Patent Publication Number: US-2010109637-A1

Title: Sensor system and method

Description:
This application is a Continuation of U.S. patent application Ser. No. 11/738,795, filed on Apr. 23, 2007, which is a Continuation-in-Part (CIP) of U.S. patent application Ser. No. 11/557,022, filed on Nov. 6, 2006, all of which are hereby incorporated by reference, in their entirety. 
    
    
     BACKGROUND 
     The present invention relates generally to sensors for detecting the presence of biological and biochemical target substances, and more particularly to sensors that rely on reactions between biological and biochemical target substances and target recognition element types disbursed over a sensing surface to produce an electrical charge detectable by electronic means. It relies on a combination of semiconductor integrated circuitry in combination with digital signal processing techniques to optimize the detection process and negate the undesirable effects of environmental and electrical noise and other perturbations that produce errors and decrease sensitivity. 
     Sensors, particularly biochemical sensors, have application in fields such as medical diagnostics, industrial safety, environmental monitoring and bioterror prevention for detection, identification and quantification of diseases, infectious agents, and toxic elements. They are also useful for detection, identification and quantification of biochemical elements that are beneficial to the human population and the environment. They may generally be used for detection of various biochemical substances such as viruses, bacteria, spores, allergens and other toxins. Biochemical sensors may also be useful for medical diagnostics for detecting diseases such as avian influenza and Human Immunodeficiency Virus (HIV-1)) infection. Whether found in medical laboratories or in industrial complexes for monitoring ambient air quality, sensors must be capable of rapid detection and identification of biochemical substances as well as notification to those responsible for such activities. 
     A major limitation of existing sensors and biochemical sensors, particularly when used in a field environment, is the detection sensitivity that is limited by various external factors. Detection sensitivity is an important sensor parameter that determines a minimum detectable level of particular biochemical target substances, as well as provides greater distinction among biochemical target substances. These factors may include external noise from various sources, temperature variations, electromagnetic radiation, power source perturbations, humidity, exposure to cosmic radiation and other environmental distortions. These factors degrade the signal-to-noise ratio of most biochemical sensors, which lowers detection sensitivity. Some of these factors may also cause an operating point of the sensor circuitry to drift from an optimal value, which can also lower detection sensitivity. 
     SUMMARY 
     The present invention provides a means for detecting the presence of one or more biochemical target substances, such as toxins, pathogens, nucleic acids, proteins, viruses, bacteria, spores, allergens, toxins and enzymes. It is capable of providing a high level of detection sensitivity through the use of an integrated differential pair of field effect transistors having a common substrate and common source, collocated in close proximity on a common silicon substrate. The common substrate also includes a temperature sensor and heating element. The common substrate, common source, temperature sensor and heating element are controlled by a digital signal processor for optimizing performance, including detection sensitivity. The use of a differential pair of field effect transistors reduces the effects of common mode perturbations to the differential pair. 
     An embodiment of the of the invention is a sensor system for detecting one or more target substances, comprising one or more target recognition element types disbursed over a sensor gate area of a differential pair of field effect transistors for sensing an electrical charge created when the one or more target recognition element types react with the one or more target types. The sensed electrical charge modulates a sensor channel of the differential pair field effect transistors to provide a differential output signal signature in which the differential pair of field effect transistors comprises a sensor field effect transistor and a reference field effect transistor having a common substrate connection and a common source connection controlled by a digital signal processor. A reference gate area of the reference field effect transistor is isolated from the effects of the sensed electrical charge created on the sensor gate area, the digital signal processor for monitoring parameters of the differential pair, executing optimization algorithms, and controlling the operating characteristics to provide a differential output signal signature of the differential pair based on the optimization algorithms. The digital signal processor measures, processes, identifies and stores a differential output signal signature from the differential pair of field effect transistor when a reaction of the one or more target recognition element types with the one or more target types is sensed by the sensor gate area. There is a means for notifying a user of the detection. Detection can be continuous, instantaneous and occur in real-time. 
     The invention comprises a sensor system for detecting one or more target substances, comprising: one or more target recognition element types disbursed over a sensor gate area of a differential pair of field effect transistors. A digital signal processor monitors parameters of the differential pair of field effect transistors and controls operating characteristics of the differential pair of field effect transistors to an optimum operating range for signal sensing. The differential pair of field effect transistors senses an electrical charge created by a reaction between the one or more target recognition element types and the one or more target substances in proximity of the sensor gate area, and provides a responsive output signal. The digital signal processor measures, processes, identifies and stores the responsive output signal signature, and notifies a user of an identifying result. 
     A specific target recognition element of the sensor system may react with one or more specific target types, that is, a first target recognition element type may react with a first target type. The sensor system may further comprise an operating structure of the differential pair of field effect transistors selected from the group consisting of p-channel enhancement mode, p-channel depletion mode, n-channel enhancement mode, and n-channel depletion mode. In the sensor system, the differential pair of field effect transistors may be fabricated on a common silicon substrate in close proximity to one another for minimizing differences in environmental and electrical influences between both field effect transistors in the differential pair. In the sensor system, the digital signal processor may control the operating characteristics of the differential pair by controlling a common substrate voltage, a common source current, and a quiescent drain voltage of the reference field effect transistor based on the optimization algorithms. The sensor system may further comprise a temperature sensor and a heating means fabricated on a single silicon substrate with the differential pair of field effect transistors. The digital signal processor of the sensor system may read the temperature sensor signal and control the temperature of the single silicon substrate by controlling a signal to the heating means. The temperature sensor and heating means of the sensor system controlled by the digital signal processor may be used for self-cleaning the sensor gate area, for preparing the sensor gate area for disbursement of one or more target recognition element types, and for maintaining a stable temperature during normal sensing operations. A single target recognition element type of the sensor system disbursed over the sensor gate area may react with only a single target type for producing a unique time-varying, signature output signal from the sensor field effect transistor and reference field effect transistor of the differential pair. The time-varying signature output signal comprises an amplitude and a plurality of frequencies. The digital signal processor of the sensor system may include a memory having a plurality of stored signature output signals for comparing with the measured signature output signal and identifying the single target type. A first target recognition element type of the sensor system disbursed over the sensor gate area may react with only a first target type and a second target recognition element type disbursed over the sensor gate area may react with only a second target type for producing a unique time-varying, superimposed first and second signature output signal from the sensor field effect transistor and reference field effect transistor of the differential pair. The digital signal processor of the sensor system may include a memory having a plurality of stored signature output signals for comparing the stored signature signals with the measured superimposed first and second signature output signal and identifying the first and second target type. 
