Method and device for predicting service life of wide bandgap semiconductor detector and optoelectronic device

Abstract

The invention discloses a life prediction method and device for a wide bandgap semiconductor detector and a photoelectronic device, and the method comprises the following steps: building a complete multi-segment device performance failure model, and introducing a key fitting coefficient group; under different environmental conditions, performing multi-stress accelerated aging on the to-be-tested device and calculating the responsivity of the detector; performing mathematical model fitting on the data of the performance of the to-be-tested device along with time change under different environmental conditions, determining a fitting coefficient, and obtaining a life prediction model of the to-be-tested device; and predicting the service life of the to-be-tested device under different conditions by using the service life prediction model. The service life prediction model formula and the accelerated aging test method established by the invention can efficiently predict the service life of the detector and the optoelectronic device, and are suitable for service life evaluation of different chips and devices in various working environments; and an acceleration factor model is also adopted to predict the attenuation condition of the detector in long-term use in a short time, so that the time required for life evaluation is greatly shortened.

Description

Technical Field

[0001] The present invention relates to the field of photodetectors, and particularly to a method and device for predicting the lifetime of a wide-bandgap semiconductor detector and optoelectronic devices. Background Art

[0002] Semiconductor Classification Semiconductors can be classified into narrow-bandgap semiconductors (Eg < 1 eV), medium-bandgap semiconductors (1 < Eg < 2.5 eV), and wide-bandgap semiconductors (Eg > 2.5 eV) according to the band gap (Band Gap, Eg). Semiconductors with different band gaps have different physical properties and application scenarios. Due to its relatively large band gap, wide-bandgap semiconductors have unique electrical and optical properties, providing new possibilities for the development of high-performance optoelectronic devices.

[0003] Applications and Challenges of Photodetectors Photodetectors are increasingly widely used in fields such as national defense, aerospace, environmental monitoring, and medical imaging. Especially the demand for use in extreme environments (such as high temperature, high humidity, strong radiation, etc.) is increasing day by day, posing higher requirements for the reliability and lifetime of the detectors. However, current research on the lifetime prediction of wide-bandgap semiconductor detectors is still in the exploratory stage. A systematic lifetime prediction model has not been established, and the laws of detector performance degradation and lifetime under different conditions are not clear. This makes it difficult to accurately estimate the service life of detectors in practical applications, increasing the costs of equipment maintenance and replacement, and may also affect the normal operation of related systems.

[0004] Commonly used lifetime prediction models for other optoelectronic devices before mainly include the Arrhenius model, the Erying model, and the inverse power law model. These models respectively describe the influence of external factors such as temperature, humidity, electric field, and stress on the performance degradation of devices. The Arrhenius model mainly considers the influence of temperature on the chemical reaction rate, and then infers the change of device performance with temperature; the Erying model starts from the perspective of quantum mechanics and describes the influence of factors such as temperature and pressure on the reaction rate; the inverse power law model is commonly used to describe the influence of factors such as mechanical stress on the device lifetime. However, these models are not fully applicable to the performance degradation and lifetime prediction of wide-bandgap semiconductor detectors in complex environments because the performance of wide-bandgap semiconductor detectors is affected by a variety of factors comprehensively, and its internal physical mechanism is different from that of traditional optoelectronic devices. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem in the prior art that there is a lack of performance degradation and lifetime prediction of wide-bandgap semiconductor detectors in complex environments.

[0006] The technical solution adopted by the present invention to solve its technical problems is: to provide a method for predicting the lifetime of a wide-bandgap semiconductor detector and optoelectronic devices, including the following steps:

[0007] Establish a complete multi-stage device performance degradation model and introduce a set of key fitting coefficients;

[0008] Under different environmental conditions, the device under test is subjected to multi-stress accelerated aging and the responsivity of the detector is calculated; the device under test includes a wide bandgap semiconductor detector and an optoelectronic device with photoelectric aging and failure characteristics;

[0009] Perform mathematical model fitting on the data of performance changes of the device under test over time under different environmental conditions, determine the fitting coefficient, and obtain a life prediction model for the device under test;

[0010] The lifetime prediction model is used to predict the lifetime of the device under test under different conditions.

[0011] Preferably, the multi-stage device performance degradation model is expressed as:

[0012] D = K(t) + T(t) + P(t);

[0013] K(t)=D1e -αt +C1;

[0014] T(t)=-βt+C2;

[0015] P(t)=-γe at ;

[0016] Where D represents the detector performance, K(t) represents the decay in the first stage, T(t) represents the decay in the second stage, P(t) represents the sudden rapid decay in the final stage, t represents time, and α, β, γ, a, C1, and C2 are the key fitting coefficients in different stages, respectively.

