Elliptic polarization measurement method and system of semiconductor device, and optimization method of optical model

Abstract

The invention provides an ellipsometry method and system of a semiconductor device and a storage medium. The ellipsometry method for the semiconductor device comprises the following steps: acquiring a first optical model of a measuring machine; integrating the smoothness parameters of the first spectrum at a plurality of wavelength positions according to a plurality of preset detection wavebands so as to determine the noise of the first spectrum at each detection waveband, and determining the weight coefficient of each detection waveband according to the noise; according to the weight coefficient of each detection wave band, correcting the first optical model to obtain a second optical model adapted to the material of the semiconductor device to be detected; and detecting the to-be-detected semiconductor device through the measuring machine to obtain a second spectrum, and substituting the second spectrum into the second optical model to determine the characteristic parameters of the surface of the to-be-detected semiconductor device. The method can be used for improving the repeatability and reproducibility difference of the measurement system, so that the measurement performance of the measurement system is improved.

Description

Technical Field

[0001] The present invention relates to the field of optical measurement and detection, and particularly to an ellipsometry measurement method for semiconductor devices, an ellipsometry measurement system for semiconductor devices, an optimization method for an optical model, and a computer-readable storage medium. Background Art

[0002] With the rapid development of semiconductor processes, the performance index requirements for various optical measurement and detection devices have been further improved. For example, the requirements for the differences in repeatability and reproducibility of an ellipsometry measurement system are that the proportion of repeatability and reproducibility in the overall variation (GR&R) ≤ 10%, and the number of distinguishable categories (NDC) ≥ 5. However, due to the requirements of different processes, technicians need to re-fit and model spectra with different distributions each time they perform a machine measurement system analysis. Since the sensitivity of the spectra to materials is inconsistent in different wavelength bands, the spectra in some wavelength bands change little, and the signal-to-noise ratio is relatively small compared to the relatively fixed spectral noise. In this case, the measurement results of the established model are more susceptible to spectral noise interference, thus affecting the differences in repeatability and reproducibility of the measurement system.

[0003] In order to overcome the above-mentioned defects existing in the prior art, there is an urgent need in the art for an improved ellipsometry measurement method for semiconductor devices to improve the differences in repeatability and reproducibility of the measurement system, thereby improving the measurement performance of the measurement system. Summary of the Invention

[0004] The following gives a brief overview of one or more aspects to provide a basic understanding of these aspects. This overview is not an exhaustive survey of all contemplated aspects, and is neither intended to identify key or decisive elements of all aspects nor to define the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to a more detailed description to follow.

[0005] In order to overcome the above-mentioned defects existing in the prior art, the present invention provides an ellipsometry measurement method for semiconductor devices, an ellipsometry measurement system for semiconductor devices, and a computer-readable storage medium. By quantifying the magnitude of the noise in each detection wavelength band of the spectrum relative to the change in the spectrum itself, the weight coefficients of each detection wavelength band in the spectrum fitting process can be dynamically adjusted to improve the differences in repeatability and reproducibility of the measurement system, thereby improving the measurement performance of the measurement system.

[0006] Specifically, the ellipsometry method for the semiconductor device provided by the first aspect of the present invention includes the following steps: obtaining a first optical model of a measurement machine. The first optical model is obtained by first spectral fitting based on reference characteristic parameters of a semiconductor sample and the first spectrum obtained by the measurement machine measuring the semiconductor sample over the entire spectrum. The semiconductor sample has the same material as the semiconductor device to be measured; according to a plurality of preset detection bands, integrating the smoothness parameters of the first spectrum at a plurality of wavelength positions to determine the noise of the first spectrum in each of the detection bands, and accordingly determining the weight coefficient of each of the detection bands; according to the weight coefficient of each of the detection bands, correcting the first optical model to obtain a second optical model adapted to the material of the semiconductor device to be measured; and detecting the semiconductor device to be measured via the measurement machine to obtain a second spectrum, and substituting the second spectrum into the second optical model to determine the actual characteristic parameters of the surface of the semiconductor device to be measured.

[0007] Further, in some embodiments of the present invention, the reference characteristic parameters include the reference film thickness and / or the reference critical dimension of the surface of the semiconductor sample, and the actual characteristic parameters correspondingly include the actual film thickness and / or the actual critical dimension of the surface of the semiconductor device to be measured.

