X-ray measurement system and X-ray measurement method

Abstract

To provide an X-ray measurement system and an X-ray measurement method.SOLUTION: A plurality of measurement signals generated by a detection object DT reflecting a plurality of X-ray beams with different energies are respectively collected by using a photodetector 2, and a plurality of fitting models are constructed based on a target structure of the detection object. Spectrum fitting analysis is performed on a plurality of metrology signals by using the fitting model to generate a plurality of fitting results to be optimized, perform statistics, and generate a plurality of parameter fitting ranges. A to-be-verified parameter group is generated based on the plurality of parameter fitting ranges, the to-be-verified parameter group is input into the plurality of fitting models, an accuracy of the to-be-verified parameter group is verified, and the to-be-verified parameter group is adjusted based on the accuracy and the plurality of parameter fitting ranges until an optimization condition is met, to obtain an optimized fitting result.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an X-ray measurement system and an X-ray measurement method, and more particularly to a wide-energy bandwidth range measurement of X-rays and a measurement method for a multi-model algorithm. [Background technology]

[0002] As the computational power of processors gradually increases, the demands on semiconductor circuits also become more precise. To manufacture circuits with an accuracy of 7 nanometers or less, exposure equipment using extreme ultraviolet (EUV) light with a wavelength of less than 13.5 nm as the light source is selected. Because EUV has a short wavelength, it is necessary to put reflective mirrors on the photomask to reflect the circuit pattern onto the wafer. The reflective mirrors are made of alternating layers of Mo and Si, and at least about 30 to 40 layers are used to achieve an EUV reflectivity of 80% or more.

[0003] Currently, monitoring critical parameters such as multilayer film thickness within an EUV photomask requires the use of conventional transmission electron microscopes (TEMs) or secondary ion mass spectrometers (SIMS). These methods are time-consuming, require sample destruction, and are limited to analyzing only surface elements. While non-destructive testing techniques using single-wavelength light sources exist, they are limited by the attenuation length of the incident light entering the sample, making it impossible to inspect deeper layers. [Overview of the Initiative] [Problems that the invention aims to solve]

[0004] Therefore, overcoming the aforementioned shortcomings by obtaining more accurate measurement results using non-destructive measurement methods has become one of the important challenges to be addressed in this field. [Means for solving the problem]

[0005] The technical problem that the present invention aims to solve is to provide an X-ray measurement system in response to the shortcomings of the prior art. The X-ray measurement system comprises an X-ray source that generates a plurality of X-ray beams having different energies and irradiates a target object with them; a photodetector that collects a plurality of measurement signals generated by the object reflecting the plurality of X-ray beams; and a processing device configured to perform the following steps, which include constructing a plurality of fitting models based on the target structure of the object; performing spectral fitting analysis on the plurality of measurement signals using the plurality of fitting models to generate a plurality of optimization target fitting results; statistically analyzing the plurality of optimization target fitting results to generate a plurality of parameter fitting ranges; generating a group of parameter to be verified based on the plurality of parameter fitting ranges; inputting the group of parameter to be verified into a plurality of fitting models; verifying the accuracy of the group of parameter to be verified; adjusting the group of parameter to be verified based on the accuracy and the plurality of parameter fitting ranges until optimization conditions are met; and taking the group of parameter to be verified that satisfies the optimization conditions as the optimization fitting result.

[0006] To solve the above-mentioned technical problems, one of the technical solutions employed in the present invention is to provide an X-ray measurement method. The X-ray measurement method includes generating a plurality of X-ray beams having different energies using at least one X-ray source and irradiating an object to be detected with them; collecting a plurality of measurement signals generated by the object reflecting the plurality of X-ray beams using a photodetector; and performing the following steps using a processing device, the steps of which include constructing a plurality of fitting models based on the target structure of the object to be detected; performing spectral fitting analysis on the plurality of measurement signals using the plurality of fitting models to generate a plurality of optimization target fitting results; statistically analyzing the plurality of optimization target fitting results to generate a plurality of parameter fitting ranges; generating a group of parameters to be verified based on the plurality of parameter fitting ranges; inputting the group of parameters to be verified into a plurality of fitting models; verifying the accuracy of the group of parameters to be verified; adjusting the group of parameters to be verified based on the accuracy and the plurality of parameter fitting ranges until the optimization conditions are met; and taking the group of parameters to be verified that satisfies the optimization conditions as the optimization fitting result. [Effects of the Invention]

[0007] One of the beneficial effects of the present invention is that the X-ray measurement system and X-ray measurement method provided in the present invention can reduce the standard deviation of the parameters of the optimization fitting result, i.e., reduce the error value, by technical means such as "irradiating a target object with multiple X-ray beams having different energies, collecting multiple measurement signals generated by the reflection of the X-ray beams by the target object using a photodetector," "constructing multiple fitting models based on the target structure of the target object," "using the fitting models to perform spectral fitting analysis on each of the multiple measurement signals to generate multiple optimization target fitting results, statistically analyzing the multiple optimization target fitting results to generate multiple parameter fitting ranges, generating a verification target parameter group based on the multiple parameter fitting ranges, inputting the verification target parameter group into multiple fitting models, verifying the accuracy of the verification target parameter group, adjusting the verification target parameter group based on the accuracy and the multiple parameter fitting ranges until the optimization conditions are met, and taking the verification target parameter group that satisfies the optimization conditions as the optimization fitting result."