[0017] Preferably, the accelerated aging of the device under test and calculation of the detector's responsivity under different environmental conditions are achieved through a multi-stress accelerated aging experimental system; the multi-stress accelerated aging experimental system includes:

[0018] High temperature aging chamber, used to provide different temperatures to simulate temperature aging;

[0019] High temperature and high humidity oven, used to provide different temperature and humidity combinations to simulate high humidity aging;

[0020] UV lighting system, used to provide ultraviolet rays of different intensities to simulate UV radiation aging;

[0021] Test system for measuring the responsivity of detectors at different optical power densities.

[0022] Preferably, the ultraviolet lighting system comprises:

[0023] Deep ultraviolet LED light source, used to provide stable ultraviolet light irradiation;

[0024] Horizontal fine-tuning slide, used to adjust the placement of the detector and radiometer to ensure that they are in the same position during the same measurement;

[0025] The T-shaped column is used to adjust the height of the light source, thereby changing the light intensity and simulating UV radiation aging of different intensities.

[0026] Preferably, the measurement process of the measurement system includes the following steps:

[0027] Different light power densities can be set by changing the distance between the light source and the detector;

[0028] Fix the device under test on the fine-tuning slide, apply a -5V bias, and measure its photocurrent I total and dark current I dark ;

[0029] Place the radiometer at the same location and record the light power density it measures;

[0030] By formula I ph =I total -I dark Calculate the responsivity of the device under test.

[0031] Preferably, the lifespan prediction model is expressed as:

[0032] L = t1 + t2;

[0033]

[0034] Where L represents the predicted lifespan, t1 represents the time required for the entire degradation process in the first stage, t2 represents the time required for the device performance to decay to y% of the original performance after entering the second stage of decay, and the device failure is defined as the time when the device performance decays to y% of the original performance; at the end of the first stage of decay, the device performance drops to x% of the initial value L0; D0 represents the initial performance of the detector, satisfying D0 = D1 + C1; E a is the activation energy of the detector, k is the Boltzmann constant, T is the absolute temperature, H R is the relative humidity, S is the deep ultraviolet light power density; A, a, b, n are the key fitting coefficients: A is a constant, a and b are the influence coefficients of light intensity and humidity on the attenuation rate, and n is the influence coefficient of humidity on the attenuation rate.

[0035] Preferably, the value range of x% is 85%-90%, and y% is 80%.

[0036] Preferably, the lifetime prediction model is used to predict the lifetime of the device under test under different conditions, specifically by directly using the specific stress value of the working environment of the device under test as the independent variable of the lifetime prediction model to obtain the corresponding dependent variable L, which is the lifetime of the device under test; the environmental stress includes temperature, humidity, and light power density.

[0037] Preferably, the method of using the life prediction model to predict the life of the device under test under different conditions includes the following steps:

[0038] The lifetime t0 of the device under test in the first stage is measured in a laboratory environment;

[0039] Detect the specific stress values of the working environment of the device under test, including temperature T1, relative humidity H R1 and optical power density S1;

[0040] Predict the time t1 required for the DUT to undergo the entire first stage of degradation in the working environment, expressed as:

[0041]

[0042] Among them, T0, H R0 and S0 are the temperature, relative humidity and light power density of the laboratory environment; a and b are the influence coefficients of light intensity on the attenuation rate; n is the influence coefficient of humidity on the attenuation rate;

[0043] Predict the lifetime t2 of the device under test in the second stage, expressed as:

[0044]

[0045] The present invention also provides a lifetime prediction device for a wide bandgap semiconductor detector and an optoelectronic device, comprising:

[0046] Establish modules, build a complete multi-stage device performance degradation model, and introduce key fitting coefficient groups;

[0047] The test module performs multi-stress accelerated aging on the device under test under different environmental conditions and calculates the responsivity of the detector; the device under test includes a wide bandgap semiconductor detector and an optoelectronic device with photoelectric aging and failure characteristics;

[0048] The fitting module performs mathematical model fitting on the data of the performance change of the device under test under different environmental conditions over time, determines the fitting coefficient, and obtains the life prediction model of the device under test;

[0049] The prediction module uses the life prediction model to predict the life of the device under test under different conditions.