[0008] Further, in some embodiments of the present invention, when the reference characteristic parameter is the reference film thickness, the step of obtaining the first optical model of the measurement machine includes: performing full-spectrum measurement on the semiconductor sample via a standard machine to determine the reference film thickness of a plurality of detection units j thereon Performing full-spectrum measurement on the semiconductor sample via the measurement machine to obtain the first spectrum of each of the detection units j thereon According to the first spectrum And the reference film thickness Construct a target equation:

[0009]

[0010] And perform an optimization solution for the material parameters NK of the material; and construct the first optical model according to the optimization solution of the material parameters NK of the material:

[0011]

[0012] Further, in some embodiments of the present invention, the material parameters NK include the refractive index N and the absorption coefficient K, and the step of performing an optimization solution for the material parameters NK of the material includes: using the Levenberg-Marquardt optimization algorithm to fit the target equation to determine the optimization solution of the material parameters NK.

[0013] Further, in some embodiments of the present invention, the smoothness parameter of the first spectrum is characterized by the multi-order derivative of the first characteristic spectrum α of the first spectrum j with respect to the wavelength λ and / or the multi-order derivative of the second characteristic spectrum β of the first spectrum j with respect to the wavelength λ characterizes.

[0014]

[0015] D represents the derivative of the corresponding spectrum at the wavelength λ i , i is the serial number of the wavelength λ, and the positive integer m≥2 is the order of the derivative.

[0016] Further, in some embodiments of the present invention, the step of integrating the smoothness parameters of the first spectrum at multiple wavelength positions according to a preset plurality of detection bands to determine the noise of the first spectrum in each of the detection bands includes: dividing the full spectrum range of the measuring machine into N detection bands. The wavelength of each detection band is denoted as [t n-1 , t n , t n-1 is the starting wavelength of the nth detection band, and t n is the ending wavelength of the nth detection band; and within the range of each detection band, integrating the smoothness parameter of the first spectrum to determine its noise in each of the detection bands:

[0017]

[0018] Further, in some embodiments of the present invention, the step of determining the weight coefficient of each detection band includes: normalizing the noise of the first characteristic spectrum α j and the second characteristic spectrum β j within each detection band:

[0019]

[0020] Calculating the weight coefficient of the detection band according to the noise after the normalization process:

[0021]

[0022] Further, in some embodiments of the present invention, the step of modifying the first optical model according to the weight coefficients of the respective detection bands to obtain a second optical model adapted to the material of the semiconductor device to be measured includes: splitting the first optical model into first sub-spectra of N said detection bands Combined model:

[0023]

[0024] where n ∈ N; and adding the weight coefficient w(n) of each said detection band to the corresponding first sub-spectrum to obtain a second optical model adapted to the material of the semiconductor device to be measured:

[0025]

[0026] Further, in some embodiments of the present invention, the step of substituting the second spectrum into the second optical model to determine the film thickness on the surface of the semiconductor device to be measured includes: splitting the acquired second spectrum into second sub-spectra of each said detection band and substituting each said second sub-spectrum into the corresponding position of the second optical model respectively to determine the film thickness on the surface of the semiconductor device to be measured

[0027] In addition, the ellipsometry system for a semiconductor device provided in the second aspect of the present invention includes a memory and a processor. A computer instruction is stored on the memory. The processor is connected to the memory and is configured to execute the computer instruction stored on the memory to implement the ellipsometry method for a semiconductor device provided in the first aspect of the present invention.

[0028] In addition, the above-mentioned method for optimizing an optical model provided in the third aspect of the present invention includes the following steps: obtaining an optical model by fitting according to the reference characteristic parameters of a semiconductor sample and the spectral data acquired after providing a detection beam to the semiconductor sample; integrating the smoothness parameters of the spectral data at multiple wavelength positions according to a plurality of preset detection bands to determine the noise of the spectral data in each said detection band, and determining the weight coefficient of each said detection band accordingly; and optimizing the optical model according to the weight coefficients of the respective detection bands.

[0029] In addition, the above-mentioned computer-readable storage medium provided in the fourth aspect of the present invention stores a computer instruction. When the computer instruction is executed by a processor, the ellipsometry method for a semiconductor device provided in the first aspect of the present invention is implemented. Description of the Drawings

[0030] After reading the detailed description of the embodiments of the present disclosure in conjunction with the following drawings, the above features and advantages of the present invention can be better understood. In the drawings, the components are not necessarily drawn to scale, and components having similar relevant characteristics or features may have the same or similar reference numerals.

[0031] Figure 1 A flowchart showing an ellipsometry method for a semiconductor device according to some embodiments of the present invention is shown.