     The recognition element may be a protein, nucleic acid, inorganic molecule or and organic molecule. The recognition element may also be an antibody, antibody fragment, oligonucleotide, DNA, RNA, aptamer, enzyme, cell fragment, receptor, bacteria, bacterial fragment, virus or viral fragment. The target substance may be a molecule, compound, complex, nucleic acid, protein, virus, bacteria, bacterial fragment, cell or cell fragment. The target substance may be a protein, nucleic acid, inorganic molecule or and organic molecule. 
     Another embodiment of the present invention includes sensor array comprising two or more sensor systems described above. The sensor array may comprise two or more sensor systems for detecting the presence of two or more target types. The sensor array may comprise a first sensor system for detecting the presence of a first target type and a second sensor system for detecting the presence of a second target type. 
     Yet another embodiment of the present invention is a sensor method for detecting the presence of one or more target types, comprising the steps of disbursing one or more target recognition element types over a sensor gate area of a differential pair of field effect transistors for sensing an electrical charge created when the one or more target recognition element types react with the one or more target types, the sensed electrical charge modulating a sensor channel of the differential pair field effect transistors, controlling a common substrate connection and a common source connection of the differential pair of field effect transistors comprising a sensor field effect transistor and a reference field effect transistor by a digital signal processor, wherein a reference gate area of the reference field effect transistor is isolated from the effects of the sensed electrical charge created on the sensor gate area, determining characteristics of the differential pair, executing optimization algorithms, and controlling the operating characteristics of the differential pair based on the optimization algorithms by the digital signal processor, measuring, processing, identifying and storing a differential output signal signature from a sensor field effect transistor and a reference field effect transistor of the differential pair by the digital signal processor when a reaction of the one or more target recognition element types with the one or more target types is sensed by the sensor gate area, and notifying a user of the detection. The disbursing step may comprise disbursing a specific target recognition element over a sensor gate area of a differential pair of field effect transistors for sensing an electrical charge created when the one or more target recognition element types react with the one or more target types, the sensed electrical charge modulating a sensor channel of the differential pair field effect transistors. The sensor method may further comprise selecting an operating structure of the differential pair of field effect transistors from the group consisting of p-channel enhancement mode, p-channel depletion mode, n-channel enhancement mode, and n-channel depletion mode. The sensor method may further comprise fabricating the differential pair of field effect transistors on a common silicon substrate in close proximity to one another for minimizing differences in environmental and electrical influences between both field effect transistors in the differential pair. The controlling step may further comprise controlling the operating characteristics of the differential pair by controlling a common substrate voltage, a common source current, and a quiescent drain voltage of the reference field effect transistor based on the optimization algorithms. The sensor method may further comprise fabricating a temperature sensor and a heating means on a single silicon substrate with the differential pair of field effect transistors controlled by the digital signal processor. The sensor method may further comprise reading the temperature sensor signal and controlling the temperature of the single silicon substrate by controlling a signal to the heating means by the digital signal processor. The sensor method may further comprise self-cleaning the sensor gate area, preparing the sensor gate area for disbursement of one or more target recognition element types, and maintaining a stable temperature during normal sensing operations by controlling the temperature sensor and heating means by the digital signal processor. The disbursing step may comprise disbursing a single target recognition element over a sensor gate area of a differential pair of field effect transistors for sensing an electrical charge created when the target recognition element reacts with the one or more target types, the sensed electrical charge modulating a sensor channel of the differential pair field effect transistors producing a unique time-varying signature output signal from the sensor field effect transistor and reference field effect transistor of the differential pair. The sensor method may further comprise storing a plurality of signature output signals in a digital signal processor memory for comparing with the measured signature output signal and identifying the single target type. The disbursing step may include disbursing a first target recognition element type over the sensor gate area that reacts with only a first target type and disbursing a second target recognition element type over the sensor gate area that reacts with only a second target type for producing a unique time-varying, superimposed first and second signature output signal from the sensor field effect transistor and reference field effect transistor of the differential pair. The time-varying signature output signal comprises an amplitude and a plurality of frequencies. The digital signal processor used in the sensor method may include a memory having a plurality of stored signature output signals for comparing with the measured superimposed first and second signature output signal and identifying the first and second target type. 
     The sensor system further comprises using the heating means to heat the sensor gate area to a temperature of between about 35° Celsius and about 80° Celsius to self-clean the sensor gate to allow for reuse of the sensor system. The digital signal processor automatically controls the parameters of the heating means for the self-cleaning of the sensor gate and sensor surface process. 
