Cluster matching of semiconductor metrology tools without dedicated quality control wafers

Abstract

Presented herein are methods and systems for calibrating metrology tool offset values ​​to match measurement results across a fleet of metrology tools. The offset value calibration is based on measurements of in-line production wafers and eliminates the need for specially manufactured and characterized quality control (QC) wafers. In this way, the entire process flow for calibrating metrology tool offset values ​​is automated and fully integrated with the bulk semiconductor manufacturing process flow. In a further aspect, the implementation of new offset values ​​is governed by one or more predetermined control limits. In yet another further aspect, the measured value of a parameter of interest is adjusted to compensate for the effects of measurement time on the wafer under measurement.

Description

[0001] Cross-reference to related applications

[0002] This patent application claims priority under 35 U.S.C. §119 to U.S. Provisional Patent Application Serial No. 63 / 030,935, filed May 28, 2020, entitled “A Tool-To-Tool Matching Algorithm by using non-Dedicated Quality Control Wafers in a Fleet of Metrology Tools,” the subject matter of which is incorporated herein by reference in its entirety. Technical Field

[0003] The described embodiments relate to metrology systems and methods, and more particularly, the described embodiments relate to methods and systems for improving measurement accuracy. Background Art

[0004] Semiconductor devices, such as logic and memory devices, are typically manufactured using a sequence of processing steps applied to a sample. Various features and multiple structural levels of a semiconductor device are formed by these processing steps. For example, photolithography is a semiconductor manufacturing process that involves creating patterns on a semiconductor wafer. Additional examples of semiconductor manufacturing processes include, but are not limited to, chemical mechanical polishing, etching, deposition, diffusion, metallization, and ion implantation. Multiple semiconductor devices can be manufactured on a single semiconductor wafer and then separated into individual semiconductor devices.

[0005] Accumulated failures in one or more process steps can lead to reduced device yield from the semiconductor manufacturing process flow. Metrology processes are used at various steps during the semiconductor manufacturing process to detect defects on the wafer to promote higher yields. For example, metrology tools measure pattern dimensions, film thickness, interlayer alignment, pattern placement, surface topography, optoelectronic properties, and more. Metrology techniques offer high throughput capabilities without the risk of sample destruction. Many optical and X-ray metrology-based techniques, including scatterometry and reflectometry implementations and associated analysis algorithms, are commonly used to characterize the critical dimensions, film thickness, composition, and other parameters of nanoscale structures.

[0006] The performance, integration, and reliability of semiconductor devices have continued to improve over time due to increasing process resolution and increasingly complex device structures. Improving process resolution can reduce the minimum critical size of fabricated structures. Process resolution is primarily driven by the wavelength of the light source used in the fabrication process. The latest extreme ultraviolet lithography (EUV) light sources produce a wavelength of 13.5 nanometers, enabling the fabrication of features smaller than 32 nanometers. Furthermore, more complex device structures, such as FinFET structures and vertical NAND structures, have been developed to improve overall performance, energy cost, integration, and reliability.

[0007] As devices, such as logic and memory devices, progress toward smaller nanometer-scale dimensions, characterization becomes increasingly difficult. Devices incorporating complex three-dimensional geometries and materials with diverse physical properties contribute to characterization difficulties. Metrology systems are generally required to measure devices at more process steps and with greater precision.

[0008] In addition to accurate device characterization, measurement consistency across various measurement applications and across a fleet of metrology systems tasked with the same measurement objectives is also important. If measurement consistency degrades in a manufacturing environment, consistency between processed semiconductor wafers is lost and yields drop to unacceptable levels. Matching measurement results across applications and across multiple systems (i.e., tool-to-tool matching) ensures that measurements on the same wafer for the same application produce identical results.

[0009] Systematic errors exist in each metrology tool in a fleet, even if each metrology tool in the fleet is well calibrated. These systematic errors cause measurement results to shift between different tools in the fleet. The measurement results associated with each tool are added to an offset value assigned to each metrology tool to compensate for these systematic errors. After this adjustment, the measurement results monitored in the statistical process control (SPC) system are consistent across the fleet of metrology tools. In this way, any deviations in the manufacturing process can be detected based on the SPC chart.

[0010] A statistical process control monitor is needed to predict the expected device yield across a fleet of metrology tools that measure wafers at the same process step. An offset associated with each metrology tool is introduced to compensate for systematic variations in the metrology tool fleet. Without offset compensation, measurements of a quality control (QC) wafer passing through a metrology tool are offset or shifted from measurements of the same QC wafer passing through another, otherwise identical, metrology tool.

[0011] The offset associated with each metrology tool is typically compensated for by adding an offset calibration value to each tool's reported measurement value. The offset calibration value associated with each tool is typically determined from QC measurements of a dedicated set of QC wafers measured by each metrology tool in the fleet. Each tool's offset calibration value is evaluated based on raw measurement data. This effectively amplifies process variations captured by measurements performed by the metrology tool fleet by minimizing the impact of tool mismatch.