[0032] Figure 2 A schematic diagram showing the principle of an ellipsometry method for a semiconductor device according to some embodiments of the present invention is shown.

[0033] Figure 3 A spectrogram showing a first characteristic spectrum according to some embodiments of the present invention is shown.

[0034] Figure 4 A spectrogram showing a second characteristic spectrum according to some embodiments of the present invention is shown.

[0035] Figure 5 A schematic diagram showing the principle of an ellipsometry method for a semiconductor device according to some embodiments of the present invention is shown.

[0036] Figure 6 A bar chart showing the proportion of each component of the overall variance before adjusting the weight system according to some embodiments of the present invention is shown.

[0037] Figure 7 A bar chart showing the proportion of each component of the overall variance after adjusting the weight system according to some embodiments of the present invention is shown. Detailed Embodiments

[0038] The following specific embodiments illustrate the embodiments of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Although the description of the present invention will be introduced in conjunction with preferred embodiments, this does not mean that the features of this invention are limited to this embodiment. On the contrary, the purpose of introducing the invention in conjunction with the embodiment is to cover other alternatives or modifications that may be extended based on the claims of the present invention. In order to provide a deep understanding of the present invention, many specific details will be included in the following description. The present invention can also be implemented without using these details. In addition, some specific details will be omitted in the description to avoid confusing or obscuring the key points of the present invention.

[0039] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be a direct connection or an indirect connection through an intermediate medium, and it may be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0040] In addition, the "upper", "lower", "left", "right", "top", "bottom", "horizontal", and "vertical" used in the following description should be understood as the orientations shown in this section and the relevant drawings. This relative term is only for convenience of description and does not mean that the device described needs to be manufactured or operated in a specific orientation, so it should not be construed as a limitation to the present invention.

[0041] It can be understood that although terms such as "first", "second", and "third" can be used herein to describe various components, regions, layers, and / or parts, these components, regions, layers, and / or parts should not be limited by these terms, and these terms are only used to distinguish different components, regions, layers, and / or parts. Therefore, the first component, region, layer, and / or part discussed below can be referred to as the second component, region, layer, and / or part without departing from some embodiments of the present invention.

[0042] As mentioned above, with the rapid development of semiconductor processes, the performance index requirements of various optical measurement and detection devices have been further improved. For example, the requirements for the repeatability and reproducibility differences of an ellipsometry system are that the proportion of repeatability and reproducibility in the overall variation (GR&R) ≤ 10%, and the number of distinguishable categories (NDC) ≥ 5. However, due to the requirements of different processes, when analyzing the machine measurement system each time, technicians need to refit and model different distributed spectra. Since the sensitivity of the spectra to materials is inconsistent in different bands, the spectra in some bands change little. Compared with the relatively basic fixed spectral noise, the signal-to-noise ratio is relatively small. In this case, the measurement results of the established model are more susceptible to spectral noise interference, thus affecting the repeatability and reproducibility differences of the measurement system.

[0043] In order to overcome the above-mentioned defects existing in the prior art, the present invention provides an ellipsometry method for semiconductor devices, an ellipsometry system for semiconductor devices, and a computer-readable storage medium, which can dynamically adjust the weight coefficients of each detection band in the spectral fitting process by quantifying the magnitude of the noise of each detection band of the spectrum relative to the change of the spectrum itself, so as to improve the repeatability and reproducibility differences of the measurement system, thereby improving the measurement performance of the measurement system.

[0044] In some non-limiting embodiments, the ellipsometry system of the semiconductor device provided by the second aspect of the present invention includes a memory and a processor. Herein, the memory includes, but is not limited to, the computer-readable storage medium provided by the aforementioned fourth aspect, on which computer instructions are stored. The processor is connected to the memory and is configured to execute the computer instructions stored on the memory to implement the ellipsometry method of the semiconductor device provided by the first aspect of the present invention, and / or the optimization method of the optical model provided by the third aspect of the present invention.

[0045] The working principle of the above ellipsometry system of the semiconductor device will be described below in combination with some embodiments of the optimization method of the optical model and the ellipsometry method of the semiconductor device. Those skilled in the art can understand that these method embodiments are only some non-limiting implementation manners provided by the present invention, aiming to clearly show the main concept of the present invention and provide some specific solutions convenient for the public to implement, rather than limiting all functions or all working manners of the ellipsometry system of the semiconductor device. Similarly, the ellipsometry system of the semiconductor device is also only a non-limiting implementation manner provided by the present invention, and does not limit the execution subject and execution order of each step in these methods.