     In another aspect, a sensor method for forming an array comprises assembling an array of two or more sensors according to the method described above. The sensor method may comprise assembling an array of two or more sensors for detecting the presence of two or more target types. The sensor method may comprise assembling a first sensor system for detecting the presence of a first target type and a second sensor system for detecting the presence of a second target type. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       These and other features, aspects and advantages of the present invention will become better understood with regard to the following description and accompanying drawings wherein: 
         FIG. 1A  depicts a diagram of a single target recognition element disbursed over a sensor gate area and a multitude of targets and target types; 
         FIG. 1B  depicts a diagram of a single target recognition element disbursed over a gate area binding with a target substance in the presence of a multitude of target types; 
         FIG. 1C  depicts a diagram of a plurality of target recognition element types disbursed over a gate area binding with a plurality of target substances in the presence of a multitude of target types; 
         FIGS. 2A-2H  and  2 J depict side views of processing steps for fabricating a differential pair of field effect transistors on a silicon substrate; 
         FIG. 3  depicts a top view of a dual fabricated differential pair of field effect transistors on a silicon substrate; 
         FIG. 4  depicts an electrical equivalent circuit of a packaged dual fabricated differential pair of field effect transistors on a silicon substrate; 
         FIG. 5A  depicts a conceptual relationship between analog differential pair sensor circuits and a digital signal processor; 
         FIG. 5B  depicts a simplified diagram of a sensor system including a differential pair of field effect transistors, two current sources, a digital signal processor and associated circuitry; 
         FIG. 5C  depicts a detailed diagram of a sensor system including a differential pair of field effect transistors, two current sources, a digital signal processor and associated circuitry; 
         FIGS. 6A-6C  depict the steps of a sensor optimization algorithm executing in a digital signal processor for automatically controlling the operating characteristics of the differential pair of field effect transistors as shown in  FIGS. 5A and 5B ; 
         FIG. 7A  depicts typical plotted parametric data obtained from a differential pair of p-channel depletion mode field effect transistors by a digital signal processor where  FIG. 7A  represents data collected in step  656  and stored in step  658  of  FIG. 6B ; 
         FIG. 7B  depicts typical plotted parametric data obtained from a differential pair of n-channel depletion mode field effect transistors by a digital signal processor  FIG. 7B  represents data collected in step  656  and stored in step  658  of  FIG. 6B ; 
         FIG. 7C  depicts an optimization method using the plotted parametric data of  FIG. 7A , shown as a reference transistor; 
         FIG. 7D  depicts an optimization method using the plotted data of  FIG. 7C , shown without chemistry applied, after chemistry and biology are applied, and after an environmental change in acidity (Ph); 
         FIG. 8  depicts process steps for implementing an operational embodiment of the present invention; and 
         FIGS. 9A-9D  show typical responses from a differential pair of field effect transistors with binding and without binding of a target recognition element and a target substance. 
         FIG. 10A  illustrates a two-by-two sensor array in a system configuration where the recognition elements in the array may be selected from one of the embodiments shown herein; 
         FIG. 10B  illustrates a four-by-four sensor array in a system configuration where the recognition elements in the array may be selected from one of the embodiments shown herein. 
     
    
    
     DETAILED DESCRIPTION OF THE DRAWINGS 
     The differential pair field effect sensor and reference elements described below may comprise either p-channel devices or n-channel devices, and may be either depletion mode or enhancement mode devices. Where it is necessary to show a particular device, an arbitrary choice of a p-channel depletion mode is illustrated. 
     The terms “target”, “target substance” or “target type” mean any material, the presence or absence of which is to be detected and that is capable of interacting with a recognition element. The targets that may be detected include, without limitation, molecules, compounds, complexes, nucleic acids, proteins, such as enzymes and receptors, viruses, bacteria, cells and tissues and components or fragments thereof. As a result, the methods disclosed herein are broadly applicable to many different fields including medical diagnostics, proteomics, genomics, public health, environmental monitoring, drug testing and discovery, biodefense, automated testing and telemedicine. Exemplary targets include, without limitation, biochemical weapons such as anthrax, botulinum toxin, and ricin, environmental toxins, insecticides, aerosol agents, proteins such as enzymes, peptides, and glycoproteins, nucleic acids such as DNA, RNA and oligonucleotides, pathogens such as viruses and bacteria and their components, blood components, drugs, organic and inorganic molecules, sugars, and the like. The target may be naturally occurring or synthetic, organic or inorganic. 
     The term “recognition element” refers to any chemical, molecule or chemical system that is capable of interacting with a target or target type. Recognition elements can be, for example and without limitation, antibodies, antibody fragments, peptides, proteins, glycoproteins, enzymes, nucleic acids such as oligonucleotides, aptamers, DNA, RNA, organic and inorganic molecules, sugars, polypeptides and other chemicals. A recognition element can also be a thin film that is reactive with a target of interest. 
     Turning to  FIG. 1A ,  FIG. 1A  depicts a diagram  100  of a single target recognition element type  140  disbursed over a sensor gate area  117  of a differential pair field effect sensor element and a multitude of target types  130 ,  132 ,  134 ,  136 . The target recognition elements  140  may or may not be encased in a gel  148 , which allows target types  130 ,  132 ,  134 ,  136  to pass through and bind with the target recognition elements  140 . The field effect sensor element includes a sensor gate area  117  positioned between a source  120  and a drain  122  doped into a silicon base substrate  150 . A silicon oxide layer  115  is grown over the substrate  150 , drain  120  and source  122 . An insulating layer may or may not be deposited over the sensor gate area  117 . Metal interconnections  125 ,  127  connect the drain  120  and source  122  to external terminals of the device. A passivating layer  110  may be applied over the entire device except for the sensor gate area  117 . 
     Turning to  FIG. 1B ,  FIG. 1B  depicts a diagram  160  of a single target recognition element  140  disbursed over a sensor gate area  117  binding with a target substance  130  in the presence of a multitude of target types  130 ,  132 ,  134 ,  136 .  FIG. 1B  is the same as  FIG. 1A  except it shows a single target type  140  that binds with a single target recognition element type  130  to produce a unique signature signal that distinguishes the reaction and differentiates the bound target from other targets. 
     Turning to  FIG. 1C ,  FIG. 1C  depicts a diagram  170  of a plurality of target recognition element types  140 ,  142 ,  146  disbursed over a gate area  117  binding with a plurality of target types  130 ,  132 ,  136  in the presence of a multitude of target types  130 ,  132 ,  134 ,  136 . Note that with multiple target recognition types  140 ,  142 ,  146 , multiple target types  130 ,  132 ,  134 ,  136  may be sensed. For example, the sensor gate element having a coating of H5 and N1 target recognition element types would be capable of sensing the H5N1 avian flu virus. The resultant signature signal output from such a sensor element upon sensing the H5N1 virus would be a superposition of the H5 signature signal shown in  FIG. 9B  and the N1 signature signal shown in  FIG. 9D , which could be easily stored in the pre-stored signature signal library within a digital signal processor or personal computer. 