[0008] To further understand the features and technical content of the present invention, please refer to the following detailed description and drawings of the invention, however, the drawings provided are for reference and illustrative purposes only and are not intended to limit the invention. [Brief explanation of the drawing]

[0009] [Figure 1] This is a schematic diagram of an X-ray measurement system according to an embodiment of the present invention. [Figure 2] This is a schematic diagram of an X-ray measurement system having multiple target materials according to an embodiment of the present invention. [Figure 3A] This is a functional block diagram of an X-ray measurement method according to an embodiment of the present invention. [Figure 3B] This is a functional block diagram of an X-ray measurement method according to an embodiment of the present invention. [Figure 4] It is a diagram of X-ray energy-depth corresponding to an element or a compound. [Figure 5] It is a spectrum diagram of the first X-ray beam of the X-ray measurement system according to the present invention. [Figure 6] It is a spectrum diagram of the second X-ray beam of the X-ray measurement system according to the present invention. [Figure 7] It is a spectrum diagram of the third X-ray beam of the X-ray measurement system according to the present invention. [Figure 8] It is a schematic diagram of the first fitting model of the X-ray measurement system according to the present invention. [Figure 9] It is a schematic diagram of the second fitting model of the X-ray measurement system according to the present invention. [Figure 10] It is a schematic diagram of the third fitting model of the X-ray measurement system according to the present invention.

Embodiments for Carrying Out the Invention

[0010] Hereinafter, embodiments of the "X-ray measurement system and X-ray measurement method" disclosed in the present invention will be described by way of specific examples. A person skilled in the art can understand the advantages and effects of the present invention from the disclosed content. The present invention can be implemented or applied through other different specific embodiments, and various detailed descriptions in this specification can also be modified and changed in various ways without departing from the idea of the present invention based on different perspectives and applications. Also, it should be noted in advance that the drawings of the present invention are only shown schematically and are not drawn based on actual dimensions. The following embodiments are used to explain the technical content of the present invention in more detail, but the disclosed content is not intended to limit the protection scope of the present invention. Also, the term "or" in this specification should be understood to include any one or a combination of multiple of the related listed items according to the actual situation.

[0011] Figure 1 is a schematic diagram of an X-ray measurement system according to an embodiment of the present invention. Figure 2 is a schematic diagram of an X-ray measurement system having multiple target materials according to an embodiment of the present invention. As shown in Figure 1, the first embodiment of the present invention provides an X-ray measurement system comprising an X-ray source 1, a photodetector 2, and a processing device 3.

[0012] The X-ray source 1 generates multiple X-ray beams with different energies and irradiates the object DT to be detected. The X-ray source 1 may also include an X-ray generator 10 and an X-ray lens group 20. In the X-ray source 1, the electron beam generates X-ray beams with different energies through different target materials. As shown in Figure 2, the X-ray generator 10 may also include an electron beam generator 11 and a target material 12. The electron beam generator 11 irradiates different target materials with the electron beam to generate multiple X-ray beams with different wavelengths. The target materials are different materials such as copper, molybdenum, silver, and aluminum. The multiple X-ray beams with different wavelengths may include, for example, a first X-ray beam in the energy range of 90 eV to 94 eV, a second X-ray beam in the energy range of 1480 eV to 1490 eV, and a third X-ray beam in the energy range of 8040 eV to 8900 eV. X-ray source 1 generates X-ray beams with different wavelengths and emits them onto the object to be detected DT. The object to be detected DT may have a multilayer structure. For example, the object to be detected DT is an extreme ultraviolet (EUV) photomask with a multilayer structure.

[0013] Furthermore, since X-ray beams with different energies have different attenuation lengths for different materials, the X-ray measurement system can detect the target object DT by employing X-ray beams with different energy ranges for materials used in the multilayer structure of the target object DT. It should be noted that the attenuation length indicates the penetration depth achievable when an element or compound is irradiated with X-rays of a specific energy, and the energy of that X-ray decreases to 1 / e (approximately 1 / 2.72 of the original intensity). This can be used to analyze the analytical sensitivity of the X-rays at this specific energy.