[0012] In some examples, an offset calibration value for each tool is calculated using a calibration process for a specific process step and a cluster of metrology tools with nominally identical hardware and software configurations.

[0013] In this example, a QC wafer is manufactured under process of record (POR) conditions in a particular process step. Next, the QC wafer is measured by all metrology tools in the metrology tool fleet. For example, if the measurement is a critical dimension (CD) measurement, a CD measurement (CD1, CD2, CD3, ..., CDn) is obtained from each tool in a group of n tools in the metrology tool fleet. An average value m of the measured CD values ​​is determined, where m is the mean or median of the measured CD values. An offset associated with each tool is determined as the difference between the measured CD value associated with each tool and the average value. For example, for the i-th tool, offset Δi = m - CD i Finally, the offset value associated with each tool is used to adjust the reported measurement value from the corresponding tool. For example, Δi is used to adjust the reported CD measurement value from the i-th tool, CD i *, including CD i *=CD i +Δi*R, where R is a scaling value having a value selected by the user between 0 and 1.

[0014] The above-described calibration process for determining offset calibration values ​​is repeated as operating conditions change (eg, process changes, metrology tool preventative maintenance, tool repairs, scheduled updates to tool offsets, etc.).

[0015] Unfortunately, traditional methods for calibrating metrology tool offsets to match measurements across a metrology tool fleet are time-consuming and expensive. For example, the production, characterization, and maintenance of QC wafers are prohibitively expensive in a high-volume production environment. QC wafers must be safely secured and transported to each tool and manually loaded and unloaded at each tool. Costs and damage risks are multiplied when a metrology tool fleet includes tools in different, remote facilities. These time and cost constraints limit tool-to-tool matching, especially across fabs, where the additional time and risk involved in transporting QC wafers is significant.

[0016] As metrology systems evolve to measure devices in more process steps and with higher precision, the complexity of the tool offset calibration process also increases. Improved methods and tools for reducing the time and cost associated with calibrating metrology tool offset values ​​so that measurement results match across a fleet of metrology tools are desired. Summary of the Invention

[0017] Presented herein are methods and systems for calibrating metrology tool offsets to match measurement results across a fleet of metrology tools. Specifically, the offset calibration described herein is based on measuring inline production wafers and eliminates the need for using specially manufactured and characterized quality control (QC) wafers. Eliminating the use of dedicated QC wafers significantly reduces the operational constraints and costs of maintaining tool-to-tool matching in semiconductor manufacturing environments, particularly when tool-to-tool matching is required across different fabs.

[0018] Furthermore, the entire process flow for calibrating metrology tool offsets is automated and fully integrated with the bulk of the semiconductor manufacturing process flow. This enables seamless updates of metrology tool offsets without manual intervention or interruption to the process flow. Consequently, tool-to-tool matching of metrology tools is automatically maintained at low operating costs by eliminating the need for dedicated quality control wafers and reducing the use of human operators.

[0019] In a further aspect, implementation of the new offset value is regulated by one or more predetermined control limits. In some embodiments, the one or more predetermined control limits are determined by a user.

[0020] In another further aspect, the measured value of the parameter of interest is adjusted to compensate for the effect of measurement time on the wafer under measurement.

[0021] The foregoing is a summary and therefore necessarily simplifies, generalizes, and omits details; therefore, those skilled in the art will appreciate that the summary is illustrative only and is not intended to be limiting. Other aspects, inventive features, and advantages of the devices and / or processes described herein will be apparent from the non-limiting detailed description set forth herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 is a diagram illustrating a system 100 for measuring characteristics of a semiconductor wafer according to the methods described herein.

[0023] Figure 2 is a diagram illustrating a cluster of metrology tools 151 - 154 undergoing offset calibration according to the methods described herein.

[0024] Figure 3A is a graph 180 illustrating measured parameter values ​​by four different tools over a 30 day period before any offset correction is applied.

[0025] Figure 3B is a graph 181 illustrating the offset parameter values ​​implemented daily for each of four different tools over a 30-day period.

[0026] Figure 3C is a graph 182 illustrating measured parameter values ​​by four different tools over a 30 day period after applying an offset correction.

[0027] Figure 3D is a graph 183 illustrating the standard deviation of uncorrected and corrected measured parameter values ​​across four different tools over a 30-day period.

[0028] Figure 4 A method 200 for calibrating offset values ​​for group matching in at least one novel aspect is described. DETAILED DESCRIPTION

[0029] Reference will now be made in detail to background examples and some embodiments of the invention, examples of which are illustrated in the accompanying drawings.

[0030] In a high-volume semiconductor manufacturing environment, a fleet of nominally identical metrology tools is used to perform measurements of structural and material properties (e.g., material composition of structures and films, dimensional properties, etc.) at specific steps in the semiconductor manufacturing process flow. Calibration of the offset values ​​associated with each metrology tool ensures that the measurement results from each metrology tool are comparable across the fleet. In other words, if a particular production wafer is measured by two different metrology tools within the fleet, the measurement results should be very close to the same value, free of systematic errors associated with any particular tool.