     Turning to  FIGS. 2A-2H  and  2 J,  FIGS. 2A-2H  and  2 J depict side views  200  of processing steps for fabricating a differential pair of field effect transistors on a silicon substrate base  215 .  FIG. 2A  depicts a p-type or an n-type substrate base  215  where a layer of silicon oxide  210  has been grown on the surface of the substrate base  215 .  FIG. 2B  depicts contact openings  212  created in the oxide layer  210  by a common photolithographic/photoresist process used in the semiconductor industry.  FIG. 2C  depicts an addition of p++ or n++wells  220 ,  225  doped into the substrate base  215  to form drain regions  220  and source regions  225 .  FIG. 2D  further depicts removal of certain oxide areas for the creation of channel areas  230  in the substrate base. The channel areas  230  may or may not require additional doping.  FIG. 2E  depicts re-creation of an oxide covering  210  over the channel area  230 , if the channel area creation required removal of an original oxide covering  210 .  FIG. 2F  depicts the addition of a metal interconnection  240  to the drain  220  and a metal interconnection  245  to the source  225  of sensor transistor (this may be the sensor drain)  280  and reference field effect transistor (this may be the reference drain)  290  that comprise the differential pair.  FIG. 2G  depicts the opening of a gate area  250  by removal of the oxide layer  210  of the sensor from the sensor field effect transistor  280 . The oxide layer  210  from the gate area  255  of the reference field effect transistor  290  is left intact.  FIG. 2H  depicts an option of covering the gate area  250  of the sensor field effect transistor  280  with a protective insulating layer  260 . And finally,  FIG. 2J  depicts completion of the differential pair of a sensor field effect transistor  280  and a reference field effect transistor  290  with a covering the completed structure with a passivating layer  265 , except for the gate area  250  of the sensor field effect transistor  280 , which is not covered with a passivating layer  265 . 
     Turning to  FIG. 3 ,  FIG. 3  depicts a top view  300  of a first differential pair of field effect transistors  360 ,  365  and a second pair of field effect transistors  385 ,  390 , all fabricated on a silicon substrate  395 . A drain of a sensor field effect transistor  360  of the first differential pair of field effect transistors  360 ,  365  is interconnected to a wire bonding area  310  by a metallic interconnect  312 . The sources of the sensor field effect transistor  360  and reference field effect transistor  365  of the first differential pair of field effect transistors  360 ,  365  are connected together and interconnected to a common wire bonding area  315  by a metallic interconnect  317 . A drain of the reference field effect transistor  365  of the first differential pair of field effect transistors  360 ,  365  is interconnected to a wire bonding area  320  by a metallic interconnect  322 . Similarly, a drain of a sensor field effect transistor  385  of the second differential pair of field effect transistors  385 ,  390  is interconnected to a wire bonding area  345  by a metallic interconnect  347 . The sources of the sensor field effect transistor  385  and reference field effect transistor  390  of the second differential pair of field effect transistors  385 ,  390  are connected together and interconnected to a common wire bonding area  350  by a metallic interconnect  352 . A drain of the reference field effect transistor  390  of the second differential pair of field effect transistors  385 ,  390  is interconnected to a wire bonding area  355  by a metallic interconnect  357 . A heating element  380  embedded in the substrate  395  is connected to wire bonding areas  325 ,  340  by metallic interconnects  327 ,  342 , respectively. A temperature sensing element  375  embedded in the substrate  395  is connected to wire bonding areas  330 ,  335  by metallic interconnects  332 ,  334 , respectively. A metallic film deposition  370  is positioned within the boundaries of the heating element  380  and overlays the field effect transistors  360 ,  365 ,  385 ,  390  and the temperature sensing element  375  to provide uniform heat distribution. Note that each differential pair of field effect transistor  360 ,  365  and  385 ,  390 , are located in close proximity to each other in order to be under the influence of the same common mode environmental conditions, such as temperature, electromagnetic radiation, noise, and other factors such as light, cosmic rays, and the like. Common mode electrical signal effects from such common mode environmental conditions will be canceled out by the common mode rejection capabilities of the field effect differential pair. 
     Turning to  FIG. 4 ,  FIG. 4  depicts an electrical equivalent circuit  400  of a packaged dual fabricated differential pair of field effect transistors  460 ,  465 ,  485 ,  490 , heating element  480  and temperature sensing element  475  on a connecting point of the silicon substrate  455 . A drain of a reference field effect transistor of a first pair of field effect transistors is connected to a connecting point  410 , and a drain of a sensor field effect transistor of a first pair of field effect transistors is connected to a connecting point  420 . A common source of the sensor and reference field effect transistors of the first field effect transistor pair is connected to a connecting point  415 . A drain of a reference field effect transistor of a second pair of field effect transistors is connected to a connecting point  445 , and a drain of a sensor field effect transistor of a second pair of field effect transistors is connected to a connecting point  455 . A common source of the sensor and reference field effect transistors of the second field effect transistor pair is connected to a connecting point  450 . A base substrate common to the four field effect transistors is connected to a connecting point  495 . A heating element is connected to connecting points  425 ,  440 , and a temperature sensing element is connected to connecting points  430 ,  435 . 
     Turning to  FIG. 5A ,  FIG. 5A  depicts a conceptual relationship  500  between analog differential pair sensor circuits  503  and a digital signal processor  504 . The analog differential pair sensor circuits  503  include analog adjusting circuitry that surrounds the differential pair and comprises current sources and balancing circuitry. The digital signal processor  504  senses the analog parameters of the analog differential pair sensor circuits  503  through the analog to digital converters  549  and determines optimized values for setting the analog values of the current sources and balancing circuitry through the digital to analog converters  547 . Other analog to digital converters  549  are used to detect the optimized output signal from the analog differential pair sensor circuits  503  when a reaction between a target recognition element and a target is sensed. These signals are processed by the digital signal processor  504  for identifying the sensed target, which is provided as an output. This configuration represents a unique configuration whereby a digital signal processor is in a feedback loop of an analog circuit for balancing and optimizing the analog circuitry. 
