Encyclopedia of Smart Materials (Vols 1 and 2) - M. Schwartz (2002) WW Part 14 docx

P1: FCH/FYX P2: FCH/FYX QC: FCH/UKS T1: FCH PB091-S-DRV-II January 23, 2002 21:38 SOUND CONTROL WITH SMART SKINS 1031 800 Frequency (Hz) Plate Passive control Active/Passive control Power (dB) 1000 1200 1400 1600400 5 10 15 20 25 30 35 40 45 50 600 Figure 4. Radiated power for a broadband 1I1O case using multiple smart foam modules operating in phase. reference signal for the LMS control approach was taken from the internal signal generator used to drive the distur- bance (termed internal reference). Figure 4 presents the radiated power with and without control, when all the smart skin cells are wired together in phase as a single channel of control. The error signal is provided by a single microphone located close to the smart foam surface and at the plate-foam center. Also shown is the passive effect of the smart skin when it is located on the plate but not activated. It is apparent that the passive effect of the skin is good at high frequencies above 1000 Hz but is limited to resonant frequencies of the base plate be- low this value. Turning on the active control provides rea- sonable attenuation at low frequencies, though there are some frequency ranges where the control is negligible, for instance near 900Hz. In this case the smart skin transfer function is reduced in level. We now extend the controller so that the six smart skin modules can be controlled in- dependently with a six by six LMS control arrangement. Figure 5 presents these new results for the low frequency range. For the results of Figure 5 three different reference signals control configuration are also studied: one using 300 −20 −10 0 10 20 30 40 400 500 600 Frequency (Hz) Attenuated SPL (dB) 700 800 900 1000 External ref/No F.B. removal Ext ref/No F.B. removal Internal ref Figure 5. Attenuated SPL for broadband 6I6O case using multiple-independent smart foam modules. an internal reference, one using an external reference signal taken from an accelerometer located on the plate (representing a more realistic arrangement), and an ex- ternal reference signal with feedback (FB) from the active component ofthe smart skin removed (1). It is appar- ent that much improved performance is achieved over the SISO case of Fig. 4, particularly for the internal reference case, due to the multicell active skin being able to match the complex radiation impedance load near 900 Hz, for ex- ample (3). In this case the smart skin transfer function is also modified in a distributed manner. Using an external reference signal also provides reason- able attenuation; however, it is reduced from the internal case implying that the system is acausal (1). Some of the lost performance is recovered when feedback removal is employed, indicating that the smart foam vibration has some input to the plate system. Recently the smart foam skin has been used to demon- strate control of interior noise in aircraft (4). Figure 6 shows a smart foam skin covering four panels in the crown section of the fuselage of a Cessna business jet. The application is focused toward reducing cockpit noise due P1: FCH/FYX P2: FCH/FYX QC: FCH/UKS T1: FCH PB091-S-DRV-II January 23, 2002 21:38 1032 SOUND CONTROL WITH SMART SKINS Error microphones M3 C3 Top euselage ribs Microphone traverse C4 C2 C1 M2 M1 M4 Figure 6. Cessna crown panel control arrangement. to exterior flow separation over the crown of the aircraft. Error microphones were located as shown at the ear lo- cations of the crew and a microphone traverse was used to measure the sound pressure levels in a plane at the crew head height. The flow noise disturbance was simu- lated by an exterior speaker located just over the crown of the aircraft and driven by band-limited white noise. A four by four feedforward LMS control approach was im- plemented using a realistic reference signal taken from an interior mounted accelerometer located on the fuselage at the aircraft crown (i.e., just under the excitation location). Figure 7 presents tabular results of the attenuation achieved at the error sensors (near the crews’ ears) with an excitation band of 500 to 900 Hz. The reference speaker refers to the use of a reference signal from the signal driv- ing the disturbance. The reference accelerometer refers to the use of a fuselage-mounted accelerometer as a refer- ence sensor and in this case attenuation of the order of 2 to 4 dB are achieved. The global attenuation measured us- ing the microphone traverse was found to be 2.5 dB with the active skin turned on. However, the active skin also provides a passive attenuation of 4 dB when