[0031] Presented herein are methods and systems for calibrating metrology tool offsets to match measurements across a fleet of metrology tools. Specifically, the methods and systems described herein employ in-line production wafers and eliminate the need for specially manufactured and characterized quality control (QC) wafers. Eliminating the use of dedicated QC wafers significantly reduces the operational constraints and costs of maintaining tool-to-tool matching in semiconductor manufacturing environments, particularly when tool-to-tool matching is required across different fabs.

[0032] Using inline production wafers to calibrate metrology tool offsets allows for greater flexibility in wafer selection and measurement sequences because calibration data is derived from measurements on inline production wafers, rather than inserting dedicated QC wafers into the production flow. For example, when calibration is based on measurements on inline production wafers, metrology tool offset calibration can be based on a significantly larger set of wafers.

[0033] Furthermore, the entire process for calibrating metrology tool offsets is automated and fully integrated with the bulk of the semiconductor manufacturing process flow. This enables seamless updates of metrology tool offsets without manual intervention and disruption to the bulk of the semiconductor manufacturing process flow.

[0034] In this way, tool-to-tool matching of metrology tools is automatically maintained at low operating costs by eliminating the need for dedicated quality control wafers and reducing the utilization of human operators.

[0035] Figure 1A system 100 is described for measuring characteristics of semiconductor wafers such as critical dimension (CD), film thickness, optical properties and material composition, overlay, lithography focus / dose, etc. Figure 1 As shown in FIG, system 100 can be used to perform spectroscopic ellipsometric measurements of one or more structures 114 of a semiconductor wafer 112 disposed on a wafer positioning system 110. In this aspect, system 100 may include a spectroscopic ellipsometer 101 equipped with an illuminator 102 and a spectrometer 104. The illuminator 102 of system 100 is configured to generate illumination of a selected wavelength range and direct it toward the structures 114 disposed on the surface of semiconductor wafer 112. Spectrometer 104, in turn, is configured to receive light from the surface of semiconductor wafer 112. It should be further noted that a polarization generator 107 is used to polarize the light emitted from illuminator 102 to produce a polarized illumination beam 106. Radiation reflected by the structures 114 disposed on wafer 112 passes through a polarization analyzer 109 to spectrometer 104. Radiation received by spectrometer 104 in a collection beam 108 is analyzed with respect to polarization state to allow spectral analysis of the radiation to be transmitted by the analyzer. These spectra 111 are passed to a computing system 130 for analysis of the structures 114.

[0036] In a further embodiment, the measurement system 100 includes one or more computing systems 130 configured to execute an automated measurement tool to estimate a value 115 of a parameter of interest associated with one or more structures 114 under measurement. In a preferred embodiment, the measurement tool is a set of program instructions 134 stored in a memory (e.g., memory 132 or an external memory). The program instructions 134 are read and executed by one or more processors 131 of the computing system 130 to estimate the value of the parameter of interest. The computing system 130 may be communicatively coupled to the spectrometer 104. In one aspect, the computing system 130 is configured to receive measurement data 111 associated with measurements (e.g., critical dimensions, film thickness, composition, process, etc.) of a structure 114 of a sample 112. In one example, the measurement data 111 includes an indication of a measured spectral response of the sample through the measurement system 100 based on one or more sampling processes from the spectrometer 104. In some embodiments, the computing system 130 is further configured to determine a sample parameter value 115 of the structure 114 from the measurement data 111. In an example, computing system 130 is configured to access one or more measurement libraries of pre-computational models to determine a value of at least one sample parameter value associated with target structure 114. In some examples, the measurement libraries are stored in memory 132.

[0037] Figure 2 An illustration depicting a cluster of metrology tools 151-154 undergoing calibration of offset values ​​according to the methods described herein. Figure 2As depicted, metrology tools 151-154 are a cluster of metrology tools tasked with measuring structures fabricated on different wafers using the same series of process steps in a production environment. Wafers 141-143 are wafers that have undergone the same series of processing steps and are presented to metrology tools 151-154, respectively, at the same process steps.

[0038] like Figure 2 As depicted in FIG, wafers 141-143 are measured by a plurality of metrology tools of the set of metrology tools 151-154. Estimates 161-164 of the parameter of interest are generated by the metrology tools 151-154, respectively. The measurements 161-164 are transmitted to an offset calibration server 170.

[0039] The offset calibration server 170 includes one or more computing systems configured to execute an offset calibration tool to estimate the offset value 118 transmitted to each of the metrology tools 151-154. In a preferred embodiment, the offset calibration tool is a set of program instructions 174 stored in a memory (e.g., memory 172 or external memory). The program instructions 174 are read and executed by one or more processors 171 of the computing system 130 to estimate the offset value. The offset calibration server 170 can be communicatively coupled to the metrology tools 151-154. In one aspect, the offset calibration server 170 is configured to receive measurement data 161-164 associated with measurements of parameters of interest (e.g., critical dimensions, film thickness, composition, process, etc.) of one or more structures disposed on wafers 141-143, respectively. In one example, the measurement data 161-164 includes an indication of a measured critical dimension of the structures disposed on wafers 141-143, respectively.