     Turning to  FIG. 5B ,  FIG. 5B  depicts a simplified diagram of a sensor system  501  including a differential pair of field effect transistors  514 , two current sources  502 ,  526 , a digital signal processor  504 , a personal computer  506  and associated circuitry. The differential pair of field effect transistors  514 , comprising a sensor field effect transistor  516  and reference field effect transistor  520 , detects reactions at the sensor gate surface  518  between target recognition elements and target substances while providing a means for rejection common mode signals affecting both field effect transistors in the differential pair  514 . Detected reactions provide a normal mode signal at the sensor gate surface  518  which is amplified by the differential pair  516 ,  520 , to provide an amplified differential signal at the drains  517 ,  521  of the differential pair  516 ,  520 . A differential amplifier  512  amplifies and converts the differential drain signals to a normal mode signal, which is sent to the digital signal processor  504  for processing as described below. The output signal at the drain  517  of the sensor field effect transistor  516  is also sent to the digital signal processor  504 . Resistors  508 ,  510  are connected to the drains  571 ,  521  of the field effect differential pair  516 ,  520  for providing a source of drain current to the differential pair  516 ,  520 . A common source resistor  524  connected to the common sources  513  of the differential pair  516 ,  520  enable the differential operation of the differential pair  516 ,  520 . Control of a current source  526  connected to the common source resistor  524  and of a voltage at the common base substrate  515  via resister  522  of the differential pair  516 ,  520  by the optimization algorithms in the digital signal processor  504 , while monitoring the common base substrate voltage  513  and the voltage at the output of the current source  526 , enables the optimization algorithms in the digital signal processor  504  to maintain the differential pair  516 ,  520  in an optimal operating condition by removing distortions that degrade signal sensitivity. The digital signal processor  504  optimization algorithms also keep the differential pair  516 ,  520  in balance by controlling and monitoring the current source  502  connected to the reference field effect transistor drain  521 . A personal computer  506  provides a user interface for control of the digital signal processor  504 . The digital signal processor  504  is connected to a memory  505  that includes a plurality of stored signature outputs signals for comparing with the signature output signal generated from a target interaction to identify a target type. 
     Turning to  FIG. 5C ,  FIG. 5C  depicts a detailed diagram of a sensor system  530 , including a differential pair of field effect transistors  514 , two current sources  532 ,  590 , a digital signal processor  504 , a personal computer  506  and associated circuitry. As described above, the differential pair of field effect transistors  514 , comprising a sensor field effect transistor  516  and reference field effect transistor  520 , detects reactions at the sensor gate surface  518  between target recognition elements and target substances while providing a means for rejection common mode signals affecting both field effect transistors in the differential pair  514 . Detected reactions provide a normal mode signal at the sensor gate surface  518  which is amplified by the differential pair  516 ,  520 , to provide an amplified differential signal at the drains  517 ,  521  of the differential pair  516 ,  520 . After the differential drain signals are buffered by buffer amplifiers  554 ,  558 , a differential amplifier  556  amplifies and converts the differential drain signals to a normal mode signal, which is sent to the digital signal processor  504  via level shifting circuits for processing as described below. Level shifting circuits are controlled by the digital signal processor  504  and are used to maintain a signal with the dynamic range of the analog-to-digital converters within the digital signal processor  504 . Level shifting circuits comprising a differential amplifier  550  and a digital-to-analog converter  552  maintain the sensor field effect transistor signal from a buffer amplifier  554  within dynamic range of an analog-to-digital converter within the digital signal processor  504 . Level shifting circuits comprising a differential amplifier  560  and a digital-to-analog converter  562  maintain the normal mode drain signal from a differential amplifier  556  within dynamic range of an analog-to-digital converter within the digital signal processor  504 . Level shifting circuits comprising a differential amplifier  580  and a digital-to-analog converter  582  maintain the differential pair  564  common source voltage at the output of a buffer amplifier  578  within dynamic range of an analog-to-digital converter within the digital signal processor  504 . The output signal at the drain  517  of the sensor field effect transistor  516  is sent to the digital signal processor  504  via a buffer amplifier  554  and level shifting circuitry  550 ,  552 . Resistors  508 ,  510  are connected to the drains  517 ,  521  of the field effect differential pair  516 ,  520  for providing a source of drain current to the differential pair  516 ,  520 . A common source resistor  524  connected to the common sources  513  of the differential pair  516 ,  520  enable the differential operation of the differential pair  516 ,  520 . The optimization algorithms in the digital signal processor  504  control a current source  590 ,  588  connected to the common source resistor  524  via a digital-to-analog converter  594  and amplifier  592 , and control a voltage at the common base substrate  515  of the differential pair  516 ,  520  via a digital-to-analog converter  574 , amplifier  572  and resistor  570 . The algorithms also monitor the common base substrate voltage via a buffer amplifier  576  and the voltage at the output of the current source  590 ,  588  via an amplifier  586 . These control and monitoring functions by the digital signal processor optimization algorithms enable the digital signal processor  504  to maintain the differential pair  516 ,  520  in an optimal operating condition and remove distortions that degrade signal sensitivity. The optimization algorithms in the digital signal processor  504  also keep the differential pair  516 ,  520  in balance by controlling a current source  532 ,  538  via a digital-to-analog converter  546  and amplifier  544 , and by monitoring, via an amplifier  548 , the current source  532 ,  538  connected to the reference field effect transistor drain  521 . A personal computer  506  provides a user interface for control of the digital signal processor  544 . The digital signal processor  504  is connected to a memory  505  that includes a plurality of stored signature outputs signals for comparing with the signature output signal generated from a target interaction to identify a target type. 
     The detailed sensor system  530  shown in  FIG. 5C  enables the digital signal processor  504  using optimization algorithms to compensate the field effect differential pair  514  for continuously changing environmental factors by altering the operating point on the voltage-current characteristics of the differential pair  514 . The control of the differential pair  514  is achieved by two current sources  532 ,  590  and the base substrate voltage that performs the role of a common gate for all devices on the substrate. The control scheme requires that a change in any one parameter of channel resistance, differential pair balance or average drain voltage requires an adjustment of the other two. 
     The detailed diagram of  FIG. 5C  also includes controlling the temperature operating characteristic using a heating element  564  embedded in the substrate containing the differential pair  514  via a digital-to-analog converter  540  and amplifier  542 . Also included in the substrate is a temperature sensing element  566  connected to the digital signal processor  504  for controlling the substrate temperature. A conventional proportional control algorithm may be used in the digital signal processor  504  for maintaining the substrate at a desired temperature. The temperature of the substrate may be used to maintain a temperature most favorable for reactions between target recognition elements and targets. This temperature may be different for different target recognition elements and different targets, but is generally between 28° and 35° Celsius in order to obtain reactions within a reasonably short sampling time of several minutes. The temperature may also be controlled for sensor self-cleaning and for target recognition element deposition on the sensor gate area  518 . For self cleaning the sensor surface, the heating element is used to heat the sensor surface from between about 35° Celsius and about 80° Celsius. 
