Temperature-independent chemical and biological sensors

Abstract

Method for detecting chemical or biological materials in a fluid, comprising: measuring (48) real parts and imaginary parts of impedance spectra of a sensor resonance antenna (18) coated with a display material (14) at a variety of temperatures, wherein temperature-dependent reaction coefficients of a property of the sensor resonance antenna (18) and the display material (14) differ from each other; calculating (48) at least six spectral parameters of the sensor resonance antenna (18) coated with the display material (14) from each of the measured impedance spectra; performing a multivariate analysis (50) of the spectral parameters and reducing the spectral parameters to a single data point per measured impedance spectrum at a temperature in order to selectively identify an analyte.and determining one or more environmental parameters from the reduced spectral parameters using stored calibration coefficients (52), wherein the determination of the one or more environmental parameters is independent of the temperature (54).

Description

BACKGROUNDThe subject matter disclosed herein relates to chemical and biological sensors, and more particularly to very selective temperature independent chemical and biological sensors.Chemical and biological sensors are often used in a number of applications where detection of various vapors can be used to detect useful information. For example, measuring the presence of vapors by detecting a change in certain environmental variables within or around a sensor may be particularly useful for monitoring changes in biopharmaceutical products, foods or beverages, for monitoring industrial areas of chemical or physical hazards, as well as in safety applications such as monitoring residential areas, safety in airports, in various environmental and clinical settings, and other public sites where detection of certain harmful and / or toxic vapors may be particularly useful.One technique for indicating such environmental changes is by employing a sensor, such as an RFID (passive radio frequency identification) sensor, coated with a particular indicator material. In addition, sensors may be arranged in an array of individual transducers coated with one or more display materials. Many sensor arrangements include a number of identical sensors. While using identical sensors facilitates manufacture of the sensor assembly, such an assembly may have limited capabilities by indicating only a single response (e.g., resistance, current, capacitance, work function, mass, optical thickness, light intensity, etc.). However, in certain applications, multiple reactions or changes in multiple properties may occur. In such applications, it may be useful to include a series of sensors in which different transducers in the array use the same or different responses (e.g., resistance, current, capacitance, work function, mass, optical thickness, light intensity, etc.), and they are coated with different display materials so that more than one property can be measured. Unfortunately, fabricating a sensor assembly having individual sensors that are unitarily fabricated to indicate a particular response complicates the fabrication of the assembly.In many practical applications, it is useful to employ very selective chemical and biological sensors. It is often desirable to provide a sensor arrangement capable of displaying multiple vapors and vapor mixtures in the presence of other vapors and mixtures. The greater the number of vapors and vapor mixtures that may be present, the more difficult it may be to accurately indicate and recognize a specific type of vapor or vapor mixture. This may be particularly the case when one or more vapors are present in higher orders of magnitude than other vapors of interest to be detected. For example, high humidity environments impair the ability of traditional sensors to detect selected vapors. Further, temperature variations reduce the accuracy of chemical and biological display when sensors are employed, such as individual sensors or sensors arranged in an array.US 2009 / 0 278 685 A1 describes a method for detecting chemical or biological materials in a fluid. The method includes measuring the complex impedance of an RFID sensor coated with a display material, wherein the temperature dependent response coefficients of at least one property of the sensor resonant antenna and the display material are different from each other. The method further comprises calculating at least six spectral parameters, which is performed at a plurality of temperatures in a calibration step. The method further comprises reducing an impedance spectrum to a single data point using multivariate analysis and determining an environmental parameter from the impedance spectrum independent of temperature using stored calibration coefficients.Various embodiments disclosed herein address one or more of the challenges listed above.BRIEF DESCRIPTIONAccording to the invention, a method for detecting chemical or biological materials in a fluid is provided. The method includes measuring real parts and imaginary parts of impedance spectra of a sensor resonant antenna coated with a display material at a plurality of temperatures. The temperature-dependent response coefficients of a property of the sensor resonant antenna and the display material are different from each other. The method further comprises calculating at least six spectral parameters of the sensor resonant antenna coated with the display material from each of the measured impedance spectra. The method further comprises performing a multivariate analysis of the spectral parameters and reducing the spectral parameters to a single data point per measured impedance spectrum at a temperature to selectively identify an analyte (a material to be analyzed). The method further comprises determining one or more environmental parameters from the reduced spectral parameters using stored calibration coefficients. The determination of the one or more environmental parameters is independent of temperature.Further advantageous embodiments of the invention are set forth in the dependent claims.DRAWINGThese and other features, aspects and advantages of the present invention will become more fully understood from a reading of the following detailed description with reference to the accompanying drawings, in which like reference numerals represent like parts throughout the figures, wherein: FIG. 1 shows a display system according to embodiments of the invention; FIG. 2 shows an RFID sensor according to embodiments of the present invention; FIG. 3 shows an RFID sensor according to other embodiments of the invention; FIG. 4 shows measured responses of an RFID sensor according to embodiments of the present invention; FIG. 5 is a flow chart showing a method for analyzing a vapor in the presence of variable temperature according to embodiments of the invention; and FIGS. 6-11 show test data demonstrating a single sensor capable of distinguishing between moisture levels independent of temperature, according to embodiments of the invention.DETAILED DESCRIPTIONEmbodiments disclosed herein provide temperature independent methods and systems for selective vapor sensing, wherein a single sensor is provided and is capable of detecting multiple vapors and / or mixtures of vapors alone or in the presence of each other. Examples of general methods for vapor display using a single sensor are described in U.S. patent application Ser. No. 12 / 942,732, entitled "Highly Selective Chemical and Biological Sensors," which is incorporated herein by reference. The disclosed sensors are capable of detecting various vapors and mixtures in the presence of variable temperature, even in a high humidity environment or in an environment where one or more vapors have a substantially higher concentration (e.g., 10x) as compared to other components in the mixture. Each sensor includes an inductor-capacitor-resistor (LCR) resonant circuit coated with a display material. Temperature-dependent response coefficients of a property of the LCR circuit and the display material are different from each other. The differences in the temperature-dependent response coefficients of the property affect the measurements of the disclosed sensors. However, knowing the temperature-dependent response coefficients of the property and / or knowing how the sensor is affected by the differences in the temperature-dependent response coefficients of the property are used along with a multivariate analysis of the measured impedance of the sensor to provide temperature-independent selective vapor readings and improved response stability. For example, a look-up table may be developed that includes coefficients that rely on experimental testing of the sensor. During use of the sensor, the experimentally determined coefficients can be used in the multivariate analysis to account for variations in temperature during display. Other embodiments disclosed herein provide temperature independent methods and systems for selective chemical and biological display, providing a single sensor capable of detecting multiple chemical or biological materials in liquids and / or mixtures of chemical and biological materials alone or in the presence of each other.Non-limiting examples of LCR sensors include RFID sensors with an integrated circuit (IC) memory chip, RFID sensors with an IC chip, and RFID sensors