Patent Publication Number: US-9410900-B2

Title: Infrared detector device inspection system

Description:
RELATED PROVISIONAL APPLICATION 
     This application is related to and claims the benefit of priority of provisional U.S. patent application Ser. No. 62/001,886, filed May 22, 2014, entitled “Carrier Lifetime Mapping Measurement for Infrared Detectors”, which is incorporated herein by reference. 
    
    
     STATEMENT OF GOVERNMENTAL INTEREST 
     This invention was made with United States Government support under Contract No. DE-AC04-94AL85000 between Sandia Corporation and the United States Department of Energy. The United States Government has certain rights in this invention. 
    
    
     BACKGROUND INFORMATION 
     1. Field 
     The present disclosure relates generally to sensors and, in particular, to a method and apparatus for inspecting infrared sensors. Still more particularly, the present disclosure relates to a method and apparatus for inspecting materials for infrared sensors. 
     2. Background 
     Optical detector devices are hardware that respond to light. For example, an infrared focal plane array (FPA) is a type of infrared detector device that generates images using infrared light. These infrared detector devices include materials that generate signals when exposed to infrared light, and circuits that process the signals. 
     The infrared focal plane array functions by absorbing photons in a material. The absorption of the photons results in signals being generated based on the carriers that are detected in the material. These signals are used to form images. 
     The photons absorbed in the material cause the formation of carriers in the material. Carriers are electron-hole pairs. For example, when a photon is absorbed in the material, an electron in a valance band in the material may gain energy and jump to a conduction band leaving a hole in the valence band to form a carrier. These carriers may be detected to create signals used to form an image. 
     A circuit connected to the material detects a voltage caused by the carriers. Based on the detection of the voltage generated by the carriers, signals may be generated by the circuit to form the image. 
     The carriers have a lifetime during which the carriers are present before recombination occurs. Recombination occurs when an electron fills the hole. For example, collisions between at least two electrons in a conduction band may result in one of the electrons recombining in the valence band. This type of recombination is an auger recombination. Radiative recombination is another type of recombination that involves band to band recombination. The length of time during which a carrier exists before recombination is referred to as a carrier lifetime. 
     In some cases, recombination may occur before the carriers can be detected and before the signals can be generated. The quality of the material may affect the ability of an optical sensor to generate signals in response to photons or thermal energy. Defects in the material used to detect photons may result in a recombination occurring quick enough such that a signal is not generated or the signal is not generated at a level that accurately reflects the presence of the carriers. This type of recombination is a Shockley-Read Hall (SRH) recombination, which is also referred to as a trap-assisted recombination. 
     These inconsistencies in the material may be, for example, a defect, a material impurity, or some other undesired inconsistency. This type of recombination is undesirable because a signal is not generated indicating the detection of a photon. As a result, the infrared detector device may not indicate as many detections of photons as desired. 
     As a result, signals may be generated that are not caused by the absorption of photons by the material. Consequently, the performance of an infrared detector device may suffer from this type of recombination. 
     The amount of Shockley-Read Hall recombination that occurs depends on the quality of the material. The quality of the material may vary between infrared detector devices and within an infrared detector device. 
     The variance of the quality of materials may result in an undesired quality in the images generated by an infrared focal plane array. For example, the inconsistencies in an infrared focal plane array may result in an undesired quality in a pixel or in hundreds of pixels depending on the size and location of the inconsistencies. 
     Inspections of the material for infrared focal plane arrays are performed. Defects in the material are often not readily identifiable, however, until the infrared focal plane array is fully fabricated and connected to circuits to read signals and generate images. 
     Testing at this stage of manufacturing for infrared focal plane arrays may be more expensive and time-consuming than desired. For example, if the images generated by an infrared focal plane array do not have a desired level of quality, the infrared focal plane array may be discarded. At this point, the cost and time to connect the circuits to the material has occurred. As a result, new circuits are needed, as well as another piece, or chip, of the material. 
     The large format of infrared focal plane arrays is very expensive and the production is generally of a low volume, such as 10 devices or less. Thus, it is desirable to know whether the quality of the material is suitable for use in an infrared focal plane array as soon as possible to avoid wasting resources on continuing manufacturing of an infrared focal plane array that has defects in the material for detecting photons. 
     Therefore, it would be desirable to have a method and apparatus that take into account at least some of the issues discussed above, as well as other possible issues. For example, it would be desirable to have a method and apparatus for inspecting materials at a time in manufacturing that overcome the technical problem of wasting resources and time that occurs when infrared detector devices are currently tested. 
     SUMMARY 
     Methods and apparatuses for identifying carrier lifetimes are disclosed herein. An embodiment of the present disclosure provides a method for identifying carrier lifetimes. A beam of light is sent to a group of locations on a material for an optical device. Photons emitted from the material are detected at each of the group of locations. A carrier lifetime is identified for each of the group of locations based on the photons detected from each of the group of locations. 
     Another embodiment of the present disclosure provides an apparatus comprising an inspection system. The inspection system sends a beam of light to a group of locations on a material for an optical device; detects photons emitted from the material at each of the group of locations; and identifies a carrier lifetime for each of the group of locations based on the photons detected from each of the group of locations. 
     Yet another embodiment of the present disclosure provides an inspection system comprising a test platform, a light source, a detector, and an analyzer. The test platform is configured to hold a material for an optical device. The light source sends a beam of light to a group of locations on the material held by the test platform. The detector detects photons emitted from the material at each of the group of locations in response to the beam of light being sent to the group of locations. The analyzer identifies a carrier lifetime for each of the group of locations based on the photons detected from each of the group of locations and a simulation of the photons emitted from the material at each of the group of locations. 
     Still another embodiment of the present disclosure provides a method for inspecting a material for an infrared detection device. The material for the infrared detection device is placed into an interior of a vessel. A vacuum is applied to the vessel. The material is cooled to a temperature at which the infrared detection device incorporating the material operates. A laser beam is sent through a window in the vessel onto the material in the vessel to form a spot for the laser beam on the material. The spot is moved to locations on the material. Photons emitted from the material are detected at each of the locations to which the spot moves. A carrier lifetime is identified for each of the locations based on the photons detected from each of the locations and a simulation of the photons emitted from the material at each of the locations. 
     The features and functions can be achieved independently in various embodiments of the present disclosure or may be combined in yet other embodiments in which further details can be seen with reference to the following description and drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an illustration of a block diagram of an inspection environment in accordance with an illustrative embodiment; 
         FIG. 2  is an illustration of a block diagram of an inspection system in accordance with an illustrative embodiment; 
         FIG. 3  is an illustration of a block diagram of a process for identifying carrier lifetimes in accordance with an illustrative embodiment; 
         FIG. 4  is an illustration of a block diagram of data flow simulating trap-assisted recombination for a material in accordance with an illustrative embodiment; 
         FIG. 5  is an illustration of a block diagram of data flow for generating an estimate of error for trap-assisted recombination for a material in accordance with an illustrative embodiment; 
         FIG. 6  is an illustration of an inspection environment in accordance with an illustrative embodiment; 
         FIG. 7  is an illustration of a graph of recombination rates from a simulation in accordance with an illustrative embodiment; 
         FIG. 8  is an illustration of a graph of photons detected and the simulated estimate of detected photons for different carrier lifetimes in accordance with an illustrative embodiment; 