     Turning to  FIGS. 6A-6C ,  FIG. 6A  depicts the steps of a sensor optimization algorithm  600  executing in a digital signal processor for controlling the differential pair of field effect transistors as shown in  FIGS. 5A and 5B  above. The sensor optimization algorithm is started  610  manually by the operator. An initialization routine  612 , described in more detail below in  FIG. 6B  below, results in the storing of parametric data  614 , illustrated in  FIG. 7A  and  FIG. 7B , for the sensor field effect transistor S 1  and the reference field effect transistor R 1  derived from measurements performed on the differential pair by the algorithms in the digital signal processor using DAC 4 , DAC 5 , DAC 6 , B 3 , B 4  and A 9  ( 582 ,  574 ,  594 ,  578 ,  576 ,  586 ) shown in  FIG. 5B . Based on the data  614  gathered during execution of the initialization routine  612  and illustrated in  FIG. 7A  and  FIG. 7B , optimized parameter values for the sensor field effect transistor S 1  are determined  616 , and the optimal operating point of the sensor field effect transistor S 1  is identified. The output voltage of DAC 5  and DAC 6  ( 574 ,  594  in  FIG. 5B ) are adjusted  618  to provide source current for the sensor field effect transistor S 1  and the reference field effect transistor R 1 , and drain voltage to the common substrate base of the differential pair that conforms to optimized parameter values. The differential pair is then balanced  622 , as described in further detail in  FIG. 6C  described below. The actual position of the sensor field effect transistor S 1  operating point is determined  626  and compared to the computed optimal operating point  628 . If the S 1  operating point is optimal, the processing of recognition element reactions with targets is conducted  630 , and any reaction data is stored  632 . This reaction data are used for analyzing and final decision-making about chemical and biochemical processes on the surface of the S 1  sensor. If a STOP command is not received from an operator  636 , and S 1  is optimal  642 , the target recognition process continues  630 . If S 1  is found to be not optimal the initialization step is repeated  612 . Returning to step  628 , if the determined operating point is significantly different from the computed operating point  628 , the optimization process of the differential pair of field effect transistors is conducted. If the S 1  operating point is not optimal  628 , it is determined if the source current source is optimal  634 . If the source current is not optimal  634 , the current is adjusted via DAC 6   640  ( 594  in  FIG. 5B ), the differential pair is balanced according to  FIG. 6C  below  644 , and it is then determined if the drain voltage is optimal  624 . If, in step  634 , it was determined that the current source current is optimal, it is also then determined if the drain voltage is optimal  624 . If the S 1  drain voltage is not optimal  624 , DAC 5  ( 574  in  FIG. 5B ) is adjusted  620  and the differential pair is balanced  622  according to  FIG. 6C  below. If the S 1  drain voltage is optimal  624 , the differential pair is also balanced  622   
       FIG. 6B  depicts the steps required  650  for the initialization step in  FIG. 6A  above. The initialization process is to control and confirm the functionality of differential pair of field effect transistors. Upon initialization  654 , transistor curve data and work point of differential pair S 1  and R 1  are collected  656  and stored  658 . The drain-to-source voltage data of the differential pair ( 514  in  FIG. 5B ) is determined by varying the source current via DAC 6  ( 594  in  FIG. 5B ) for incremental values of base substrate voltage  656  via DAC 5  ( 574  in  FIG. 5B ). The base voltage, source voltage and current source output voltage are simultaneously measured ( 576 ,  578 ,  586  in  FIG. 5B ) Sampled data values of the drain-to-source voltage and source current for the sensor field effect transistor S 1  and reference field effect transistor R 1  are stored  658 . These sampled data values are represented by the data points plotted in  FIG. 7A  and  FIG. 7B . From this data, it is determined if R 1  is operational  660 . If either R 1  is not operational  660  or S 1  is not operational  662 , the sensor is not functional  664  and further processing is stopped.  668 . If both R 1  is operational  660  and S 1  is operational  662 , control is returned to step  616  in  FIG. 6A . 
       FIG. 6C  depicts the steps required to balance the differential pair of field effect transistors S 1  and R 1   680 . When started  684 , the difference between the drain voltages of S 1  and R 1  are measured  686  via B 1  and B 2  ( 554 ,  558 ) in  FIG. 5B . If the difference is zero  688 , control is returned to the requesting step  692  in  FIG. 6A . If the difference is not zero  688 , DAC 1  ( 546  in  FIG. 5B ) is adjusted so that the difference in drain voltages of R 1  and S 1  is zero  690 , and control is returned to the requesting step  692  in  FIG. 6A . 
     Turning to  FIG. 7A ,  FIG. 7A  depicts typical plotted parametric data  700  obtained in step  656  of  FIG. 6B  above from a differential pair of p-channel depletion mode field effect transistors by a digital signal processor. The data points represent values of source current  710  as the drain to source voltage  720  is varied while holding constant incremental values of base-source voltage  730 ,  732 ,  734 ,  736 ,  738  for the sensor field effect transistor and the reference field effect transistors. Each data point on the graph represents a value of source current for a given value of drain-source voltage and a given value of base-source voltage. 
     Turning to  FIG. 7B ,  FIG. 7B  depicts typical plotted parametric data  750  obtained in step  656  of  FIG. 6B  above from a differential pair of n-channel depletion mode field effect transistors by a digital signal processor. The data points represent values of source current  760  as the drain to source voltage  770  is varied while holding constant incremental values of base-source voltage  780 ,  782 ,  784 ,  786  for the sensor field effect transistor and the reference field effect transistors. Each data point on the graph represents a value of source current for a given value of drain-source voltage and a given value of base-source voltage. 
     Turning to  FIG. 7C ,  FIG. 7C  depicts an optimization method using the plotted static parametric data of  FIG. 7A , shown as a reference transistor. An optimum operating point  746  of the sensor field effect transistor of a differential pair of field effect transistors is determined by choosing a line  742  that is tangent to a maximum response curve  714  at between a 40° and 45° angle  740  to the horizontal  744 . The 40° to 45° angle  740  is chosen to give a maximum gain and dynamic range of the differential pair analog circuitry without saturating the analog circuitry, while maintaining an acceptably low noise level from the analog circuitry. As shown in  FIG. 7C , an optimized operating point  746  gives a source current of ISO  748  and a drain-to-source voltage of VDSO  750 . 
