Method for evaluating semiconductor samples, apparatus for evaluating semiconductor samples, and method for manufacturing semiconductor wafers

Abstract

A method for evaluating a semiconductor sample is provided, comprising: obtaining a decay curve by subjecting a semiconductor sample to evaluation to a measurement by an optical conduction decay method; performing the measurement multiple times while changing the surface charge density; performing signal data processing on at least one decay curve among the decay curves obtained by the multiple measurements using a model equation including an exponential decay term and an integer term; obtaining the recombination lifetime τeff of the semiconductor sample from the exponential decay equation obtained by the signal data processing; obtaining a quadratic function from the measurement results obtained by the multiple measurements, wherein the value related to the surface charge density is the variable x and the value related to the integer term is the variable y; and obtaining the surface recombination lifetime τs of the semiconductor sample from the quadratic function.

Description

Technology Field

[0001] The present invention relates to a method for evaluating a semiconductor sample, an apparatus for evaluating a semiconductor sample, and a method for manufacturing a semiconductor wafer. Background Technology

[0002] The photoconductivity decay method, generally referred to as the PCD method, is widely used for evaluating semiconductor samples. Prior art literature

[0003] Japanese Published Patent Application No. 2019-012740 Japanese Published Patent Application No. Sho 58-181549

[0004] Akira Usami, Fukuyasu Sone, Koji Murai, Kenji Sano, *Laser Research*, Vol. 12, No. 10, pp. 585-594; Akira Usami, Shinichi Kandachi, Botsushi Kudo, *Applied Physics*, Vol. 49, No. 12, 1980, pp. 1192-1197 The problem to be solved

[0005] For example, for silicon wafers, which are an example of semiconductor samples, a method for measuring recombination lifetime by the PCD method has been standardized (SEMI MF1535. Test Methods for Carrier Recombination Lifetime in Silicon Wafers by Noncontact Measurement of Photoconductivity Decay by Microwave Reflectance. 2007; hereinafter referred to as "SEMI Standard").

[0006] The aforementioned SEMI standard describes the first-order mode method and the 1 / e lifetime method as methods for determining the recombination lifetime by the PCD method. In the first-order mode method, the time constant in the range where exponential decay can be considered in the damping curve obtained by measurement by the PCD method is defined as the first-order mode lifetime τ1. The first-order mode lifetime τ1 is the Shockley-Read-Hall (SRH) recombination lifetime (i.e., bulk lifetime) τ b and surface recombination lifetime τ s By, Equation: 1 / τ1 = 1 / τ b +1 / τ s It is represented as. Meanwhile, in the 1 / e lifetime method, when t0 is the time at which excess carriers in a semiconductor sample are excited by a light pulse, t1 is the time until the signal intensity becomes 1 / e times (V1 = V0 / e) with respect to the peak value V0 of the signal intensity V, and the 1 / e lifetime τ e ne, sik: τ e It is expressed as t1 - t0.

[0007] In the above method, the recombination lifetime is calculated under the assumption that the decay of excess carrier concentration takes the form of exponential decay due to the contribution of SRH recombination (i.e., bulk recombination) alone. However, as described, for example, in Patent Document 2, the recombination lifetime (in Patent Document 2, "effective lifetime τ eff In the section stated as 」, the SRH recombination lifetime (bulk lifetime) τ, which is determined by the purity of the semiconductor crystal, crystal defects, etc., of the semiconductor sample under evaluation b In addition to, the surface recombination lifetime τ sIt is also involved. For example, in high-cleanliness silicon wafers, the contribution of SRH recombination becomes relatively weak, making it impossible to ignore contributions such as surface recombination. Consequently, when PCD measurements are performed on high-cleanliness silicon wafers, for instance, the decay curve becomes distorted due to the influence of surface recombination at the end of decay, resulting in non-exponential decay. For instance, in such cases, it is difficult to accurately measure the recombination lifetime using the above method, which is performed under the assumption that the decay of excess carrier concentration takes the form of exponential decay due to the contribution of SRH recombination alone.

[0008] Regarding surface recombination, evaluation methods considering surface recombination are proposed in Patent Document 1, Patent Document 2, and Non-Patent Document 1 and Non-Patent Document 2. However, the method proposed in Patent Document 1 lacks universality because it requires two measurements per sample, making it unsuitable for samples where the recombination lifetime depends on the elapsed time from the surface treatment, and because the creation of a database is indispensable for interpretation. Furthermore, the methods proposed in Patent Document 2, Non-Patent Document 1, and Non-Patent Document 2 are all methods that eliminate deviation from exponential decay caused at the beginning of decay by the influence of modes higher than the first mode as an effect of surface recombination. Therefore, these methods cannot reduce or eliminate the effect of deviation from exponential decay at the end of decay.

[0009] Taking the above into consideration, one aspect of the present invention aims to provide a new evaluation method for evaluating the recombination lifetime of a semiconductor sample with high precision. means of solving the problem

[0010] As a result of repeated careful consideration, the inventors have determined that by performing signal data processing on the damping curve as follows, the recombination lifetime τ effIt has been newly discovered that it becomes possible to calculate with high precision. Furthermore, the inventors have found that by using the model equation as follows, the recombination lifetime τ eff In addition to, surface recombination lifetime τ s I newly discovered that it is also possible to obtain it.

[0011] One aspect of the present invention is as follows.

[0012] [1] Obtaining a decay curve by applying the semiconductor sample to the evaluation target to the light conduction decay method, and performing this multiple times with different surface charge densities.

[0013] Performing signal data processing based on a model equation including an exponential decay term and an integer term for at least one decay curve among the decay curves obtained by the above multiple measurements,

[0014] From the exponential decay equation obtained by the above signal data processing, the recombination lifetime τ of the semiconductor sample eff Finding,

[0015] Deriving a quadratic function from the measurement results obtained by the above multiple measurements, wherein the value related to surface charge density is the variable x and the value related to the integer term is the variable y, and,

[0016] From the above quadratic function, the surface recombination lifetime τ of the semiconductor sample s Finding

[0017] A method for evaluating a semiconductor sample, comprising

[0018] [2] Hagi-sik (11)':

[0019] C min =τ eff / τ s ×n0···(11)'

[0020] (In Equation (11)', n0: equilibrium carrier concentration)

[0021] C in minSetting as the minimum value of y in the above quadratic function, the surface recombination lifetime τ s A method for evaluating a semiconductor sample as described in [1], which yields

[0022] [3] The above reconnection lifetime τ eff and the surface reconnection lifetime τ s From, the SRH recombination lifetime τ of the semiconductor sample b Finding

[0023] A method for evaluating a semiconductor sample as described in [1] or [2], further comprising

[0024] [4] The above SRH recombination lifetime τ b 를, 하기식 (1)':

[0025] 1 / τ eff = 1 / τ b +1 / τ s ···(1)'

[0026] Evaluation method of a semiconductor sample described in [3] obtained from.

[0027] [5] Thickness d of the semiconductor sample and surface recombination lifetime τ s From, the following formula (12):

[0028] S r =d / (2τ) S )···(12)

[0029] The surface recombination rate S of the semiconductor sample by r Finding

[0030] A method for evaluating a semiconductor sample as described in any of [1] to [4], further comprising

[0031] [6] By performing the above signal data processing, the integer term in the above model equation is eliminated to obtain the above equation of exponential decay, and,

[0032] From the above exponential decay equation, the time constant τ b －1 +τ S－1 Finding

[0033] Additionally include, and τ b is the SRH reunion lifetime, and τ S A method for evaluating a semiconductor sample described in any of [1] to [5], which is the surface recombination lifetime.