[0014] In this embodiment, when the detection target DT is an EUV photomask, for example, it may include one or more of an inter-diffusion layer, a reflective composite layer, a capping layer (CL), and a low thermal expansion material layer (LTEM). For example, an inter-diffusion layer may be measured using an X-ray beam in the energy range of 90 eV to 94 eV, the reflective composite layer and the capping layer (CL) inside the photomask may be measured using an X-ray beam in the energy range of 1480 eV to 1490 eV, and the low thermal expansion material layer (LTEM) may be measured using an X-ray beam in the energy range of 8040 eV to 8900 eV. In this embodiment, the inter-expansion layer is an oxide layer generated during the formation of the photomask, contains a large amount of light elements such as molybdenum disilicide (MoSi2), molybdenum trisilicide (Mo5Si3), and ruthenium oxide (RuO), and is applicable to measurement by X-rays in the low energy range of 90 eV to 94 eV.

[0015] On the other hand, the capping layer contains ruthenium and ruthenium compounds. The reflective composite layer has about 40 pairs of repeating layers and is formed by an alternating material layer composed of two or more types of metal elements. For example, the reflective composite layer of this embodiment includes about 40 pairs of molybdenum-silicon thin film pairs (Mo / Si) and is applicable to measurement by X-rays in the energy range of 1480 eV to 1490 eV.

[0016] The low thermal expansion material layer is usually located at the bottom of the EUV photomask and is a thick multilayer film containing fused silicon, fused quartz, calcium fluoride, silicon carbide, silicon oxide-titanium oxide alloy, and / or other suitable materials known in the art, and is applicable to measurement by X-rays in the energy range of 8040 eV to 8900 eV.

[0017] After irradiating the object to be detected DT with X-rays of different energies, the photodetector 2 may collect multiple measurement signals reflected from the object to be detected DT. The processing unit 3 includes multiple measurement tools for analyzing the multiple measurement signals. Here, the multiple measurement signals include reflected X-ray light, scattered light, diffracted light, or fluorescence emitted when the object to be detected DT is excited by the X-rays. The measurement tools include an X-ray reflectivity (XRR) analyzer, an X-ray fluorescence spectrometer (XRF), a small-angle X-ray scattering (SAXS) analyzer, an X-ray diffractometer (XRD), or other devices capable of measurement using X-rays as a light source. The X-ray measurement system of the present invention may analyze the multiple measurement signals collected by the object to be detected DT. The measurement signals and measurement tools are not limited to the types described above. Specifically, if the measurement signal is reflected light, a reflected light detector may be used as the second detector in the X-ray measurement system, and an XRR analyzer may be used as the measurement tool to analyze the reflected light of the X-ray beam reflected by the object to be detected DT. Alternatively, if the measurement signal is fluorescence, when an X-ray beam is irradiated onto the object to be detected DT, electrons in the inner orbitals are excited by the X-rays, and electrons in high-energy levels transition to low-energy levels, filling the vacancies created by the excited electrons, thereby releasing the corresponding energy, i.e., the corresponding fluorescence is emitted. A fluorescence detector may be used as the second detector, and an X-ray fluorescence spectrometer may be used as the measurement tool to analyze the collected fluorescence and obtain a fluorescence spectrum. Alternatively, if the measurement signal is scattered light, a scattered light detector may be used as the second detector, and a SAXS analyzer may be used as the measurement tool to perform small-angle X-ray scattering analysis. Alternatively, if the measurement signal is diffracted light, a diffracted light receiver is used as receiver 2, and an X-ray diffractometer is used as the measurement tool to collect and analyze the diffracted light generated by the object DT being detected.

[0018] Figure 4 is a diagram of X-ray energy-depth corresponding to an element or compound. As shown in Figure 4, each measurement signal is a reflection spectrum generated by irradiating the target object with each X-ray beam at multiple different incidence angles and collected by the photodetector 2. The X-axis represents the X-ray energy, and the Y-axis represents the X-ray penetration depth. As the X-ray beam passes through the EUV mask and radiates to each layer structure, the X-ray energy is attenuated as it passes through different elements or compounds, i.e., reduced to approximately 0.367 times the original intensity. Since X-ray beams in different energy ranges have different optical sensitivities to the material layers, the analytical sensitivity of the light source energy can be analyzed.

[0019] The processing unit 3 of the present invention is a general-purpose processor, a computer, a specific hardware device having a particular logic circuit, or a device having a specific function. The processing unit 3 of this embodiment further comprises an electromagnetic wave calculation engine. The electromagnetic wave calculation engine is an algorithm implemented in a computer-related hardware device. The electromagnetic wave calculation engine includes the Finite-Difference Time-Domain (FDTD) algorithm, the Distorted Wave Born Approximation (DWBA) algorithm, the Rigorous Coupled Wave Analysis (RCWA) algorithm, the Discrete Dipole Approximation (DDP) algorithm, and the Boundary Element Method (BEM).