         FIG. 9  is an illustration of a map representing trap-assisted recombination lifetimes for a material in accordance with an illustrative embodiment; 
         FIG. 10  is an illustration of a map having a higher resolution in accordance with an illustrative embodiment; 
         FIG. 11  is an illustration of a map generated from reading signals from an infrared focal plane array in accordance with an illustrative embodiment; 
         FIG. 12  is an illustration of a flowchart of a process for identifying carrier lifetimes in a material for use in an optical device in accordance with an illustrative embodiment; 
         FIG. 13  is an illustration of a flowchart of a process for identifying carrier lifetimes in accordance with an illustrative embodiment; 
         FIG. 14  is an illustration of a flowchart of a process for identifying trap-assisted recombination lifetimes in accordance with an illustrative embodiment; and 
         FIG. 15  is an illustration of a block diagram of a data processing system in accordance with an illustrative embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     The illustrative embodiments recognize and take into account one or more different considerations. For example, the illustrative embodiments recognize and take into account that testing a material that detects photons earlier during manufacturing may reduce the expense and time needed to manufacture infrared focal plane arrays or other infrared detector devices. 
     The illustrative embodiments recognize and take into account that inspecting a material that detects photons for an infrared detector device prior to attaching circuits to the material is desirable. If the material has undesired inconsistencies at a level that makes the material unsuitable for use in an infrared detector device, then the material layer may be discarded without discarding the circuits, and time taken to attach the circuits to the material and other manufacturing steps may be reduced or avoided. 
     The illustrative embodiments recognize and take into account that auger recombination and radiative recombination occur at rates that are intrinsic to the material being used for the detector. In other words, the rate at which these two types of recombination occur is only based on the material and not based on other factors. As a result, the lifetime of carriers based on these two types of recombination may be identified. These rates of recombination are referred to as recombination rates. 
     The illustrative embodiments also recognize and take into account that a trap-assisted recombination occurs from inconsistencies in the material. In other words, a trap-assisted recombination is not based on the properties of the material itself. For example, a trap-assisted recombination occurs when a defect is present in the material rather than some intrinsic property of the material. 
     The illustrative embodiments recognize and take into account that the carrier lifetime of the material as a whole depends on the carrier lifetimes of carriers as affected by these three types of recombination mechanisms. The illustrative embodiments recognize and take into account that the rates of auger recombination and radiative recombination do not vary for a particular material used in an optical device. 
     The illustrative embodiments recognize and take into account that the rate of recombination caused by trap-assisted recombination may vary at different locations in a material when defects are present. Thus, the illustrative embodiments recognize and take into account that the carrier lifetime for carriers that recombine from trap-assisted recombination may be the dominant contributor to the overall lifetime of carriers in the material. 
     The illustrative embodiments recognize and take into account that radiative recombination results in a photon being emitted from the material. The illustrative embodiments recognize and take into account that the emission of this photon may be used to inspect the material without connecting the material to circuits to generate signals from carriers. 
     For example, the illustrative embodiments recognize and take into account that when defects are absent in the material, trap-assisted recombination is substantially constant throughout the material. Consequently, the photons emitted from the material by radiative recombination are also substantially consistent. 
     When defects are present, the illustrative embodiments also recognize and take into account that trap-assisted recombination may be higher in areas where defects are located. As a result, the emission of photons in these locations may vary from other locations in the material where defects are not present. 
     Thus, the illustrative embodiments provide a method and apparatus for identifying carrier lifetimes in a material for an optical device. In one illustrative example, a method sends a beam of light to a group of locations on the material. Photons emitted from the material at each of the group of locations are detected. A carrier lifetime is identified for each of the group of locations based on the photons detected from each of the group of locations. 
     In this manner, the detection of carriers using circuits attached to a material is not needed to inspect the material. Instead, the photons emitted from the material may be used to identify carrier lifetimes for the material at different locations. 
     With reference now to the figures, and in particular, with reference to  FIG. 1 , an illustration of a block diagram of an inspection environment is depicted in accordance with an illustrative embodiment. Inspection environment  100  is an environment in which inspection system  102  may perform an inspection of material  104 . In the illustrative example, material  104  is a material that generates a response to light  106 . For example, material  104  may be a photosensitive material that has a bandgap. In the illustrative examples, the bandgap is a direct bandgap. 
     The bandgap is an energy range in the material where electron states cannot exist. The band gap represents the minimum energy difference between the top of the valence band and the bottom of the conduction band. The top of the valence band and the bottom of the conduction band, however, are not generally at the same value of the electron momentum. A direct band gap is present when the top of the valence band and the bottom of the conduction band occur at the same value of momentum. 
     This inspection of material  104  may be used to determine the suitability of material  104  for use in optical device  108 . Optical device  108  is a hardware device that responds to light  106 . For example, optical device  108  may be, for example, infrared detector device  110 . More specifically, optical device  108  may be infrared focal plane array  112 . 
     In an illustrative example, a number of different types of material may be used. For example, material  104  may be selected from one of mercury cadmium telluride (MCT), indium antimonide (InSb), indium arsenic antimonide (InAsSb), gallium indium arsenide (InGaAs), or some other suitable semiconductor that is sensitive to light  106  in the form of infrared light when optical device  108  is infrared detector device  110 . As used herein, “a number of” when used with reference to items means one or more items. For example, a number of types of materials is one or more types of materials. 
     In this illustrative example, inspection system  102  performs an inspection of material  104  to determine whether performance  114  of material  104 , in response to light  106 , is suitable for use in optical device  108 . Performance  114  may not be as high as desired when defect  116  is present in material  104 . Defect  116  may be, for example, at least one of an impurity, a different element being present in material  104 , a break, a crack, a void, an undesired lattice pattern, or some other inconsistency in material  104 . 
     As used herein, the phrase “at least one of,” when used with a list of items, means different combinations of one or more of the listed items may be used and only one of each item in the list may be needed. In other words, at least one of means any combination of items and number of items may be used from the list but not all of the items in the list are required. The item may be a particular object, thing, or a category. 
     For example, without limitation, “at least one of item A, item B, or item C” may include item A, item A and item B, or item B. This example also may include item A, item B, and item C or item B and item C. Of course, any combinations of these items may be present. In some illustrative examples, “at least one of” may be, for example, without limitation, two of item A; one of item B; and ten of item C; four of item B and seven of item C; or other suitable combinations. 
     In operation, inspection system  102  generates beam  118  of light  106  with a group of characteristics  120 . As depicted, the number of characteristics  120  includes at least one of duration, intensity, spot size, wavelength, or other suitable characteristics for light  106 . 
     During operation, inspection system  102  sends beam  118  of light  106  to a group of locations  124  on material  104 . As used herein, “a group of”, when used with respect to items, means one or more items. For example, a group of locations  124  is one or more of locations  124 . 
     Inspection system  102  detects photons  132  emitted from material  104  at each of the group of locations  124 . As depicted, inspection system  102  identifies carrier lifetime  128  for each of the group of locations  124  to form a group of carrier lifetimes  130  for material  104  based on photons  132  detected from each of the group of locations  124 . 