it is installed over the bare fuselage panels and not turned on. Thus the total global attenuation of the smart foam active skin is around 6.5 dB, a significant difference. It also apparent from Fig. 7 that one of the main limitations on achievable attenuation is the causality of the controller when using an accelerometer as a reference signal. When the reference signal is taken from the speaker drive signal the control path delay is less, and the performance increases markedly. The results do, however, demonstrate the potential of the smart foam skin in reducing structurally radiated sound in a realistic application. PIEZOELECTRIC DOUBLE AMPLIFIER SMART SKIN Piezoelectric transducers tend to be high-force, low- displacement devices (1). In contrast, active noise control applications in air require high-displacement actuators, particularly at very low frequencies. Thus much of the work in developing piezoelectric based actuators for ac- tive noise control applications has been in designing de- vices that amplify their displacement. This amplification Error mic. 1 Averaged attenuation (dB) 0 5 10 15 20 25 Error mic. 2 Reference speaker Reference accelerometer with feedback removal Reference accelerometer without feedback removal Error mic. 3 Error mic. 4 Figure 7. Averaged attenuation microphones for band-limited 500 to 900 Hz excitation. is usually based on a geometric lever-type principle, and thus results in lower output force. More explicitly, the ac- tuators are designed to have the correct source impedance relative to their load. In our application, the load is air with a relatively low impedance, thus the device needs to have a low source impedance for maximum power output. Figure 8 shows a schematic diagram of a piezoelectric double amplifier actuator, which is the basis of the second active skin concept (5). The legs of the element consist of piezoelectric bimorphs or unimorphs. In this case, the piezoelectric transducers are manufactured from the ce- ramic material PZT (1). These devices are amplifiers in that due to their asymmetry, small in-plane motions are amplified to larger transverse tip motions at the top of the legs. The tops of the legs are connected to a triangular or curved stiff, lightweight diaphragm as shown. Thus as the legs move in, the diaphragm is squeezed upward. Since the diapraghm axis is transverse to the tip motion, very small tip motions cause very large diapraghm motions (i.e., amplify it) in a vertical direction. Thus the complete struc- ture comprises a double amplifier actuator and gives am- plification ratios of diaphragm to piezoelectric element in-plane deflection of the order of 20 : 1. The whole configuration can be built in heights typically ranging from 50 60 1.3 2 34 PZT-Brass-PZT Bimorph leg Speaker paper diaphragm 0.56 Figure 8. The active skin element. (domains in mm) P1: FCH/FYX P2: FCH/FYX QC: FCH/UKS T1: FCH PB091-S-DRV-II January 23, 2002 21:38 SOUND CONTROL WITH SMART SKINS 1033 Vibrating plate surface PZT Bimorphs Active-Skin diaphragm Figure 9. Smart skin constructed from piezoelectric double- amplifier elements. 3 to 6 cm, leading to a fairly compact device. In construct- ing an active skin of such devices, a number of them are positioned to completely cover the surface of a structure as shown in Fig. 9. The devices can be either located directly on the structure as shown or positioned just above it with a small air gap. In addition, the devices can be wired together as one channel of control or independently controlled, de- pending on the complexity of the base structural response. Figure 10 shows an actual device designed and constructed by the Materials Research Laboratory at Pennsylvania State University. The device is 50 × 60 mms, 34 mms high, and was found to have a maximum cover displacement of 300 µm at 100 Hz. Figure 11 shows six of the devices arranged to completely cover the surface of a 170 × 150 mm aluminum plate of 1.5 mm thickness. In this test arrangement, the active skin cells are located on a perforated aluminum sheet which is located 5 mm from the surface of the radiating plate. Thus the active skin has a small air gap between its bottom surface and the radiating surface of the structure (5). Small accelerometers located on each active cell diaphragmn are also apparent in Fig. 11. These accelerometers are used to provide time domain estimates of the radiated pressure in the far-field from the Figure 10. A single active-skin cell. Figure 11. The active-skin in a top-mounted SAS configuration. measured surface vibration data, termed structural acous- tic sensing (SAS) and described in (6). Such approaches