[0050] The present invention has the following beneficial effects: the present invention directly calculates the lifespan of detectors and other optoelectronic devices through a life prediction formula, and is applicable to life assessments in various working environments; the present invention also adopts an acceleration factor model to predict the attenuation of detectors in long-term use in a short period of time, significantly shortening the time required for life assessment; the present invention can be widely used in multiple fields such as product research and development, quality control, and industrial applications, providing a theoretical basis for the reliability design of detectors.

[0051] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments, but the present invention is not limited to the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A diagram showing the steps of a method according to an embodiment of the present invention;

[0053] Figure 2 A schematic diagram of a wide bandgap semiconductor detector attenuation curve according to an embodiment of the present invention;

[0054] Figure 3 Data curves showing the performance degradation of LEDs, photodetectors, and solar cells as they age;

[0055] Figure 4 2 is a structural diagram of a device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The embodiment of the present invention provides a life prediction method for an optoelectronic device with photoelectric aging and failure characteristics.

[0057] See also Figure 1 FIG. 1 is a diagram showing steps of a method according to an embodiment of the present invention, comprising the following steps:

[0058] S101, establish a complete multi-stage device performance degradation model and introduce a key fitting coefficient group;

[0059] S102, performing multi-stress accelerated aging on the device under test under different environmental conditions and calculating the responsivity of the detector; the device under test includes a wide bandgap semiconductor detector and an optoelectronic device with photoelectric aging failure characteristics;

[0060] S103, performing mathematical model fitting on the data of performance changes of the device under test under different environmental conditions over time, determining fitting coefficients, and obtaining a life prediction model for the device under test;

[0061] S104, using the life prediction model to predict the life of the device under test under different conditions.

[0062] The embodiment of the present invention uses a wide bandgap semiconductor detector as an example to illustrate the detailed process. During long-term use, the performance degradation of the detector generally undergoes a trend of first exponential decay and then linear decay. The exponential decay phase is long, which is not conducive to quickly obtaining life prediction results. Therefore, through multi-stress accelerated aging experiments, the exponential phase is accelerated to skip the linear decay phase, so that the detector enters the linear decay phase as soon as possible, improving the efficiency and accuracy of life prediction. In order to achieve multi-stress aging acceleration and accurately measure the detector's responsiveness under different optical power densities, different temperatures, and different temperature and humidity conditions, a complete test system has been designed. The system consists of the following parts:

[0063] Fixed deep ultraviolet LED light source: provides stable ultraviolet light irradiation.

[0064] X-axis rack-type fine-tuning slide and Z-axis T-column combination platform: used to control the relative positions of the detector, irradiometer and light source to achieve precise control.

[0065] Keithley 2450 source meter: used to apply bias voltage and measure the photogenerated current of the detector.

[0066] UV radiometer: used to monitor the power density of ultraviolet light irradiating on the detector surface in real time.

[0067] High temperature aging chamber, provides different temperatures to simulate temperature aging.

[0068] High temperature and high humidity oven provides different temperature and humidity combinations to simulate the synergistic aging effect of high temperature and humidity.

[0069] During the test, the X-axis slide is used to adjust the position of the light source on the detector and the radiometer to ensure that both receive the same light power density. First, the detector is fixed on the fine-tuning slide and a -5V bias is applied to measure its photocurrent and dark current. Then, the radiometer is placed in the same position and the corresponding light power density is recorded. I ph =I total -I dark Calculate the detector's responsivity. By varying the light source-detector distance, different optical power densities can be achieved. A high-temperature aging chamber can be used to provide different temperatures to simulate temperature aging. A high-temperature, high-humidity oven can be used to provide different combinations of temperature and humidity to simulate high-humidity aging.

[0070] During the experiment, the detector is tested every certain period of time, its performance changes are recorded, and a performance decay curve is drawn, such as Figure 2As shown in the figure, the detector's responsivity changes over aging time through two distinct phases: an initial exponential decay and a mid-stage linear decay. Furthermore, some detectors also exhibit a sudden, rapid decay in the later stages of aging, which is classified as a third phase. Based on this observation, mathematical modeling of the decay characteristics of different phases was developed, ultimately leading to the general formula for detector performance degradation, D = K(t) + T(t) + P(t).