     In the illustrative example, inspection system  102  detects photons  132  emitted from material  104  instead of detecting carriers  134  that may be formed in material  104  as part of inspecting material  104  for suitability for use in optical device  108 . As a result, a circuit does not need to be connected to material  104  to inspect material  104  in identifying the presence of carriers  134  and carrier lifetimes  130 . 
     Thus, in an illustrative example, inspection system  102  may be used to inspect material  104  at an earlier point in time as compared to currently used inspection techniques. Currently used techniques are employed to read signals after circuits are connected to the material. With inspection system  102 , material  104  may be inspected without connecting a circuit to material  104 . 
     As a result, the illustrative example provides a technical solution for inspecting materials at a time in manufacturing that overcomes the technical problem of wasting resources and time that occurs when infrared detector devices are currently tested. In this manner, a technical effect occurs in which the manufacturing of optical devices may occur at a lower cost, with less time, or both at a lower cost and with less time. 
     With reference next to  FIG. 2 , an illustration of a block diagram of an inspection system is depicted in accordance with an illustrative embodiment. An illustration of one implementation for inspection system  102  in  FIG. 1  is shown. In the illustrative examples, the same reference numeral may be used in more than one figure. This reuse of a reference numeral in different figures represents the same element in the different figures. 
     In this illustrative example, inspection system  102  includes a number of different components. As depicted, inspection system  102  includes test platform  200 , light source  202 , detector  204 , and analyzer  206 . 
     Test platform  200  is a physical structure that holds material  104  for inspection in this illustrative example. For example, test platform  200  may be vessel  208 . Material  104  may be placed into interior  210  of vessel  208  and held within interior  210  for inspection. 
     In the illustrative example, vessel  208  may take various forms. As depicted, vessel  208  may be selected from one of a vacuum flask, a Dewar flask, a thermos, a vacuum chamber, a pressurized chamber, or some other suitable structure. 
     As depicted, material  104 , held by test platform  200 , may be in various structures, part of various structures, or form various structures. For example, material  104  may be located in a structure selected from one of a wafer, a chip, an infrared detector device, an infrared focal plane array, or some other structure that is placed into interior  210  of vessel  208 . 
     In the illustrative example, light source  202  is a hardware system that generates light  106  that is directed onto material  104 . For example, light source  202  may include at least one of a light generator, optics, fiber-optic cables, or other suitable components for generating light  106  and directing light  106  onto material  104 . 
     In this illustrative example, light source  202  generates light  106  with a group of characteristics  120  that is suitable to cause the generation of carriers  134  in material  104  and the emission of photons  132 . For example, light source  202  may generate beam  118  of light  106  as a beam of coherent light. More specifically, beam  118  of light  106  may be a laser beam. Still more specifically, beam  118  of light  106  may be pulsed for a duration of time when light is sent to material  104 . 
     Beam  118  of light  106  may be directed by light source  202  onto material  104  located in interior  210  of vessel  208  through window  212  in vessel  208 . In this illustrative example, photons  132  are emitted from material  104  when beam  118  of light  106  is directed onto material  104 . 
     Also, beam  118  of light  106  may be moved to locations  124  on material  104 . The movement of beam  118  of light  106  from location to location in locations  124  results in photons  132  being emitted from location to location in locations  124 . 
     As depicted, detector  204  is a hardware system that detects photons  132  emitted from locations  124  on material  104 . Detector  204  may be implemented using at least one of an active pixel sensor, a charge coupled device (CCD), a cryogenic detector, a photoresistor, or other suitable devices. 
     Detector  204  generates data  214  from detecting photons  132 . In this particular example, detector  204  sends data  214  to analyzer  206 . 
     In the illustrative example, analyzer  206  identifies carrier lifetimes  130  for locations  124  based on data  214 . In this manner, analyzer  206  identifies carrier lifetime  128  for each of the group of locations  124  based on photons  132  detected from each of the group of locations  124 . 
     In this illustrative example, analyzer  206  also may control the operation of at least one of light source  202  or detector  204 . Analyzer  206  may be implemented in software, hardware, firmware or a combination thereof. When software is used, the operations performed by analyzer  206  may be implemented in program code configured to run on hardware, such as a processor unit. When firmware is used, the operations performed by analyzer  206  may be implemented in program code and data and stored in persistent memory to run on a processor unit. When hardware is employed, the hardware may include circuits that operate to perform the operations in analyzer  206 . 
     In the illustrative examples, the hardware may take the form of a circuit system, an integrated circuit, an application-specific integrated circuit (ASIC), a programmable logic device, or some other suitable type of hardware configured to perform a number of operations. With a programmable logic device, the device may be configured to perform the number of operations. The device may be reconfigured at a later time or may be permanently configured to perform the number of operations. Programmable logic devices include, for example, a programmable logic array, programmable array logic, a field programmable logic array, a field programmable gate array, and other suitable hardware devices. Additionally, the processes may be implemented in organic components integrated with inorganic components and may be comprised entirely of organic components excluding a human being. For example, the processes may be implemented as circuits in organic semiconductors. 
     In this illustrative example, analyzer  206  may be implemented in computer system  216 . Computer system  216  is a hardware system that includes one or more data processing systems. When more than one data processing system is present, those data processing systems may be in communication with each other using a communications medium. The communications medium may be a network. The data processing systems may be selected from at least one of a computer, a server computer, a tablet, or some other suitable data processing system. 
     With reference now to  FIG. 3 , an illustration of a block diagram of a process for identifying carrier lifetimes is depicted in accordance with an illustrative embodiment. In this illustrative example, analyzer  206  receives data  214  about photons  132  detected by detector  204 . 
     In this illustrative example, analyzer  206  identifies carrier lifetime  128  for each of the group of locations  124  based on photons  132  detected from each of the group of locations  124 . This identification takes into account that photons  132  are caused in part by recombination of carriers  134  in material  104  that occurs from radiative recombination  300 . The part of photons  132  that occurs from radiative recombination is known as photoluminescence. 
     Radiative recombination  300  is substantially consistent for material  104 . Defect  116  does not affect radiative recombination  300 . The rate of radiative recombination  300  is based on the selection of material  104  and the concentration of carriers  134  in material  104  caused by beam  118  of light  106 . 
     In this illustrative example, changes in photons  132  emitted by radiative recombination  300  may be affected by trap-assisted recombination  302 . Trap-assisted recombination  302  may reduce radiative recombination  300 . Additionally, trap-assisted recombination  302  may increase the dark currents present in material  104 . 
     In this illustrative example, analyzer  206  identifies carrier lifetime  128  for each of the group of locations  124  based on data  214  about photons  132  emitted from material  104  and simulation  306  of photons  132  emitted from material  104  at each of the group of locations  124 . 
     In this illustrative example, simulation  306  simulates recombinations of carriers  134  in material  104 . Simulation  306  may simulate radiative recombination  300 , trap-assisted recombination  302 , and auger recombination  308 . 
     In simulation  306 , radiative recombination  300  and trap-assisted recombination  302  are assumed to be substantially the same material  104 . As a result, the emission of photons  132  should not vary based on radiative recombination  300  and auger recombination  308 . Changes in trap-assisted recombination  302  may result in changes in the numbers of photons  132  that are emitted from material  104 . 
     As depicted in simulation  306 , trap-assisted recombination  302  for material  104  is simulated in response to beam  118  of light  106  on material  104 . As depicted, trap-assisted recombination  302  may be varied in simulation  306 . This variation of trap-assisted recombination  302  is performed to find a level of trap-assisted recombination  302  that causes photons  132  emitted from material  104  in simulation  306  to match photons  132  as detected by detector  204  within a desired level of variance. 