[0040] exist Figure 2 In the depicted embodiment, a record of measurements performed by each of the metrology tools in the fleet is stored in a data host (e.g., memory 175) accessible from the offset calibration server 170. The measurement record includes measurement recipe information, metrology tool information, wafer lot information, wafer information, measurement time, measurement parameter values ​​to which the current offset is applied, and the current offset value for each tool. Equation (1) describes a set of current offset values, each corresponding to a different metrology tool in the fleet of M metrology tools.

[0041] {Δ1, Δ2, Δ3, .., Δ m} (1)

[0042] like Figure 2As depicted in FIG, offset calibration task configuration information 117 is received from a user input source 116 to an offset calibration server 170. In one example, the user input source 116 is a user interacting with a peripheral device, such as a mouse, keyboard, touch screen, etc., to input the offset calibration task configuration information via a graphical user interface (GUI). The offset calibration task configuration information 117 defines the offset calibration task parameters required to perform offset calibration. By way of non-limiting example, the offset calibration task configuration information 117 includes measurement recipe information, measurement parameters to be matched, control limits for the measurement parameters, a measurement time frame, etc. In one example, the measurement time frame is defined by a measurement start time and a measurement end time, typically defined with a resolution of at least one second.

[0043] Measurement records that meet the task requirements defined by the offset calibration task configuration information 117 are loaded from each of the metrology tools or the memory 175. In some examples, the measurement records are reviewed against a set of predetermined mandatory criteria to verify their validity. In some examples, the criteria are defined in the offset calibration task configuration information 117. By way of non-limiting example, the validity criteria include the goodness of the measurement, the measurement status (e.g., normal versus abnormal measurement), and the data within the measurement time frame.

[0044] After the appropriate measurement data is loaded onto the offset calibration server 170, the measurement log is organized into two parts: 1) the measured values ​​of the parameters of interest, and 2) the current offset value associated with each parameter. The measurement values ​​are grouped by wafer, including the measurement time and measurement values ​​from one or more metrology tools for each wafer.

[0045] like Figure 2 As depicted in FIG, the offset calibration server 170 determines the deviation of each metrology tool relative to the average of all metrology tools. It is not necessary to run each wafer through all metrology tools in the group to be matched. Generally, each wafer in the wafer set presented herein for generating measurement data for group matching is measured by two or more different metrology tools in the group to be matched. Furthermore, each metrology tool in the group to be matched should measure at least one wafer in the wafer set presented herein for generating measurement data for group matching.

[0046] In one example, a cluster of five metrology tools is to be matched. A first wafer is measured on metrology tools #1, #2, and #4 of the cluster of five metrology tools. The offset associated with each of these tools is determined by the offset calibration server 170 according to equation (2),

[0047]

[0048] Among them, p mn is the value of the measurement parameter of interest from the nth wafer measured by the mth tool, It is p 11 、p 21 and p 41 The average value of δ mn is the deviation associated with the mth tool and the nth wafer. In this example, the average value is determined as the mean or median.

[0049] Additionally, the offset calibration server 170 determines an average of the offsets for each metrology tool of the fleet across all wafers measured by each metrology tool. The average offset is determined by the offset calibration server 170 according to equation (3),

[0050]

[0051] in, is the mean deviation of the mth instrument.

[0052] For m tools, the average deviation associated with each metrology tool of the population of metrology tools to be matched is described by equation (4).

[0053]

[0054] The offset calibration server 170 determines a new offset value based on the average deviation associated with each metrology tool according to equation (5),

[0055]

[0056] Among them, Δ′ m is the new offset value associated with the parameter of interest measured by the mth tool, and r is a scaling ratio having a positive value of 1 or less. The value of the scaling ratio r is selected by the user as part of the configuration information 117 to moderate the changes made to the offset value due to the offset calibration process. For m tools, the new offset value associated with each metrology tool of the population of metrology tools to be matched is described by equation (6).

[0057] {Δ′1,Δ′2,Δ′3,...Δ′ m} (6)

[0058] like Figure 2 As depicted in FIG, updated offset values ​​118 for all tools are transmitted from the offset calibration server 170 to the metrology tools 151 through 154. As illustrated, new offset value 118A (Δ′ 1) is transmitted to metrology tool 151, new offset value 118B (Δ′ 2) is transmitted to metrology tool 152, new offset value 118C (Δ′ 3) is transmitted to metrology tool 153, and new offset value 118D (Δ′ m ) is transmitted to the metrology tool 154. In some other embodiments, the new offset value is stored in a memory (eg, memory 175).