[0020] Figures 3A and 3B are functional block diagrams of an X-ray measurement method according to an embodiment of the present invention. As shown in Figures 3A and 3B, the measurement method includes obtaining multiple structural parameters of the target structure TS using a multi-model calculation algorithm for data measured from X-ray beams of different energy bands. When the object to be detected DT is an EUV photomask having a multilayer structure as described above, the target structure TS may include multiple material layers designed according to the structure of the object to be detected DT, and the multiple structural parameters may include, for example, the thickness, density, or roughness of each material layer.

[0021] The arithmetic processing performed by the processing unit 3 includes the following steps:

[0022] Step S1: Multiple measurement signals are acquired using multiple measurement tools. Step S1 further includes steps S11 and S12.

[0023] Step S11: Multiple X-ray sources are used to generate multiple X-ray beams with different energies, which are then irradiated onto the object DT to be detected.

[0024] Step S12: Using the photodetector 2, multiple measurement signals generated by the reflection of multiple X-ray beams by the object DT to be detected are collected.

[0025] Steps S11 and S12 will be described in more detail. The measurement signals in this embodiment include a first measurement signal SP1, a second measurement signal SP2, and a third measurement signal SP3. For example, the first measurement signal SP1 is obtained by using a first X-ray beam in the energy range of 90 eV to 94 eV and measuring the photomask sample with a first measurement tool and performing calculations. The second measurement signal SP2 is obtained by using a second X-ray beam in the energy range of 1480 eV to 1490 eV and measuring the photomask sample with a second measurement tool and performing calculations. The third measurement signal SP3 is obtained by using a third X-ray beam in the energy range of 8040 eV to 8900 eV and measuring the photomask sample with a third measurement tool and performing calculations. In this embodiment, the number of measurement tools is not limited. It should be noted that the first, second, and third measurement tools used in this step each include the configuration of the X-ray source 1 and photodetector 2 described above, but the only difference is the X-ray energy used. The numbers of the first, second, and third measurement tools are merely examples, and they may be X-ray reflectance analyzers, X-ray fluorescence spectrometers, small-angle X-ray scattering analyzers, X-ray diffractometers, or other devices capable of measurement using X-rays as a light source.

[0026] Figure 5 is a spectral diagram of the first X-ray beam of the X-ray measurement system according to the present invention. Figure 6 is a spectral diagram of the second X-ray beam of the X-ray measurement system according to the present invention. Figure 7 is a spectral diagram of the third X-ray beam of the X-ray measurement system according to the present invention.

[0027] As shown in Figures 5 to 7, a measurement signal is obtained by measuring a photomask sample using three different energy X-ray beams. In Figures 5 to 7, the X-axis represents the measurement angle in degrees. The Y-axis represents the intensity of the measurement signal collected by the X-rays, and the unit is the count value (counts per second, CPS) obtained by integrating the photons received by the photodetector in one second. Figures 5 to 7 show the measurement signals collected by measuring a photomask sample using X-ray beams of different energies. The measurement signal includes first data SP1 collected by irradiation with the first X-ray beam, second data SP2 collected by irradiation with the second X-ray beam, and third data SP3 collected by irradiation with the third X-ray beam. The processing device 3 can perform calculations based on the characteristics of the measured spectral curves to obtain the structural parameters of each material layer. These structural parameters include thickness, density, and roughness. The characteristics of the spectral curve include the slope of the curve or the interval between specific peaks. Since the spectral curves shown in Figures 5 to 7 are different, the thickness, density, and roughness of each material layer obtained by X-ray beams in different energy ranges are also different.

[0028] Step S2: Multiple fitting models are constructed based on the target structure of the object to be detected, and calculations are performed using an electromagnetic wave calculation engine corresponding to the measurement tool.

[0029] The processing unit 3 constructs multiple fitting models FM based on the target structure TS of the object to be detected DT, and executes an electromagnetic wave calculation engine corresponding to each fitting model FM to perform spectral fitting analysis of the corresponding measurement signal based on the target structure TS and obtain the corresponding optimized fitting result. For example, in this embodiment, the first parameter fitting model FM1 and the first electromagnetic wave calculation engine EM1 both correspond to the first measurement tool. The second parameter fitting model FM2 and the second electromagnetic wave calculation engine EM2 both correspond to the second measurement tool. In this embodiment, the third parameter fitting model FM3 and the third electromagnetic wave calculation engine EM3 both correspond to the third measurement tool.

[0030] When constructing a model, different calculation modes may be applied to each material layer depending on factors such as the importance of each material layer or changes in process conditions to construct a fitting model. The processing unit 3 performs spectral fitting analysis of the corresponding measurement signal based on the target structure TS by executing an electromagnetic wave calculation engine corresponding to each fitting model, and obtains the corresponding optimized fitting result. The present invention includes multiple binding calculation modes. In a binding calculation mode, multiple material layers of the target structure TS are divided into one or more calculation groups, each calculation group is either an independent calculation group or a binding calculation group, and the electromagnetic wave calculation engine performs spectral fitting analysis on the measurement signal based on this one or more calculation groups.