allow integration of the sensors into the smart skin itself. The test plate and the active cells were mounted in a rigid baffle located in the anechoic chamber at VAL. A noise disturbance to the plate was provided by a small shaker attached to the back of the plate and driven with band-limited random noise. The radiated sound from the plate-skin structure was measured using an array of 16 microphones located on a hemispherical tube structure as described above and a microphone traverse that could measure the sound directivity in the horizontal midplane of the plate. The total radiated power from the plate could be calculated from the 16 pressure levels measured by the microphone hemispherical array (5). Figure 12 depicts a schematic of the experimental rig and the control arrangement. The control approach used was the Filtered -x LMS algorithm (1) implemented on a TMSC40 DSP. The shaker was driven with band lim- ited noise of 175 to 600 Hz. The Filtered -x algorithm was Amplifier Shaker Aluminum panel Baffle Microphones Accelerometers Active-skin C40 DSP Filtered-x LMS controller C30 DSP SAS Filter controller Figure 12. The active-skin experimental setup. P1: FCH/FYX P2: FCH/FYX QC: FCH/UKS T1: FCH PB091-S-DRV-II January 23, 2002 21:38 1034 SOUND CONTROL WITH SMART SKINS 75 −90° −45° 45° 0° θ 90° 69 62 56 50 Sound pressure level (dB) Before control After control 56 62 69 75 Figure 13. Total in-plane acoustic directivity (SPL), top-mounted accelerometer configuration with microphone error sensing. executed with a 2000 Hz sample rate, and 175 and 96 tap FIR filters were used for the control and system iden- tification paths, respectively. Since six independent cells were located on the structure to comprise the active skin, a six by six controller was implemented (5). Two tests were performed using different error sensors. In the first test, six microphones evenly distributed over the microphone array were used as conventional pressure error sensors located in the radiated far field. In the second test, the diaphragm accelerometer signals were used in the structural acoustic sensing approach, described in (6), to estimate the pres- sures at the same locations as the previous error micro- phones. These estimates were then used as error signals for the LMS algorithm. Figure 13 presents experimental results of the directiv- ity of the total radiated sound power measured using the far-field microphone traverse before and after the control using the active skin elements. It is apparent that the active skin provides global sound pressure level atten- uation of the order of 10 dB, which is impressive since the excitation band encompasses multiple modes of vi- bration of the radiating plate (5). Figure 14 shows the corresponding radiated power versus frequency. Good con- trol is seen over the complete bandwidth of 170 to 600 Hz except around 350 and 530 Hz, where anti-resonances occur in the plate-active skin system. The overall sound power reduction for the results of Fig. 14 is 10.9 dB. Fur- ther experiments were conducted using the accelerometers in the SAS approach, and the results are presented in Fig. 15. Good attenuation is evident across the frequency band, except near the system anti-resonance. The over- all reduction is now 9.5 dB, which is still impressive. Thus the results demonstrate that it is possible to utilize an active skin that can provide significant attenuation of sound radiated from a structure vibrating in complex re- sponse shapes. The successful use of the accelerometers is significant in that it shows that an active skin with completely integrated actuators and sensors can be con- structed to provide very significant broadband attenua- tion of sound radiated from structures under broadband excitation (5). 200 30 35 40 45 50 55 60 65 70 250 300 Before control After control 350 400 Frequency (Hz) Sound power level (dB) 450 500 550 600 Figure 14. Radiated sound power spectra, top-mounted accelero- meter configuration with microphone error sensing. SMART SKINS FOR SOUND REFELECTION CONTROL It should be noted that the above mentioned smart skin approaches could also be used to absorb sound imping- ing on structures by coating the structure with the smart skin. However, in this application, a modified sensing ap- proach is needed in which the reflected or scattered wave components are independently (than the total pressure field) sensed and minimized by the controller. Fuller et al. (7) discuss such approaches using the smart foam noted above, and a combination of two microphones located near the smart foam surface are used to separate out the re- flected wave