[0059] In a further aspect, implementation of the new offset value is regulated by one or more predetermined control limits. In some embodiments, the one or more predetermined control limits are determined by a user as part of the offset calibration task configuration information 117.

[0060] In some embodiments, the average deviation associated with each metrology tool is compared to one or more predetermined thresholds to determine whether the average deviation is within a range of values. If the average deviation value exceeds an upper predetermined threshold, the average deviation is limited to the upper predetermined value or set to 0. Alternatively, if the average deviation value is less than a lower predetermined threshold, the average deviation is limited to the lower predetermined value or set to 0.

[0061] In some embodiments, the new offset value is compared to one or more predetermined thresholds to determine whether the new offset value is within a range of values. If the new offset value exceeds an upper predetermined threshold, the new offset value is limited to the upper predetermined value or set to 0. Alternatively, if the new offset value is less than a lower predetermined threshold, the new offset value is limited to the lower predetermined value or set to 0.

[0062] In another further aspect, the measured value of the parameter of interest is adjusted to compensate for the measurement time.

[0063] In some instances, measurements characterizing structures fabricated on a wafer drift over time, measurement time, or both. For example, airborne molecular contamination (AMC) is the time-dependent accumulation of contaminants that shifts measurements. In another example, the power and duration of the incident radiation used to perform the measurement induce material changes on the wafer that shift the measurement over measurement time. Consequently, the value of a parameter of interest determined from measurements of a particular structure may trend upward or downward over time or measurement time.

[0064] The magnitude of measurement errors induced by time-dependence or measurement-time-dependence phenomena is exacerbated by the use of dedicated QC wafers, which are used for relatively long periods of time and are subject to significantly more measurement time than the inline production wafers described herein. Consequently, there is a risk that the QC wafers may not be representative of the current production wafers after a significant amount of time has passed.

[0065] However, by using in-line production wafers to significantly reduce the risk of time-dependent or measurement-time-dependent drifts, an additional step is described for adjusting the measured values ​​of the parameters of interest to compensate for the measurement time.

[0066] In one example, at least one wafer is measured by the same metrology tool at two different times. For each measurement, the time at which the measurement was performed is saved in a memory (e.g., memory 175). Additional measurements of the wafer on the same tool at different times enable calculation of a trend in the value of the measurement parameter as a function of the time elapsed between measurements. In this way, for example, trending effects due to airborne molecular contamination can be compensated. In some embodiments, the trending behavior is assumed to be a linear function of time. In these embodiments, the difference in the measured parameter values ​​divided by the time difference between the measurements quantifies the trend, as illustrated in equation (7),

[0067]

[0068] Wherein k is the slope of the trend measurement parameter, p1 is the value of the measurement parameter at the first measurement by the first metrology tool, T1 is the time of the first measurement by the first metrology tool, p′1 is the value of the measurement parameter at the subsequent measurement by the first metrology tool, and T′1 is the time of the subsequent measurement by the first metrology tool.

[0069] In one example, the detrended value of the measurement parameter of any other metrology tool of the metrology tool population is determined according to equation (8),

[0070] p′ x =p x -k(T x -T1) (g)

[0071] where p x is the value of the measurement parameter measured by the xth metrological tool, T x is the time of measurement by the xth measuring tool, and p′ x is the value of the detrended measured parameter value associated with the measurement of the parameter by the xth instrument.

[0072] In general, the measurement parameter values ​​associated with each measurement of this wafer can be detrended as described above.For example, a set of detrended measurements for a particular wafer by m metrology tools of a metrology tool cluster can be represented by equation (9).

[0073] {p′1, p′2, p′3,...p′ m} ((9)

[0074] The effect of wafer trending on measurement mismatch is significantly reduced by detrending the measurement data in the manner described herein. In some examples, the offset calibration server 170 uses the detrended measurement data determined according to equation (8) to determine the deviation value of each metrology tool relative to the average of all metrology tools, as described with reference to equation (2).

[0075] In some embodiments, the times described with reference to equations (7) and (8) are replaced by the number of measurements of a measurement sequence performed on the wafer. In this way, for example, trend effects due to radiation dose can be compensated, which scale with the number of times the wafer is measured.

[0076] refer to Figures 3A to 3D An exemplary calibration of offset parameter values ​​across a metrology tool fleet is illustrated below. Four optical critical dimension (OCD) metrology tools from the fleet are implemented in a production environment. The metrology tool fleet measures wafers at the same production step in the manufacturing process flow. More specifically, each inline production wafer is measured by one of the four metrology tools in the fleet. Each day, an inline production wafer is selected and measured by two or more metrology tools from the fleet for tool matching as described herein. In this manner, the offset parameter values ​​associated with each tool used to measure the selected wafer on a given day are updated on that day, while tools not used to measure the selected wafer on that day are not updated on that day. To ensure periodic updates for each tool in the fleet, the two or more tools selected to measure the selected wafer on a given day are rotated between the fleets.

