanism, we could take action to avert disasters caused by material's failure. We could also avoid the unnecessary sacrifice of materials by replacing them prematurely lest they should fail. 2. The measure of intelligence-- Technological Wisdom Index The author proposes the following index to measure the merits of intelligence. MI = number of merit / ( number of component )n
(n>l)
Simpler structures with less components are considered to be more advanced. When there is addition of a sensor for an additional merit, MI decreases. The way to achieve higher values is integration of functional and structural materials. The following examples explain the index. 2.1. No necessity of electrical assistance Since most functional materials need computers and integrated circuits now, it may seem difficult to get a useful function without the assistance of electricity. The present author, however, considers the humidity adjustment of wood in old Japanese log storehouses an original intelligent mechanism. In comparison, the "spaghetti syndrome" needs humidity sensors, dehumidifiers, humidifiers, temperature sensors, heaters, coolers, many circuits, and so on. In addition, emergency dynamos and circuits are necessary to provide against accidents. The system becomes complicated and consumes much energy. One recent example is photochromic glass, where optical transmittance is automatically adjusted without electricity. This character may be achieved by installing an optical sensor and polarizer on ferroelectric ceramics. The degree of intelligence is much higher in photochromic glass, even though the response is slower than the ferroelectric device. Another example is the vibration damper already adopted for buildings which works even during electricity outage. Of course there are proposed dynamic damping mechanisms. We cannot expect that they work perfectly during very strong earthquakes. Electricity may eventually become out-of-date. 2.2. No additional sensors The present author has discovered the self-diagnosis function in CFGFRP, carbon fiber and glass fiber reinforced plastics, which are used as replacements for iron bars in concrete structures [2]. A typical example of the load-strain change of electrical resistance characteristic of the materials is shown in Figure 1. We can see a tremendous change in electrical resistance at the point corresponding with one where carbon fibers are broken before fatal fracture as shown around (A) in Figure 1. We can note a not-yet fatal fracture with a very distinct signal. This corresponds with a health examination. Residual increase of resistance observed when
41 unloaded, around (B) in Figure 1, shows a history of the specimens which have suffered damage close to fatal fracture. This method, therefore, also tells of past disease. Maintenance of large-scale structures, architecture or aircraft, is expected to be easier with this method. The material, CFGFRP, has intelligence to not fracture suddenly as structural material to diagnose present and past stress, and to foresee fatal fracture as functional material a sensor. There are many merits without the addition of complicated sensor systems. The method applied to check the damage of materials is very simple. Only a very conventional tester is needed. The number of components is not large because of integration of structural and functional materials. It is clear that the value of the wisdom index is high.
s!. Load
7-
.d
""~="
./" 6-
9 ~
-,L."-
./
s-
"='=" ' " ' ,
9
/ 0
0~ 4
"0 m 0 ,,,.I
// /
'; 2~
-
0 " 0
-
./.
1
-!
/
~ 0.5
1.0
1. 5
0 ......-.J 0 2.0
Strain/%
Figure 1. Load - Strain- &R-Characteristic of CFGFRP ( C= PAN-HMCF, R0--40~).
42 2.3. Simplicity of Structures 2.3.1. Thermistors A I ~ C (positive temperature coefficient) thermistor is a good example of intelligent material with a simple structure. From the viewpoint of heater performance, the IrI'C thermistor is more intelligent than the NTC (negative temperature coefficient) one. Figure 2 shows a comparison between a PTC thermistor and an NTC one. The resistivity of NTC thermistor decreases with temperature. An increase in temperature gives rise to an increase in electric current. This is positive feedback and difficult to control. When an NTC thermistor is used as a heating element, we have to add a temperature-control circuit. On the other hand, the I ~ C thermistor is a heater below the Curie Temperature (Tc), it is a critical temperature sensor, and it is a Switch since above the temperature the resistivity increases tremendously. It is multifunctional material. The structure is very simple and it is intelligent not because of the multifunctions but because of the self-adjusting mechanism. The temperature vs. resistivity characteristics give rise to a strong negative-feedback mechanism. We do not have to equip any electric circuits to control temperature.
|
i
i||
m
i
T
!
R
i
t
i
T-"~
(a) PTC
Figure 2. Two types of ceramic thermistors.
T--~
Co) NTC
43 2.3.2. Humidity sensor Some porous ceramic semiconductors work as a humidity sensor. The conductivity of the material increases with the adsorption of water vapor under humid conditions and decreases with the removal of adsorbed water molecules under dry conditions. Removal is, however, very slow at room temperature. In order that the water molecule adsorption sites remain fully active, one must frequently carry out a so-caged cleaning operation to remove the adsorbed water molecules at high temperature. During such cleaning treatments, the sensor cannot supply any information about current humidity. This is a disadvantage arising from the lack of a seE-recovery mechanism. The author's group has constructed a new type of ceramic humidity sensor [3]. This sensor, made of p / n contact, CuO p-type and ZnO n-type semiconductors, measures current across the interface required for electrolyzing water adsorbed around the contact points [4]. The adsorbed water is electrolyzed into gases. This means automatic cleaning. This has saved a circuit or treatment to remove water molecules adsorbed around the contact points, while the humidity sensor made of porous ceramic semiconductors cannot be operated without the treatment. The voltage-current characteristic changes with humidity, as shown in Figure 3.