[0046] Specifically, please refer to Figure 1 and Figure 2 . Figure 1 Fig. shows a schematic flowchart of an ellipsometry method of a semiconductor device provided according to some embodiments of the present invention. Figure 2 Fig. shows a schematic diagram of the principle of an ellipsometry method of a semiconductor device provided according to some embodiments of the present invention.

[0047] As Figure 1 and Figure 2 shown, the above ellipsometry system provided by the second aspect of the present invention can first execute the optimization method of the optical model provided by the third aspect of the present invention.

[0048] Specifically, the present invention can first obtain a first optical model of the measurement tool. Herein, the first optical model is obtained by first spectral fitting based on the reference characteristic parameters of a semiconductor sample and the first spectrum obtained by the measurement tool for full-spectrum measurement of the semiconductor sample. The semiconductor sample has the same material and device structure as the semiconductor device to be measured.

[0049] Further, in some embodiments, the above reference characteristic parameters include the reference film thickness and / or reference critical dimension on the surface of the semiconductor sample, and the actual characteristic parameters correspondingly include the actual film thickness and / or actual critical dimension on the surface of the semiconductor device to be measured. Herein, the reference critical dimension and actual critical dimension of the wafer are key structure parameters on the surface of the wafer, such as line width CD, height HT, trench depth Depth, and sidewall angle SWA.

[0050] Specifically, as Figure 2 shown, when the reference characteristic parameter is the reference film thickness, the ellipsometry system can perform full-spectrum measurement on a semiconductor sample via a standard machine to determine the reference film thickness of multiple detection units j thereon

[0051] After that, as Figure 2 shown, the ellipsometry system can perform full-spectrum measurement on a semiconductor sample via a measurement machine to obtain the first spectrum of each detection unit j thereon

[0052] After that again, the ellipsometry system can build a target equation according to the first spectrum and the reference film thickness :

[0053]

[0054] wherein, SysPram are the system parameters of the measurement machine, including but not limited to the angle of incidence (AOI), numerical aperture (NA), polarization angle (P), and analyzer angle (A), and NK are the material parameters of the semiconductor sample, including but not limited to the refractive index N and absorption coefficient K.

[0055] In some embodiments where optimization of the system parameters of the measurement machine does not need to be considered, the target equation can be simplified to:

[0056]

[0057] After that again, the ellipsometry system can, based on the above target equation, adopt optimization algorithms such as Levenberg-Marquardt to fit the target equation to determine the optimized solution of the material parameter NK, and then build the first optical model of the measurement machine according to the optimized solution:

[0058]

[0059] Please refer to Figure 3 and Figure 4 . Figure 3 shows the spectrogram of the first characteristic spectrum provided according to some embodiments of the present invention. Figure 4 shows the spectrogram of the second characteristic spectrum provided according to some embodiments of the present invention.

[0060] Furthermore, in the embodiments shown in Figure 3 and Figure 4 , spectral simulation is performed on an HfO2 film layer grown on a silicon substrate, and the smoothness parameter of the above first spectrum , is from the first characteristic spectrum α of the first spectrum ​j The multi - order derivative with respect to wavelength λ and / or the second characteristic spectrum β of the first spectrum j The multi - order derivative with respect to wavelength λ Characterize:

[0061]

[0062] where D represents the derivative of the corresponding spectrum at wavelength λ i , i is the serial number of wavelength λ, and the positive integer m≥2 is the order of the derivative.

[0063] Here, due to the variation of the first spectrum itself, generally setting m = 2 can eliminate the influence of its own variation by using the second - order derivative, so as to obtain the magnitude of the noise relative to the variation of the first spectrum itself. Further, in some embodiments where the first spectrum has obvious high - frequency oscillations (e.g., high - frequency periodic signals), technicians can also set a larger derivative order m>2 to characterize the magnitude of the noise relative to the variation of the first spectrum itself.

[0064] After that, as Figure 1 and Figure 2 shown, the ellipsometry system can integrate the smoothness parameters of the first spectrum at multiple wavelength positions according to multiple preset detection bands to determine the noise of the first spectrum in each detection band, and accordingly determine the weight coefficients of each detection band.

[0065] Specifically, the ellipsometry system can divide the full - spectrum range of the measurement stage into N detection bands. Here, the wavelength of each detection band is denoted as [t n-1 , t n , t n-1 is the starting wavelength of the nth detection band, and t n is the ending wavelength of the nth detection band.