without an IC memory chip (chipless RFID sensors). LCR sensors may be wireless or wired. To collect data, an impedance spectrum is acquired over a relatively narrow frequency range, such as the resonant frequency range of the LCR circuit. The technique further includes computing the multivariate signature of the captured spectrum and manipulating the data to detect the presence of certain vapors and / or vapor mixtures. The presence of vapors is detected by measuring changes in dielectric, dimensional, charge transfer and other changes in the properties of the materials employed by observing the changes in the electronic resonant properties of the circuit. Using a mathematical procedure such as principal component analysis (PCA) and others, multiple vapors and mixtures can be detected in the presence of each other and in the presence of an interference, as described below. Embodiments disclosed herein provide temperature independent methods and systems for selectively displaying fluids, wherein a single sensor is provided and is capable of detecting multiple fluids and / or mixtures of fluids alone or in the presence of each other. Further embodiments disclose methods of manufacturing such sensors by assembling a transducer including the LCR circuit and disposing the display material over at least a portion of the transducer, wherein the temperature dependent response coefficients of a property of the transducer and the display material are different from each other. In other embodiments, in addition to chemical sensors for vapors and fluids, biological sensors may also have temperature independent detection capabilities.In order to more clearly and accurately describe the subject matter of the claimed invention, the following definitions of specific terms are given, which are used in the following description and the appended claims.The term "fluid" includes gases, vapors, liquids, particles, biological particles, biological molecules and solids.The term "digital ID" includes all data stored in a memory chip of the RFID sensor. Non-limiting examples of these data are manufacturer identification, electronic pedigree data, user data, and calibration data for the sensor.The term "monitoring process" includes, but is not limited to, measuring physical changes occurring around the sensor. For example, monitoring processes include monitoring changes in a biopharmaceutical, food, or beverage manufacturing process related to changes in physical, chemical, and / or biological properties of an environment around the sensor. Monitoring processes may also include those industrial processes that monitor physical changes as well as changes in a composition or position of a component. Non-limiting examples include home country security monitoring, residential protection monitoring, environmental monitoring, in-bed patient clinical or monitoring, airport security monitoring, boarding pass issuing, and other public events. The monitoring may be carried out when the sensor signal has reached a recognizable stationary reaction and / or when the sensor shows a dynamic reaction. The steady-state sensor response is a response of the sensor over a predetermined period of time, at which the response does not change in a detectable manner over the measurement time. Measurements of steady state sensor responses over time thus produce similar values. The dynamic sensor response is a response of the sensor due to a change in the measured environmental parameter (temperature, pressure, chemical concentration, biological concentration, etc.). The dynamic sensor response thus changes significantly over the measurement time for generating a dynamic signature of the response with respect to the measured environmental parameter / s. Non-limiting examples of the dynamic signature of the response include an average response slope, an average response magnitude, a greatest positive slope of the signal response, a greatest negative slope of the signal response, an average change in the signal response, a maximum positive change in the signal response, and a maximum negative change in the signal response. The generated dynamic signature of the reaction can be used to further promote the selectivity of the sensor in dynamic measurements of individual vapors and mixtures thereof. The generated dynamic signature of the response can also be used to further optimize the combination of display material and transducer geometry to promote the selectivity of the sensor in dynamic and steady state measurements of individual vapors and mixtures thereof.The term "environment / environmental parameter" is used to refer to measurable environmental variables within or around a manufacturing or monitoring system. The measurable environmental variables include at least one of the physical, chemical, and biological properties, and include, but are not limited to, measurements of temperature, pressure, material concentration, conductivity, dielectric properties, the number of dielectric, metallic, chemical, or biological particles in proximity to or in contact with the sensor, the dose of ionizing radiation, and the intensity of light.The term "analyte" includes any desired measured environmental parameter.The term "interference" includes any undesirable environmental parameter that undesirably affects the accuracy and precision of measurements with the sensor. The term "interference" refers to a fluid or environmental parameter (including, but not limited to, temperature, pressure, light, etc.) that can potentially generate an interference response by the sensor.The term "multivariate analysis" refers to a mathematical method used to analyze more than one variable of the sensor response and provide the information about the type of at least one environmental parameter from the measured sensor spectral parameters and / or quantitative information about the level of the at least one environmental parameter from the measured sensor spectral parameters. The term "principal component analysis (PCA)" refers to a mathematical method used to reduce the multidimensional data sets to smaller dimensions for analysis. The principal component analysis is part of the self-analysis methods of the statistical analysis of multivariate data and it can be carried out using a covariance matrix or correlation matrix. Non-limiting examples of tools of multivariate analysis include canonical correlation analysis, regression analysis, nonlinear regression analysis, principal component analysis, discriminant function analysis, multidimensional scaling, linear discriminant analysis, logical regression, or neural network analysis.The term "spectral parameter" is used to refer to measurable variables of the sensor response. The sensor response is the impedance spectrum of the sensor resonant circuit of the LCR or RFID sensor. In addition to measuring the impedance spectrum in the form of Z parameters, S parameters and other parameters, the impedance spectrum (its two real and imaginary parts) can be simultaneously analyzed using various parameters for analysis, such as the frequency of the maximum of the real part of the impedance (F p), the magnitude of the real part of the impedance (Z p), the resonant frequency of the imaginary part of the impedance (F 1) and the anti-resonant frequency of the imaginary part of the impedance (F 2), the signal magnitude (Z 1) at the resonant frequency of the imaginary part of the impedance (F 1), the signal magnitude (Z 2) at the antiresonant frequency of the imaginary part of the impedance ((F 2) and the zero reactance frequency (F z, frequency at which the imaginary part of the impedance is zero). Other spectral parameters may be measured simultaneously using the total impedance spectra, e.g., the quality factor of the resonance, the phase angle, and the magnitude of the resonance. Collectively, "spectral parameters" calculated from the impedance spectra are referred to herein as "features" or "descriptors.". The appropriate selection of features is made from all potential mark-times that can be calculated from spectra. Multivariable spectral parameters are described in U.S. patent application Ser. No. 12 / 118,950, entitled "Methods and systems for calibration of RFID sensors," which is incorporated herein by reference.The term "resonant impedance" or "impedance" refers to the measured sensor frequency response, around the resonance of the sensor from which the sensor "spectral parameters" are extracted.The term "protective material" includes, but is not limited to, materials on the LCR or RFID sensor that protect the sensor from inadvertent mechanical, physical, or chemical action while permitting the making of the intended measurements. For example, an intended measurement may include measurement of solution conductivity, wherein a protective film separates the sensor from the liquid solution and yet allows an electromagnetic field to enter the solution. An example of a protective material is a paper film that is laid on the sensor to protect the sensor from mechanical damage and abrasion. Another non-limiting example of a protective material is a polymeric film applied to the sensor to protect the sensor from corrosion when placed in a liquid for measurements. A protective material may also be a polymer film placed on the sensor to protect it from short circuits of the sensor's antenna circuit when placed in a conductive liquid for measurements. Non-limiting examples of