[0071] First, in the initial stage of aging, the detector's responsivity decreases rapidly, showing a typical exponential decay trend, which indicates that the performance degradation of the detector is mainly affected by the internal defects of the material, the interface state, etc., and K(t) = D1e -αt +C1 is used to describe the performance decay rate of the detector. As time goes by, the performance decay rate of the detector tends to be stable and enters the linear decay stage. At this time, the decay is mainly controlled by stable physical mechanisms, such as the reduction of carrier mobility inside the device and the degradation of electrode contact. It is fitted with T(t) = -βt+C2. After aging to a certain stage, the responsivity of some detectors suddenly decreases, indicating the existence of sudden accelerated decay. This may be caused by factors such as device packaging failure, electrode damage, and microcrack expansion caused by internal stress concentration. Therefore, an additional exponential term P(t) = -γe is introduced. at , which is used to simulate the impact of these accidental events on detector performance. By fitting experimental data, it is found that this model can well describe the complete decay process of the detector and effectively improve the accuracy of lifetime prediction.

[0072] The exponential decay model K(t) = D1e is obtained. -αt After + C1, the physical meaning of each parameter in the model is further explored to establish a more accurate life prediction model. Among them, D0 represents the initial performance of the detector, satisfying D0 = D1 + C1, t is the operating time (hours), and α is the attenuation coefficient, which determines the aging rate of the detector. In addition, external stress factors that affect the attenuation rate are considered, including temperature (T), relative humidity (H R ) and deep ultraviolet light power intensity (S), and through fitting the experimental data, the quantitative relationship between α and these stress factors was further derived.

[0073] Specifically, the attenuation coefficient α follows the thermally activated attenuation model and satisfies the following relationship: Among them, A is a constant, E a is the activation energy of the detector, k is the Boltzmann constant (8.62×10 -5 eV / K), T is the absolute temperature (K), H R is the relative humidity, S is the deep ultraviolet light power density, a and b are the influence coefficients of light intensity on the attenuation rate, and n is the influence coefficient of humidity on the attenuation rate.

[0074] The formula shows that the detector's decay rate is mainly dominated by temperature-activated decay, while relative humidity and ultraviolet radiation also have a significant impact on the decay rate.

[0075] Through experimental fitting, the activation energy E of the detector was successfully solved. a , further revealing the decay mechanism of detectors under different aging conditions. This research not only deepens our understanding of the detector aging process, but also lays the foundation for more accurate lifetime prediction models.

[0076] In the detector aging curve, assume that the first exponential decays to x% of the initial value; in the experiment, the range of x% is about 85%-90%. Then the following relationship is obtained:

[0077]

[0078] Based on this condition, the calculation formula for the detector's first-stage life t1 can be derived:

[0079]

[0080] Combined with the expression of the attenuation coefficient α, the life formula is further obtained:

[0081]

[0082] To study the impact of different environmental conditions on the detector aging rate, a multi-stress acceleration factor was further introduced in the first stage to calculate the relative lifespan change under different aging conditions. When the detector is aged under the environmental parameters (T1, HR1, S1) and (T2, HR2, S2), the first stage aging time is t11 and t12 respectively; the multi-stress acceleration factor θ is:

[0083]

[0084] The independent variables in the life prediction model are the environmental stresses of the detector's operation, including temperature, humidity, and optical power density, and the dependent variable is the detector's service life. Based on these environmental stresses and the multiple stress aging factors in the model, the detector's future degradation trend is determined, yielding the detector's lifespan. By substituting the ratio of the actual state to the accelerated aging state into the accelerated attenuation factor, we can derive the actual operating lifespan. Substituting this ratio into the laboratory lifespan data yields the predicted actual lifespan.

[0085] In the above experimental scheme, detectors were tested to determine the trends in the responsivity of multiple detectors over aging time. Based on the performance degradation trends of the detectors under different conditions, a detector attenuation model and the effects of different stresses on the detectors were determined. This model then determined the relationship between the detector lifespan and different stresses. The lifespan model can then be used to determine when a detector will reach failure criteria or to predict its health status after a certain period of operation in different environments. This model eliminates the need for extensive historical usage data to determine aging trends, simplifying the detector lifespan prediction process.

[0086] Specifically, the detector life prediction model finally obtained by fitting is expressed as:

[0087] L = t1 + t2;

[0088]

[0089] Wherein, L represents the predicted lifespan, t1 represents the time required for the entire degradation process in the first stage, and t2 represents the time required for the device performance to decay to 80% of the original performance after entering the second stage of decay. In this embodiment, device failure is defined as the time when the device performance decays to 80% of the original performance. At the end of the first stage of decay, the device performance drops to X% of the initial value L0. D0 represents the initial performance of the detector, satisfying D0=D1+C1. E a is the activation energy of the detector, k is the Boltzmann constant, T is the absolute temperature, H R is the relative humidity, S is the deep ultraviolet light power density; A, a, b, n are the key fitting coefficients: A is a constant, a and b are the influence coefficients of light intensity and humidity on the attenuation rate, and n is the influence coefficient of humidity on the attenuation rate.