[0066] After that, the ellipsometry system can integrate the smoothness parameters of the first spectrum within the range of each detection band to determine its noise in each detection band:

[0067]

[0068] After that, as Figure 1 and Figure 2 shown, the ellipsometry system can determine the weight coefficients of each detection band according to the noise of the first spectrum in each detection band.

[0069] Specifically, the ellipsometry system can normalize the noise of the first characteristic spectrum α j and the second characteristic spectrum β j within each detection band:

[0070]

[0071] After that, the ellipsometry system can calculate the weight coefficients of the detection bands according to the normalized noise:

[0072]

[0073] In this way, the ellipsometry system can adjust the weight coefficients of each detection band, making the weight coefficients of the detection bands with large noise smaller during fitting, so as to reduce the influence of noise on the spectral fitting process during measurement, thereby improving the fitting effect, the stability of the measurement result, and the repeatability and temperature performance of the measurement system.

[0074] After that, as Figure 1 and Figure 2 shown, the ellipsometry system can correct the first optical model according to the weight coefficients of each detection band to obtain a second optical model suitable for the material of the semiconductor device to be measured.

[0075] Specifically, the ellipsometry system can first split the above first optical model into a combined model of the first sub-spectra of N detection bands :

[0076]

[0077] where n ∈ N.

[0078] After that, the ellipsometry system can add the weight coefficients w(n) of each detection band to the corresponding first sub-spectra to obtain a second optical model suitable for the material of the semiconductor device to be measured:

[0079]

[0080] In this way, by performing the above steps of the optical model optimization method, the present invention can reconstruct the optical model suitable for the material of the semiconductor device to be measured through the setting of noise and weight coefficients, so as to obtain more accurate device detection results.

[0081] After that, the ellipsometry system can continue to execute the remaining steps of the ellipsometry method for semiconductor devices, detect the semiconductor device to be measured via a measurement station to obtain a second spectrum, and substitute the second spectrum into the second optical model to determine the film thickness on the surface of the semiconductor device to be measured.

[0082] Specifically, the ellipsometry system can split the obtained second spectrum into second sub-spectra of each detection band

[0083] After that, the ellipsometry system can substitute each second sub-spectrum into the corresponding position of the second optical model respectively to determine the actual film thickness of the surface of the semiconductor device to be measured

[0084] In addition, please refer to Figure 5 . Figure 5 FIG. shows a schematic diagram of the principle of an ellipsometry method for a semiconductor device provided according to some embodiments of the present invention.

[0085] As Figure 5 shown, when the reference characteristic parameter is the reference critical dimension, the ellipsometry system can perform a full-spectrum measurement on the semiconductor sample via a standard machine tool to determine the reference critical dimensions of multiple detection units j thereon

[0086] After that, as Figure 5 shown, the ellipsometry system can perform a full-spectrum measurement on the semiconductor sample via a measurement machine tool to obtain the first spectrum of each detection unit j thereon

[0087] After that again, the ellipsometry system can build a target equation according to the first spectrum and the reference critical dimension :

[0088]

[0089] wherein, SysPram are the system parameters of the measurement machine tool, including but not limited to the angle of incidence (AOI), numerical aperture (NA), polarization angle (P), and analyzer angle (A), and NK are the material parameters of the semiconductor sample, including but not limited to the refractive index N and absorption coefficient K.

[0090] In some embodiments where it is not necessary to consider the optimization of the system parameters of the measurement machine tool, the target equation can be simplified to:

[0091]

[0092] After that again, the ellipsometry system can, based on the above target equation, adopt an optimization algorithm such as Levenberg-Marquardt to fit the target equation to determine the optimal solution of the material parameter NK, and then build the first optical model of the measurement machine tool according to the optimal solution:

[0093]

[0094] Furthermore, in some embodiments, the smoothness parameter of the above first spectrum is determined by the first characteristic spectrum α of the first spectrum jThe multi - order derivative with respect to wavelength λ and / or the second characteristic spectrum β of the first spectrum j The multi - order derivative with respect to wavelength λ Characterize:

[0095]

[0096] where D represents the derivative of the corresponding spectrum at wavelength λ i , i is the serial number of wavelength λ, and the positive integer m≥2 is the order of the derivative.