[0034] [7] The above signal data processing includes repeating the operation of sampling a time series signal modeled by the above model equation and taking the difference, [6] a method for evaluating a semiconductor sample.

[0035] [8] A method for evaluating a semiconductor sample as described in [7], further comprising performing auto-scaling to determine the sampling area for performing the above sampling.

[0036] [9] A method for evaluating a semiconductor sample described in [8], wherein the region with less influence from Auger recombination and less influence from noise is determined as the sampling region by the above auto-scaling.

[0037]

[10] The above model equation is the following equation (10)':

[0038] xi(ti)=A×exp[-(τ b －1 +τ S －1 )ti]-C ···(10)'

[0039] (In Equation (10)', ti: elapsed time after excitation light irradiation, xi(ti): signal intensity at elapsed time ti, τ b : SRH reunion lifetime, τ S : Surface recombination lifetime, A, C: integers)

[0040] A method for evaluating semiconductor samples as described in any of [1] to [9].

[0041]

[11] Hagi-sik (11)':

[0042] C min =τ eff / τs ×n0···(11)'

[0043] (In Equation (11)', n0: equilibrium carrier concentration)

[0044] C in min Setting as the minimum value of y in the above quadratic function, the surface recombination lifetime τ s Calculate,

[0045] The above recombination lifetime τ eff and the surface reconnection lifetime τ s From, the SRH recombination lifetime τ of the semiconductor sample b Additionally, it includes finding,

[0046] The above SRH recombination lifetime τ b 를, 하기식 (1)':

[0047] 1 / τ eff = 1 / τ b +1 / τ s ···(1)'

[0048] Obtaining from,

[0049] Obtaining the equation for exponential decay by eliminating the integer term in the model equation through the above signal data processing, and

[0050] From the above exponential decay equation, the time constant τ b －1 +τ S －1 Finding

[0051] Additionally include, and τ b is the SRH reunion lifetime, and τ S is the surface recombination lifetime, and

[0052] The above signal data processing includes repeating the operation of sampling a time series signal modeled by the above model equation and taking the difference.

[0053] It further includes performing auto-scaling to determine the sampling region for performing the above sampling, and

[0054] By the above auto-scaling, an area with minimal Auger recombination influence and minimal noise influence is determined as the sampling area, and

[0055] The above model equation is the following equation (10):

[0056] xi(ti)=A×exp[-(τ b －1 +τ S －1 )ti]-C···(10)'

[0057] (In Equation (10)', ti: elapsed time after excitation light irradiation, xi(ti): signal intensity at elapsed time ti, τ b : SRH reunion lifetime, τ S : Surface recombination lifetime, A, C: integers)

[0058] A method for evaluating semiconductor samples as described in any of [1] to

[10] .

[0059]

[12] Hagi-sik (11)':

[0060] C min =τ eff / τ s ×n0···(11)'

[0061] (In Equation (11)', n0: equilibrium carrier concentration)

[0062] C in min Setting as the minimum value of y in the above quadratic function, the surface recombination lifetime τ s Calculate,

[0063] The thickness d of the semiconductor sample and the surface recombination lifetime τ s From, the following formula (12):

[0064] S r =d / (2τ) S )···(12)

[0065] The surface recombination rate S of the semiconductor sample by r Additionally, it includes finding,

[0066] Obtaining the equation for exponential decay by eliminating the integer term in the model equation through the above signal data processing, and

[0067] From the above exponential decay equation, the time constant τ b －1 +τ S －1 Finding

[0068] Additionally include, and τ b is the SRH reunion lifetime, and τ S is the surface recombination lifetime, and

[0069] The above signal data processing includes repeating the operation of sampling a time series signal modeled by the above model equation and taking the difference.

[0070] It further includes performing auto-scaling to determine the sampling region for performing the above sampling, and

[0071] By the above auto-scaling, an area with minimal Auger recombination influence and minimal noise influence is determined as the sampling area, and

[0072] The above model equation is the following equation (10):

[0073] xi(ti)=A×exp[-(τ b －1 +τ S －1 )ti]-C···(10)'

[0074] (In Equation (10)', ti: elapsed time after excitation light irradiation, xi(ti): signal intensity at elapsed time ti, τ b : SRH reunion lifetime, τ S : Surface recombination lifetime, A, C: integers)

[0075] A method for evaluating semiconductor samples as described in any of [1] to

[11] .

[0076]

[13] A semiconductor sample evaluation device for performing the semiconductor sample evaluation method described in any of [1] to

[12] ,

[0077] A measuring unit that applies a semiconductor sample to be evaluated for measurement using the optical conductivity attenuation method, and

[0078] A processing unit that performs signal data processing on the above damping curve using a model equation including an exponential damping term and an integer term, and performs the calculation of the above quadratic function.

[0079] The evaluation device including

[0080]

[14] An evaluation device described in

[13] in which the light pulse intensity is variable in the above-mentioned measuring part.

[0081]

[15] The above measuring unit further includes a corona charge processing unit, an evaluation device as described in

[13] or

[14] .

[0082]

[16] The above measuring unit further includes a surface charge density related value measuring unit for measuring the surface charge density related value of the semiconductor sample to be measured, as described in any one of

[13] to

[15] .

[0083]

[17] In the above measuring unit, the light pulse intensity is variable, and

[0084] The evaluation device described in any one of

[13] to

[16] , wherein the above measuring unit further comprises a corona charge processing unit and a surface charge density related value measuring unit for measuring a surface charge density related value of a semiconductor sample subjected to the above measurement.

[0085]

[18] Manufacturing a semiconductor wafer lot containing multiple semiconductor wafers,

[0086] Extracting at least one semiconductor wafer from the above semiconductor wafer lot,

[0087] Evaluating the above-mentioned extracted semiconductor wafer by the evaluation method described in any of [1] to

[12] , and

[0088] As a result of the above evaluation, semiconductor wafers from the same semiconductor wafer lot as the semiconductor wafer judged to be good are put into preparation for shipment as product semiconductor wafers.

[0089] A method for manufacturing a semiconductor wafer including

[0090]

[19] Manufacturing a semiconductor wafer for evaluation under test manufacturing conditions,

[0091] Evaluating the above-mentioned semiconductor wafer for evaluation by the semiconductor sample evaluation method described in any of [1] to

[12] ,

[0092] Based on the results of the above evaluation, determining the manufacturing conditions with modifications added to the above test manufacturing conditions as the actual manufacturing conditions, or determining the above test manufacturing conditions as the actual manufacturing conditions, and,

[0093] Manufacturing a semiconductor wafer under the actual manufacturing conditions determined above

[0094] A method for manufacturing a semiconductor wafer including Effects of the invention

[0095] According to one aspect of the present invention, the recombination lifetime τ eff It becomes possible to calculate with high precision, and additionally, the surface recombination lifetime τ s It also becomes possible to obtain . Brief explanation of the drawing