protective films are paper, polymeric, and inorganic films such as polyester, polypropylene, polyethylene, polyether, polycarbonate, polyethylene terephthalate, zeolites, metal organic frameworks, and cavitands. The protective material may be disposed between the transducer and the display film to protect the transducer. The protective material may be disposed on the display film, which is itself disposed on the transducer, to protect the display film and the transducer. The protective material on the display film, which is itself on the transducer, may serve as a filter material to protect the display film from being exposed to gaseous or ionic interference. Non-limiting examples of filter materials include zeolites, metalorganic frameworks, and cavitands.The term "display materials and display films" as used herein includes, but is not limited to, materials deposited on an electronic transducer module, such as LCR circuit components or an RFID tag, to perform the function of predictably and reproducibly affecting the sensor impedance response upon interaction with the environment. For example, a conductive polymer such as polyaniline alters its conductivity upon exposure to solutions of different pH. When such a polyaniline film is deposited on the LCR or RFID sensor, the impedance response of the sensor changes as a function of pH. Such an LCR or RFID sensor thus operates as a pH sensor. When such a polyaniline film is deposited on the LCR or RFID sensor for detection in a gas phase, the impedance response of the sensor changes even upon exposure to basic (e.g., NH 3) or acidic (e.g., HCl) gases. Alternatively, the display film may be a dielectric polymer. Sensor films include, but are not limited to, polymeric, organic, inorganic, biological, composite, and nanocomposite films that alter their electrical and / or dielectric properties based on the environment in which they are disposed. Non-limiting additional examples of sensor films may be a sulfonated polymer such as nafion, an adhesive polymer such as silicone adhesive, or an inorganic film such as sol-gel film, a composite film such as carbon black-polyisobutylene film, a nanocomposite film such as carbon nanotube nafion film, gold nanoparticle polymer film, metal nanoparticle polymer film, electrically spun polymer nanofibers, electrically spun inorganic nanofibers, electrically spun composite nanofibers, or films / fibers doped with organic, organometallic, or biologically derived molecules, or any other display material. To prevent the material in the sensor film from leaching into the liquid environment, the display materials are attached to the sensor surface using standard techniques such as covalent bonding, electrostatic bonding, and other standard techniques known to those skilled in the art. In addition, the display material has at least two temperature-dependent response coefficients related to temperature-dependent changes in the dielectric constant of the material and the resistance of the display material.The terms "transducer" and "sensor" are used to refer to electronic devices, such as RFID devices intended for display. A "transducer" is a device before it is coated with a display or protective film or before it is calibrated for a display application. The transducer includes at least three temperature-dependent response coefficients of temperature-dependent changes in the capacitance C, resistance R and inductance L of the LCR circuit. "Sensor" is a device typically after it is coated with a display or protective film and after it has been calibrated for the display application.The term "RFID tag" as used herein refers to identification and reporting technology that uses electronic tags to identify and / or track items to which the RFID tag may be attached. An RFID tag typically includes at least two components, the first component being an integrated circuit (IC) memory chip for storing and processing information and for modulating and demodulating a radio frequency signal. This memory chip can also be used for other specialized functions, for example it can contain a capacitor. It may also include at least one input for an analog signal, such as a resistor input, a capacitance input or an inductance input. In the case of a chipless RFID tag, the RFID tag may not include an IC memory chip. This type of RFID tag may be useful in applications where a specific RFID tag does not need to be identified, but rather a signal indicating only the presence of the tag provides useful information (e.g., product security applications). The second component of the RFID tag is an antenna for receiving and transmitting the radio frequency signal.The term "RFID sensor" is an RFID tag with an added display function, such as when an antenna of the RFID tag also performs display functions by changing its impedance parameters as a function of environmental changes. The accurate determinations of environmental changes with such RFID sensors are made by analysis of the resonant impedance. RFID tags can be converted to RFID sensors, for example, by coating the RFID tag with a display film. By coating the RFID tag with a display film, the electrical response of the film is translated into simultaneous changes to the impedance response, resonant peak position, peak width, peak height and peak symmetry of the impedance response of the sensor antenna, magnitude of the real portion of the impedance, resonant frequency of the imaginary portion of the impedance, anti-resonant frequency of the imaginary portion of the impedance, zero reactance frequency, phase angle and magnitude of the impedance, and others as described in the definition of the term sensor "spectral parameter". The "RFID sensor" may have an integrated circuit (IC) memory chip attached to the antenna or may not have an IC memory chip. An RFID sensor without an IC memory chip is an LCR sensor. An LCR sensor is composed of known components, such as at least one inductor (L), at least one capacitor (C), and at least one resistor (R), to form an LCR circuit.The term "disposable container" includes, but is not limited to, manufacturing or monitoring equipment and packaging that can be disposed of or preconditioned for reuse after use. Disposable packaging in the food industry includes, but is not limited to, food and beverage packaging and confectionery and confection boxes. Disposable monitoring components include, but are not limited to, disposable cartridges, dosimeters, and collectors. Disposable manufacturing containers include, but are not limited to, disposable vessels, bags, compartments, cans, fittings, and columns.The term "writing instrument / reader" includes, without being limited thereto, a combination of devices for writing and reading data into the memory of the memory chip and for reading the impedance of the antenna. Another term "writing instrument / reading device" is "interrogation device".In accordance with embodiments disclosed herein, an LCR or RFID sensor for displaying vapors, vapor mixtures, chemical and biological materials is described. As previously indicated, the RFID sensor includes an RFID tag coated with a temperature dependent response coefficient display material of a characteristic different from that of the LCR circuit. In one embodiment, a passive RFID tag may be used. As can be appreciated, an RFID tag may include an IC memory chip connected to an antenna coil for connection to a writing device / reader. The IC memory chip can read by illuminating the tag with a radio frequency (RF) and / or microwave carrier signal sent by the writing instrument / reader. When the RF and / or microwave field passes through the antenna coil, an alternating current (AC) voltage is generated across the coil. The voltage is rectified in the microchip to provide a direct current (DC) voltage for microchip operation. The IC memory chip starts to function when the DC voltage reaches a predetermined level. By detecting the RF and / or microwave signal backscattered from the microchip, the information stored in the microchip can be completely identified. The distance between the RFID tag / sensor and the reader / writer is governed by design parameters which include the operating frequency, the RF and / or microwave power level, the reader / writer receiving sensitivity, antenna dimensions, data rate, communication protocol and microchip power requirements. The distance between the "RFID sensor" without an IC memory chip (chipless RFID sensor or LCR sensor or LCR transducer) and the sensor reader is governed by the design parameters including the operating frequency, the RF or microwave power level, the sensor reader reception sensitivity, and the antenna dimensions.In one embodiment, a passive RFID tag may be used with or without an IC memory chip. Advantageously, a passive RFID tag is not dependent on a battery for operation. However, the communication distance between the writing instrument / reader and the RFID tag is typically limited to a close range because the passive tag is operated only with microwatts of the RF power from the writing instrument / reader. For passive markers operating at 13.56 MHz, the reading distance is typically no more than a few centimeters. The typical operating frequency range of 13.56 MHz passive RFID tags for digital ID writing / reading ranges from 13.553 to 13.567 MHz. The typical operating frequency range of 13.56 MHz passive RFID sensors for indicating environmental changes around