     Turning to  FIG. 7D ,  FIG. 7D  depicts an optimization method using the static plotted data and method of  FIG. 7C , shown as a family of curves A 1 -A 4   786  without chemistry applied, a family of curves B 1 -B 4   776  after chemistry and biology are applied, and a family of response curves C 1 -C 4   766  after an environmental change in acidity (Ph). The optimized operating points  782 ,  772 ,  762  are determined by finding a point where a line  784 ,  774 ,  764  at an angle between 40° and 45° to the horizontal is tangent to a maximum response curve in a family of response curves  786 ,  776 ,  766 , respectively. As these families of curves illustrate, the shape of the response curves are changing dynamically as environmental and operating conditions change. In order to achieve sufficient gain, response times and stability of the analog circuitry, this dynamic condition must be dynamically stabilized by the optimizing operation of the digital signal processor. 
     Turning to  FIG. 8 ,  FIG. 8  depicts process steps for implementing an operational embodiment of the present invention  800 . The process  800  is started  810  by cleaning and activating the surface of the sensor  815 . This may be accomplished by mechanical chiseling, laser cleaning, chemically cleaning or thermally cleaning, so as not to affect the effectiveness of the sensor elements. Thermally cleaning the sensor elements comprises raising the temperature of the sensor surface using the sensor heating element ( 564  in  FIG. 5C ) to a cleaning temperature in excess of the normal operating temperature, typically between 35° Celsius and 80° Celsius. The sensor surface is then treated with a silane solution, washed and cured  820 . The surface of the sensor element is then treated with cross-linkers  825  to provide an appropriate orientation to the target recognition elements. The surface of the sensor element is then coated with selected target recognition elements  830  capable of uniquely sensing specific target types, such as an H5 antibody and an N1 antibody and may be suspended in a gel. The sensor optimization algorithm described above in  FIG. 6A  is executed  835  and the system is then deployed to expose the sensor element to targets  840 . The system then looks for an output signature signal from the sensor element  845 . If an output signature signal is detected, it is measured  850  and converted to a digital representation  855 . The output signal may be a measurement of conductance, voltage, current, capacitance and resistance that is converted to a digital representation. The digital representation may be a time-varying signal having an amplitude and a plurality of frequencies. The output signature signal is then compared to a library of pre-stored signature signals  860  to determine if there exists a match to a known target or target type  860 . If no match exists  865 , the system returns to sensing an output signal from the sensor element  845 . If a match is found between the output signature signal and one or more pre-stored signature signals in the library  865 , an event log and notification is generated and sent to appropriate authorities  870 . Based on either pre-selected automatic criteria or user selected criteria, an alert may be sent  870 . It must then be determined if it is necessary to clean the sensor surface  875 . If the sensor surface requires cleaning  875 , the process then returns to the beginning for cleaning the sensor surface  815 . If the sensor surface does not require cleaning  875 , the system returns to executing the sensor operating algorithm  835  and exposing the sensor elements to harmful antigens  840 . Operation may be continuous and event detection may occur in real-time. 
     The processes of attaching recognition elements to a sensor and the binding or interaction that occurs when a recognition element combines with a target type are well-known in the art. The recognition elements are attached to the sensor surface, usually by a covalent attachment method (although in other embodiments non-covalent attachment methods may be used). 
     The process of binding between a recognition element that is an antibody and a target type that is an antigen will be described and is for illustration purposes. It should be understood that the present invention is not limited to antibodies and proteins but includes all the types of recognition elements and target types defined and listed above. 
     The process of binding is well understood at the conceptual level though the process is complex at the atomic level. Several recent studies have mapped the structural changes, kinetics and thermodynamics that occur in specific recognition element and target interactions (James &amp; Tawfik, 2005; Grubor et al. 2005; Xavier et al. 1997; 1998, 1999; Jackson 1998; Sinha, et al. 2002). Conceptually the interaction involves numerous dipole-dipole interactions resulting from the specific amino-acids mostly within a region of the antibody known as the hypervariable region and with specific features or amino-acids within the antigen (epitope-region). The antibody and antigen may each be considered as complex dipoles with their own electric fields, which result from negative and positive charged regions. For an antibody and antigen, the interaction or binding process involves forming multiple non-covalent bonds and involves various electrostatic attractive and repulsive forces such as hydrogen-bonds, electrostatic forces, Van der Waals and hydrophobic forces between the individual dipole-regions. Though some individual bonds may be weak, the cumulative effect may be very strong. This overall strength of the interaction is known as its affinity. The strength of bonding is a function of the number, separation and nature of these individual bonds. Since these bonds are non-covalent, binding is reversible. 
     The first steps of interaction involve long-distance attraction of oppositely charged dipoles which serve to bring potential binding partners into relatively close proximity. If it is assumed the antibody is covalently attached to the surface, this will mainly involve attraction of the antigen towards the antibody. However, it is recognized that protein molecules (and antigens) are inherently flexible, and that a certain degree of distortion of both the antibody and antigen molecule will occur, and this may alter the distribution of charge on these molecules. As two well-matched molecules, that when a recognition element and a target that have a strong binding affinity, approach each other, the generalized dipole-dipole attraction will be superseded by more specific interactions (including but not limited to charge-based attraction, repulsion and neutralization) between individual amino-acids or groups of amino-acids within the antibody and antigen and may involve further protein conformational changes, particularly around the specific amino-acids involved in the interaction. Known as induced-fit, this conformational rearrangement process is an important feature of interaction specificity, and results in a complex with a favorable thermodynamic state, and involves both backbone and side-chain rearrangements and the formation of specific hydrogen-bonds. Even small changes in the charge distribution at the interaction site during the interaction process can result in quite large changes in interaction strength which translate into differences in bonding strength and specificity. These processes involve changes in enthalpy such as formation or dissolution of bonds (including but not limited to hydrogen bonds, Van der Waals, salt-bridges and the like) or the displacement of water, as well as changes in overall entropy (binding favored by an increase in entropy). As the interaction proceeds, various changes in charge distribution may occur, which will result in changes in the electrical field of the individual entities. These changes in charge, especially those close to the sensor surface are registered by the sensor device and recorded. 