FED C -I-'2 A
+1 E cO '= B L__ L_
-A
O
C D E F
--I
--2 ,
I --20
t
I, --10
,~
! 0
I
39~ 60%RH 80%RH 92%RH
_l
+ I0
.I
f
+20
V01tage/V Figure 3. Humidity-dependent voltage-current characteristic changes of an intelligent humidity sensor made by heterocontact between copper oxide and zinc oxide (All measurements were carried out at room temperature, RH = relative
hunud~ty).
44 In the CuO/ZnO heterocontact type of humidity sensor, the amount of water adsorption in the vicinity of the heterocontacts changes with humidity. This is also found for porous humidity sensors of the usual type with homophase contacts. Electron holes are injected by the p-type semiconductor electrode into the adsorbed water molecules, giving rise to protons in the adsorbed water. The positive charges from the protons are neutralized with negative charges injected by the n-type semiconductor electrode to liberate hydrogen gas. As a consequence, the adsorbed water is electrolyzed. During measurements, the cleaning process is always working, since the cleaning or self-recovery treatment is itself a working mechanism. If we look at the CuO/ZnO heterocontact from the viewpoint of humidity sensor performance compared with the porous ceramic type humidity sensor, we see more intelligence in the former. 2.4. Tuning capability There is the porous ceramic semiconductor type gas sensor using zinc or tin oxide. It is, however, very difficult to distinguish one gaseous species from another, for example, carbon monoxide from hydrogen. It has been proposed to use computers to judge different kinds of gaseous species. The computers memorizing how sensors react to each gaseous species evaluate the data from the sensors and give judgments. They need many sensors.
2.0
v
.1,,q
.g..q
o
1.5 I
1.0
0.0
0
1.0
2.0
Appliedvoltage (V )
Figure 4. The relation between gas sensitivity and the forward applied voltage in CuO/ZnO heterocontact. Gas concentrations are 8000 ppm. Measuring temperature is 260 ~
45 The p / n contact humidity sensor also works as a very selective carbon monoxide gas sensor [5]. The sensitivity changes with the bias applied across the p / n contact, as shown in Figure 4. Selectivity and sensitivity for carbon monoxide gas is maximum when the CuO side is positively biased at about 0.5 volt. Although sensitivity decreases above the bias, selectivity becomes uniform for all kinds of flammable gaseous species. This effect constitutes a "tuning". Sometimes we need to change the behavior or characteristics of materials from the outside. We may call this "tuning" the device. It avoids having to employ a large number of different components. The material with tuning capability achieves a high value in wisdom index. The present author proposes that the intelligent mechanisms are classified into two levels. Self-diagnosis, self-recovery and self-adjustment belong to primary intelligence. Tuning capability to control these primary intelligent mechanisms as we want should be called advanced intelligence. 3. Conclusion Intelligent materials are required to make technology friendly for the environment and people. The intelligent mechanisms, such as self-diagnosis, selfrecovery, self-adjustment and tuning capability for saving complexity and/or recycling must be achieved by simple methodology. The author proposes the technological wisdom index to measure the merits of intelligence and has shown typical cases. References 1.
2. 3. 4. 5.
K. Yamayoshi and H. Yanagida, Chemistry Today, 1992 [5] (1992) 13; H. Yanagida, Intelligent Materials, 2 [1] (1992) 6, 1st International Conference on Intelligent Materials, March 23-25, 1992 Oiso, Japan; H. Yanagida, Symposium of University of Tokyo, Jan. 28, 1992; H. Yanagida, Electronic Ceramics, 22 [5] (1991) 5; H. Yanagida, Lecture. U. S. - India - Japan Joint Symposium upon Electronic Ceramics, Jan. 16, 1989, Pune, India; H. Yanagida, Angewandte Chemie, 100 [10] (1988) 1443. N. Muto, H. Yanagida, M. Miyayama, T. Nakatsuji, M. Sugita and Y. Ohtsuka, J. Ceram. Soc. Jpn., 100 [4] (1992) 585. K. Kawakami and H. Yanagida, Yogyo Kyokaishi, 87 (1979) 112. Y. Nakamura, M. Ikejiri, M. Miyayama, K. Koumoto and H. Yanagida, Nippon Kagaku Kaishi, 1985 (1985) 1154. Y. Nakamura, T, Tsurutani, M. Miyayama, O. Okada, K. Koumoto and H. Yanagida, Nippon Kagaku Kaishi, 1987 (1987) 477.