information from the total pressure field (7). Figure 16 shows a schematic of the experimental testing in a plane wave acoustic standing wave tube. The noise is generated by a speaker at the right end of the tube and im- pinges on the smart foam. The two microphones are used to separate out the reflected and incident wave responses from the total pressure field. The reflected wave signal is used as error information to the LMS controller. The con- troller thus provides a control signal to the smart foam to minimize the reflected signal. Figure 17 presents the measured intensity of the inci- dent and reflected wave intensities versus frequency with the control off and on. With the control off, the incident and reflected intensities are almost equal at low frequencies 200 30 35 40 45 50 55 60 65 70 75 250 300 350 400 Frequency (Hz) Sound power level (dB) 450 500 550 600 Before control After control Figure 15. Radiated sound power spectra, top-mounted ac- celerometer configuration with SAS error sensing. P1: FCH/FYX P2: FCH/FYX QC: FCH/UKS T1: FCH PB091-S-DRV-II January 23, 2002 21:38 SOUND CONTROL WITH SMART SKINS 1035 B&K 2032 analyzer Amplifier RS-232 Amplifier Wave deconvolution Incident wave Reflected wave Reflected wave component Microphone amplifier Microphones Standing wave tube Active foam Disturbance input signal Computer with LMS controller Control signal Signal generator signal error signal Acoustic source LP filter Figure 16. Smart skin reflection con- trol experimental arrangement. below 300 Hz, implying that the smart foam is acting like a rigid surface with very little sound absorption. Above 300Hz, as is expected, the foam provides increasing pas- sive sound absorption, and the reflected intensity is less than the incident. When the active control is turned on, the incidentintensity remainsthe same, but the smart skin leads to a significant reduction in reflected sound energy below 300 Hz. This reduction in reflected sound due to the smart skin is apparent over the complete frequency range of Fig. 17.The twomicrophones can also be used to measure the acoustic impedance of the smart foam. When the con- trol is turned on at low frequencies, the normal acoustic impedance of the foam falls from very large values to be almost identical to the characteristic impedance of the air. Thus the active element in conjunction with the controller 100 130 120 110 100 90 80 70 60 50 40 30 150 200 300 400 500 Frequency (Hz) Incident wave Reflected wave Reflected wave under control Intensity (dB) 600 700 800 900 1000 Figure 17. Reflection control using a smart skin. of the smart foam have modified the smart foam dynamics so that it looks like a perfectly sound absorbing surface. ADVANCED CONTROL APPROACHES FOR SMART SKINS The conventional control approaches used with a smart skin can be divided into two types; multi-channel feedfor- ward, which is generally used when access to a coherent reference signal is available, and multiple input-multiple output state space feedback methods, which are often used when such a convenient reference signal is not available. These approaches are summarized in (1). As discussed above, the smart skin approach relies on covering a ma- jor part of the structure with independently controllable P1: FCH/FYX P2: FCH/FYX QC: FCH/UKS T1: FCH PB091-S-DRV-II January 23, 2002 21:38 1036 SOUND CONTROL WITH SMART SKINS Performance metrics Centralized processor Local control rules Multiple independent control signals Figure 18. Biological control approach. elements. It can thus be seen that when the structure is large and/or the frequency of interest high (or wave- length relative to the structure short), many smart skin elements are required, implying a control approach with a very high number of control channels. In this case, the conventional approaches are likely to be unsuitable due mainly to computational limits on the control processor and stability/performance aspects. There are two different approaches suitable for high sensor/actuator count sys- tems (8, 9). Both approaches are hierarchical and are in- spired by biological systems of muscle control. They are thus termed BIO controllers. In the first approach, the smart skin elements are ar- ranged into groups of “slave” actuators under the con- trol of a “master” actuator. A schematic of the controller is shown in Fig. 18. A top-level centralized controller is used to send signals to the master actuators. Simple local control laws are used to modify and apply the same sig- nal to nearby slave actuators. For example a very simple local law discussed in (8) would be take the same control signal, apply it to an