     The desired level of variance is how much difference between photons  132  being simulated and photons  132  as detected is acceptable for simulating the emission of photons  132  in simulation  306  versus the emission of photons  132  detected by detector  204 . The desired level of variance may be based on some level of acceptable error. 
     Analyzer  206  identifies carrier lifetime  128  for each of the group of locations  124  to form a group of carrier lifetimes  130  for the group of locations  124  based on trap-assisted recombination  302  identified that causes emission of photons  132  and simulation  306  to match photons  132  detected by detector  204  with a desired level of variance. In the illustrative example, analyzer  206  may perform analysis  310  based on photons  132  detected by detector  204  and photons  132  in simulation  306 . The analysis may be based on varying the amount of trap-assisted recombination  302 . 
     As depicted, analyzer  206  may perform action  312  based on analysis  310 . Action  312  may take a number of different forms. In one illustrative example, action  312  includes generating map  314 . Map  314  may be a map of carrier lifetimes  130  in material  104 . 
     Map  314  may be used to perform other actions. For example, map  314  may be used to identify portions of material  104  that may be used for optical devices. For example, map  314  may indicate that one portion of material  104  may be suitable for use in an optical device while another portion of material  104  is unsuitable for use in an optical device. 
     As another example, map  314  may be used as a guide to show what parts of material  104  should be used. For example, map  314  may show how material  104  may be diced when material  104  is in a wafer. The dicing of material  104  may be in a manner that leaves portions of material  104  for other suitable uses in optical devices. The other portions of material  104  may be discarded or recycled. 
     In another illustrative example, action  312  may take other forms in addition to or including generating map  314 . For example, action  312  may include at least one of sending a message, generating an alert, recommending discarding material  104  in the case that material  104  is not suitable for use, or other suitable actions. 
     As a result, computer system  216  in  FIG. 2  operates as a special purpose computer system in which analyzer  206  in computer system  216  enables identifying carrier lifetimes  130  in material  104  in various ones of locations  124 . In particular, analyzer  206  transforms computer system  216  into a special purpose computer system as compared to currently available general computer systems that do not have analyzer  206 . 
     Computer system  216  performs a transformation of data  214 . For example, analyzer  206  in computer system  216  uses the number of photons detected in data  214  to identify the carrier lifetime for trap-assisted recombination  302  by comparing photons  132  detected with photons that would be emitted in a simulation of trap-assisted recombination  302  for the material such that the data has a different function or has a different use. 
     Turning to  FIG. 4 , an illustration of a block diagram of data flow simulating trap-assisted recombination for a material is depicted in accordance with an illustrative embodiment. In this figure, an example of data flow of a process used to identify trap-assisted recombination  302  for material  104  through simulation  306  is shown. In this illustrative example, simulation  306  includes search tool  400  and simulation calculator  402 . 
     Search tool  400  identifies trap-assisted recombination  302  for material  104  by searching for a solution to a variable that reduces an amount of error to a desired level. As depicted, the error is between an estimate of detected photons based on the variable and actual detected photons from material  104 . 
     In this illustrative example, the variable is range of trap-assisted recombination lifetimes  404 . Range of trap-assisted recombination lifetimes  404  is a range of values of trap-assisted recombination lifetimes for material  104 . Trap-assisted recombination lifetime  406  is the average carrier lifetime in material  104  before trap-assisted recombination occurs. 
     As depicted, search tool  400  generates trap-assisted recombination lifetime  406  based on the range of trap-assisted recombination lifetimes  404 . Search tool  400  sends trap-assisted recombination lifetime  406  to simulation calculator  402 . 
     Simulation calculator  402  identifies estimate of detected photons  408  based on trap-assisted recombination lifetime  406  received from search tool  400  and simulation information  410 . Simulation calculator  402  then identifies error  412  based the difference between estimate of detected photons  408  and detected photons  414  in data  214 . Detected photons  414  is data about photons  132  emitted from material  104 . 
     Simulation calculator  402  sends error  412  to search tool  400 . The process illustrated in  FIG. 4  is repeated until search tool  400  finds the trap-assisted recombination lifetime in range of trap-assisted recombination lifetimes  404  for which error  412  is closest to zero. In other words, search tool  400  identifies the trap-assisted recombination lifetime in range of trap-assisted recombination lifetimes  404  for which the estimate of detected photons  408  is closest to detected photons  414 . 
     As depicted, simulation calculator  402  also generates electron concentration  416 , hole concentration  418 , auger recombination  308 , radiative recombination  300 , and trap-assisted recombination  302  based on simulation information  410  and trap-assisted recombination lifetime  406 . Electron concentration  416  is the number of electrons per unit volume at a selected temperature in the absence of photon absorption. Hole concentration  418  is the number of electron-holes per unit volume at a selected temperature in the absence of photon absorption. 
     Turning next to  FIG. 5 , an illustration of a block diagram of data flow for generating an estimate of error for trap-assisted recombination for a material is depicted in accordance with an illustrative embodiment. In this figure, an example of data flow used to identify error  412  based on the difference between estimate of detected photons  408  and detected photons  414  is shown. Simulation calculator  500  in  FIG. 5  is an example of simulation calculator  402  in  FIG. 4 . 
     In this example, simulation calculator  500  uses simulation information  410  in generating error  412 . In this example, simulation information  410  is provided by a human operator. The types of information in simulation information  410  include intrinsic carrier concentration  502 , donor doping concentration  504 , acceptor doping concentration  506 , equilibrium electron concentration  508 , equilibrium hole concentration  510 , thickness of material  512 , radiative recombination rate coefficient  514 , auger recombination rate coefficients  516 , trap-assisted recombination lifetime  518 , laser spot size on sample  520 , laser wavelength  522 , laser power  524 , and laser pulse duration  526 . 
     In this example, intrinsic carrier concentration  502  is the number of electrons and electron-holes per unit volume which are free of defects in material  104 . These defects are examples of defect  116  in  FIG. 1 . 
     Donor doping concentration  504  is the number of atoms per unit volume placed in material  104  that provide an excess electron. An excess electron is an electron without a corresponding electron-hole. 
     As depicted, acceptor doping concentration  506  is the number of atoms per unit volume placed in material  104  that provides an excess electron-hole. An excess electron-hole is an electron-hole without a corresponding electron. 
     Equilibrium electron concentration  508  is the number of electrons per unit volume at a given temperature in the absence of photon absorption. Equilibrium hole concentration  510  is the number of electron-holes per unit volume at a given temperature in the absence of photon absorption. 
     Radiative recombination rate coefficient  514  is a value used to indicate the rate of radiative recombination for the concentration of electrons and electron-holes in material  104 . Auger recombination rate coefficients  516  are values used to indicate the rate of auger recombination for the concentration of electrons and electron-holes in material  104 . 
     In this illustrative example, trap-assisted recombination lifetime  518  is an estimate of the rate of trap-assisted recombination for the concentration of electrons and electron-holes in material  104 . For example, trap-assisted recombination lifetime  518  may be used by search tool  400  in  FIG. 4  as trap-assisted recombination lifetime  406 . 
     Laser spot size on sample  520  is the size of beam  118  of light  106  on material  104 . The size is described as a diameter or radius if the laser spot is circular in the illustrative example. 
     As depicted, laser wavelength  522  is the wavelength of beam  118  of light  106 . Laser power  524  is the power of beam  118  of light  106 . Laser pulse duration  526  is the amount of time beam  118  of light  106  is sent to material  104 . 
     In this figure, simulation calculator  500  identifies trap-assisted recombination lifetime  518  in simulation information  410 . Trap-assisted recombination lifetime  518  may be an estimate. 
     Simulation calculator  500  identifies error  412  based on the difference between estimate of detected photons  408  and detected photons  414  in data  214 . Simulation calculator  500  identifies estimate of detected photons  408  using the following equations:
 