[0077] Figure 3A 1 is a graph 180 illustrating parameter values ​​measured by four different tools over a 30 day period before any offset correction is applied. Plot line 180A depicts the measurement results for tool #1, plot line 180B depicts the measurement results for tool #2, plot line 180C depicts the measurement results for tool #3, and plot line 180D depicts the measurement results for tool #4. Figure 3A As illustrated in , the wafers measured by each tool are different, and the wafers measured by each tool are different each day. Therefore, the uncorrected measurements show differences across tools and over time (e.g., from day to day) due to systematic tool differences and actual dimensional differences on the measured wafers.

[0078] Figure 3B 1 is a graph 181 illustrating the offset parameter values ​​implemented for each of tools #1 through #4 on a daily basis over a 30-day period. Plot line 181A depicts the offset parameter values ​​implemented for tool #1, plot line 181B depicts the offset parameter values ​​implemented for tool #2, plot line 181C depicts the offset parameter values ​​implemented for tool #3, and plot line 181D depicts the offset parameter values ​​implemented for tool #4. Figure 3B As depicted in FIG, there are occasionally large shifts in the offset parameter values ​​implemented for a particular tool. This occurs when a large change occurs, such as when a preventative maintenance event is performed on the tool. Figure 3B As illustrated in , the offset parameter values ​​determined according to the methods described herein are able to compensate for tool changes and maintain inter-tool matching.

[0079] Figure 3C1 is a graph 182 illustrating parameter values ​​measured by four different tools over a 30 day period after applying an offset correction. Plot line 182A depicts the measurement results for tool #1, plot line 182B depicts the measurement results for tool #2, plot line 182C depicts the measurement results for tool #3, and plot line 182D depicts the measurement results for tool #4. Figure 3C As illustrated in , the wafers measured by each tool are different, and the wafers measured by each tool are different every day. Therefore, the corrected measurements show the differences across tools and over time (e.g., day to day) due to actual dimensional differences on the measured wafers, while the impact of systematic tool differences has been significantly reduced.

[0080] Figure 3D 1 is a graph 183 illustrating the standard deviation of uncorrected and corrected measured parameter values ​​across four different tools over a 30-day period. Plot line 183A depicts the standard deviation of the uncorrected measured parameter values ​​across the four tools over a 30-day period. Plot line 183B depicts the standard deviation of the corrected measured parameter values ​​across the four tools over a 30-day period. Figure 3D As shown in Figure 2, the standard deviation of the measurement parameter of interest across all tools is reduced by a factor of approximately 3.5 by implementing the offset parameter values ​​determined according to the method described herein. Thus, it is clearly shown that the impact of systematic differences across a population of metrology tools on measurement accuracy can be reduced.

[0081] It should be appreciated that the various steps described herein can be implemented by a single computer system 170 or, alternatively, multiple computer systems 170. Furthermore, different subsystems of the system 100 (e.g., the spectroscopic ellipsometer 101) can include computer systems suitable for implementing at least a portion of the steps described herein. Therefore, the above description should not be construed as limiting the present invention, but is merely illustrative. Furthermore, the computing system 170 can be configured to perform any other steps of any method embodiment described herein.

[0082] Computing system 170 may include, but is not limited to, a personal computer system, a mainframe computer system, a workstation, a graphics computer, a parallel processor, or any other device known in the art. In general, the term "computing system" may be broadly defined to encompass any device having one or more processors that execute instructions from a memory medium. In general, computing system 170 may be integrated with a measurement system (e.g., measurement system 100) or, alternatively, may be separate from any measurement system. In this regard, computing system 170 may be remotely located and receive measurement data and user input 117 from any measurement source and user input source, respectively.

[0083] Program instructions 174 implementing methods, such as those described herein, may be transmitted via a transmission medium such as a wire, cable, or wireless transmission link. The memory 172 storing program instructions 174 may include computer-readable media such as read-only memory, random access memory, magnetic or optical disks, or tape.

[0084] Additionally, the computer system 170 may be communicatively coupled to the metrology tool or user input source 116 in any manner known in the art.

[0085] Computing system 170 can be configured to receive and / or acquire data or information from user input source 116 and metrology system subsystems (e.g., spectrometer 104, illuminator 102, and the like) via a transmission medium, which can include wired and / or wireless components. In this manner, the transmission medium can serve as a data link between computer system 170, user input source 116, and the metrology system (e.g., metrology system 100). Furthermore, computing system 170 can be configured to receive measurement data via a storage medium (i.e., memory). For example, spectral results obtained using the spectrometer of ellipsometer 101 can be stored in a permanent or semi-permanent memory device (not shown). In this regard, spectral results can be input from an external system. Furthermore, computer system 170 can send data to the external system via the transmission medium.

[0086] Figure 2 The embodiment of the offset calibration server 170 illustrated in may be further configured as described herein. Additionally, the server 170 may be configured to perform any other blocks of any method embodiment described herein.