[0096] Figure 1 is an explanatory diagram of a specific example of signal data processing. Figure 2 is an explanatory diagram of a specific example of signal data processing. Figure 3 is an explanatory diagram of a specific example of signal data processing. FIG. 4 is an explanatory diagram of an example of a method for evaluating a semiconductor sample according to one aspect of the present invention. Figure 5 shows the results of a comparison between an example (new method) of a semiconductor sample evaluation method according to one aspect of the present invention and a conventional method. Figure 6 shows the results of a comparison between an example (new method) of a semiconductor sample evaluation method according to one aspect of the present invention and a conventional method. Figure 7 shows the results of a comparison between an example (new method) of a semiconductor sample evaluation method according to one aspect of the present invention and a conventional method. Fig. 8 shows the surface recombination lifetime τ s This is a schematic diagram of the plot for derivation. Figure 9 shows the quadratic curve obtained in Example 1. Figure 10 shows the quadratic curve obtained in Example 2. Figure 11 shows the attenuation curve obtained by measuring an n-type silicon wafer (single-crystal silicon wafer) using the μ-PCD method after chemical passivation treatment as a surface treatment. Figure 12 shows the fitting curve obtained by first-order mode lifetime fitting and the fitting curve obtained by 1 / e lifetime fitting of the damping curve shown in Figure 11. Specific details for implementing the invention

[0097] (Form for carrying out the invention)

[0098] [Evaluation Method for Semiconductor Samples]

[0099] A method for evaluating a semiconductor sample according to one aspect of the present invention comprises obtaining a decay curve by subjecting a semiconductor sample to be evaluated to a measurement by an optical conduction decay method, performing this multiple times while changing the surface charge density; performing signal data processing on at least one decay curve among the decay curves obtained by the multiple measurements using a model equation including an exponential decay term and an integer term; and determining the recombination lifetime τ of the semiconductor sample from the exponential decay equation obtained by the signal data processing. effCalculating , obtaining a quadratic function from the measurement results obtained by the above multiple measurements, wherein the value related to the surface charge density is the variable x and the value related to the integer term is the variable y, and obtaining the surface recombination lifetime τ of the semiconductor sample from the above quadratic function s It includes finding.

[0100] The above evaluation method will be explained in more detail below.

[0101] <Semiconductor Samples Subject to Evaluation>

[0102] The subject of evaluation in the above evaluation method may be a semiconductor sample. Examples of semiconductor samples include various types such as single-crystal silicon, polycrystalline silicon, and SiC. The shape and dimensions of the semiconductor sample subject to evaluation are not particularly limited. As an example, the semiconductor sample subject to evaluation may be a wafer-shaped semiconductor sample, i.e., a semiconductor wafer, for example, a single-crystal silicon wafer. However, the semiconductor sample subject to evaluation may have a shape other than a wafer. Furthermore, the conductivity type of the semiconductor sample subject to evaluation is not particularly limited and may be either n-type or p-type.

[0103] Measurement by optical conduction attenuation method

[0104] Regarding the measurement by the optical conductivity attenuation method in the above evaluation method, known technology may be applied. Specific examples of the optical conductivity attenuation method include microwave optical conductivity attenuation (μ-PCD). However, the measurement by the optical conductivity attenuation method in the above evaluation method is not limited to the μ-PCD method. For example, considering the maximum carrier injection amount of a typical μ-PCD device, if the semiconductor sample to be evaluated is p-type silicon, its resistivity is suitable to be about 1 to 100 Ωcm, and if it is n-type silicon, its resistivity is suitable to be about 0.5 to 100 Ωcm.

[0105] In the measurement, excess carriers in the semiconductor sample to be evaluated are first excited by an optical pulse. Therefore, as the PCD device, a PCD device capable of setting the optical pulse intensity to a desired value (i.e., variable) in the measurement section is used, and the measurement is performed by setting the optical pulse intensity to an appropriate value.

[0106] In addition, as described below, to perform multiple measurements by changing the surface charge density, a PCD device equipped with a corona charge processing unit in the measurement section can be used to perform multiple measurements by changing the number of corona charges, for example. For example, a PCD device equipped with a corona charge processing unit capable of applying positive, negative, or both positive and negative charges to the surface of a single semiconductor sample using the corona charge method, or applying positive or negative charges to the surfaces of multiple semiconductor samples using the corona charge method, may be used. Alternatively, to perform multiple measurements by changing the surface charge density, the surface charge density of the semiconductor sample to be measured may be changed by changing the concentration of the agent (e.g., iodine, quinhydrone, etc.) used in the chemical passivation treatment and / or by changing the treatment time. In this case, it is preferable to use a PCD device having a device configuration corresponding to chemical passivation. Examples of such PCD devices include a device equipped with a mechanism for measuring a semiconductor sample while it is placed in a transparent bag made of polyethylene, after applying a chemical solution (e.g., iodine-ethanol solution) to the surface of the semiconductor sample outside the device, and a device equipped with a mechanism for measuring the sample while it is placed in a transparent bag made of polyethylene.

[0107] In addition, as a PCD device, a device equipped with a surface charge density-related value measuring device, such as surface charge amount and surface potential, can be used. For example, the surface charge density at each measurement can be obtained by measuring the surface charge amount and surface potential using a surface charge density-related value measuring device, such as a Kelvin probe or a non-contact CV measuring device. As an example of a surface charge density-related value measuring device, a non-contact CV measuring device can be cited, which forms a gap between the surface of a semiconductor sample and an electrode facing the surface and applies a voltage between them to measure the surface charge density-related value.

[0108] A decay curve is obtained by measurement using the above-described optical conduction decay method. Specifically, the decay curve is a curve representing the change in signal intensity over time with respect to the elapsed time after excitation light irradiation. "Elapsed time after excitation light irradiation" is, more specifically, the elapsed time from the point of termination of excitation light irradiation. Furthermore, for example, in the μ-PCD method, the signal intensity is the intensity of the reflected microwave. FIG. 11 shows a decay curve obtained by measuring an n-type silicon wafer (single-crystal silicon wafer) using the μ-PCD method after chemical passivation treatment as a surface treatment. The decay curve shown in FIG. 11 is deformed due to the influence of surface recombination from the mid-term region to the late-term region. FIG. 12 shows a fitting curve obtained by fitting the first-mode lifetime as described in the SEMI standard and a fitting curve obtained by fitting the 1 / e lifetime as described in the SEMI standard to the decay curve shown in FIG. 11. The two fitting curves shown in Fig. 12 are not suitable for the decay curve, particularly from the mid-term to the late-term region. This is because, in the first-mode method and the 1 / e lifetime method, fitting is performed under the assumption that the decay of excess carrier concentration takes the form of exponential decay due to the contribution of only SRH recombination.

[0109] In this regard, the above evaluation method performs signal data processing on the attenuation curve as described in detail below, thereby recombining the lifetime τ eff It becomes possible to obtain with high precision.

[0110] Reunion Lifetime τ eff Derivation of

[0111] (Signal data processing for damping curves)

[0112] In the above evaluation method, signal data processing is performed on at least one attenuation curve among those obtained by measurement of the semiconductor sample under evaluation using the optical conduction attenuation method, using a model equation including an exponential attenuation term and an integer term. The attenuation curves subjected to signal data processing may be just one or two or more. In the case of two or more, for example, the average value of the recombination lifetime obtained from signal data processing for each attenuation curve is the recombination lifetime τ of the semiconductor sample under evaluation. eff It can be adopted as such. As for the attenuation curve for signal data processing, among the multiple attenuation curves obtained by the multiple measurements, it is preferable to use the attenuation curve obtained by measurement under conditions where the surface charge density is small, and it is even more preferable to use the attenuation curve obtained by measurement under conditions where the surface charge density is smallest among the multiple measurements. For example, when changing the surface charge density by changing the number of corona charges, it is preferable to use the attenuation curve obtained by measurement with zero corona charge counts. Although it is most preferable to use the attenuation curve obtained by measurement under conditions where the surface charge density is zero, in practical terms, the surface charge density can generally be measured in cases where the value exceeds zero.