 n ( t+Δt )= n ( t )+Δ tG   optical ( t )−Δ t ( U   aug   +U   rad   +U   SRH )  (1)
 
 p ( t+Δt )= p ( t )+Δ tG   optical ( t )−Δ t ( U   aug   +U   rad   +U   SRH )  (2)
 
where equations (1) and (2) are used to determine the carrier concentration of both electrons n and holes p after a time step Δt; G optical (t) is the optical carrier generation rate; and U aug , U rad , and U SRH  are the net recombination rates respectfully from auger, radiative, and trap-assisted recombination.
 
     These recombination rates are identified using the following equations: 
                     U   aug     =         C   n     ⁡     (         n   2     ⁢   p     -       n   0   2     ⁢     p   0         )       +       C   p     ⁡     (       np   2     -       n   0     ⁢     p   0   2         )                 (   3   )                 U   rad     =     B   ⁡     (     np   -     n   i   2       )               (   4   )                 U   SRH     =       (     np   -     n   i   2       )           τ     SRH   -   n       ⁡     (     p   +     p   1       )       +       τ     SRH   -   p       ⁡     (     n   +     n   1       )                   (   4   )                   n   0     ⁢     p   0       =     n   i   2             (   5   )               
where n 0  and p 0  are the equilibrium concentrations of electrons and holes, and n 1  is the intrinsic carrier concentration; n 1  and p 1  are the trap-assisted recombination densities which are set equal to n 0  and p 0  when lack of knowledge about the nature of the defect states is present; and τ SRH-n  and τ SRH-p  are the trap-assisted recombination lifetimes for electrons and holes, which are set equal to each other and regarded as the primary variables of interest.
 
     Simulation calculator  500  identifies recombination rate coefficients using the following equations: 
                   B   =     5.8   ×     10     -   13       ⁢       ɛ   ∞       ⁢       (       m   0         m   c   *     +     m   v   *         )       3   2       ⁢     (     1   +       m   0       m   c   *       +       m   0       m   v   *         )     ×       (     300   T     )       3   2       ⁢     (       E   g   2     +     3   ⁢           ⁢     kTE   g       +     2.75   ⁢           ⁢     k   2     ⁢     T   2         )               (   6   )                 C   n     =         (       m   c   *       m   0       )     ⁢              F   1     ⁢     F   2            2         2   ⁢           ⁢       n   i   2     ⁡     (     3.8   ×     10     -   18         )       ⁢         ɛ   ∞   2     ⁡     (     1   +       m   c   *       m   v   *         )         1   2       ⁢     (     1   +       2   ⁢           ⁢     m   c   *         m   v   *         )     ×       (       E   g     kT     )         -   3     2       ⁢     exp   ⁡     (       -       1   +       2   ⁢           ⁢     m   c   *         m   v   *           1   +       m   c   *       m   v   *             ⁢       E   g     kT       )                   (   7   )                 C   p     =       C   n     ⁡     [       1   -       3   ⁢           ⁢     E   g       kT         6   ⁢     (     1   -       5   ⁢           ⁢     E   g         4   ⁢           ⁢   kT         )         ]               (   8   )               
where B, C n , and C p  are recombination rate coefficients; m 0  is the mass of an electron, and m* c  and m* v  are the effective masses of electrons and holes in the conduction and valence bands; and |F 1 F 2 | is the overlap integral of the Bloch functions, and its value is 0.2 in these simulations because the actual value is not precisely known.
 