[0031] Hereinafter, three aspects of the fitting model will be further described. FIG. 8 is a schematic diagram of the first fitting model of the X-ray measurement system according to the present invention. FIG. 9 is a schematic diagram of the second fitting model of the X-ray measurement system according to the present invention. FIG. 10 is a schematic diagram of the third fitting model of the X-ray measurement system according to the present invention. As shown in FIGS. 8 to 10, the X-ray measurement system of this embodiment includes a first fitting model, a second fitting model, and a third fitting model. As shown in FIG. 8, in the first fitting model, each layer of a plurality of material layers is divided into independent calculation groups. Each material layer in the first fitting model is calculated by an electromagnetic wave calculation engine, which requires the most calculation time and calculation capacity among the three fitting model samples. As shown in FIG. 9, in the second fitting model, these material layers are divided into n independent calculation groups and N binding calculation groups, where n > N. As shown in FIG. 10, in the third fitting model, these material layers are divided into m independent calculation groups and M binding calculation groups, where m < M. Here, the n independent calculation groups and the m independent calculation groups each include at least four material layers M1, M2, M3, and M4. The first parameter fitting model FM1, the second parameter fitting model FM2, and the third parameter fitting model FM3 of the present invention can select fitting models in different aspects according to whether the parameters of the material layer are important for the manufacturing process. Thereby, unnecessary calculations can be reduced, the calculation time can be shortened, and the measurement accuracy can be improved.

[0032] Step S3: Using a plurality of fitting models, perform spectral fitting analysis on each measurement signal to generate a plurality of optimization target fitting results.

[0033] The optimization target fitting results include multiple primary structural parameters for describing multiple material layers, and multiple primary error values ​​corresponding to each of the primary structural parameters (Calibration Optimization with Standard Technique, COST) COSTX1~COSTX n and multiple first variance numbers Δp1~Δp n It includes.

[0034] Specifically, the electromagnetic wave calculation engine stored in the processing unit 3 performs spectral fitting analysis on the corresponding measurement signal and generates the optimization target fitting result. As shown in Figures 3A and 3B, the processing unit 3 constructs a first parameter fitting model FM1, and the first electromagnetic wave calculation engine EM1 corresponding to the first parameter fitting model FM1 performs spectral fitting analysis on the first measurement signal SP1 and generates the first optimization target fitting result. The second electromagnetic wave calculation engine EM2 corresponding to the second parameter fitting model FM2 performs spectral fitting analysis on the second measurement signal SP2 and generates the second optimization target fitting result. The third electromagnetic wave calculation engine EM3 corresponding to the third parameter fitting model FM3 performs spectral fitting analysis on the third measurement signal SP3 and generates the third optimization target fitting result.

[0035] As described above, the present invention acquires measurement data from N measuring instruments, constructs a fitting model corresponding to each, then performs fitting analysis on multiple measurement signals using N parameter fitting models, and finally obtains multiple first error values ​​COSTX1~COSTX corresponding to multiple first structural parameters through corresponding N electromagnetic wave calculations. n and multiple first variance numbers Δp1~Δp n The following may be generated. Multiple first error values ​​and multiple first variance numbers are the results of the first optimization target fitting. Here, the error values ​​may be optimization calibration values ​​according to standard techniques, and the present invention is not limited to the above example.

[0036] For example, the target structure TS has six material layers, including the first material layer ML1, the second material layer ML2, the third material layer ML3, the fourth material layer ML4, the fifth material layer ML5, and the sixth material layer ML6. When the first electromagnetic wave calculation engine EM1, corresponding to the first parameter fitting model FM1, performed a spectral fitting analysis on the first measurement signal SP1, the numerical values ​​for the thickness of each material layer in the target structure TS were obtained as follows: ML1, ML2, ML3, ML4, ML5, ML6: 20, 20, 20, 20, 20. When the second electromagnetic wave calculation engine EM2, corresponding to the second parameter fitting model FM2, performed a spectral fitting analysis on the second measurement signal SP2, the numerical values ​​for the thickness of each material layer in the target structure TS were obtained as follows: ML1, ML2, ML3, ML4, ML5, ML6: 60, 40, 60, 40, 60, 40. Since the above data will be statistically analyzed as a sequence, the units of thickness will not be stated. The two sequences of thicknesses for each material layer generated by the aforementioned fitting analysis represent the two optimization target fitting results. The number of material layers in this embodiment is not limited to six, and the values ​​generated after performing the spectral fitting analysis are not limited to the thickness of each material layer.

[0037] Step S4: Statistically analyze the results of multiple optimization target fittings, generate multiple parameter fitting ranges, and generate a group of parameters to be validated based on the multiple parameter fitting ranges.

[0038] Here, the parameter group to be verified includes a plurality of second structural parameters describing each material layer. Furthermore, the X-ray measurement method further includes generating this parameter group to be verified using a random number method based on these parameter fitting ranges, inputting these parameter groups to their fitting models by alternating combinations to verify their accuracy, and adjusting the parameter group to be verified by alternating combinations again based on this accuracy and these parameter fitting ranges.