in-phase, out-of-phase, or off-phase LMS γ c = −1,0,1 Σ γ 2 = −1,0,1 H c w e d H 2 G H 1 FIR filter Reference Figure 19. BIO controller with phase local control law. Radiated sound Structure Actuator Sensor Control law Local controller Local controller command signal Top level controller Averaged performance metric Figure 20. Schematic of a BIO controller arrangement. slave actuator via simple analog switches and keep the setting that gives the lowest cost function value. Figure 19 shows a block diagram realization of such a control system for a feedforward approach. The process then continues to the next slave actuator, and so on, in a predetermined pattern. For the system of Fig. 19 the top-level controller could be digital, while the local control changes occur via simple analog-switching circuits. The approach in effect takes many independent actuators and connects them to- gether via the local controller to create a suboptimal dis- tributed actuator driven by one (or few) channel of control from the top-level centralized controller. The net result of such approaches is a large reduction in control channels to the top-level digital controller, and thus the computa- tional overhead requirements are vastly reduced. The BIO approach in effect takes advantage of some limited knowl- edge of the dynamics of the distributed system to be con- trolled in order to reduce the extensive number crunching required in fully coupled optimal approaches. In the second approach, local analog feedback loops are closed around individual smart skin elements and associ- ated sensors as shown in Fig. 20. The analog local feedback loops have programmable feedback gains that are adapted by a higher-level digital controller in order to minimize a global cost function (obtained from an array of sensors) such as radiated sound power from the structure covered by the smart skin (9). Such approaches have been used to control sound radiation from very large structures. As with all feedback approaches, stability is an important is- sue. Thus work has also been performed to increase the stability margins via using directional feedback sensors to partially de-couple each local feedback loops. In addition, specialized distributed actuators are used that rolloff in level in the higher-frequency regions where the local open loop transfer function becomes non-minimum phase. CONCLUSION The results presented have demonstrated the high poten- tial for the implementations of a smart skin approach for reducing sound radiated from vibrating structures when the radiating structure is massive, stiff (i.e., low mobility), or the source vibration pattern is complex. The smart skin P1: FCH/FYX P2: FCH/FYX QC: FCH/UKS T1: FCH PB091-S-DRV-II January 23, 2002 21:38 SPIN-CROSSOVER MATERIALS 1037 has also demonstrated the possibility of combining active and passive control approaches in order to increase the control bandwidth and the efficiency of the active portion. A configuration has been demonstrated that further shows that the error sensors can be integrated directly into the skin and still result in a far-field sound reduction. BIBLIOGRAPHY 1. C.R. Fuller, S.J. Elliott, and P.A. Nelson, Active Control of Vibration. Academic Press, San Diego, CA, 1996. 2. C.A. Gentry, C. Guigou, and C.R. Fuller. JASA 101(4): 1771– 1778 (1997). 3. C.A. Gentry, C. Guigou, and C.R. Fuller. Submitted to JASA, 1999. 4. C. Guigou and C.R. Fuller. Proc. SPIE Smart Structures and Materials Conf., San Diego, CA, SPIE Vol. 3044, pp. 68–78, 1997. 5. B.D. Johnson, M.S. Thesis. VPI& SU. Blacksburg, VA, 1997. 6. J.P. Maillard and C.R. Fuller. JASA, 98(5): 2613–2621 (1995). 7. C.R. Fuller, M.J. Bronzel, C.A. Gentry, and D.E. Whittington Proc. NOISE-CON 94, pp. 429–436, 1994. 8. C.R. Fuller and J.P. Carneal. JASA, 93(6): 3511–3513 (1993). 9. M. Kidner and C.R. Fuller, Proc. 8th Conf. on Nonlinear Vibra- tions, Stability and Dynamics of Structures. Blacksburg, VA, July 2000. SPIN-CROSSOVER MATERIALS JOEL S. MILLER University of Utah, Chemistry Salt Lake City, UT Smart materials respond to their environment as illus- trated by photochromic eyeglasses, that darken upon ex- posure to ultraviolet light to attenuate additional ultra- violet light. Hence, materials that have fast reversible responses to environmental stimuli are sought as compo- nents of smart systems. Similar to photochromic materi- als, thermochromic materials reversibly respond to heat and exhibit substantial color changes upon small changes in temperature. Spin-crossover materials (1) are a class of thermochromic materials that possess fast, reversible color changes amenable to display and