[0090] Specifically, when using the detector life prediction model to predict the life of the device under different conditions, the specific stress value of the detector working environment is directly used as the independent variable of the detector life prediction model to obtain the corresponding dependent variable L, which is the detector life; the environmental stress includes temperature, humidity, and light power density.

[0091] Specifically, the detector life prediction model is used to predict the life of the device under different conditions, and multiple stress acceleration factors can also be used. Specifically, the following steps are included:

[0092] The life of the detector in the first stage t0 was measured in a laboratory environment;

[0093] Detect the specific stress values of the detector working environment, including temperature T1, relative humidity H R1 and optical power density S1;

[0094] The time t1 required for the detector to go through the first stage of the exhaustion process in the working environment is predicted to be:

[0095]

[0096] Among them, T0, H R0 and S0 are the temperature, relative humidity and light power density of the laboratory environment; a and b are the influence coefficients of light intensity on the attenuation rate; n is the influence coefficient of humidity on the attenuation rate;

[0097] The predicted life of the detector in the second stage, t2, is expressed as:

[0098]

[0099] It is also found that the embodiment of the present invention is not only applicable to detectors, but also the decay trends of other optoelectronic devices such as LEDs and solar cells can be classified in the same way. Figure 3 As shown in the figure, the performance attenuation curve fitting images of LED, photodetector and solar cell with aging time reported in the literature prove the universality of this model.

[0100] By fitting data from other literature, it is found that, except for the exponential decay of light-emitting diodes, both photodetectors and solar cells can be summarized as first exponential and then linear, indicating that the device aging time is not long enough. This patent innovatively predicts a sudden rapid decay in the late aging period and fits it with the T(t) model. Therefore, the multi-stage device performance degradation model of the embodiment of the present invention can be used not only for wide-bandgap semiconductor detectors, but also for the life prediction of other optoelectronic devices. The decay models of relevant optoelectronic devices are summarized in the following table:

[0101] light-emitting diodes Photodetectors solar cells <![CDATA[D φ =K(t)]]> <![CDATA[D R =K(t)+T(t)]]> <![CDATA[D Q =K(t)+T(t)]]>

[0102] See also Figure 4 FIG. 1 is a structural diagram of a device according to an embodiment of the present invention, comprising:

[0103] Establishing module 401, establishing a complete multi-stage device performance degradation model and introducing a key fitting coefficient group;

[0104] Testing module 402, performing multi-stress accelerated aging on a device under test under different environmental conditions and calculating the detector responsivity; the device under test includes a wide bandgap semiconductor detector and an optoelectronic device with photoelectric aging failure characteristics;

[0105] The fitting module 403 performs mathematical model fitting on the data of performance changes of the device under test under different environmental conditions over time, determines the fitting coefficient, and obtains a life prediction model for the device under test;

[0106] The prediction module 404 uses the life prediction model to predict the life of the device under test under different conditions.

[0107] It can be seen that the lifetime prediction method and device of a wide bandgap semiconductor detector proposed in the present invention can more accurately describe the detector degradation law and realize lifetime prediction more quickly.

[0108] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for predicting the lifetime of wide bandgap semiconductor detectors and optoelectronic devices, characterized in that: The following steps are involved: Establish a complete multi-stage device performance degradation model and introduce a set of key fitting coefficients; Under different environmental conditions, the device under test is subjected to multi-stress accelerated aging and the responsivity of the detector is calculated; the device under test includes a wide bandgap semiconductor detector and an optoelectronic device with photoelectric aging and failure characteristics; Perform mathematical model fitting on the data of performance changes of the device under test over time under different environmental conditions, determine the fitting coefficient, and obtain a life prediction model for the device under test; The lifetime prediction model is used to predict the lifetime of the device under test under different conditions.

2. The lifetime prediction method of a wide bandgap semiconductor detector according to claim 1, characterized in that: The multi-stage device performance degradation model is expressed as: D = K(t) + T(t) + P(t); K(t)=D1e -αt +C1; T(t)=-βt+C2; P(t)=-γe at ; Where D represents the detector performance, K(t) represents the decay in the first stage, T(t) represents the decay in the second stage, P(t) represents the sudden rapid decay in the final stage, t represents time, and α, β, γ, a, C1, and C2 are the key fitting coefficients in different stages, respectively.