[0113] In the above model equation, the integer term is included in addition to the exponential decay term. The inventors believe that it is appropriate to represent the decay curve when surface recombination occurs as an equation including the exponential decay term and the integer term, preferably an equation in which the integer term is subtracted from the exponential decay term. By performing signal data processing to eliminate the integer term from such an equation, only the exponential decay term remains. That is, an equation for exponential decay is obtained. By utilizing this equation for exponential decay, the value of the recombination lifetime can be obtained as a value that includes the effects of SRH recombination and surface recombination. Accordingly, it becomes possible to determine the recombination lifetime of a semiconductor sample under evaluation with high precision. Below, such signal data processing will be explained in more detail.

[0114] If the excess carrier concentration is x[1 / cm³] and x(t) is a function of time, the function x(t) can be approximately expressed by the following equation (1).

[0115] x(t)=A×exp[-(τ b －1 +τ S －1 )t]-C···(1)

[0116] In Equation (1), τ b represents the SRH recombination lifetime, the unit is, for example, μsec, and τ S represents the surface recombination lifetime, and the unit is, for example, μsec. A and C each independently represent an integer [1 / cm³], preferably a defined integer. A and C are τ b －1 +τ S －1 It is an integer determined by. The above equation (1) is a function suitable under conditions where the excess carrier concentration is greater than the equilibrium carrier concentration, where both SRH reconnection and surface reconnection by surface level contribute to the reconnection lifetime, and the excess carrier concentration is a function of time x(t).

[0117] As a model equation for performing signal data processing based on Equation (1), the following Equation (10)' can be used.

[0118] xi(ti)=A×exp[-(τ b －1 +τ S －1 )ti]-C···(10)'

[0119] In Equation (10)', ti is the elapsed time after excitation light irradiation, xi(ti) is the signal intensity at the elapsed time ti, the unit is, for example, mV, and τ b is the SRH reunion lifetime, and τ S τ is the surface recombination lifetime, A and C are each independently integers, and the unit is, for example, mV. The above model equation (10)' includes an exponential decay term and an integer term, and specifically, the exponential decay term 「A×exp[-(τ b －1 +τ S －1 It is an equation in which the integer term "C" is subtracted from )ti]」. Equation (10)' is an example of the above model equation. For example, if signal data processing is performed to eliminate the integer term for a model equation containing an integer term such as Equation (10)', only the exponential decay term remains, so the time constant τ is obtained by the exponential decay approximation method. b －1 +τ S －1 (The sum of the reciprocal of the surface recombination lifetime and the reciprocal of the SRH recombination lifetime) can be calculated. The τ obtained in this way b －1 +τ S －1 The reciprocal of, the recombination lifetime τ of the semiconductor sample under evaluation eff It can be adopted as the value of . As an exponential decay approximation method, general exponential decay approximations such as the first lifetime method and the 1 / e lifetime method can be used.

[0120] Below, a specific example of signal data processing is described using the case where the above model equation is Equation (10)'. However, the signal data processing described below is an example, and the present invention is not limited to such examples.

[0121] Signal data processing may include determining a sampling region in an attenuation curve obtained by measurement using the optical conduction attenuation method, and repeating the operation of sampling a time-series signal (specifically, a measurement point on the attenuation curve) modeled by the above model equation in this sampling region and taking the difference. The determination of the sampling region can be performed, for example, by auto-scaling, and specific examples include the following method. For example, according to the following method, an area with a small influence of Auger recombination and a small influence of noise can be determined as the sampling region. That is, in the attenuation curve obtained by measurement using the optical conduction attenuation method, by excluding a high-intensity area with a large influence of Auger recombination and a low-intensity area with a large influence of noise, it becomes possible to make an area with a strong influence of SRH recombination and surface recombination the sampling region.

[0122] First, a location at an arbitrary signal strength (e.g., 60% of the peak value) is set as the starting point of the sampling area, and signal data processing is performed once. Regarding the calculation result obtained by signal data processing, R 2 Values ​​that can serve as indicators of the degree of fit to exponential decay, such as the value and the sum of squared residuals, are calculated. The degree of fit to exponential decay is evaluated based on whether the calculated value of these indicators satisfies a preset threshold value.

[0123] The above calculated value is a preset threshold value (for example, R 2 If ≥0.99) is satisfied, the starting point of the sampling area set above can be determined as the starting point of the sampling area when performing signal data processing.

[0124] The above calculated value is a preset threshold value (for example, R 2 If the condition ≥0.99 is not satisfied, the starting point of the sampling area is shifted toward the side with lower signal strength and recalculation is performed. Recalculation may be performed once or two or more times, and if the evaluation result in the recalculation satisfies a preset threshold value, the starting point in the recalculation may be determined as the starting point of the sampling area.

[0125] The endpoint of the sampling area can be a location where the Signal-to-Noise Ratio (SN ratio) is below a preset threshold value. The SN ratio can be calculated, for example, by the following formula. The threshold value of the above SN ratio may be, for example, 5 dB or less, and it is preferable to determine the endpoint as a location where the signal's SN ratio is 0 dB, that is, a location where the noise and the signal are of equal magnitude.

[0126] SN ratio [dB] = 20log 10 [(Signal dispersion at any given time) / (Noise dispersion at equilibrium)]

[0127] FIGS. 1 to 3 are explanatory diagrams of specific examples of signal data processing. Signal data processing can be performed as follows, for example, by setting the sampling score to 3N points. Here, N is any integer and can be, for example, 2 or greater. Also, N can be, for example, 333 or less if all points of the signal data are 1000. That is, N can be, for example, an integer less than or equal to "T × 1 / 3" if all points of the signal data are T.

[0128] First, based on the starting point (the 1st point), the average A1 of the 1st to Nth points and the average B1 of the N+1st to 2Nth points are calculated (see Fig. 1).

[0129] A1={x(t1)+x(t2)+… +x(t N )} / N

[0130] B1={x(tN＋1 )+x(t N＋2 )+… +x(t 2N )} / N

[0131] The value obtained by subtracting B1 from A1 is set as Y(t1).

[0132] Y(t1)=A1-B1

[0133] Next, based on the second point, the average A2 of the 2nd point to the N+1st point and the average B2 of the N+2nd point to the 2N+1st point are calculated (see Fig. 2).

[0134] A2={x(t2)+x(t3)+… +x(t N＋1 )} / N

[0135] B2={x(t N＋2 )+x(t N＋3 )+… +x(t 2N＋1 )} / N

[0136] The value obtained by subtracting B2 from A2 is set as Y(t2).

[0137] Y(t2) = A2 - B2

[0138] Continuing the same calculation, finally the average A of the N+1 to 2N points N＋1 and the average B of the 2N+1 to 3N points N＋1 Calculate (see Fig. 3).

[0139] A N＋1 =x(t N＋1 )+x(t N＋2 )+… +x(t 2N )} / N

[0140] B N＋1 =x(t 2N＋1 )+x(t 2N＋2 )+… +x(t 3N )} / N

[0141] A N＋1 From B N＋1 The value obtained by subtracting Y(t N＋1 ...does as ).