[0097] Here, due to the variation of the first spectrum itself, generally setting m = 2 can eliminate the influence of its own variation by using the second - order derivative, so as to obtain the magnitude of the noise relative to the variation of the first spectrum itself. Further, in some embodiments where the first spectrum has obvious high - frequency oscillations (e.g., high - frequency periodic signals), technicians can also set a larger derivative order m>2 to characterize the magnitude of the noise relative to the variation of the first spectrum itself.

[0098] After that, as Figure 1 and Figure 5 shown, the ellipsometry system can integrate the smoothness parameters of the first spectrum at multiple wavelength positions according to multiple preset detection bands to determine the noise of the first spectrum in each detection band, and accordingly determine the weight coefficients of each detection band.

[0099] Specifically, the ellipsometry system can divide the full - spectrum range of the measurement stage into N detection bands. Here, the wavelength of each detection band is denoted as [t n-1 , t n , where t n-1 is the starting wavelength of the nth detection band, and t n is the ending wavelength of the nth detection band.

[0100] After that, the ellipsometry system can integrate the smoothness parameters of the first spectrum within the range of each detection band to determine its noise in each detection band:

[0101]

[0102] After that, as Figure 1 and Figure 5 shown, the ellipsometry system can determine the weight coefficients of each detection band according to the noise of the first spectrum in each detection band.

[0103] Specifically, the ellipsometry system can normalize the noise of the first characteristic spectrum α j and the second characteristic spectrum β j within each detection band:

[0104]

[0105] After that, the ellipsometry system can calculate the weight coefficients of the detection bands based on the normalized noise:

[0106]

[0107] In this way, the ellipsometry system can adjust the weight coefficients of each detection band, making the weight coefficients of the detection bands with large noise smaller during fitting, so as to reduce the influence of noise on the spectral fitting process during measurement, thereby improving the fitting effect, the stability of the measurement result, and the repeatability and temperature performance of the measurement system.

[0108] After that, as Figure 1 and Figure 5 shown, the ellipsometry system can optimize and correct the first optical model according to the weight coefficients of each detection band to obtain a second optical model suitable for the material of the semiconductor device to be measured.

[0109] Specifically, the ellipsometry system can first split the above first optical model into a combined model of the first sub-spectra of N detection bands :

[0110]

[0111] where n ∈ N.

[0112] After that, the ellipsometry system can add the weight coefficients w(n) of each detection band to the corresponding first sub-spectra to obtain a second optical model suitable for the material of the semiconductor device to be measured:

[0113]

[0114] After that, the ellipsometry system can detect the semiconductor device to be measured through the measurement station as described above to obtain the second spectrum, and substitute the second spectrum into the second optical model to determine the actual critical dimension of the surface of the semiconductor device to be measured.

[0115] Specifically, the ellipsometry system can split the obtained second spectrum into the second sub-spectra of each detection band

[0116] After that, the ellipsometry system can substitute each second sub-spectrum into the corresponding position of the second optical model to determine the actual critical dimension of the surface of the semiconductor device to be measured

[0117] Further, in order to verify the improvement of various indicators of the measurement system during the measurement process of the semiconductor device by the ellipsometry method for the semiconductor device provided in the first aspect of the present invention, those skilled in the art can take a thin film with a Cauchy material model as an example, and calculate the proportion of repeatability and reproducibility in the overall variance (GR&R), the number of distinguishable categories (NDC), the proportion of repeatability difference and reproducibility difference in the overall variance respectively before and after adjusting the weight coefficient.

[0118] Please refer to Figure 6 and Figure 7 . Figure 6 shows a bar chart of the proportion of each component of the overall variance before adjusting the weight system according to some embodiments of the present invention. Figure 7 shows a bar chart of the proportion of each component of the overall variance after adjusting the weight system according to some embodiments of the present invention.

[0119] As Figure 6 shown, %Con is the ratio of the variance of each difference to the variance of the overall variance, %GRR is the ratio of the standard deviation of each difference to the standard deviation of the overall variance, and %P / T is the ratio of the standard deviation of each difference to the tolerance. Before adjusting the weight coefficient, in the measurement results of the top film thickness by the ellipsometry system, the proportion of repeatability difference and reproducibility difference in the overall variance GR&R = 11.31%, where the proportion of repeatability difference in the overall variance (Repeatability) = 10.49%, and the proportion of reproducibility difference in the overall variance (Reproducibility) = 4.24%.

[0120] Here, in the process of determining the repeatability difference and reproducibility difference, those skilled in the art can assume that o operators measure the same p parts a total of n times, and calculate the mean square error MS between parts in the measurement results P , the mean square error MS between operators O , the mean square error MS of the interaction between parts and operators on the left and right PO , and the mean square error MS of random error E .