[0087] In general, any number of parameters of interest may be selected and provide a basis for offset value calibration. Exemplary parameters of interest include geometric parameters (e.g., shape parameters such as critical dimension (CD), sidewall angle (SWA), height (H), etc.), composition, film thickness, bandgap, electrical properties, lithography focus, lithography dose, overlay, and other process parameters (e.g., resist state, partial pressure, temperature, focus model).

[0088] Figure 4 A method 200 for calibrating offset values ​​for group matching in at least one novel aspect is described. The method 200 is suitable for use by an offset calibration server (e.g., Figure 2 170) is implemented as described in the offset calibration server 170. In one aspect, it should be recognized that the data processing blocks of method 200 can be implemented via pre-programmed algorithms executed by one or more processors of computing system 170 or any other general-purpose computing system. It should be recognized that the specific structural aspects of system 170 are not intended to be limiting, but should be interpreted as being illustrative only.

[0089] In block 201, a plurality of measurements of a parameter of interest characterizing one or more structures disposed on a plurality of inline production wafers are received. Each of the plurality of inline production wafers is measured at a same process step of a semiconductor manufacturing process flow. The plurality of measurements of the parameter of interest are associated with measurements of each of the plurality of wafers by two or more metrology systems of a metrology system cluster.

[0090] In block 202 , a first measurement deviation associated with a metrology system of a population of metrology systems is determined relative to an average measurement value across each of one or more metrology systems used to measure a first inline production wafer of a plurality of inline production wafers.

[0091] In block 203 , an updated offset value for a metrology system of the metrology system population is determined based at least in part on the first measured deviation.

[0092] In block 204 , a correction value for the measurement of the parameter of interest by the metrology system is estimated based on the updated offset value.

[0093] In an optional block (not shown), the updated offset value is stored in a memory of the computing system (eg, memory 172 of computing system 170 or an external memory).

[0094] Although the methods discussed herein are explained with reference to metrology systems such as metrology system 100, any metrology system configured to illuminate and detect radiation reflected, transmitted, or diffracted from a sample, including optical and X-ray based metrology systems, can be used to implement the exemplary methods described herein. Exemplary systems include angle-resolving reflectometers, scatterometers, reflectometers, ellipsometers, spectroscopic reflectometers or ellipsometers, beam profile reflectometers, multi-wavelength two-dimensional beam profile reflectometers, multi-wavelength two-dimensional beam profile ellipsometers, rotating compensator spectroscopic ellipsometers, and the like. By way of non-limiting example, an ellipsometer can include a single rotating compensator, multiple rotating compensators, a rotating polarizer, a rotating analyzer, a modulating element, multiple modulating elements, or no modulating element.

[0095] It should be noted that the output from the metrology system can be configured in such a way that the metrology system uses more than one technology.In fact, the application can be configured to employ any combination of available metrology subsystems within a single tool or across many different tools.

[0096] Systems implementing the methods described herein can also be configured in many different ways. For example, various wavelengths (including visible light, ultraviolet light, infrared light, and X-rays), angles of incidence, polarization states, and coherence states can be considered. In another example, the system can include any of a number of different light sources (e.g., directly coupled light sources, laser-continuous plasma light sources, etc.). In another example, the system can include elements for conditioning the light directed to or collected from the sample (e.g., apodizers, filters, etc.).

[0097] In the field of semiconductor metrology, a metrology system may include an illumination system that illuminates a target, a collection system that captures relevant information provided by the interaction (or lack of interaction) of the illumination system with the target, device, or feature, and a processing system that analyzes the collected information using one or more algorithms. Metrology tools can be used to measure structural and material properties associated with various semiconductor manufacturing processes (e.g., material composition, dimensional properties of structures and films (e.g., film thickness and / or critical dimensions of structures), overlay, etc.). These measurements are used to facilitate process control and / or throughput efficiency in semiconductor die manufacturing.

[0098] The metrology system may include one or more hardware configurations that can be used in conjunction with specific embodiments of the present invention to, for example, measure various semiconductor structure and material properties described above. Examples of such hardware configurations include, but are not limited to, each of the following: a spectroscopic ellipsometer (SE), an SE with multiple illumination angles, an SE that measures Mueller matrix elements (e.g., using a rotational compensator), a single wavelength ellipsometer, a beam profile ellipsometer (angle-resolved ellipsometer), a beam profile reflectometer (angle-resolved reflectometer), a broadband reflectance spectrometer (spectral reflectometer), a single wavelength reflectometer, an angle-resolved reflectometer, an imaging system, and a scatterometer (e.g., a spot analyzer).

[0099] Hardware configurations can be separated into discrete operating systems. Alternatively, one or more hardware configurations can be combined into a single tool. An example of combining multiple hardware configurations into a single tool is described in U.S. Patent No. 7,933,026 (the entire contents of which are incorporated herein by reference for all purposes). In many cases, multiple metrology tools are used to measure single or multiple metrology targets. This is described, for example, in U.S. Patent No. 7,478,019 to Zangooie et al., the entire contents of which are incorporated herein by reference for all purposes.