[0039] Continuing from the example of step S3 described above, two sequences of thicknesses for each material layer are statistically analyzed to generate a fitting range for the thickness of each material layer, i.e., a parameter fitting range. For example, the first material layer ML1 has a thickness range of 20-60, the second material layer ML2 has a thickness range of 20-40, the third material layer ML3 has a thickness range of 20-60, the fourth material layer ML4 has a thickness range of 20-40, the fifth material layer ML5 has a thickness range of 20-60, and the sixth material layer ML6 has a thickness range of 20-40.

[0040] Next, a group of parameters to be validated is generated based on these parameter fitting ranges. Within the fitting range of the thickness of each material layer, a random array of different thickness combinations is generated. For example, one group of parameters to be validated contains two sequences, and each value in each sequence is selected from the parameter fitting range of each material layer. Specifically, the first value of the first sequence is generated randomly from the thickness range of the first material layer ML1. That is, the first value is generated randomly from the range of 20 to 60. The second value of the first sequence is generated randomly from the thickness range of the second material layer ML2 (value range 20 to 40). Similarly, the sixth value of the first sequence is generated randomly from the thickness range of the sixth material layer ML6 (value range 20 to 40). Likewise, each value in the second sequence is generated randomly in order from the thickness range of the first material layer ML1 to the sixth material layer ML6. The first and second sequences constitute a single group of parameters to be validated. In other words, one group of parameters under verification includes at least two sequences to be combined alternately. However, the number of sequences in the present invention is not limited to two.

[0041] Step S5: Input this group of parameters under validation into multiple fitting models and verify their accuracy.

[0042] This parameter group to be verified is combined alternately and then input into these fitting models to verify their accuracy. For example, this parameter group to be verified includes a first numerical sequence and a second numerical sequence. By randomly selecting N numerical values from the first numerical sequence and exchanging them with the corresponding numerical values in the second numerical sequence, a third numerical sequence and a fourth numerical sequence are obtained. For example, by randomly selecting the numerical values from the first material layer ML1 to the third material layer ML3 from the first numerical sequence and exchanging them with the numerical values from the first material layer ML1 to the third material layer ML3 in the second numerical sequence, a third numerical sequence and a fourth numerical sequence are obtained. That is, the third numerical sequence and the fourth numerical sequence are different from the first numerical sequence and the second numerical sequence. Next, the third numerical sequence and the fourth numerical sequence are input into these fitting models, and the accuracy of the third numerical sequence and the fourth numerical sequence is verified.

[0043] The steps to verify the accuracy of this parameter group to be verified are to input this parameter group to be verified into these fitting models, and generate a plurality of fitting results to be verified, a corresponding plurality of second error values COSTX’1~COSTX’ n and a plurality of second variances Δp’1~Δp’ n and compare these second error values COSTX’1~COSTX’ n with these first error values COSTX1~COSTX n respectively, and compare these second variances Δp’1~Δp’ n with these first variances Δp1~Δp n respectively.

[0044] Step S6: Based on this accuracy and these parameter fitting ranges, adjust this parameter group to be verified.

[0045] Based on the comparison results, check whether the optimization conditions are met. If the optimization conditions are met, this group of parameters under verification can be considered the result of the optimization fitting. If the optimization conditions are not met, adjust this group of parameters under verification by combining them alternately again, based on the accuracy and the range of these parameter fittings.

[0046] If the optimization conditions are met, multiple second error values ​​COSTX'1~COSTX' n This is a set of multiple first error values ​​COSTX1~COSTX n Each of these is smaller than the second variance numbers Δp'1~Δp' n These are the first variance numbers Δp1~Δp n The optimization conditions are determined to be met when each of these values ​​is smaller than the given value.

[0047] If the optimization conditions are not met, multiple second error values ​​COSTX'1~COSTX' n This is a set of multiple first error values ​​COSTX1~COSTX n Each of these is larger than the second variance numbers Δp'1~Δp' n These are the first variance numbers Δp1~Δp n This means that each of them is larger than the specified values. In response to the judgment that the optimization conditions are not met, this group of parameters under verification is adjusted based on these parameter fitting ranges, and the accuracy of this group of parameters under verification is judged after the adjustment. After obtaining a structural solution with a reduced number of variances, the optimization calibration values ​​(COSTX'1, COSTX'2…COSTX') are used. n ) and fitting variances (Δp'1, Δp'2…Δp' n It was confirmed that all of these values ​​were smaller than when no loop processing was performed.