     As an example for the common infrared detector material mercury cadmium telluride (MCT), simulation calculator  500  identifies intrinsic carrier concentration n 1  and band gap E g  for MCT as a function of temperature T and composition x as found in the material Hg (1-x) Cd x Te. Simulation calculator  500  identifies intrinsic carrier concentration n 1  and band gap E g  for MCT using the following equations: 
     
       
         
           
             
               
                 
                   
                     E 
                     g 
                   
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                       - 
                       0.302 
                     
                     + 
                     
                       1.93 
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                       x 
                     
                     + 
                     
                       5.35 
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                         10 
                         
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                     + 
                     
                       0.832 
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                         x 
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                   ( 
                   9 
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                     n 
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                         5.585 
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     Simulation calculator  500  further identifies equilibrium carrier concentrations using the following equations: 
                     n   0     =           N   D     -     N   A       2     +           (         N   D     -     N   A       2     )     2     +     n   i   2                   (   11   )                 p   0     =           N   A     -     N   D       2     +           (         N   A     -     N   D       2     )     2     +     n   i   2                   (   12   )               
where N D  and N A  are the donor and acceptor doping concentrations.
 
     The illustration of inspection environment  100  and the different components in inspection environment  100  in  FIGS. 1-5  are not meant to imply physical or architectural limitations to the manner in which an illustrative embodiment may be implemented. Other components in addition to or in place of the ones illustrated may be used. Some components may be unnecessary. Also, the blocks are presented to illustrate some functional components. One or more of these blocks may be combined, divided, or combined and divided into different blocks when implemented in an illustrative embodiment. 
     For example, inspection system  102  may include one or more test platforms in addition to or in place of test platform  200  in  FIG. 2 . Additional detectors may be used with these test platforms. Further, light source  202  may be a single light generator with optics for fiber-optic cables to correct light  106  to other materials in addition to material  104  that may be located in the different test platforms. 
     With reference now to  FIG. 6 , an illustration of an inspection environment is depicted in accordance with an illustrative embodiment. In this depicted example, inspection environment  600  is an example of one implementation for inspection environment  100  shown in block form in  FIG. 1 . 
     Inspection system  602  in inspection environment  600  performs an inspection of test sample  604 . Test sample  604  is a material that has a direct bandgap that is intended for use in an infrared detector device, such as an infrared focal plane array. 
     In this illustrative example, inspection system  602  includes a number of different components. As depicted, inspection system  602  includes Dewar flask  606 , pulsed laser system  608 , fast detector  610 , and computer  612 . 
     As depicted, Dewar flask  606  is an example of an implementation for test platform  200  in  FIG. 2 . Fast detector  610  is an example of an implementation for detector  204  in  FIG. 2 . 
     As depicted, pulsed laser system  608  is an example of light source  202  in  FIG. 2 . Computer  612  is an example of analyzer  206  in  FIG. 2 . 
     In this illustrative example, Dewar flask  606  is a structure in which test sample  604  may be placed for inspection. In this illustrative example, a vacuum may be drawn within Dewar flask  606 . Additionally, the temperature may be lowered to a cryogenic temperature within Dewar flask  606 . This cryogenic temperature is the temperature at which an infrared detection device operates. 
     Pulsed laser system  608  includes a number of components. As depicted, pulsed laser system  608  includes laser generator  614 , optical fiber  616 , and optics  618 . 
     Laser generator  614  generates a laser beam that is pulsed. This pulsed laser beam may be directed through optical fiber  616  to optics  618 . In this illustrative example, optics  618  includes a number of different components. As depicted, optics  618  includes beam splitter  620 , mirror  622 , lens  624 , and lens  625 . 
     Pulsed laser path  626  is sent from optical fiber  616  to test sample  604  located in Dewar flask  606 . Part of pulsed laser path  626  is defined by beam splitter  620  and lens  624 . Pulsed laser path  626  goes into Dewar flask  606  through window  628  in Dewar flask  606 . 
     In response to the laser beam following pulsed laser path  626 , photons are emitted from test sample  604 . These photons follow return path  630 . Return path  630  goes from test sample  604  to fast detector  610 . Return path  630  passes through window  628  and passes through beam splitter  620 . Return path  630  then goes to fast detector  610  via mirror  622  and through lens  625 . 
     In this illustrative example, fast detector  610  is a detector with a response time that is shorter than the carrier lifetime of test sample  604 . Fast detector  610  generates data in response to detecting the photons reaching fast detector  610  along return path  630  for the route. The data is sent to computer  612 . 
     In this illustrative example, computer  612  analyzes the data. Additionally, computer  612  also controls the operation of pulsed laser system  608  and fast detector  610 . 
     In this illustrative example, optics  618  and optical fiber  616  are associated with platform  632 . When one component is “associated” with another component, the association is a physical association in the depicted examples. For example, a first component, optics  618  or optical fiber  616 , may be considered to be physically associated with a second component, platform  632 , by at least one of being secured to the second component, bonded to the second component, mounted to the second component, welded to the second component, fastened to the second component, or connected to the second component in some other suitable manner. The first component also may be connected to the second component using a third component. The first component may also be considered to be physically associated with the second component by being formed as a part of the second component, an extension of the second component, or both. 
     As depicted, platform  632  is a physical structure that is configured to move about a number of axes. For example, platform  632  may allow for 6 degrees of freedom in positioning and moving pulsed laser path  626  with respect to test sample  604 . More particularly, pulsed laser path  626  may be positioned and moved along three perpendicular axes of three-dimensional space and rotated about the three perpendicular axes with respect to test sample  604 . This movement may allow for directing a pulsed laser beam to different locations on test sample  604 . In the illustrative example, platform  632  may be, for example, a housing, a frame, or some other suitable type of structure. 
     The illustration of inspection environment  600  in  FIG. 6  is only meant as an example of one implementation for inspection environment  100  shown in block form in  FIG. 1 . The illustration of inspection environment  600  is not meant to limit the manner in which other illustrative examples may be implemented. 
     For example, Dewar flask  606  may be moved in place of or in addition to the movement of platform  632 . As another example, pulsed laser system  608  may include one or more other optical fibers in addition to optical fiber  616 . As a result, multiple laser beams may be directed towards one or more samples that may be located in Dewar flask  606  for other test platforms that may be used in place of or in addition to Dewar flask  606 . 
     As another example, pulsed laser system  608  may include an oscilloscope that reads the data from fast detector  610 . In this example, the oscilloscope sends the data to computer  612 . 
     With reference next to  FIG. 7 , an illustration of a graph of recombination rates from a simulation is depicted in accordance with an illustrative embodiment. In this illustration, graph  700  shows output from simulation  306 . In graph  700 , x-axis  702  is time in seconds, and y axis  704  is the rates of recombination or hole concentration in centimeters −3 . As depicted, the lines shown on graph  700  represent recombination rates for different types of recombination for material  104  and hole concentration rate  705  for material  104 . 
     In the illustrative example, line  706  shows hole concentration rate  705 . Hole concentration rate  705  in line  706  is based on hole concentration  418 . The types of recombination rates for material  104  shown in graph  700  include radiative recombination rate  708 , trap-assisted recombination rate  710 , auger recombination rate  712 , and total recombination rate  714 . 
     As depicted, radiative recombination rate  708  is based on radiative recombination  300 ; trap-assisted recombination rate  710  is based on trap-assisted recombination  302 ; and auger recombination rate  712  is based on auger recombination  308 . Recombination rates are based on recombination lifetimes. Total recombination lifetime is based on the following equation: 
                     1     τ   total       =       1     τ   rad       +     1     τ   SRH       +     1     τ   aug                 (   14   )               
where τ total  total recombination lifetime, τ rad  is radiative recombination lifetime, τ SRH  is trap-assisted recombination lifetime, and τ aug  is auger recombination lifetime.
 