[0121] After that, those skilled in the art can calculate the variance accordingly Variance between parts Variance between operators and the variance of the interaction between parts and operators on the left and right

[0122]

[0123] After that, those skilled in the art can calculate the repeatability difference, reproducibility difference, difference between parts and the overall variance:

[0124]

[0125] After that, the technician can determine the proportion of the repeatability difference in the overall variation and the proportion of the reproducibility difference in the overall variation:

[0126]

[0127]

[0128] Here, the repeatability difference refers to the measurement variability generated by measuring the film thickness of the same sample to be measured multiple times on the same machine. The reproducibility difference refers to the measurement variability generated by measuring the film thickness of the same sample to be measured on different machines. The smaller the proportion of the repeatability difference and the reproducibility difference in the overall variation (GR&R), the better the repeatability and reproducibility of the measurement system during measurement.

[0129] In addition, before the weight coefficient adjustment, the number of distinguishable categories NDC of the ellipsometry measurement system is 12. Here, the number of distinguishable categories (NDC, Number of Distinct Categories) represents the ability of the measurement system to distinguish film thickness differences. The larger the number of distinguishable categories, the more capable the measurement system is of distinguishing subtle film thickness differences, and the better the repeatability and reproducibility during measurement.

[0130] As Figure 7 shown, compared with Figure 6 , after the weight coefficient adjustment, in the measurement results of the film thickness of the top layer film by the ellipsometry measurement system, the proportion of the repeatability difference and the reproducibility difference in the overall variation GR&R = 7.89%, a decrease of 30.24%. Among them, the proportion of the repeatability difference in the overall variation Repeatability = 6.75%, a decrease of 35.65%, and the proportion of the reproducibility difference in the overall variation Reproducibility = 4.09%, a decrease of 3.54%.

[0131] In addition, after the weight coefficient adjustment, the number of distinguishable categories NDC of the ellipsometry measurement system is 17, an increase of 41.67%.

[0132] In summary, the ellipsometry measurement method for semiconductor devices, the ellipsometry measurement system for semiconductor devices, and the computer-readable storage medium provided by the present invention can all dynamically adjust the weight coefficients of each detection band in the spectral fitting process by quantifying the magnitude of the noise of each detection band of the spectrum relative to the change in the spectrum itself, so as to improve the repeatability and reproducibility differences of the measurement system, thereby improving the measurement performance of the measurement system.

[0133] Although the methods described above are illustrated and described as a series of acts for simplicity of explanation, it should be understood and appreciated that the methods are not limited by the order of the acts, because according to one or more embodiments, some acts may occur in different orders and / or concurrently with other acts not illustrated and described herein but understood by those skilled in the art.

[0134] Those skilled in the art will appreciate that information, signals, and data can be represented using any of a variety of different technologies and techniques. For example, the data, instructions, commands, information, signals, bits, symbols, and chips described above throughout this description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or optical particles, or any combination thereof.

[0135] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithmic steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, the various illustrative components, blocks, modules, circuits, and steps are described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

[0136] The various illustrative logical modules and circuits described in connection with the embodiments disclosed herein can be implemented or executed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

[0137] The steps of a method or algorithm described in connection with the embodiments disclosed in this specification can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read from, and write to, the storage medium. In an alternative, the storage medium may be integrated into the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and the storage medium may reside as discrete components in a user terminal.

[0138] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted via a computer-readable medium as one or more instructions or code. The computer-readable medium includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage medium may be any available medium that can be accessed by a computer. By way of example and not limitation, such computer-readable medium can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. As used herein, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable medium.

[0139] The following description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An ellipsometry method for a semiconductor device, characterized in that, Including the following steps: Obtain a first optical model of a measurement machine stage, where the first optical model is obtained by first spectral fitting based on reference characteristic parameters of a semiconductor sample and a first spectrum obtained by the measurement machine stage measuring the semiconductor sample in the full spectrum, and the semiconductor sample has the same material as the semiconductor device to be measured; Integrate the smoothness parameters of the first spectrum at multiple wavelength positions according to a plurality of preset detection bands to determine the noise of the first spectrum in each detection band, and accordingly determine the weight coefficient of each detection band; Modify the first optical model according to the weight coefficient of each detection band to obtain a second optical model adapted to the material of the semiconductor device to be measured; and Detect the semiconductor device to be measured through the measurement machine stage to obtain a second spectrum, and substitute the second spectrum into the second optical model to determine the actual characteristic parameters on the surface of the semiconductor device to be measured.