the RFID sensor is from about 5 MHz to about 20 MHz, more preferably from 10 to 15 MHz. The requirement for this frequency range is to be able to identify the tag with a writing instrument / reader operating at 13.56 MHz while the sensor part of the RFID tag is operating from 5 to 20 MHz.Depositing display films on passive RFID tags generates chemical or biological RFID sensors. The RFID indication is made by measuring changes in the impedance of the RFID sensor as a function of environmental changes around the sensor, as will be further described below. If the frequency response of the antenna coil after deposition of the display film does not exceed the operating frequency range of the marker, then the information stored in the microchip can be identified with a conventional RFID reader / writer. An impedance analyzer (sensor reader) can read the impedance of the antenna coil to relate the changes in impedance to the chemical or biological materials of interest and correct for temperature instabilities around the sensor.In operation, after coating the RFID tag with a chemically sensitive film, both the digital tag ID and the impedance of the tag antenna can be measured. The measured digital ID provides information about the identity of the tag itself, such as an object on which that tag is mounted and the characteristics of the sensor (e.g., calibration curves for various conditions, manufacturing parameters, expiration date, etc.). For multi-component detection, multiple properties can be determined from the measured real and imaginary parts of the impedance of a single RFID sensor, as will be described further below.In summary and in accordance with the embodiments described herein, the sensor should have a number of characteristics to achieve detection of analytes in the presence of temperature variations. First, the selected transducer should include a multivariate output to independently detect the effects of various environmental parameters on the sensor. Second, the display material should have a retained response to an analyte over a wide range of temperature changes. The reaction to the relatively low analyte concentrations should not be completely suppressed by the relatively large temperature changes. Third, temperature-affected responses of the display material and transducer are allowed, but should be in different directions from the transducer's multivariate output response.To achieve these characteristics, in one embodiment, the display material has multiple response mechanisms to vapors, these response mechanisms being related to changes in the dielectric constants, resistance, and swelling of the display material, these changes not being fully related to each other and producing different patterns upon exposure to individual vapors and mixtures thereof. Further, the LCR transducer may have multiple components of the LCR response from the LCR circuit, where these multiple components of the LCR response originate from the various factors affecting the transducer circuit, non-limiting examples including material resistance and capacitance, contact resistance and capacitance between the transducer and the display material, and resistance and capacitance between the transducer substrate and the display material. The LCR converter may have multiple conditions of operation of the LCR circuit where an integrated circuit chip is part of the sensor circuit.One method of controlling the temperature corrected sensor response includes powering the integrated cleavage chip to affect the impedance spectral profile. The different impedance spectral profiles alter the temperature dependent sensor response based on interactions with various vapours and chemical and biological materials. The IC chip or memory chip on the resonant antenna contains a rectifier diode and can be operated at various power levels to affect the impedance spectral profile of the sensor. The differences in spectral profiles at different power levels are addressed in different values of F p, F 1, F 2, F z, Z p, Z 1, Z 2 and calculated values of C and R. In one embodiment, the improved temperature independent sensor operation is achieved by the appropriate selection of at least one power level of the IC chip or IC memory chip operation. In another embodiment, the improved temperature independent sensor operation is achieved by the proper selection of at least two power levels of the IC chip or IC memory chip operation and analyzing the sensor's combined impedance spectral profiles under different power levels. The supplying of the sensor with at least two power levels is carried out in the alternating manner between a relatively low and a relatively high power. Alternately supplying the sensor with at least two power levels is performed on the time scale that is at least five times faster than the dynamic changes in the measured environmental parameters. In all of these embodiments, the powering is at different power levels in the range of -50 dBm to +40 dBm, and provides the capability to achieve temperature independent sensor operation.The improved temperature independent LCR circuit operation is achieved by varying the operating performance of the integrated circuit chip to improve temperature dependent response. In particular, the sensor calibration for temperature independent operation is performed with at least two operating power levels of the integrated circuit chip of the sensor. The sensor is first operated at a rather low power so that the integrated circuit chip is substantially turned off (the power is between about -50 dBm and -10 dBm), and the temperature dependent coefficients of the transducer and the display material are determined in the presence and absence of analytes. Next, the sensor is operated at a rather high power so that the integrated circuit chip is substantially turned on (the power is between about -10 dBm and +40 dBm), and the temperature dependent coefficients of the transducer and the display material are determined in the presence and absence of the analytes.Referring now to FIG. 1, a display system 10 is provided to illustrate the principle of temperature independent selective vapor display using an RFID sensor 12 coated with a display material 14. The display material 14 has at least two temperature-dependent response coefficients of dielectric constant and resistance characteristics. In FIG. 2, the sensor 12 is a resonant circuit that includes an inductor-capacitor-resistor structure (LCR) coated with the display material 14. The LCR structure includes at least three temperature dependent response coefficients of the inductance L, capacitance C, and resistance R characteristics of the LCR circuit. The at least three temperature-dependent response coefficients of the characteristics of the LCR circuit differ from one another by at least about 5%. In addition, the at least two temperature-dependent response coefficients of the characteristics of the display material 14 differ by at least about 5% from the at least three temperature-dependent response coefficients of the characteristics of the LCR circuit. The display material 14 is applied to the display region between the electrodes constituting a sensor antenna 18 constituting the resonant circuit. As will be described below, the impedance response of the circuit is changed by applying the display material 14 to the resonant circuit. The sensor 12 may be a wired sensor or a wireless sensor. The sensor 12 may also include a memory chip 16 coupled to the resonant antenna 18 that is coupled to a substrate 20. The memory chip 16 may include manufacturing, user, calibration, and / or other data stored therein. The memory chip 16 is an integrated circuit device and includes an RF signal modulation circuit fabricated using a complementary metal oxide semiconductor (CMOS) process and a nonvolatile memory. The components of the RF signal modulation circuit include a diode rectifier, a power supply voltage regulator, a modulator, a demodulator, a clock generator, and other components.Figure 3 illustrates an alternative embodiment of the sensor 12 designated by the reference numeral 21, wherein a complementary sensor 23 comprising the display material 14 is mounted over the antenna 18 and the integrated circuit (IC) memory chip 16 to change the impedance response of the sensor. In another embodiment (not shown), a complementary sensor may be mounted over an antenna that does not have an IC memory chip and change the response of the impedance of the sensor. Non-limiting examples of complementary sensors include parallel connected sensors, resistive sensors, and capacitive sensors. Complementary sensors are described in U.S. Patent Application Serial No. 12 / 118,950, entitled "Methods and systems for calibration of RFID sensors," which is incorporated herein by reference.In one embodiment, a 13.56 MHz RFID tag may be used. During operation of the display system 10, the impedance Z(f) of the sensor antenna 18 and the digital sensor calibration parameters stored on the memory chip 16 may be obtained. Referring to FIG. 1, measurement of the resonant impedance Z(f) of the antenna 18 and reading / writing of digital data from the memory chip 16 are performed via mutual inductance coupling between the RFID sensor antenna 18 and the pickup coil 22 of a reader 24. As shown, the reader 24 may include an RFID sensor impedance reader 26 and an integrated circuit memory chip reader 28. The interaction