[0048] [Beneficial effects from the examples] One of the beneficial effects of the present invention is that the X-ray measurement system and X-ray measurement method provided in the present invention can reduce the standard deviation of the parameters of the optimization fitting result, that is, reduce the error value, by technical means such as "irradiating a target object with multiple X-ray beams having different energies, and collecting multiple measurement signals generated by the reflection of the X-ray beams by the target object using a photodetector," "constructing multiple fitting models based on the target structure of the target object," and "performing spectral fitting analysis on each of the multiple measurement signals using the multiple fitting models, generating parameters to be verified based on the fitting analysis results, verifying the accuracy, making adjustments according to the accuracy, repeating until the optimization conditions are met, and obtaining the optimization fitting result."

[0049] Furthermore, the X-ray measurement system and X-ray measurement method provided by the present invention allow for the selection of different types of fitting models during the model building stage, depending on whether the parameters of the material layer are important to the manufacturing process. This reduces unnecessary calculations, shortens calculation time, and improves measurement accuracy.

[0050] The information disclosed herein represents only preferred embodiments of the present invention and does not limit the scope of the claims. Accordingly, all equivalent technical modifications made using the specification and drawings of the present invention are included within the scope of the claims. [Explanation of Symbols]

[0051] 1:X-ray source 10: X-ray generator 20: X-ray lens group 11: Electron beam generator 12: Target material 2:Receiver 3: Processing Unit S1~S6: Step M1, M2, M3, M4: Material layer

Claims

1. The method involves generating multiple X-ray beams with different energies using at least one X-ray source and irradiating the object to be detected with them. Using a photodetector, multiple measurement signals generated by the reflection of multiple X-ray beams by the object to be detected are collected, The following steps are performed using the processing unit, Includes, The aforementioned step is, Constructing multiple fitting models based on the target structure of the object to be detected, Using multiple fitting models, spectral fitting analysis is performed on multiple measurement signals to generate multiple optimization target fitting results. The process involves statistically analyzing multiple optimization target fitting results to generate multiple parameter fitting ranges, The process involves generating a group of parameters to be validated based on multiple parameter fitting ranges, inputting the group of parameters to be validated into multiple fitting models, verifying the accuracy of the group of parameters to be validated, adjusting the group of parameters to be validated based on the accuracy and the multiple parameter fitting ranges until the optimization conditions are met, and using the group of parameters to be validated that satisfies the optimization conditions as the optimization fitting result. including, An X-ray measurement method characterized by the following features.

2. Each of the measurement signals is a reflection spectrum generated by irradiating the object to be detected with each of the X-ray beams at multiple different incidence angles and collected by the photodetector. The X-ray measurement method according to claim 1.

3. The X-ray beam includes a first X-ray beam in the energy range of 90 eV to 94 eV, a second X-ray beam in the energy range of 1480 eV to 1490 eV, and a third X-ray beam in the energy range of 8040 eV to 8900 eV. The X-ray measurement method according to claim 2.

4. The target structure comprises a plurality of material layers, and the processing apparatus performs spectral fitting analysis of the corresponding measurement signal based on the target structure by executing an electromagnetic wave calculation engine corresponding to each fitting model, thereby obtaining the corresponding optimized fitting result. The X-ray measurement method according to claim 2.

5. The step of performing spectral fitting analysis by executing the electromagnetic wave calculation engine further includes dividing the multiple material layers of the target structure into one or more calculation groups, each of which is an independent calculation group or a bound calculation group, and the electromagnetic wave calculation engine performing spectral fitting analysis on the measurement signal based on one or more of the calculation groups. The X-ray measurement method according to claim 4.

6. In the first fitting model among the multiple fitting models, each of the multiple material layers is divided into independent calculation groups. In the second fitting model among the multiple fitting models, the multiple material layers are divided into n independent operation groups and N binding operation groups, where n > N. In the third fitting model among the multiple fitting models, the multiple material layers are divided into m independent calculation groups and M binding calculation groups, where m < M. The X-ray measurement method according to claim 5.

7. Each of the n independent operation groups and the m independent operation groups includes at least four of the material layers. The X-ray measurement method according to claim 6.

8. The multiple optimization target fitting results include a plurality of first structural parameters for describing the plurality of material layers, a plurality of first error values ​​and a plurality of first variance numbers corresponding to each of the plurality of first structural parameters. The X-ray measurement method according to claim 6.

9. The aforementioned group of parameters to be verified includes a plurality of second structural parameters for describing each of the material layers, The aforementioned X-ray measurement method is, The method further includes generating the parameter groups to be validated using a random number method based on a plurality of parameter fitting ranges, inputting the parameter groups to be validated alternately into a plurality of fitting models to verify the accuracy, and adjusting the parameter groups to be validated by combining them alternately again based on the accuracy and the plurality of parameter fitting ranges. The X-ray measurement method according to claim 8.

10. The step of verifying the accuracy of the parameter group to be verified is: The aforementioned group of parameters to be validated is input into multiple fitting models, and multiple validation fitting results, corresponding multiple second error values, and multiple second variance numbers are generated. Comparing each of the multiple second error values ​​with each of the multiple first error values, This includes comparing a plurality of the aforementioned second variance numbers with a plurality of the aforementioned first variance numbers, The X-ray measurement method according to claim 9.