     Turning to  FIG. 8 , an illustration of a graph of photons detected and the simulated estimate of detected photons for different carrier lifetimes is depicted in accordance with an illustrative embodiment. As depicted in graph  800 , carrier lifetimes from a simulation and data generated from the detection of photons are shown. 
     In this illustration, graph  800  shows examples of the trap-assisted recombination lifetimes identified by simulation  306  in  FIG. 4  for different locations on material  104 . In graph  800 , x-axis  802  is time in seconds, and y axis  804  is detection of photons in millivolts on a logarithmic scale. 
     As depicted, line  806  shows an estimate of detected photons for a trap-assisted lifetime of 1 μs. Trap-assisted lifetime in line  806  is identified by simulation  306  based on detected photons  808 ; trap-assisted lifetime in line  810  is identified by simulation  306  based on detected photons  812 ; and trap-assisted lifetime in line  814  is identified by simulation  306  based on detected photons  816 . These detected photons are examples of detected photons  414  for three different locations of material  104 . These trap-assisted recombination lifetimes are the trap-assisted recombination lifetimes for which error  412  is closest to zero for the different locations. 
     Turning now to  FIG. 9 , an illustration of a map representing trap-assisted recombination lifetimes for a material is depicted in accordance with an illustrative embodiment. In  FIG. 9 , map  900  is an example of one form of map  314  in  FIG. 3 . As depicted, map  900  is an image of a material that has been inspected. 
     In this illustrative example, scale  901  is a legend for the trap-assisted recombination lifetimes in microseconds shown on map  900 . Locations  902  on map  900  are identified by x-axis  904  and y-axis  906  of map  900 . Map  900  shows different trap-assisted lifetimes in different regions. For example, region  908  shows trap-assisted recombination lifetimes that are longer than region  910  and may be more suitable for use in an infrared detector device. As another example, region  910  shows trap-assisted recombination lifetimes that may not be suitable for use in infrared detector devices. A defect is present in region  910  in this example. 
     In this illustrative example, a 0.5 mm laser spot size was used to identify the trap-assisted recombination lifetimes shown on map  900  for material  104 . As depicted, defect  912  in material  104  is in region  910 . 
     With reference next  FIG. 10 , an illustration of a map having a higher resolution is depicted in accordance with an illustrative embodiment. In this illustration, map  1000  shows locations  1002  that represent additional trap-assisted recombination lifetimes identified by simulation  306  for material  104 . Map  1000  is a higher resolution map of region  910  in  FIG. 9 . In this illustrative example, a 0.15 mm laser spot size was used to identify the trap-assisted recombination lifetimes of material  104  for region  910  having defect  912 . 
     With reference now to  FIG. 11 , an illustration of a map generated from reading signals from an infrared focal plane array is depicted in accordance with an illustrative embodiment. In this illustration, map  1100  is an infrared image generated by an infrared focal plane array. The infrared focal plane array in this example is formed using region  910  of material  104 . As depicted, section  1102  of map  1100  shows defect  912  in material  104 . 
     Turning next to  FIG. 12 , an illustration of a flowchart of a process for identifying carrier lifetimes in a material for use in an optical device is depicted in accordance with an illustrative embodiment. The process illustrated in  FIG. 12  may be implemented in inspection environment  100  in  FIG. 1 . In particular, the process may be implemented in inspection system  102  to inspect material  104  and identify carrier lifetimes  130  to determine suitability of material  104  for use in optical device  108 . 
     The process begins by sending a beam of light to a group of locations on the material (step  1200 ). The process then detects photons emitted from the material at each of the group of locations (step  1202 ). 
     Next, the process identifies a carrier lifetime for each of the group of locations based on the photons detected from each of the group of locations (step  1204 ). The process then performs an action (step  1206 ) with the process terminating thereafter. 
     With reference now to  FIG. 13 , an illustration of a flowchart of a process for identifying carrier lifetimes is depicted in accordance with an illustrative embodiment. The process illustrated in  FIG. 13  is an example of one implementation for step  1204  in  FIG. 12 . 
     The process begins by simulating trap-assisted recombination for the material in response to the beam of light on the material in the simulation (step  1300 ). The process also simulates an occurrence of radiative recombination in response to the beam of light in the simulation (step  1302 ). 
     The process varies the trap-assisted recombination in the simulation to find a level of the trap-assisted recombination that causes the photons emitted from the material to match the photons detected within a desired level of variance (step  1304 ). The process identifies the carrier lifetime for each of the group of locations based on the trap-assisted recombination identified (step  1306 ) with the process terminating thereafter. 
     Turning to  FIG. 14 , an illustration of a flowchart of a process for identifying trap-assisted recombination lifetimes is depicted in accordance with an illustrative embodiment. The process illustrated in Figure is an example of one implementation for step  1304  in  FIG. 13 . 
     The process begins by generating a trap-assisted recombination lifetime based on a range of trap-assisted recombination lifetimes (step  1400 ). The process identifies an estimate of detected photons based on the trap-assisted recombination lifetime and simulation information (step  1402 ). 
     The process then identifies an amount of error based on the difference between the estimate of detected photons and detected photons in data (step  1404 ). The detected photons are an example of detected photons  414  emitted from material  104 . In the illustrative example, steps  1400 - 1404  may be repeated until the process finds the trap-assisted recombination lifetime in range of trap-assisted recombination lifetimes for which the error is closest to zero. 
     The flowcharts and block diagrams in the different depicted embodiments illustrate the architecture, functionality, and operation of some possible implementations of apparatuses and methods in an illustrative embodiment. In this regard, each block in the flowcharts or block diagrams may represent at least one of a module, a segment, a function, or a portion of an operation or step. For example, one or more of the blocks may be implemented as program code, in hardware, or a combination of the program code and hardware. When implemented in hardware, the hardware may, for example, take the form of integrated circuits that are manufactured or configured to perform one or more operations in the flowcharts or block diagrams. When implemented as a combination of program code and hardware, the implementation may take the form of firmware. 
     In some alternative implementations of an illustrative embodiment, the function or functions noted in the blocks may occur out of the order noted in the figures. For example, in some cases, two blocks shown in succession may be performed substantially concurrently, or the blocks may sometimes be performed in the reverse order, depending upon the functionality involved. Also, other blocks may be added in addition to the illustrated blocks in a flowchart or block diagram. For example, simulation of the recombination of carriers in  FIG. 13  may also include simulating auger recombination. 