between the RFID sensor 12 and the pickup coil 22 can be described using a general mutual inductance coupling circuit model. The model includes an inherent impedance Z C of the pickup coil 22 and an inherent impedance Z S of the sensor 12. The mutual inductance coupling M and the inherent impedances Z C and Z S are related by the total measured impedance Z T across the terminal of the pickup coil 22, as represented by the following equation: where ω is the radians carrier frequency and M is the coefficient of mutual inductance coupling M.The display is performed by monitoring the changes in the properties of the display material 14 as determined by the electromagnetic field generated in the antenna 18 (FIG. 2 ). After reading the RFID sensor 12 with the pickup coil 22, the electromagnetic field generated in the sensor antenna 18 extends from the plane of the sensor 12 and is affected by the dielectric properties of an adjacent environment, which provides the opportunity for measurements of physical, chemical or biological parameters.The display is performed by monitoring the changes in the properties of the display material 14 as detected by the electromagnetic field generated in the complementary sensor 23 (FIG. 3 ). After reading the RFID sensor 12 with the pickup coil 22, the electromagnetic field generated in the complementary sensor 23 extends from the plane of the complementary sensor 23 and is affected by the dielectric properties of an adjacent environment, which provides the opportunity for measurements of physical, chemical or biological parameters.FIG. 4 illustrates an example of measured responses of an example RFID sensor 12 including the sensor's full impedance spectra and multiple individually measured spectral parameters, according to embodiments of the invention. To selectively detect multiple vapors or fluids using a single RFID sensor, such as RFID sensor 12, the real Z re( f) and imaginary Z im( f) parts of the impedance spectra Z(f)=Z re( f)+jZ im( f) are measured by sensor antenna 18 coated with a display material and at least four spectral parameters are calculated from the measured Z re( F) and Z im( f) as shown in graph 30 of FIG. 4. Seven spectral parameters may be calculated as shown in the graph of Figure 4. These parameters include the frequency position F p and magnitude Z p of Z re( f), the resonant F 1 and antiresonant F 2 frequencies of Z im( f), the impedance magnitudes Z 1 and Z 2 at F 1- and F 2- frequencies, respectively, and the zero reactance frequency FZ. Additional parameters, such as a quality factor, may also be calculated. From the measured parameters, resistance R, capacitance C and other parameters of the resonance antenna 18 coated with a display film can also be determined. Multivariate analysis can be used to reduce the dimensionality of the impedance response from either the measured real Z re( f) and imaginary Z im( f) parts of the impedance spectra or the calculated parameters F p, Z p, F 1 and F 2 and possibly other parameters to a single data point in a multi-dimensional space for selective quantification of various vapors or fluids, as will be appreciated by those skilled in the art and as will be further described below.The accepted limitations of impedance spectroscopy in practical sensors for trace detection of analytes include relatively low sensitivity and prohibitively long acquisition times over the broad frequency range. Embodiments described herein improve the ability to measure changes in characteristics of the display material by applying the material to the electrodes of the LCR sensor resonant circuit. Similarly, the disclosed embodiments promote the ability to measure changes in properties of the fluid proximate the electrodes of the LCR sensor resonant circuit. Experimental testing investigated the effects of a changing dielectric constant on the display electrodes both with and without a resonator. Compared to conventional impedance spectroscopy, the bare resonant LCR sensor gave at least 100 times an improvement in signal-to-noise (SNR) over the narrowest measured range of Δε with the corresponding improvement in the detection limit of determinations of the dielectric constants.Operation of the LCR sensor as analyzed using tools of multivariate analysis offers an advantage of improved selectivity over processing of individual reactions of individual sensors. In particular, test results indicate the relationships between F p and Z p and the relationships between the calculated sensor resistance R and the calculated sensor capacitance C have much less selectivity between reactions to various vapors or fluids as compared to the relationships between multivariable parameters that show more variation, as discussed in detail below. Further, the LCR sensors exhibit independent contact resistance and contact capacitance responses that improve the overall selectivity of the multivariable response of the LCR sensors. This selectivity improvement originates from the independent contributions of contact resistance and contact capacitance responses to the sensor's equivalent circuit responses.The various components of the RFID sensor, such as sensors 12 and 21 shown in FIGS. 1-3, each have different physical properties, such as, but not limited to, thermal conductivity, thermal expansion, elastic modulus, electrical resistance, impedance, and so forth. Such properties can be influenced by changes in temperature. The temperature-dependent response coefficient of a property is defined as the relative change of the property when the temperature is changed by a fixed amount such as 1°C. The property may vary with temperature, for example, in a linear manner or polynomial, logarithmic, or exponential. Some properties may increase with temperature and other properties may decrease with temperature. For example, the temperature-dependent response coefficient of impedance between the display material 14 and another component of the RFID sensor 12 or 21 may be different, such as, but not limited to, the memory chip 16, the antenna 18, the substrate 20, the coil 22, the integrated circuit (IC) chip, the transducer, or film. In other words, the impedance of the display material 14 may vary with temperature differently than the other components of the RFID sensor 12 or 21. In contrast, for the same change in temperature of 1°C, the impedance of antenna 18 of RFID sensor 12 or 21 may increase by 0.8 ohms. The percentage difference between the two temperature-dependent reaction coefficients of the impedance is about 22%. In various embodiments, the absolute values of the temperature-dependent response coefficients of a property of the LCR circuit and the display material 14 may be between about 0.5% and 500%, 2% and 100% or 5% and 50%. Based on the differences in the temperature-dependent response coefficients of the LCR circuit and the display material 14, the RFID sensor 12 or 21 can selectively detect analyte fluid from an analyzed fluid mixture substantially independent of temperature.FIG. 5 is a flow chart 40 showing an exemplary method of analyzing a vapor in the presence of a variable temperature using the RFID sensor 12 or 21, wherein the temperature-dependent response coefficients of the impedance of the display material 14 and the other components of the RFID sensor 12 or 21 are not the same. In the following stages, a multivariate analysis of the measured impedance of the RFID sensor 12 or 21 is used to provide a temperature independent vapor response. In a first stage 42, the RFID sensor 12 or 21 performs the displaying of a vapor by monitoring the changes in the properties of the display material 14 as determined by the electromagnetic field generated in the antenna 18 as described in detail above. In a second stage 44, temperature fluctuations occur which influence the impedance of the RFID antenna circuit and of the display material 14. However, the impedance of the RFID antenna circuit and the display material 14 are not equally affected due to the differences in the temperature-dependent response coefficients of the impedance of the RFID antenna circuit and the display material 14. The differences in the temperature-dependent response coefficients of the impedance of the RFID antenna circuit and display material 14 affect the measured impedance spectra of the resonant antenna. In a third stage 46, the RFID sensor 12 or 21 indicates variations in the concentration of the vapor to be quantified. Temperature fluctuations can continue to occur in the third stage 46. In a fourth stage 48, the RFID sensor 12 or 21 measures the impedance spectra of the resonant antenna. Various spectral parameters can be calculated from the measured real and imaginary parts of the impedance spectra, as described in detail above. In a fifth stage 50, the multivariate analysis of the full impedance spectra or calculated spectral parameters is performed as described in detail below.In a sixth stage 52, suitable multivariate calibration values or calibration coefficients stored in the memory chip 16 of the RFID sensor 12 or 21 are obtained. The calibration coefficients are determined during experimental testing of the RFID sensor 12 or 21. For example, the RFID sensor 12 or 21 is used to indicate different vapor concentrations at different temperatures. PCA or any other multivariate analytical method or combination of methods can then be used to generate response curves for each of the measured