[0142] Y(t N＋1 )=A N＋1 -B N＋1

[0143] The time series signal data sequence obtained by continuing the above calculations has the integer term in Equation (10)' removed, and becomes the following exponential decay Equation (2). By applying the general exponential decay approximation method to this Equation (2), the time constant τ b －1 +τ S －1 can be obtained. The 「τ」 obtained in this way b －1 +τ S －1 」, the recombination lifetime τ of the semiconductor sample under evaluation eff It can be adopted as the value of . Examples of the above exponential decay approximation methods include the first mode method and the 1 / e lifetime method.

[0144] Y(t)=A'×exp[-(τ b －1 +τ S －1 )t]···(2)

[0145] (A': arbitrary integer)

[0146] (Reunion lifetime τ eff Specific form of the calculation method)

[0147] FIG. 4 is an explanatory diagram of an example of a method for evaluating a semiconductor sample according to one aspect of the present invention.

[0148] The damping curve shown in the left diagram of Fig. 4 is identical to the damping curve shown in Fig. 11, and is a damping curve obtained by measuring an n-type silicon wafer (single-crystal silicon wafer, resistivity: 10 Ω cm) using the μ-PCD method after chemical passivation treatment as a surface treatment. Here, the maximum carrier injection amount of μ-PCD was approximately 1 E17 / cm³. Furthermore, "E17" is "×10 17 It represents 」

[0149] With respect to the damping curve shown in the left diagram of FIG. 4, signal data processing was performed using Equation (10)' as a model equation, with the sampling score set to 3N points, as previously explained with reference to FIGS. 1 to 3. The starting point of the sampling area is the threshold value "R 2 It was determined by the method described above with the condition ≥0.99. The endpoint of the sampling area was set to the location where the SN ratio is 0 dB, as described above.

[0150] By performing the above signal data processing, the integer term in Equation (10)' is eliminated, and a linear equation of Equation (2) consisting only of the exponential decay term (solid line in the right diagram of FIG. 4) is obtained. For this linear equation, by applying the first mode method, the time constant τ b －1 +τ S －1 Find , and this time constant τ b －1 +τ S －1 The recombination lifetime obtained as the reciprocal of (Example A in Table 1) was the value shown in Table 1.

[0151] For the damping curve shown in the left drawing of Fig. 4, the recombination lifetimes obtained by applying the first mode method and the 1 / e method described in the SEMI standard, respectively, are also shown in Table 1.

[0152]

[0153] From the results shown in Table 1, it can be seen that in the conventional first mode method and 1 / e lifetime method, the value of the recombination lifetime is underestimated by about 60% compared to Example A.

[0154] Next, it was confirmed by the following method that the function of Equation (1) is a function of time close to the actual decay.

[0155] First, to determine the remaining undetermined parameter integers A and C in Equation (1), fitting was performed as follows.

[0156] The time constant τ obtained in the above example b －1 +τ S －1 Using this, Equation (1) becomes exp[-(τ b －1 +τ S －1 With respect to )t], it takes the form of a linear equation. That is, in the sampling region determined by auto-scaling, the attenuation curve is, as shown in the left diagram of Fig. 5, exp[-(τ b －1 +τ S －1 A straight line can be approximated for )t], and integers A and C can be obtained as its slope and intercept.

[0157] The time constant τ obtained in this way b －1 +τ S －1 When applying Equation (1) using integers A and C, as shown in the right-hand figure of FIG. 5, a fitting curve with a damping curve suitable over a wide range (new method fitting in the right-hand figure of FIG. 5) was obtained compared to the case fitted by the first mode method or the 1 / e lifetime method (first mode lifetime fitting, 1 / e lifetime fitting in the right-hand figure of FIG. 5).

[0158] From the above results, it can be confirmed that the function of Equation (1) is a function of time close to the actual decay.

[0159] FIGS. 6 and 7 show the results of comparison between an example (new method) of a semiconductor sample evaluation method according to one aspect of the present invention and a conventional method.

[0160] In the left diagram of FIG. 6, for a plurality of n-type silicon wafers in which a recombination lifetime value of approximately 7,000 μsec is obtained by a method similar to Example A above, the recombination lifetime value obtained by a method similar to Example A (new method in FIG. 6) and the recombination lifetime value obtained by the conventional method, the first mode method ("conventional method" in FIG. 6) are shown. The right diagram of FIG. 6 shows the CV value (standard deviation / arithmetic mean × 100, unit: %) of the measurement result shown in the left diagram of FIG. 6. From the results shown in FIG. 6, it can be confirmed that the deviation of the recombination lifetime value is suppressed in the new method compared to the conventional method.

[0161] FIG. 7 shows the damping curve obtained by measurement by the μ-PCD method for sample circle 1, which has the largest difference in the forward direction, and sample circle 2, which has the largest difference in the negative direction, in the conventional method of FIG. 6, and the fitting curve obtained by fitting by Equation (1) as described above, and the fitting curve obtained by fitting by the conventional method of the first mode method. FIG. 7 also shows the recombination lifetime values ​​of each sample obtained by the new method and the conventional method. From the results shown in FIG. 7, it can be confirmed that the function of Equation (1) is a function of time close to the actual damping.

[0162] Surface reconnection lifetime τ s , SRH reunion lifetime τ b , surface recombination rate S r Derivation of

[0163] Surface reconnection lifetime τ sRegarding the derivation of [the term], as a result of the inventor's examination of the example, the integer term C in Equation (10)' can be expressed as Equation (11) by using the Poisson equation for the charge distribution (relationship between carrier concentration and surface charge density) near the surface of a semiconductor sample. Since it was revealed from Equation (11) that the integer term is a quadratic expression of the surface charge density Qs, it was newly discovered that it can be interpreted as a quadratic function.

[0164] C = (τ eff / τ s ) / (2kTε s ε0)×Q s 2 +τ eff / τ s ×n0···(11)

[0165] In Equation (11), k is the Boltzmann constant [eV / K], T is the absolute temperature [K], and ε s ε₀ is the permittivity of the semiconductor sample [F / m], ε₀ is the permittivity of vacuum [F / m], Q s ε is the surface charge density [F / m²], and n0 is the equilibrium carrier concentration [cm²]. －3 ]am.

[0166] τ in Equation (11) eff As previously described, it can be derived by performing a fitting calculation according to Equation (10)' on the attenuation curve obtained by subjecting the semiconductor sample to evaluation to measurement by the optical conductivity attenuation method.

[0167] Next, FIG. 8 shows the surface recombination lifetime τ s This is a schematic diagram of the plot for derivation. τ sTo derive the attenuation curve, the semiconductor sample under evaluation is subjected to measurement by the photoconductivity attenuation method, and this process is repeated multiple times with varying surface charge densities. For the attenuation signals obtained for each different surface charge density in this way, if the integer term C calculated using Equation (10)' is plotted against the surface charge density Qs, it becomes a quadratic function as shown in Equation (11) (see FIG. 8). The minimum value C of the quadratic function shown in FIG. 8 min is the second term of the equilibrium equation (11) "τ" eff / τ s It is represented by the following formula (11)' which represents ×n0.

[0168] C min =τ eff / τ s ×n0···(11)'

[0169] Therefore, the minimum value C of the quadratic function min Equilibrium carrier concentrations n0 and τ eff By substituting into Equation (11)', the surface recombination lifetime τ s ...can be calculated. However, in the μ-PCD method, the microwave reflectance signal intensity is measured as voltage, and the unit of C is voltage. Therefore, the relationship between the reflectance signal intensity and the carrier concentration is calculated using the amount of carrier injection by the optical pulse and the initial microwave reflectance signal intensity. The equilibrium carrier concentration n0 is the equilibrium carrier concentration of the semiconductor sample being measured.