     Turning now to  FIG. 15 , an illustration of a block diagram of a data processing system is depicted in accordance with an illustrative embodiment. Data processing system  1500  may be used to implement computer system  216  in  FIG. 2 . In this illustrative example, data processing system  1500  includes communications framework  1502 , which provides communications between processor unit  1504 , memory  1506 , persistent storage  1508 , communications unit  1510 , input/output (I/O) unit  1512 , and display  1514 . In this example, communications framework  1502  may take the form of a bus system. 
     Processor unit  1504  serves to execute instructions for software that may be loaded into memory  1506 . Processor unit  1504  may be a number of processors, a multi-processor core, or some other type of processor, depending on the particular implementation. 
     Memory  1506  and persistent storage  1508  are examples of storage devices  1516 . A storage device is any piece of hardware that is capable of storing information, such as, for example, without limitation, at least one of data, program code in functional form, or other suitable information either on a temporary basis, a permanent basis, or both on a temporary basis and a permanent basis. Storage devices  1516  may also be referred to as computer readable storage devices in these illustrative examples. Memory  1506 , in these examples, may be, for example, a random access memory or any other suitable volatile or non-volatile storage device. Persistent storage  1508  may take various forms, depending on the particular implementation. 
     For example, persistent storage  1508  may contain one or more components or devices. For example, persistent storage  1508  may be a hard drive, a flash memory, a rewritable optical disk, a rewritable magnetic tape, or some combination of the above. The media used by persistent storage  1508  also may be removable. For example, a removable hard drive may be used for persistent storage  1508 . 
     Communications unit  1510 , in these illustrative examples, provides for communications with other data processing systems or devices. In these illustrative examples, communications unit  1510  is a network interface card. 
     Input/output unit  1512  allows for input and output of data with other devices that may be connected to data processing system  1500 . For example, input/output unit  1512  may provide a connection for user input through at least of a keyboard, a mouse, or some other suitable input device. Further, input/output unit  1512  may send output to a printer. Display  1514  provides a mechanism to display information to a user. 
     Instructions for at least one of the operating system, applications, or programs may be located in storage devices  1516 , which are in communication with processor unit  1504  through communications framework  1502 . The processes of the different embodiments may be performed by processor unit  1504  using computer-implemented instructions, which may be located in a memory, such as memory  1506 . 
     These instructions are referred to as program code, computer usable program code, or computer readable program code that may be read and executed by a processor in processor unit  1504 . The program code in the different embodiments may be embodied on different physical or computer readable storage media, such as memory  1506  or persistent storage  1508 . 
     Program code  1518  is located in a functional form on computer readable media  1520  that is selectively removable and may be loaded onto or transferred to data processing system  1500  for execution by processor unit  1504 . Program code  1518  and computer readable media  1520  form computer program product  1522  in these illustrative examples. In one example, computer readable media  1520  may be computer readable storage media  1524  or computer readable signal media  1526 . 
     In these illustrative examples, computer readable storage media  1524  is a physical or tangible storage device used to store program code  1518  rather than a medium that propagates or transmits program code  1518 . Alternatively, program code  1518  may be transferred to data processing system  1500  using computer readable signal media  1526 . Computer readable signal media  1526  may be, for example, a propagated data signal containing program code  1518 . For example, computer readable signal media  1526  may be at least one of an electromagnetic signal, an optical signal, or any other suitable type of signal. These signals may be transmitted over at least one of communications links, such as wireless communications links, optical fiber cable, coaxial cable, a wire, or any other suitable type of communications link. 
     The different components illustrated for data processing system  1500  are not meant to provide architectural limitations to the manner in which different embodiments may be implemented. The different illustrative embodiments may be implemented in a data processing system including components in addition to or in place of those illustrated for data processing system  1500 . Other components shown in  FIG. 15  can be varied from the illustrative examples shown. The different embodiments may be implemented using any hardware device or system capable of running program code  1518 . 
     Thus, the illustrative embodiments provide a method and apparatus for identifying carrier lifetimes for materials for use in optical detectors. In this illustrative example, inspection system  102  may be used to identify carrier lifetimes for the material used in an infrared detector device such as an infrared focal plane array. In other illustrative examples, inspection system  102  may be used to identify carrier lifetimes for a material used in other types of optical devices such as those used to detect visible light, ultraviolet light, or other wavelengths of radiation. 
     With an illustrative example, inspection of the material may be performed sooner in manufacturing. By identifying carrier lifetimes from photons emitted in response to light directed onto the material, inspecting materials using an illustrative example occurs at a time in manufacturing sooner than is currently performed. This type of inspection allows for inspecting the material at a sooner point in time in manufacturing than when inspections currently occur. The technical problem of wasting resources and time that occurs when infrared detector devices are currently tested is reduced or avoided. A technical effect occurs in which manufacturing infrared detector devices may occur more quickly and at a lower cost as compared to currently used manufacturing processes that inspect infrared detector devices when they are complete. 
     The description of the different illustrative embodiments has been presented for purposes of illustration and description and is not intended to be exhaustive or limited to the embodiments in the form disclosed. The different illustrative examples describe components that perform actions or operations. In an illustrative embodiment, a component may be configured to perform the action or operation described. For example, the component may have a configuration or design for a structure that provides the component an ability to perform the action or operation that is described in the illustrative examples as being performed by the component. 
     Many modifications and variations will be apparent to those of ordinary skill in the art. Further, different illustrative embodiments may provide different features as compared to other desirable embodiments. The embodiment or embodiments selected are chosen and described in order to best explain the principles of the embodiments, the practical application, and to enable others of ordinary skill in the art to understand the disclosure for various embodiments with various modifications as are suited to the particular use contemplated.