memory devices (2). These color changes can also be induced by light (photo- chromic) or pressure (piezochromic) as well as heat. Due to the nature of the mechanism of their thermo-, photo-, or piezochromic responses (i.e., redistribution of the electron density at a metal ion site within the molecule), they are extremely fast and reversible. As a consequence of the (1) fast colorchange, (2)strong contrastbetween colors, and (3) the intermolecular interactions within the solid, the differ- ing colors can be maintained for a long period of time, and (4) due to the lack of moving parts (i.e., no bond breaking or forming), these materials are completely recyclable and amenable to fast, low power-consuming, high-data-density display (2,3) and storage devicesand “smart” materials and systems of the future. Low spin 1 A 1g Spectrochemical series increasing ligand field, ∆ ∆ High spin 5 T 2g Figure 1. Switchover from a high-spin (S = 2) state to a low-spin (S = 0), as a Fe(II) state compound is cooled, requires ligands in the middle of the spectrochemical series. This transition can also be induced by light or pressure. Thermochromism results from transition-metal com- plexes, such as Fe(II), which can be thermally stimulated to change from a colored low-spin electronic state to a fre- quently colorless high-spin state (1a) (Fig. 1). The high- spin 5 T 2g ground state for Fe(II) has a t 2g –e g splitting , of <11,000 cm −1 , and the low-spin 1 A 1g excited state for Fe(II) has a  of >21,000 cm −1 .  ∼16,000 cm −1 for Fe(II) surrounded with six unsaturated nitrogen-bound ligands, FeN 6 , can be induced to switch between the high-spin and low-spin states. Upon switching between the high- and low-spin states on cooling, FeN 6 has a significant de- crease in Fe–N distances by 19 ± 5 pm, and an increase in the magnetic susceptibility χ due to a change of four in the number of unpaired electrons. From a thermody- namic perspective, the enthalpy His10± 6 kJ/mol, and the entropy Sis52± 13 J/K r mol; hence, the transi- tion is entropy-driven (1a). Additionally and importantly, the color changes from deeply colored red/purple to color- less upon switching to the high-spin state (see later). Con- comitantly, the unit cell typically changes significantly. The color change of the spin state switch is similar to that of liquid crystal displays (LCD) prevalent in digital watches; however, as a consequence of the mechanism, the thermochromic metal complexes change colors much faster without degradation upon cycling with respect to LCDs (3). Due to the change from low to high spin, this class of materials is referred to as spin-crossover materials. In addition to the technologically important color changes, spin-crossover materials also exhibit a small, but mea- surable change in magnetic susceptibility. This sharp transition in the change in the magnetic properties is illustrated by the temperature dependence of the magnetic susceptibility–temperature product for Fe(o- phenanthroline) 2 (NCS) 2 , which undergoes a first-order phase transition from a low- to a high-spin state at −97 ◦ C (4), (Fig. 2). Materials that can be easily and reversibly stimulated to change colors for an innumerable number of cycles have been exploited for display devices. Liquid crystal displays (LCD) found in digital watches, are a common example (3). Materials that have greater switching speeds, sharper contrast, and enhanced stability enabling more duty cycles may lead to improved display and memory devices in the future. Spin-crossover materials can exhibit sharp color changes from small changes in temperature (i.e., they are dramatically thermochromic). As a consequence of the thermochromic mechanism (redistribution of the electron density within the molecule without either bond breaking P1: FCH/FYX P2: FCH/FYX QC: FCH/UKS T1: FCH PB091-S-DRV-II January 23, 2002 21:38 1038 SPIN-CROSSOVER MATERIALS 3 2 1 150 200 250 Temperature, T, K T c = −97°C χT, emuK/mol Figure 2. Temperature dependence of the magnetic suscepti- bility–temperature product for Fe(o-phenanthroline) 2 (NCS) 2 , which undergoes a first-order phase transition from a low- to a high-spin state at 176 K (−97 ◦ C) (4a). or forming), they are extremely fast and recyclable and hence are candidates for high-data-density display and storage devices of the future. For display/memory devices, it is necessary that the transition temperature (T) is near room temperature, ∼22 ◦ C. This is, however, insufficient because the ambient temperature fluctuates and hence the transition needs to be effected over a broad temperature range, 17 ± 27 ◦ C. To achieve this, the system