11. The optimization condition is determined to be satisfied when, in accordance with the fact that each of the multiple second error values ​​is smaller than each of the multiple first error values, and each of the multiple second variance numbers is smaller than each of the multiple first variance numbers, If it is determined that the optimization conditions are not met, the group of parameters to be verified is adjusted based on a plurality of parameter fitting ranges, and the accuracy of the adjusted group of parameters to be verified is determined. The X-ray measurement method according to claim 10.

12. An X-ray source that generates multiple X-ray beams with different energies and irradiates the object to be detected, A photodetector that collects multiple measurement signals generated by the reflection of multiple X-ray beams by the object to be detected, A processing unit configured to perform the following steps, Equipped with, The aforementioned step is, Constructing multiple fitting models based on the target structure of the object to be detected, Using multiple fitting models, spectral fitting analysis is performed on multiple measurement signals to generate multiple optimization target fitting results. The process involves statistically analyzing multiple optimization target fitting results to generate multiple parameter fitting ranges, The process involves generating a group of parameters to be validated based on multiple parameter fitting ranges, inputting the group of parameters to be validated into multiple fitting models, verifying the accuracy of the group of parameters to be validated, adjusting the group of parameters to be validated until the optimization conditions are met based on the accuracy and the multiple parameter fitting ranges, and taking the group of parameters to be validated that satisfies the optimization conditions as the optimization fitting result. including, An X-ray measurement system characterized by the following features.

13. Each of the measurement signals is a reflection spectrum generated by irradiating the object to be detected with each of the X-ray beams at multiple different incidence angles and collected by the photodetector. The X-ray measurement system according to claim 12.

14. The X-ray beam includes a first X-ray beam in the energy range of 90 eV to 94 eV, a second X-ray beam in the energy range of 1480 eV to 1490 eV, and a third X-ray beam in the energy range of 8040 eV to 8900 eV. The X-ray measurement system according to claim 13.

15. The target structure comprises a plurality of material layers, and the processing apparatus performs spectral fitting analysis of the corresponding measurement signal based on the target structure by executing an electromagnetic wave calculation engine corresponding to each fitting model, thereby obtaining the corresponding optimized fitting result. The X-ray measurement system according to claim 13.

16. The step of performing spectral fitting analysis by executing the electromagnetic wave calculation engine further includes dividing the multiple material layers of the target structure into one or more calculation groups, each of which is an independent calculation group or a bound calculation group, and the electromagnetic wave calculation engine performing spectral fitting analysis on the measurement signal based on one or more of the calculation groups. The X-ray measurement system according to claim 15.

17. In the first fitting model among the multiple fitting models, each of the multiple material layers is divided into independent calculation groups. In the second fitting model among the multiple fitting models, the multiple material layers are divided into n independent operation groups and N binding operation groups, where n > N. In the third fitting model among the multiple fitting models, the multiple material layers are divided into m independent calculation groups and M binding calculation groups, where m < M. The X-ray measurement system according to claim 16.

18. Each of the n independent operation groups and the m independent operation groups includes at least four of the material layers. The X-ray measurement system according to claim 17.

19. The multiple optimization target fitting results include a plurality of first structural parameters for describing the plurality of material layers, a plurality of first error values ​​and a plurality of first variance numbers corresponding to each of the plurality of first structural parameters. The X-ray measurement system according to claim 17.

20. The aforementioned group of parameters to be verified includes a plurality of second structural parameters for describing each of the material layers, The aforementioned processing apparatus is The system is configured to generate the parameter groups to be validated using a random number method based on a plurality of parameter fitting ranges, to input the parameter groups to be validated into a plurality of fitting models by alternating combinations of the parameter groups to be validated to verify the accuracy, and to further adjust the parameter groups to be validated by alternating combinations again based on the accuracy and the plurality of parameter fitting ranges. The X-ray measurement system according to claim 19.

21. The step of verifying the accuracy of the parameter group to be verified is: The aforementioned group of parameters to be validated is input into multiple fitting models, and multiple validation fitting results, corresponding multiple second error values, and multiple second variance numbers are generated. Comparing each of the multiple second error values ​​with each of the multiple first error values, This includes comparing a plurality of the aforementioned second variance numbers with a plurality of the aforementioned first variance numbers, The X-ray measurement system according to claim 20.

22. The optimization condition is determined to be satisfied when, in accordance with the fact that each of the multiple second error values ​​is smaller than each of the multiple first error values, and each of the multiple second variance numbers is smaller than each of the multiple first variance numbers, If it is determined that the optimization conditions are not met, the group of parameters to be verified is adjusted based on a plurality of parameter fitting ranges, and the accuracy of the adjusted group of parameters to be verified is determined. The X-ray measurement system according to claim 21.

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