[0170] The second term of Equation (11) 「τ」 eff / τ s Minimum value C of ×n0 min For example, as shown in FIG. 8, measurement points are plotted on a graph with C on the vertical axis (y-axis) and surface charge density on the horizontal axis (x-axis), and the plots are fitted using known methods such as the least squares method. The value can be obtained as the minimum value of the vertical axis y in the quadratic function (quadratic curve).

[0171] In the example shown in FIG. 8, the vertical axis (y-axis) represents the absolute value of the integer term C, and the horizontal axis (x-axis) represents the surface charge density. However, the variable x on the horizontal axis is not limited to the value of the surface charge density itself. For example, the surface charge density can be changed by the number of corona charge treatments (i.e., the number of corona charges). When the surface charge density is changed by the number of corona charges, the number of corona charges may be adopted as the variable x on the horizontal axis. As an example, the number of corona charges applying a positive charge may be adopted as a positive value (e.g., x = 1 if it is 1 time) and the number of corona charges applying a negative charge may be adopted as a negative value (e.g., x = -1 if it is 1 time) as the variable x on the horizontal axis. Furthermore, the variable y on the horizontal axis is not limited to the absolute value of the integer term C, and for example, the value of the integer term C itself may be adopted as the variable y on the vertical axis.

[0172] That is, by adopting a value related to surface charge density as the variable x and a value related to the integer term as the variable y, fitting is performed on the plot obtained using a known method, to obtain a quadratic function: y=ax 2 We obtain +bx+c. a is a positive integer, and b and c are positive or negative integers or zero. The minimum value of y in this quadratic function is C in Equation (11). min As, from Equation (11)', the surface recombination lifetime τ s You can obtain .

[0173] Also, Equation (1)':

[0174] 1 / τ eff = 1 / τ b +1 / τ s ···(1)'

[0175] τ eff and τ S By substituting, the SRH recombination lifetime (bulk lifetime) τ b You can obtain .

[0176] In addition, surface recombination rate S r silver, thickness d of the semiconductor sample, and surface recombination lifetime τ s From this, it can be obtained using the following formula (12).

[0177] S r =d / (2τ) S )···(12)

[0178] [Semiconductor Sample Evaluation Device]

[0179] One aspect of the present invention relates to an evaluation apparatus for a semiconductor sample that performs the evaluation method. The evaluation apparatus includes a measurement unit that performs measurement of a semiconductor sample to be evaluated by a photoconductivity attenuation method, a processing unit that performs signal data processing on the attenuation curve using a model equation including an exponential attenuation term and an integer term, and a second-order function.

[0180] The above-mentioned measuring unit performs a measurement on a semiconductor sample to be measured using the optical conductivity attenuation method. The measuring unit may vary the optical pulse intensity. This point is as described above. In addition, in one embodiment, the measuring unit may include a corona charge processing unit to change the surface charge density. The details of the measuring unit are as described above. Furthermore, as described above regarding the PCD device, the measuring unit may be equipped with a surface charge density related value measuring device.

[0181] In order to implement a method for evaluating a semiconductor sample according to one aspect of the present invention, the processing unit of the evaluation device performs signal data processing based on a model equation including an exponential decay term and an integer term for a decay curve, and obtains the quadratic function. The processing unit may be configured using a known analysis program.

[0182] In addition, the processing unit performs signal data processing on the damping curve using a model equation including an exponential damping term and an integer term, thereby eliminating the integer term in the model equation to obtain the exponential damping equation, and obtains the time constant τ from the exponential damping equation. b －1 +τ S －1 You can obtain.

[0183] The above signal data processing may include repeating the operation of sampling a time series signal modeled by the above model equation and taking the difference.

[0184] In addition, the processing unit may perform auto-scaling to determine a sampling region for performing the sampling. Through the auto-scaling, the processing unit may determine as a sampling region a region in which the influence of recombination is minimal and the influence of noise is minimal. Such auto-scaling is as described above.

[0185] The evaluation device described above, wherein a measurement unit or a calculation unit formed separately from the measurement unit, can derive the recombination lifetime τeff of the semiconductor sample from the exponential decay equation obtained by the signal data processing. Surface recombination lifetime τs and SRH recombination lifetime τ after obtaining the quadratic function. b and surface recombination rate S r The derivation of the measurement unit or the output unit formed separately from the measurement unit may be performed. The derivation may be performed using a known analysis program provided in the measurement unit or the output unit.

[0186] In one embodiment, the evaluation device may additionally include a PCD measuring device having a measuring unit that performs measurement by the PCD method, and the processing unit and / or the calculation unit. In another embodiment, one or more computers different from the PCD measuring device having a measuring unit that performs measurement by the PCD method may include the processing unit and / or the calculation unit, and various information such as measurement results, processing results, and calculation results may be transmitted and received via wired communication or wireless communication between such computers and the PCD measuring device, or additionally between multiple computers. One computer may include the processing unit and the calculation unit, or different computers may each include the processing unit and the calculation unit.

[0187] [Method for manufacturing semiconductor wafers]

[0188] One aspect of the present invention is,

[0189] Manufacturing a semiconductor wafer lot comprising multiple semiconductor wafers,

[0190] Extracting at least one semiconductor wafer from the above semiconductor wafer lot,

[0191] Evaluating the above-mentioned extracted semiconductor wafer by the above-mentioned evaluation method, and,

[0192] As a result of the above evaluation, semiconductor wafers from the same semiconductor wafer lot as the semiconductor wafer judged to be good are put into preparation for shipment as product semiconductor wafers.

[0193] A method for manufacturing a semiconductor wafer comprising (hereinafter also referred to as “Manufacturing Method 1”)

[0194] It is about.

[0195] In addition, one aspect of the present invention is,

[0196] Manufacturing evaluation semiconductor wafers under test manufacturing conditions,

[0197] Evaluating the above-manufactured evaluation semiconductor wafer by the above-mentioned semiconductor sample evaluation method,

[0198] Based on the results of the above evaluation, determining the manufacturing conditions with modifications added to the above test manufacturing conditions as the actual manufacturing conditions, or determining the above test manufacturing conditions as the actual manufacturing conditions, and,

[0199] Manufacturing a semiconductor wafer under the actual manufacturing conditions determined above

[0200] A method for manufacturing a semiconductor wafer comprising (hereinafter also referred to as “Manufacturing Method 2”)

[0201] It is about.

[0202] In manufacturing method 1, semiconductor wafers of the same lot as the semiconductor wafer determined to be good as a result of performing a so-called extraction inspection are prepared for shipment as product semiconductor wafers. Meanwhile, in manufacturing method 2, semiconductor wafers manufactured under test manufacturing conditions are evaluated, and actual manufacturing conditions are determined based on the evaluation results. In either manufacturing method 1 or manufacturing method 2, the evaluation of the semiconductor wafer is performed by the evaluation method according to one aspect of the present invention described above.

[0203] In manufacturing method 1, the manufacturing of the semiconductor wafer lot can be performed in the same manner as a general semiconductor wafer manufacturing method. For example, a polished wafer can be cited as an example of a silicon wafer, which is a form of semiconductor wafer. A polished wafer can be manufactured by a manufacturing process that includes cutting (slicing), chamfering, rough polishing (e.g., lapping), etching, mirror polishing (finish polishing), and cleaning performed between or after the processing process of a silicon wafer from a silicon single-crystal ingot grown by the Czochralski method (CZ method), etc. Additionally, an annealed wafer can be manufactured by performing heat treatment, specifically an annealing treatment, on the polished wafer manufactured as above. An epitaxial wafer can be manufactured by growing an epitaxial layer in vapor phase (epitaxial growth) on the surface of the polished wafer manufactured as above.