temperatures. Best fit curves that best fit each of the response curves are determined and functions, such as polynomial functions, are determined to mathematically represent the best fit curves. Each function includes a plurality of numerical coefficients that characterize the function. These coefficients are then used as calibration coefficients which can be stored, for example, in memory chip 16 as a look-up table. During operation, the concentration and / or temperature of the vapor indicated by the RFID sensor 12 or 21 may not correspond to one of the experimental concentrations or temperatures. However, by using the experimentally determined calibration coefficients in the look-up table, an interpolating function (i.e., response curve) can be generated that best represents the predicted behavior of the vapor at the indicated concentration and temperature.In a seventh stage 54, the RFID sensor 12 or 21 quantitates the concentration of the vapor regardless of the variable temperature based on the multivariate analysis performed in stage 50 and the response curve determined in the sixth stage 52. The results of the fifth stage 50 multivariate analysis are inserted into the interpolated function determined in the sixth stage 52 to calculate the vapor concentration. The calculated vapor concentration is accurate because the effect of the variable temperature on the RFID sensor 12 or 21 has been taken into account in the previous stages of the flowchart 40. As shown in the flow chart 40, there is no need for a separate temperature sensor because the single RFID sensor 12 or 21 is able to provide the temperature independent vapor response based on the multivariate analysis of the measured impedance values. The RFID sensor 12 may therefore be smaller, less expensive, less complicated, and / or more reliable than other sensor systems that use a separate temperature sensor.Various display materials may be advantageously employed on the display region of the LCR resonant sensor because analyte-induced changes in the display material film affect the impedance of the LCR antenna circuit through the changes in material resistance and capacitance, contact resistance and capacitance between the transducer and the display material, and in resistance and capacitance between the transducer substrate and the display material. Such changes result in diversity in the response of a single RFID sensor and offer the opportunity to replace a whole series of conventional sensors with a single LCR or RFID sensor.Display films for the disclosed LCR and RFID sensors may include a variety of materials as long as the environmental changes are detectable by changes in the parameters of the LCR resonant circuit. Further, a temperature-dependent response coefficient of a property of the display films is different from that of the LCR circuit as described in detail above. Non-limiting examples of possible display film materials are a hydrogel such as poly(2-hydroxyethyl methacrylate), a sulfonated polymer such as nafion, an adhesive polymer such as silicone adhesive, an inorganic film such as sol-gel film, a film containing biological material such as DNA, antibody, peptide or other biomolecules deposited as a film, a film containing biological material such as DNA, antibody, enzyme, peptide, polysaccharide, protein, aptamer or other biomolecules or viruses, spores, cells deposited as part of an inorganic or polymeric film, a composite film, a nanocomposite film, a functionalized carbon nanotube film or a film, which is made of gold nanoparticles functionalized at the surface, electrically spun polymers, inorganic and composite nanofibers, and nanoparticles having an electrical property incorporated into a matrix having a different dielectric property.Display materials may be selected to have different dielectric constants ranging from about 2 to about 40. Non-limiting examples include polyisobutylene (PIB, ε' r= 2,1), ethylcellulose (EC, ε' r= 3,4), polyepichlorohydrin (PECH, ε' r= 7,4), cyanopropylmethyl phenylmethylsilicone (OV-225, ε' r= 11), dicyanoallylsilicone (OV-275, ε' r= 33). The use of these materials provides the ability to adjust the relative direction of the display response upon exposure to different dielectric constant vapors. The different partition coefficients of vapours into these or other display materials further modulate the diversity and relative direction of the response."Composite materials" are materials made from two or more materials having significantly different physical or chemical properties that remain separate and distinct at a macroscopic level within the final structure. For example, the two or more materials may have different temperature-dependent response coefficients for a property such as impedance. Non-limiting examples of composite materials include carbon black composite materials with poly(4-vinylphenol), poly(styrene-co-allyl alcohol), poly(vinyl chloride-co-vinyl acetate), and other materials. "nanocomposite materials" are materials made from two or more materials having significantly different physical or chemical properties that remain separate and different at a nanolevel within the final structure. Non-limiting examples of nanocomposite materials include carbon nanotube nanocomposite materials with polymers (such as poly(N-vinylpyrrolidone), polycarbonate, polystyrene, etc.), semiconducting nanocrystal quantum dot nanocomposite materials with polymers, metal oxide nanowires and carbon nanotubes, metal nanoparticles, or nanotubes functionalized with carbon nanotubes.Display materials exhibit analyte responses that can be described by one or more of three response mechanisms of LCR or RFID sensors, such as resistance changes, dielectric constant changes, and source changes. A display composite material can be constructed that includes multiple different individual display materials, each of which responds to analytes by predominantly different reaction mechanisms. Such display composites produce improved diversity in the multivariate response. Such display composites may be homogeneously or inhomogeneously mixed or patterned locally over specific parts of the LCR resonator.For example, a wide range of metal oxide semiconductor materials (e.g., ZnO, TiO 2, SrTiO 3, LaFeO 3 etc.) Changes in resistance when exposed to analyte gases, but some mixed metal oxides (e.g., CuO-BaTiO 3, ZnO-WO 3) change their dielectric constant / capacitance when exposed to analyte vapors. By combining these materials, either as mixtures or by spatially separate deposition on the same sensor, their separate contributions to the local environment surrounding the sensor are used to promote diversity of reaction mechanisms for a single analyte, which promotes selectivity.As another example, ligand-coated conductive (e.g., metal) nanoparticles are used as vapor indicating materials because of their large changes in resistance due to localized swelling induced by analyte adsorption into the ligand shell and the subsequent change in tunneling efficiency between adjacent conductive nanoparticles and changes in environmental dielectric constants between these conductive nanoparticles. In combination with a dielectric polymer [non-limiting examples include silicones, poly(etherurethane), polyisobutylenesiloxanefluoroalcohol, etc.], conjugated polymer [polyaniline, polythiophene, poly(vinylferrocene), poly(fluorene) diphenylpropane, poly(3,4-ethylenedioxythiophene) polypyrrole, bilypyrrole], or any other material [non-limiting examples include porphyrins, metal porphyrins, metal phthalocyanines, carbon nanotubes, semiconducting nanocrystals, metal oxide nanowires] that react to analyte adsorption with more marked changes in capacitance or resistance, a sensor was developed with a wider range of analyte responses.To avoid potentially adverse effects of dissimilar materials in a composite display material (e.g., a high dielectric constant medium that suppresses conduction in a conductive filler material) on each other, these material components are selected to undergo local phase separation due to hydrophilic / hydrophobic interactions or mutual inblendability, allowing the various mechanisms that are active in each component to be displayed by the sensor. In another embodiment, a display composite material may be formed as sectors of individual materials deposited adjacent to each other on a single sensor. In another embodiment, a display composite material may be formed as layers of individual materials deposited one on top of the other on a single sensor.In certain embodiments, display materials may be porphyrins, metal porphyrins, metal phthalocyanines, and related macrocyclics. In these materials, gas sensing is done either by π-stacking the gas into organized layers of the flat macrocells or by gas coordination to the metal center without void confinement. Metalloporphyrins offer several mechanisms of gas reaction, including hydrogen bonding, polarization, polarity interactions, metal center coordination interactions, and molecular arrangements. Molecules of porphyrins, metal porphyrins, metal phthalocyanines, and related macrocyclics can also be assembled into nanostructures.Other types of materials include oriented nanostructures in which the orientation is performed by various known methods (dielectrophoretic orientation, orientation during material polymerization, orientation due to spatial confinement, orientation during slow solvent evaporation, and