2. The ellipsometry method according to claim 1, characterized in that, The reference characteristic parameters include the reference film thickness and / or reference critical dimension on the surface of the semiconductor sample, and the actual characteristic parameters correspondingly include the actual film thickness and / or actual critical dimension on the surface of the semiconductor device to be measured.

3. The ellipsometry method according to claim 2, wherein When the reference characteristic parameter is the reference film thickness, the step of obtaining the first optical model of the measurement machine stage includes: Perform full-spectrum measurement on the semiconductor sample via a standard machine to determine the reference film thickness of multiple detection units j thereon Through the measurement machine stage, full-spectrum measurement is performed on the semiconductor sample to obtain a first spectrum of each of the detection units j thereon Based on the first spectrum and the reference film thickness Construct a target equation: And perform an optimization solution on the material parameters NK of the material; and Construct the first optical model according to the optimization solution of the material parameters NK of the material:

4. The ellipsometry method according to claim 3, characterized in that, The material parameters NK include the refractive index N and the absorption coefficient K, and the step of performing an optimization solution on the material parameters NK of the material includes: Adopt the Levenberg-Marquardt optimization algorithm to fit the target equation to determine the optimization solution of the material parameters NK.

5. The ellipsometry method according to claim 1, wherein The first spectrum The smoothness parameter of which is characterized by the multi-order derivative of the first characteristic spectrum α j of the first spectrum with respect to the wavelength λ and / or the multi-order derivative of the second characteristic spectrum β j of the first spectrum with respect to the wavelength λ Characterize Wherein, D represents the derivative of the corresponding spectrum at wavelength λ i , i is the serial number of wavelength λ, and the positive integer m ≥ 2 is the order of the derivative.

6. The ellipsometry method according to claim 5, wherein The step of integrating the smoothness parameters of the first spectrum at multiple wavelength positions according to a plurality of preset detection bands to determine the noise of the first spectrum in each detection band includes: Divide the full spectral range of the measurement machine into N detection bands, where the wavelength of each detection band is denoted as [t n-1 , t n , t n-1 is the starting wavelength of the nth detection band, and t n is the ending wavelength of the nth detection band; and Integrate the smoothness parameter of the first spectrum within the range of each of the detection bands to determine the noise thereof in each of the detection bands: ​ 7. The ellipsometry method according to claim 6, wherein The step of determining the weight coefficient of each detection band includes: For the first characteristic spectrum α j and the second characteristic spectrum β j normalize the noise within each of the detection bands: and Calculate the weight coefficient of the detection band according to the normalized noise; 8. The ellipsometry method according to claim 3, characterized in that, The step of modifying the first optical model according to the weight coefficient of each detection band to obtain a second optical model adapted to the material of the semiconductor device to be measured includes: Split the first optical model into first sub-spectra of N detection bands Combined model of: Where n ∈ N; and Add the weight coefficient w(n) of each detection band to the corresponding first sub-spectrum to obtain a second optical model adapted to the material of the semiconductor device to be measured:

9. The ellipsometry method according to claim 8, wherein, The step of substituting the second spectrum into the second optical model to determine the film thickness on the surface of the semiconductor device to be measured includes: The obtained second spectrum is split into second sub-spectra of the respective detection bands and Substitute each of the second sub-spectra into the corresponding positions of the second optical model respectively to determine the film thickness on the surface of the semiconductor device to be measured 10. An ellipsometry system for a semiconductor device, characterized in that, Including: A memory storing computer instructions thereon; And A processor connected to the memory and configured to execute the computer instructions stored on the memory to implement the ellipsometry method for semiconductor devices according to any one of claims 1 to 9.

11. An optimization method for an optical model, characterized in that, Including the following steps: According to the reference characteristic parameters of the semiconductor sample and the spectral data collected after providing a detection beam to the semiconductor sample, perform fitting to obtain an optical model; Integrate the smoothness parameters of the spectral data at multiple wavelength positions according to a plurality of preset detection bands to determine the noise of the spectral data in each of the detection bands, and determine the weight coefficient of each of the detection bands accordingly; and Optimize the optical model according to the weight coefficients of each of the detection bands.

12. A computer-readable storage medium having computer instructions stored thereon, characterized in that, When the computer instructions are executed by a processor, an ellipsometry method for a semiconductor device according to any one of claims 1 to 9 is implemented.

Images