[0204] The total number of semiconductor wafers included in a semiconductor wafer lot is not specifically limited. The number of semiconductor wafers removed from a manufactured semiconductor wafer lot and subjected to so-called extraction inspection is at least one, and may be two or more, and the number is not specifically limited.

[0205] A semiconductor wafer extracted from a semiconductor wafer lot is evaluated by an evaluation method according to one aspect of the present invention. For example, the quality of the evaluated semiconductor wafer can be determined using a recombination lifetime value obtained by such evaluation as an indicator. For example, the higher the amount of metal contamination, the higher the recombination lifetime τ measured by the PCD method. eff becomes shorter. Therefore, based on the value of the recombination lifetime measured by the PCD method, the presence and / or degree of metal contamination in the semiconductor wafer can be evaluated. Thus, for example, the recombination lifetime τ effA value of that is greater than or equal to a predetermined threshold value or exceeds a threshold value can be used as a criterion for determining a good product. Such threshold values ​​may be set according to the quality required for the product wafer. Semiconductor wafers from the same semiconductor wafer lot as the semiconductor wafer determined to be good can be submitted for preparation (e.g., packing) for shipment as product semiconductor wafers.

[0206] Regarding Manufacturing Method 2, test manufacturing conditions and actual manufacturing conditions may include various conditions in various processes for manufacturing semiconductor wafers. The various processes for manufacturing semiconductor wafers are as described above for Manufacturing Method 1. Furthermore, "actual manufacturing conditions" shall be understood to mean the manufacturing conditions of the product semiconductor wafer.

[0207] In manufacturing method 2, as a preliminary step for determining actual manufacturing conditions, test manufacturing conditions are set, and an evaluation semiconductor wafer is manufactured under these test manufacturing conditions. The manufactured semiconductor wafer is evaluated by an evaluation method according to one aspect of the present invention. The recombination lifetime τ obtained by this evaluation eff Using the value of as an indicator, it is possible to determine whether the test manufacturing condition can be adopted as the actual manufacturing condition, or whether the manufacturing condition with modifications added to the test manufacturing condition should be adopted as the actual manufacturing condition. For example, from the same perspective as previously described regarding manufacturing method 1, the obtained recombination lifetime τ eff Whether the value is above a predetermined threshold or exceeds a threshold can be used as a criterion for determining whether the test manufacturing condition can be adopted as an actual manufacturing condition. As a result of the determination, manufacturing conditions that are subject to change include, for example, manufacturing conditions that may cause metal contamination. As an example, the number of heat treatment furnaces used (e.g., replacement of parts, cleaning of parts, cleaning inside the furnace, etc.) may be cited.

[0208] For other details of manufacturing method 1 and manufacturing method 2, known technology regarding methods for manufacturing semiconductor wafers may be applied. According to manufacturing method 1 and manufacturing method 2, for example, product semiconductor wafers with low metal contamination can be stably supplied to the market.

[0209] Examples

[0210] The present invention will be further explained below based on examples. However, the present invention is not limited to the embodiments shown in the examples.

[0211] [Example 1]

[0212] μPCD measurements were performed on an n-type silicon wafer (single-crystal silicon wafer) by varying the number of corona charges. The number of corona charges applying a positive charge was set to 1, 3, or 5, and the number of corona charges applying a negative charge was set to 1, 3, or 5, with the charge amount (absolute value) for each charge being the same. The number of corona charges was adopted as the surface charge density related value with respect to variable x, the number of corona charges applying a positive charge was adopted as a positive value, and the number of corona charges applying a negative charge was adopted as a negative value. The absolute value of the integer term C, obtained from the fitting calculation of the damping curve obtained from each measurement, was adopted as the variable y.

[0213] Among the multiple damping curves obtained from multiple measurements, the damping curve obtained from the measurement at zero corona charge was selected, and a fitting calculation was performed using Equation (10)' in the same manner as described for Example A above, resulting in τ eff It was calculated as 5300 μs.

[0214] For each of the multiple damping curves obtained from multiple measurements, the integer term C was calculated from the fitting calculation results.

[0215] The above values ​​were adopted as the values ​​for the horizontal axis (x-axis) and the vertical axis (y-axis) and plotted. The minimum value of the vertical axis (the minimum value calculated by fitting a quadratic function to the average value of values ​​obtained by measuring at 50 points within each plane) and Equation (11)'(the second term of Equation (11) "τ eff / τ s From ×n0」), surface recombination lifetime τ s It was calculated as 115,000 μs (in this embodiment, n0 is 5 mV).

[0216] Also, from Equation (1)', the SRH recombination lifetime (bulk lifetime) τ b It was calculated as 5560 μs.

[0217] The above calculation results are shown in Table 2, and the quadratic curve obtained in Example 1 is shown in Fig. 9.

[0218]

[0219] In addition, the thickness d of the silicon wafer and the surface recombination lifetime τ s From, the surface recombination rate S of the silicon wafer by Equation (12) r The result of calculating was 0.34 cm / s.

[0220] [Example 2]

[0221] An example is shown using a μPCD device equipped with a corona charge processing unit and a non-contact CV device.

[0222] First, corona charge treatment was performed on an n-type silicon wafer (single-crystal silicon wafer).

[0223] Next, the surface charge amount of the wafer surface was measured using a non-contact CV device, and after calculating the surface charge density, μPCD measurements were performed.

[0224] This series of processing, measurement, and calculation was carried out by changing the number of corona charges and the state of the charge.

[0225] Among the multiple damping curves obtained from multiple measurements, the damping curve obtained from the measurement at zero corona charge was selected, and a fitting calculation was performed using Equation (10)' in the same manner as described for Example A above, resulting in τ eff It was calculated as 5300 μs.

[0226] For the measurement results obtained from multiple measurements, surface charge density was plotted on the horizontal axis and the absolute value of the integer term on the vertical axis. The minimum value on the vertical axis (the minimum value calculated by fitting a quadratic function to the average value obtained by taking measurements at 50 points within each plane) and Equation (11)'(the second term of Equation (11) "τ eff / τ s From ×n0」), surface recombination lifetime τ s It was calculated as 121,000 μs (n0 in this embodiment is 5 mV).

[0227] Also, from Equation (1)', the SRH recombination lifetime (bulk lifetime) τ b It was calculated as 5540 μs.

[0228] The above calculation results are shown in Table 3, and the quadratic curve obtained in Example 2 is shown in Fig. 10.

[0229]

[0230] In addition, the thickness d of the silicon wafer and the surface recombination lifetime τ s From, the surface recombination rate S of the silicon wafer by Equation (12) r The result of calculating was 0.32 cm / s.

[0231] Industrial applicability

[0232] One aspect of the present invention is useful in the technical field of various semiconductor wafers.