others), self-assembled (self-assembled) structures such as colloidal crystal structures of the same size of particles, multilayers of colloidal crystal films where different layers have different sizes of assembled particles, nanoparticle assemblies where the particles have a core-shell structure where the particle core has a dielectric property and the particle shell has a different dielectric property, bioinspirated materials, zero-dimensional nanomaterials, one-dimensional nanomaterials, two-dimensional nanomaterials, and three-dimensional nanomaterials.Self-assembled structures include colloidal crystal structures of the same size of particles, multilayers of colloidal crystal films where different layers have different sizes of the assembled particles, nanoparticle assemblies where the particles have core-shell structure, the particle core having a dielectric property and the particle shell having a different dielectric property. Non-limiting examples of materials of self-assembled (self-assembled) colloidal crystal structures include polystyrene, polymethyl methacrylate, polyvinyl toluene, styrene / butadiene copolymers, styrene / vinyltoluene copolymers and silica. The typical diameters of these colloidal particles will depend on the type of material and may range from 50 nanometers to 25 micrometers. Non-limiting examples of multiple layer colloidal crystal structures include at least one layer of particles of one size assembled as a colloidal array on the sensor substrate and at least one layer of particles of a different size assembled as a colloidal array on the previous layer. Non-limiting examples of bioinspirated materials include superhydrophobic or superhydrophilic coatings.Non-limiting examples of zero-dimensional nanomaterials include metal nanoparticles, dielectric nanoparticles, core-shell nanoparticles, and semiconducting nanocrystals. Non-limiting examples of one-dimensional nanomaterials include nanotubes, nanowires, nano rods, and nanofibers. Non-limiting examples of two-dimensional nanomaterials include graphene. Non-limiting examples of three-dimensional nanomaterials include self-assembled films of various layers of colloidal beads.Non-limiting examples of nanoparticles having a core-shell structure, wherein the particle core has a dielectric property and the particle shell has another dielectric property, include: metal (gold, silver, its alloy, etc.) core nanoparticles; and organic shell layers (dodecanethiol, decanethiol, 1-butanethiol, 2-ethylhexanethiol, hexanethiol, tert-dodecanethiol, 4-methoxytoluenethiol, 2-mercaptobenzoxazole, 11-mercapto-1-undecanol, 6-hydroxyhexanethiol), polymeric core (polystyrene, polymethyl methacrylate), and inorganic shell (silica), insulating core (polystyrene, polymethyl methacrylate, silica), and semiconducting shell (carbon nanotubes, TiO 2, ZnO, SnO 2, WO 3) and carbon nanotube core decorated with metal nanoparticles. The metal nanoparticles (gold, silver, their alloy, etc.), core nanoparticles, and organic shell layers can be further modified with organic and polymeric molecules. Non-limiting examples of organic molecules include porphyrins, metal porphyrins, metal phthalocyanines and macrocyclics, cavitands, supramolecular compounds. Non-limiting examples of polymeric molecules include polymeric molecules having different dielectric constants in the range of 2 to 40. Non-limiting examples include polyisobutylene (PIB, ε' r= 2,1), ethylcellulose (EC, ε' r= 3,4), polyepichlorohydrin (PECH, ε' r= 7,4), cyanopropylmethyl phenylmethylsilicone (OV-225, ε' r= 11), dicyanoallylsilicone (OV-275, ε' r= 33). A non-limiting example of the preparation of these display materials includes (1) preparation of metal core nanoparticles having an organic shell in a solvent, (2) mixing this composition with another composition of polymeric or organic molecules in a solvent, (3) preparing a display film on an LCR or RFID transducer from this combined mixture. The use of these materials in combination with metal core nanoparticles provides the ability to adjust the relative direction of the display response upon exposure to different dielectric constant vapors. The different partition coefficients of vapours into these and other display materials further modulate the diversity and relative direction of the response.Other display materials include semiconducting metal oxides, zeolites, cavitands, ionic liquids, liquid crystals, crown ethers, enzymes, poly silsesquioxanes, metal organic hydrocarbons (MOFs).Other display materials include synthetic dielectric and conductive polymers having different polymer pendant functionalities and different polymer formulations, biomolecules for the display of the gas phase, cavitands with dominant intra-cavity complexation and fully suppressed non-specific out-of-cavity adsorption of vapours by deposition of cavitands, porphyrins and related molecules as single molecules and assembled into polymers and nanostructures.In order to further improve the temperature-corrected response, the coating of display films with membrane auxiliary filter films may be carried out. Non-limiting examples of these filter films include zeolite, metal organic builder and cavitandene filters.These various display materials, given as non-limiting examples, are provided on the display region of the LCR or RFID resonant sensor because analyte-induced changes in the display material film affect the impedance of the LCR antenna circuit by the changes in material resistance and capacitance, contact resistance and capacitance between the transducer and the display material, resistance and capacitance between the transducer substrate and the display material. Such changes provide diversity in the response of a single RFID sensor and provide the opportunity to replace an entire array of conventional sensors with a single LCR or RFID sensor, as illustrated below in terms of the experimental data.EXPERIMENTAL DATAAntenna resonant structures as described above have been used to demonstrate the disclosed techniques. Various display materials were applied to the resonant antennas by conventional draw coating, drip coating and spray methods. Measurements of the impedance of the RFID sensors were performed, for example, with a network analyzer (Model E5062A, Agilent Technologies, Inc., Santa Clara, CA) under computer control using Lab VIEW. The network analyzer was used to scan the frequencies over the range of interest (i.e., the resonant frequency range of the LCR circuit) and collect the impedance response from the RFID sensors. Temperature changes were generated by placing the RFID sensor in an environmental chamber and controlling the temperature with about 0.1°C precision and accuracy.For gas sensing, various concentrations of vapors were generated using a built-in computer controlled vapor generation system. The collected impedance data were analyzed using Excel (MicroSoft Inc., Seattle, WA) or KaleidaGraph (Synergy Software, Reading, PA) and PLS_Toolbox (Eigenvector Research, Inc., Manson, WA) operated with Matlab (The Mathworks Inc., Natick, MA).Example. Accurate Detection of Moisture Levels at Various Temperatures with a Single SensorAs shown in Figures 6-11, test results were obtained to show the accurate detection of water vapor at various temperatures using a single sensor, such as sensor 12 described above. Such test results may be used to generate calibration coefficients as discussed above with reference to FIG. 5. As shown in Figures 6, 7 and 9, the sensor was exposed to various concentrations of water vapor at the following temperatures: 25°C, 30°C, 35°C and 40°C. The concentrations of water vapor tested were about 0 ppm, 2807 ppm, 4210 ppm, 5614 ppm, 7017 ppm and 8421 ppm.The indicator material used to coat the RFID tag was carefully selected and gave the ability to accurately detect the concentrations of water vapor at the four temperatures. In the present experiment, the display material selected was poly(etherurethane) (PEUT) dissolved in a non-polar solvent such as dichloromethane. During the experiment, the RFID sensor was gradually exposed to the various water vapor concentrations at each of the four temperatures. Specifically, measurements were made by placing the sensor in an environmental chamber with computer controlled temperature programming. The generation of various concentrations of water vapor was accomplished using a vapor generation system with computer controlled vapor concentration programming. The test was carried out in stages, increasing the concentration of water vapor with each stage. By monitoring changes in various properties and examining various reactions over the four temperatures and with increasing concentration levels, the data demonstrated the ability to accurately quantify water vapor concentration independent of temperature in the experiment described above.FIGS. 6 and 7 show examples of temperature effects on the individual reactions of the RFID sensor when the RFID sensor was used for measurements of a vapor (i.e., water vapor in this example). Plots 55 and 56 show significant temperature dependence of capacitance response C and resistance response R of the sensor coated with the film after the sensor was exposed to water vapor concentrations of about 0, 2807, 4210, 5614, 7017 and 8421 ppm. In other words, the capacitance and resistance response change with respect to temperature. In Figure 8, the capacitance response C is plotted against