3. The lifetime prediction method of a wide bandgap semiconductor detector according to claim 1, characterized in that: The accelerated aging of the device under test and calculation of the detector's responsivity under different environmental conditions are achieved through a multi-stress accelerated aging experimental system; The multi-stress accelerated aging experimental system includes: High temperature aging chamber, used to provide different temperatures to simulate temperature aging; High temperature and high humidity oven, used to provide different temperature and humidity combinations to simulate high humidity aging; UV lighting system, used to provide ultraviolet rays of different intensities to simulate UV radiation aging; Test system for measuring the responsivity of detectors at different optical power densities.

4. The lifetime prediction method of a wide bandgap semiconductor detector according to claim 3, characterized in that: The ultraviolet lighting system comprises: Deep ultraviolet LED light source, used to provide stable ultraviolet light irradiation; Horizontal fine-tuning slide, used to adjust the placement of the detector and radiometer to ensure that they are in the same position during the same measurement; The T-shaped column is used to adjust the height of the light source, thereby changing the light intensity and simulating UV radiation aging of different intensities.

5. The lifetime prediction method of a wide bandgap semiconductor detector according to claim 3, characterized in that: The measurement process of the measurement system includes the following steps: Different light power densities can be set by changing the distance between the light source and the detector; Fix the device under test on the fine-tuning slide, apply a -5V bias, and measure its photocurrent I total and dark current I dark ; Place the radiometer at the same location and record the light power density it measures; By formula I ph =I total -I dark Calculate the responsivity of the device under test.

6. The lifetime prediction method of a wide bandgap semiconductor detector according to claim 1, characterized in that: The life prediction model is expressed as: L = t1 + t2; Where L represents the predicted lifespan, t1 represents the time required for the entire degradation process in the first stage, t2 represents the time required for the device performance to decay to y% of the original performance after entering the second stage of decay, and the device failure is defined as the time when the device performance decays to y% of the original performance; at the end of the first stage of decay, the device performance drops to x% of the initial value L0; D0 represents the initial performance of the detector, satisfying D0 = D1 + C1; E a is the activation energy of the detector, k is the Boltzmann constant, T is the absolute temperature, H R is the relative humidity, S is the deep ultraviolet light power density; A, a, b, n are the key fitting coefficients: A is a constant, a and b are the influence coefficients of light intensity and humidity on the attenuation rate, and n is the influence coefficient of humidity on the attenuation rate.

7. The life prediction method of a wide bandgap semiconductor detector according to claim 6, characterized in that: The value range of x% is 85%-90%, and y% is 80%.

8. The lifetime prediction method of a wide bandgap semiconductor detector according to claim 1, characterized in that: The lifetime prediction model is used to predict the lifetime of the device under test under different conditions. Specifically, the specific stress value of the working environment of the device under test is directly used as the independent variable of the lifetime prediction model to obtain the corresponding dependent variable L, which is the lifetime of the device under test; the environmental stress includes temperature, humidity, and optical power density.

9. The lifetime prediction method of a wide bandgap semiconductor detector according to claim 6, characterized in that: The method of using the life prediction model to predict the life of the device under test under different conditions includes the following steps: The lifetime t0 of the device under test in the first stage is measured in a laboratory environment; Detect the specific stress values of the working environment of the device under test, including temperature T1, relative humidity H R1 and optical power density S1; Predict the time t1 required for the DUT to undergo the entire first stage of degradation in the working environment, expressed as: Among them, T0, H R0 and S0 are the temperature, relative humidity and light power density of the laboratory environment; a and b are the influence coefficients of light intensity on the attenuation rate; n is the influence coefficient of humidity on the attenuation rate; Predict the lifetime t2 of the device under test in the second stage, expressed as:

10. A lifetime prediction device for wide bandgap semiconductor detectors and optoelectronic devices, characterized in that: include: Establish modules, build a complete multi-stage device performance degradation model, and introduce key fitting coefficient groups; The test module performs multi-stress accelerated aging on the device under test under different environmental conditions and calculates the responsivity of the detector; the device under test includes a wide bandgap semiconductor detector and an optoelectronic device with photoelectric aging and failure characteristics; The fitting module performs mathematical model fitting on the data of the performance change of the device under test under different environmental conditions over time, determines the fitting coefficient, and obtains the life prediction model of the device under test; The prediction module uses the life prediction model to predict the life of the device under test under different conditions.

Images