     Turning to  FIGS. 9A-9D ,  FIGS. 9A-9D  show typical responses  900  from a differential pair of field effect transistors with binding and without binding of a target recognition element and a target. If the sensor gate area shown in  FIG. 1A  was coated with H5 target recognition elements and exposed to an H1 target type, a typical response  910  from the sensor differential pair, normalized by differential amplifier A 6   556  in  FIG. 5B , shown in  FIG. 9A  may result.  FIG. 9A  shows a negative signature response characteristic  910  indicating that an H5 target type was not detected. If the sensor gate area shown in  FIG. 1A  was coated with H5 target recognition elements and exposed to an H5 target type, a typical response  920  from the sensor differential pair, normalized by differential amplifier A 6   556  in  FIG. 5B , shown in  FIG. 9B  may result.  FIG. 9B  shows a positive signature response characteristic  920  indicating that an H5 target type was detected. If the sensor element shown in  FIG. 1A  was coated with N1 target recognition elements and exposed to an N5 target type, a typical response  930  from the sensor differential pair, normalized by differential amplifier A 6   556  in  FIG. 5B , shown in  FIG. 9C  may result.  FIG. 9C  shows a negative signature response characteristic  930  indicating that an N1 target type was not detected. If the sensor element shown in  FIG. 1A  was coated with N1 target recognition elements and exposed to an N1 target type, a typical response  940  from the sensor differential pair, normalized by differential amplifier A 6   556  in  FIG. 5B , shown in  FIG. 9D  may result.  FIG. 9D  shows a positive signature response characteristic  940  indicating that an N1 target type was detected. 
       FIG. 10A  illustrates a two by two sensor array  1010  in a typical system configuration  1000 , where the elements  1020 ,  1022 ,  1030 ,  1032  in the array may be selected from one of the embodiments of the sensor elements shown in  FIG. 2  through  FIG. 9  above or may be some other type of sensor element such as a single electron transistor. A sample of the output of the sensor elements  1020 ,  1022 ,  1030 ,  1032  is sent a digital signal processor  1040  for conversion to a digital equivalent signal sample. A plurality of digital equivalent signal samples from each sensor element in the sensor array  1010  are combined to form a digital signature signal for each element in the array  1010 . This process of digitizing outputs from the sensors and reconstructing a digital signature signal is well-known to those skilled in the relevant art of digital signal processing. The embodiment in  FIG. 10A  shows one digital signal processor  1040  connected to each individual sensor element  1020 ,  1022 ,  1030 ,  1032 . Multiple embodiments with varying combinations of sensor elements and number of digital signal processor are possible. Other embodiments may include more than one digital signal processor, for example, one digital signal processor may be present and connected to one sensor element, a second digital signal processor may be present and connected to a second sensor element, and so forth. Likewise, alternative embodiments of the sensor array may include any combinations of rows and columns of sensor elements. The one or more digital signal processors, then may compare each digitized sensor output signature signal with a library of pre-stored signature signals representing known targets that may bind with a recognition element (see  FIG. 8 ). In this manner, any target that binds with a recognition element and whose signal matches any one of the stored signals is sensed and processed in real-time. 
     The digital signal processor  1040  may process the signals using several alternate process embodiments. One embodiment is a process to sequentially compare each of a time domain digitized sensor signature signal with each of the pre-stored time domain signature signal in a signal library using cross-correlation techniques to determine a match. Another process embodiment is to sequentially convert each received digitized sensor signature signal to a frequency spectrum and then sequentially compare each of the frequency domain digitized sensor signature signals with each of the pre-stored frequency domain signature signals in the signal library using cross-correlation techniques to determine a match. 
     An example of how recognition elements rows  1070 ,  1072 ,  1074 ,  1076  and columns  1080 ,  1084 ,  1086  may be distributed on a four by four sensor array  1050  is shown in  FIG. 10B . As a first example, assume that the sensor element located at column  11080  row  1   1070  of the sensor array  1050  is coated with an H5 antibody (ligand). If the sensor array  1050  were exposed to an H1 antigen, a response from the sensor located at column  1   1080  row  1   1070  shown in  FIG. 9A  would result.  FIG. 9A  shows a negative signature response characteristic indicating that an H5 antigen was not detected. If the sensor array  1050  were exposed to an H5 antigen, a response from the sensor located at column  1   1080  row  1   1070  shown in  FIG. 9B  would result.  FIG. 9B  shows a positive signature response characteristic indicating that an H5 antigen was detected, 
     As a second example, assume that the sensor element located at column  4   1086  row  3   1074  of the sensor array  1050  is coated with an N1 antibody. If the sensor array  1050  were exposed to an N5 antigen, a response from the sensor element located at column  4   1086  row  10   1074  shown in  FIG. 9C  would result.  FIG. 9C  shows a negative signature response characteristic indicating that an N1 antigen was not detected. If the sensor array  1050  were exposed to an N1 antigen, a response from the sensor element located at column  4   1086  row  10   1074  shown in  FIG. 9D  would result.  FIG. 9D  shows a positive signature response characteristic indicating that an N1 antigen was detected. It should be noted, for example, that simultaneous positive responses from a sensor element coated with H5 antibodies and a sensor element coated with N1 antibodies would indicate a presence of the H5N1 avian flu virus. 
     It should also be noted that although the sensor arrays  1010 ,  1050  shown in  FIGS. 10A and 10B  are a two by two (2 by 2) and four by four (4 by 4) square array, respectively, an array according to the present invention may take on numerous elements and array configurations. For example, an array may be a square array, a rectangular array, a three dimensional array, a circular array and the like. The array may also include any number of array elements. It should also be noted that the examples used are illustrative only and not limited to the specific detections described. The detections illustrated in  FIGS. 9  A through  9 D and in  FIGS. 10A and 10B  may encompass detecting the presence or absence of any type of target that is capable of interacting with a recognition element and is not limited to the examples cited herein. 
     Although the present invention has been described in detail with reference to certain preferred embodiments, it should be apparent that modifications and adaptations to those embodiments might occur to persons skilled in the art without departing from the spirit and scope of the present invention.