Claims

Claim 1 Acquiring a decay curve by subjecting a semiconductor sample to evaluation to measurement by the photoconductivity decay method, performing this multiple times while changing the surface charge density; performing signal data processing on at least one decay curve among the decay curves obtained by the multiple measurements using a model equation including an exponential decay term and an integer term; and determining the recombination lifetime τ of the semiconductor sample from the exponential decay equation obtained by the signal data processing. eff Calculating , obtaining a quadratic function from the measurement results obtained by the above multiple measurements, wherein the value related to the surface charge density is the variable x and the value related to the integer term is the variable y, and obtaining the surface recombination lifetime τ of the semiconductor sample from the above quadratic function s A method for evaluating a semiconductor sample, including obtaining Claim 2 In paragraph 1, the following formula (11)':C min =τ eff / τ s ×n0···(11)'(where n0: equilibrium carrier concentration) for C min Setting as the minimum value of y in the above quadratic function, the surface recombination lifetime τ s A method for evaluating a semiconductor sample that yields Claim 3 In claim 1, the recombination lifetime τ eff and the surface reconnection lifetime τ s From, the SRH recombination lifetime τ of the semiconductor sample b A method for evaluating a semiconductor sample, additionally including obtaining Claim 4 In paragraph 3, the above SRH recombination lifetime τ b 를, Hagisik (1)':1 / τ eff = 1 / τ b +1 / τ s A method for evaluating a semiconductor sample obtained from ···(1)'. Claim 5 In claim 1, the thickness d of the semiconductor sample and the surface recombination lifetime τ s From, the following formula (12):S r =d / (2τ) S The surface recombination rate S of the semiconductor sample according to )···(12) r A method for evaluating a semiconductor sample, additionally including obtaining Claim 6 In claim 1, by performing the signal data processing, the integer term in the model equation is eliminated to obtain the equation for exponential decay, and the time constant τ is obtained from the equation for exponential decay. b －1 +τ S －1 It additionally includes finding , and τ b is the SRH reunion lifetime, and τ S A method for evaluating a semiconductor sample, which is the surface recombination lifetime. Claim 7 A method for evaluating a semiconductor sample according to claim 6, wherein the signal data processing comprises repeating the operation of sampling a time series signal modeled by the model equation and taking the difference. Claim 8 A method for evaluating a semiconductor sample according to claim 7, further comprising performing auto-scaling to determine a sampling area for performing the sampling. Claim 9 A method for evaluating a semiconductor sample according to claim 8, wherein, by the above-mentioned auto-scaling, a region having less influence from Auger recombination and less influence from noise is determined as a sampling region. Claim 10 In the first paragraph, the above model equation is the following equation (10)':xi(ti)=A×exp[-(τ b －1 +τ S －1 )ti]-C···(10)'(Equation (10)', where ti: elapsed time after excitation light irradiation, xi(ti): signal intensity at elapsed time ti, τ b : SRH reunion lifetime, τ S A method for evaluating a semiconductor sample in which : surface recombination lifetime, A, C: integer). Claim 11 In paragraph 1, the following formula (11)':C min =τ eff / τ s ×n0···(11)'(where n0: equilibrium carrier concentration) for C min Setting as the minimum value of y in the above quadratic function, the surface recombination lifetime τ s Calculate , and the above recombination lifetime τ eff and the surface reconnection lifetime τ s From, the SRH recombination lifetime τ of the semiconductor sample b It additionally includes calculating the above SRH recombination lifetime τ. b 를, Hagisik (1)':1 / τ eff = 1 / τ b +1 / τ s Obtaining from ···(1)', and by performing the signal data processing above, eliminating the integer term in the model equation to obtain the equation for exponential decay, and obtaining the time constant τ from the equation for exponential decay. b －1 +τ S －1 It additionally includes finding , and τ b is the SRH reunion lifetime, and τ S is a surface recombination lifetime, and the signal data processing includes repeating the operation of sampling a time series signal modeled by the model equation and taking a difference, and further includes performing auto-scaling to determine a sampling region for performing the sampling, and by the auto-scaling, a region that has little influence from Auger recombination and also little influence from noise is determined as the sampling region, and the model equation is the following equation (10)':xi(ti)=A×exp[-(τ b －1 +τ S －1 )ti]-C···(10)'(Equation (10)', where ti: elapsed time after excitation light irradiation, xi(ti): signal intensity at elapsed time ti, τ b : SRH reunion lifetime, τ S A method for evaluating a semiconductor sample in which : surface recombination lifetime, A, C: integer). Claim 12 In paragraph 1, the following formula (11)':C min =τ eff / τ s ×n0···(11)'(where n0: equilibrium carrier concentration) for C min Setting as the minimum value of y in the above quadratic function, the surface recombination lifetime τ s Calculate, and the thickness d of the semiconductor sample and the surface recombination lifetime τ s From, the following formula (12):S r =d / (2τ) S The surface recombination rate S of the semiconductor sample according to )···(12) r It additionally includes obtaining, and by performing the signal data processing, eliminating the integer term in the model equation to obtain the equation for exponential decay, and from the equation for exponential decay, the time constant τ b －1 +τ S －1 It additionally includes finding , and τ b is the SRH reunion lifetime, and τ S is a surface recombination lifetime, and the signal data processing includes repeating the operation of sampling a time series signal modeled by the model equation and taking a difference, and further includes performing auto-scaling to determine a sampling region for performing the sampling, and by the auto-scaling, a region that has little influence from Auger recombination and also little influence from noise is determined as the sampling region, and the model equation is the following equation (10)':xi(ti)=A×exp[-(τ b －1 +τ S －1 )ti]-C···(10)'(Equation (10)', where ti: elapsed time after excitation light irradiation, xi(ti): signal intensity at elapsed time ti, τ b : SRH reunion lifetime, τ S A method for evaluating a semiconductor sample in which : surface recombination lifetime, A, C: integer). Claim 13 An evaluation device for a semiconductor sample that performs an evaluation method for a semiconductor sample described in any one of claims 1 to 12, comprising: a measurement unit that subjectes a semiconductor sample to evaluation to measurement by an optical conductivity attenuation method; a processing unit that performs signal data processing on the attenuation curve using a model equation including an exponential attenuation term and an integer term; and a second-order function. Claim 14 In Clause 13, an evaluation device in which the optical pulse intensity in the above-mentioned measuring part is variable. Claim 15 In Clause 13, the above-mentioned measuring unit further comprises an evaluation device including a corona charge processing unit. Claim 16 In claim 13, the evaluation device further comprises a surface charge density related value measuring unit that measures a surface charge density related value of a semiconductor sample subjected to the measurement. Claim 17 An evaluation device according to claim 13, wherein in the above-mentioned measuring unit, the optical pulse intensity is variable, and the above-mentioned measuring unit further comprises a corona charge processing unit and a surface charge density related value measuring unit for measuring a surface charge density related value of a semiconductor sample subjected to the above-mentioned measurement. Claim 18 A method for manufacturing a semiconductor wafer comprising: manufacturing a semiconductor wafer lot including a plurality of semiconductor wafers; extracting at least one semiconductor wafer from the semiconductor wafer lot; evaluating the extracted semiconductor wafer by an evaluation method described in any one of claims 1 to 12; and preparing to ship a semiconductor wafer of the same semiconductor wafer lot as the semiconductor wafer determined to be good as a result of the evaluation as a product semiconductor wafer. Claim 19 A method for manufacturing a semiconductor wafer, comprising: manufacturing an evaluation semiconductor wafer under test manufacturing conditions; evaluating the manufactured evaluation semiconductor wafer by a method for evaluating a semiconductor sample described in any one of claims 1 to 12; determining, based on the result of the evaluation, manufacturing conditions with modifications added to the test manufacturing conditions as actual manufacturing conditions, or determining the test manufacturing conditions as actual manufacturing conditions; and manufacturing the semiconductor wafer under the determined actual manufacturing conditions.

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