the resistance response R of the film coated sensor at various temperatures of about 25, 30, 35 and 40°C and when exposed to water vapor concentrations of about 0, 2807, 4210, 5614, 7017 and 8421 ppm. Each line in Figure 8 corresponds to the sensor response at a particular concentration of water vapor at various temperatures. The line with the filled circles corresponds, for example, to the sensor reaction with respect to 8421 ppm of water vapor at four temperatures. The upper left part of the line corresponds to the reaction at 40° C., while the right lower part corresponds to the line corresponds to the reaction at 25° C. Figure 8 shows that temperature significantly affects the relationship between capacitance and resistance responses. It is thus difficult to distinguish between the effects of temperature and water vapor concentration based on Fig. 8. However, by applying the multivariate analysis of the sensor response as described below, significant improvements in distinguishing between effects of temperature and vapor concentration are obtained.A convenient way of analyzing various responses of the sensor is to use principal component analysis (PCA) to generate a multivariate signature. As will be appreciated, PCA analysis is a mathematical process known to those skilled in the art that is used to reduce multidimensional data sets to smaller dimensions for analysis. For example, the various reactions for each vapor at a given concentration can be reduced to a single data point and from that a single reaction for each vapor that can be represented as a vector can be recognized as shown in FIG. 9. FIG. 9 represents a PCA plot 60 of the various reactions of the six concentrations of water vapor at the four temperatures described above. Water vapor concentrations increase in the direction of arrow 62. In other words, the results at the highest concentration of water vapor, 8421 ppm, appear near the left side of plot 60, and the results at the lowest concentration of 0 ppm appear near the right side of plot 60, with the results overlapping at 0 ppm in a single data point for the four temperatures. As will be appreciated, FACTOR 1 represents the response with the greatest variation while FACTOR 2 represents the response with the next greatest variation. Compared to Figure 8, the lines representing different vapor concentrations in Figure 9 are further away from each other, indicating the improvements in distinguishing between temperature and vapor concentration effects made possible by the multivariate analysis. As shown in Fig. 9, the results at the four temperatures are clearly distinguishable from each other, although the water vapor concentrations show a larger change with respect to FACTOR 1 at 25°C compared with those at 40°C. Sensors according to various embodiments are thus capable of correcting these temperature effects in order to provide accurate information about the water vapor concentration. Specifically, best fit curves and corresponding functions can be developed for each of the four temperatures. The coefficients of these functions can then be used as calibration coefficients, as described in detail above. The current test data provides support for a sensor capable of differentiating between water vapor concentrations regardless of temperature.Using the functions and calibration coefficients based on the data collected at the experimental temperatures, the effect of the temperature on sensor measurements at other temperatures may be extrapolated or interpolated. Thus, for example, one may be able to extrapolate water vapor concentrations between 25° C. and 30° C. Such additional extrapolated data can then also be used to selectively detect water vapor concentrations at other temperatures. By varying the selected display material, selective detection of vapours other than water at temperatures and concentrations other than those described above using a single RFID sensor was shown.Other plots may be generated to further show how data collected for a single RFID sensor is used to quantify water vapor concentrations independent of temperature. For example, the data of FIG. 9 was used to generate the graph 70 of a developed quadratic model of the multivariate response of FACTOR 1 and FACTOR 2 compared to the water vapor concentration shown on the left side of FIG. 10. In other words, a quadratic model was developed to represent the results of the PCA graphical representation 60 shown in FIG. 9. Predicted values of water vapor concentration at the various conditions described in detail above were calculated using the quadratic model and compared to the actual measured values in graph 72 of FIG. 10. As shown in graph 72 of FIG. 10, the points are near a line corresponding to an inclination of one. The standard error of the quadratic model is, for example, about 212 ppm water vapor (i.e., 0.7% relative humidity). The predicted values are thus closely related to the actual values, demonstrating the predictiveness of the example sensor and method.Similarly, data from Figure 9 was used to generate the developed cubic model graph 80 of FACTOR 1 and FACTOR 2 of the multivariate response compared to the water vapor concentration shown on the left of Figure 11. In other words, a cubic model was developed to represent the results of the PCA graphical representation 60 shown in FIG. 9. Predicted values of water vapor concentration under the various conditions described in detail above were calculated using the cubic model and compared with the actual measured values in the graph of 82 of Figure 11. As shown in graph 82 of FIG. 11, the points are near a line corresponding to a slope of one. The standard cubic model error is, for example, about 188 ppm water vapor (i.e., 0.63% relative humidity). As with the quadratic model of FIG. 10, the predicted values are closely related to the actual values, which in turn demonstrates the predictiveness of the exemplary sensor and method. In other embodiments, other polynomial models, besides the quadratic and cubic models, may also be used.While only certain features of the invention have been shown and described herein, many modifications and changes will occur to those skilled in the art. It is therefore to be understood that the appended claims cover all such modifications and changes as fall within the true spirit of the invention.Methods and sensors for selectively indicating fluids are provided. A sensor includes an inductor-capacitor-resistor (LCR) resonant circuit and a display material disposed over a display region. The display region includes at least a portion of the LCR circuit. Temperature dependent response coefficients of the inductance L, capacitance C, and resistance R characteristics of the LCR circuit and display material differ by at least about 5%. The difference in temperature-dependent response coefficients of the properties of the LCR circuit and the display material allows the sensor to selectively detect analyte fluid from an analyzed fluid mixture, substantially independent of temperature.

Claims

A method of detecting chemical or biological materials in a fluid, comprising: measuring (48) real parts and imaginary parts of impedance spectra of a sensor resonant antenna (18) coated with a display material (14) at a plurality of temperatures, wherein temperature dependent response coefficients of a property of the sensor resonant antenna (18) and the display material (14) differ from each other; calculating (48) from each of the measured impedance spectra at least six spectral parameters of the sensor resonant antenna (18) coated with the display material (14); performing a multivariate analysis of the spectral parameters (50); and reducing the spectral parameters to a single data point per measured impedance spectrum at a temperature to selectively identify an analyte; and determining from the reduced spectral parameters one or more environmental parameters using stored calibration coefficients (52), wherein the determination of the one or more environmental parameters is independent of temperature (54).The method of claim 1, wherein the stored calibration coefficients are based on the effects of the various temperature dependent response coefficients of the characteristics of the sensor resonant antenna (18) and the display material (14) on the impedance spectrum.The method of claim 1, wherein measuring the impedance spectra and calculating at least six spectral parameters comprises measuring over a resonant frequency range of the sensor resonant antenna (18).The method of claim 1, wherein calculating at least six spectral parameters comprises calculating a frequency position (F p) of the real part of the respective impedance spectrum and a size of the real part (Z p) of the respective impedance spectrum.The method of claim 1, wherein calculating at least six spectral parameters comprises calculating a resonant frequency (F 1) of the imaginary part of the respective impedance spectrum and an anti-resonant frequency (F 2) of the imaginary part of the respective impedance spectrum.The method of claim 1, wherein reducing the spectral parameters to a single data point comprises computing a multivariate signature.The method of claim 1, comprising operating an integrated circuit chip at a plurality of power levels such that an inductor-capacitor-resistor (LCR) resonant circuit is operated at a plurality of conditions.

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