must exhibit history-dependent behavior (hysteresis) such that the transition temperature for color change upon increasing temperature (T↑) ex- ceeds the transition temperature for color change upon de- creasing temperature (T↓) ideally by at least 50 ◦ C, that is, T↑−T↓ > 50 ◦ C. Molecules cannot exhibit hysteretic ef- fects, but in a solid or film, interactions between molecules can lead to hysteretic effects. Hysteresis has been reported for FeL 2 (NCS) 2 (L = (N 2 (CH) 2 N–) 2 ], where T↑=−128.7 ◦ C and T↓=−149.5 ◦ C (Fig. 3). (5) Thus, although the transi- tion and T↑−T↓ temperatures are too low to be practical, the necessary phenomena have been demonstrated, and new systems that exhibit higher temperatures are needed. Using a mixture of triazole, HN(CH) 2 N 2 (trz), and aminotriazole, H 2 NN(CH) 2 N 2 (H 2 Ntrz) ligands coordi- nated with Fe(II), a polymer of [Fe(trz) 3−3x (H 2 Ntrz) 3x ] 2 3 1 100 150 200 Magnetic susceptibility•T Temperature, T, K −149.5°C T↑ −149.5°C Hysesis Figure 3. Temperature dependence of the magnetic behavior of FeL 2 (NCS) 2 showing the low-moment (purple) behavior be- low −149.5 ◦ C(T↑) and high-moment (colorless) behavior above −128.7 ◦ C(T↓) (5). 2 1 3 χT, emuK/mol Temperature, T, K 275 285 295 305 315 T ↓ = 13°C T ↑ = 39°C ∆T C = 27°C Room temperature Figure 4. Temperature dependence of the magnetic behavior of Fe(trz) 2.85 (H 2 Ntrz) 0.15 ](ClO 4 ) 2 r nH 2 O showing the low-moment (purple) (Figs.5 and 6) behavior below 39 ◦ C(T↑) and high-moment (colorless) behavior above 13 ◦ C(T↓) (6). (ClO 4 ) 2 r nH 2 O composition has been isolated, which for x = 0.05 exhibits T↑=39 ◦ C and T↓=13 ◦ C (2,6,7) (Fig. 4). These values bracket room temperature and demonstrate the feasibility of room temperature applications. In ad- dition to the change in magnetic behavior, the color con- comitantly as with hysteresis occurs (Fig. 5), from pur- ple to colorless at 21 ◦ C (Fig. 6). Solid solutions of triazole and aminotriazole can be blended to lead to a systematic change in the transition temperatures: T↑=296 − 160x and T↓=313 − 180x in units of Kelvin. Smart materials for future applications need to respond to environmental stimuli, and spin-crossover materials (1) are a moderately large class of materials that respond to heat, light, and/or pressure. This summary focuses on the use of heat to change the electronic structure of a material, which in turn leads to substantial and reversible color, magnetic, and structural changes. Most of the materials discussed in this context are inorganic coordination com- plexes demonstrating that (1) reversible first-order transi- tions occur, (2) such materials exhibit the technologically important property of hysteresis, and (3) both the transi- tions and hysteresis can occur at room temperature. 320 340 360 380 400 420 Temperature, T, K Optical density (Arbitrary) Figure 5. Temperature dependence of the optical density of Fe(trz) 2.85 (H 2 Ntrz) 0.15 ](ClO 4 ) 2 r nH 2 O at 520 nm showing hystere- sis (purple) (1a). P1: FCH/FYX P2: FCH/FYX QC: FCH/UKS T1: FCH PB091-S-DRV-II January 23, 2002 21:38 SPIN-CROSSOVER MATERIALS 1039 Figure 6. Dramatic color change for the dark purple low-spin state of [Fe(trz) 2.85 (H 2 Ntrz) 0.15 ](ClO 4 ) 2 r nH 2 O below 21 ◦ C to the colorless high-spin state at 21 ◦ C (6). ACKNOWLEDGMENTS The author acknowledges continued partial support by the Department of Energy Division of Materials Science (Grant Nos. 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Codjovi, O. Kahn, O. Groliere, and C. Jay, J. Am. Chem. Soc. 115: 9810 (1993). 7. O. Kahn, and E. Codjovi, Philos. Trans. R. Soc. London. A 354: 359 (1996). [...]... Coefficients of Zeolitesa Zeolite Chabazite ITQ-4 Si-faujasite ALPO -1 7 ITQ -1 ITQ-3 SSZ-23 MFI AFI (AlPO4 − 5) DOH MTN DDR a α (diffraction) × 10 −6 K 1 Temperature Range Ref 16 −4.3 −4.2 17 12 .1 11 .4 10 .3 15 .1 14 .5 −3 .1 −5.0 −8.7 293–873 95– 510 25–573 18 –300 323–773 323–823 323–773 393–975 424–774 573–996 463 10 02 492 11 85 81 81 77 76 75 75 75 79 79 79 79 79 All values are defined as 1/ 3 αV derived... 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Similar to photochromic materi- als, thermochromic materials. Filtered -x LMS algorithm (1) implemented on a TMSC40 DSP. The shaker was driven with band lim- ited noise of 17 5 to 600 Hz. The Filtered -x algorithm was Amplifier Shaker Aluminum panel Baffle Microphones Accelerometers Active-skin C40. t 2g –e g splitting , of < ;11 ,000 cm 1 , and the low-spin 1 A 1g excited state for Fe(II) has a  of > 21, 000 cm 1 .  16 ,000 cm 1 for Fe(II) surrounded with six unsaturated nitrogen-bound ligands, FeN 6 ,