[0100] As used herein, the term "critical dimension" includes any critical dimension of a structure (e.g., bottom critical dimension, middle critical dimension, top critical dimension, sidewall angle, grating height, etc.), any critical dimension between any two or more structures (e.g., distance between two structures), displacement between two or more structures (e.g., overlay displacement between overlapping grating structures, etc.), and dispersion property values ​​for materials in a structure or portion of a structure. Structures may include three-dimensional structures, patterned structures, overlapping structures, and the like.

[0101] As described herein, the term "critical dimension application" or "critical dimension measurement application" includes any critical dimension measurement.

[0102] As described herein, the term "metrology system" encompasses any measurement system used, at least in part, to characterize any aspect of a sample, including systems that may be referred to as "inspection" systems. Such technical terms do not limit the scope of the term "metrology system" as described herein. Furthermore, the metrology system 100 can be configured to measure patterned wafers and / or unpatterned wafers. The metrology system can be configured as an LED inspection tool, an edge inspection tool, a backside inspection tool, a macro inspection tool, or a multi-mode inspection tool (involving data from one or more platforms simultaneously), as well as any other metrology or inspection tool that benefits from calibration of system parameters based on critical dimension data.

[0103] Various embodiments of semiconductor processing systems (e.g., metrology systems or photolithography systems) that can be used to process samples are described herein. The term "sample" is used herein to refer to one or more sites on a wafer, a reticle, or any other sample that can be processed (e.g., printed or inspected for defects) by means known in the art. In some examples, a sample comprises a single site with one or more measurement targets, whose simultaneous combined measurements are considered a single sample measurement or reference measurement. In some other examples, a sample is a collection of sites, where the measurement data associated with the collective measurement site is a statistical collection of data associated with each of a plurality of sites. Furthermore, each of these plurality of sites may include one or more measurement targets associated with a sample or reference measurement.

[0104] As used herein, the term "wafer" generally refers to a substrate formed of semiconductor or non-semiconductor materials. Examples include, but are not limited to, single crystal silicon, gallium arsenide, and indium phosphide. Such substrates are commonly found and / or processed in semiconductor manufacturing facilities. In some cases, a wafer may comprise only a substrate (i.e., a bare wafer). Alternatively, a wafer may comprise one or more layers of different materials formed on a substrate. The one or more layers formed on a wafer may be "patterned" or "unpatterned." For example, a wafer may comprise multiple dies having repeatable pattern features.

[0105] A "reticle" can be a reticle at any stage of the reticle manufacturing process or a finished reticle that may or may not be released for use in a semiconductor manufacturing facility. A reticle or "mask" is generally defined as a substantially transparent substrate having substantially opaque areas formed thereon and configured in a pattern. The substrate may comprise, for example, a glass material such as amorphous SiO2. The reticle may be placed over a resist-covered wafer during the exposure step of the photolithography process so that the pattern on the reticle can be transferred to the resist.

[0106] The one or more layers formed on a wafer may be patterned or unpatterned. For example, a wafer may include multiple dies, each having repeatable pattern features. The formation and processing of such material layers may ultimately result in a completed device. Many different types of devices may be formed on a wafer, and the term "wafer" as used herein is intended to encompass a wafer having any type of device fabricated thereon known in the art.

[0107] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on a computer-readable medium or transmitted by one or more instructions or program codes on a computer-readable medium. Computer-readable media include both computer storage media and communication media, including any media that facilitates the transfer of a computer program from one location to another. Storage media may be any available media that can be accessed by a general-purpose or special-purpose computer. For example, but not limited to, such computer-readable media may include RAM, ROM, EEPROM, CD-ROM, or other optical disk storage, magnetic disk storage, or other magnetic storage devices, or any other media that can be used to carry or store desired program code components in the form of instructions or data structures and that can be accessed by a general-purpose or special-purpose computer or a general-purpose or special-purpose processor. In addition, any connection may be appropriately referred to as a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (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 typically reproduce data magnetically, while discs use lasers to reproduce data optically. Combinations of the above should be included within the scope of computer-readable media.

[0108] Although certain specific embodiments have been described above for guidance purposes, the teachings of this patent invention have general applicability and are not limited to the specific embodiments described above. Therefore, various modifications, adaptations, and combinations of the various features of the described embodiments may be practiced without departing from the scope of the invention as set forth in the claims.

Claims

1. A method comprising: receiving a plurality of measurements of a parameter of interest characterizing one or more structures disposed on a plurality of inline production wafers, wherein each of the plurality of inline production wafers is measured at a same process step of a semiconductor manufacturing process flow, wherein the plurality of measurements of the parameter of interest are associated with measurements of each of the plurality of wafers by two or more metrology systems of a metrology system cluster, wherein current values ​​of the measurements of the parameter of interest by a metrology system of the metrology system cluster are based on current offset values ​​corresponding to the metrology systems; determining a first measurement deviation associated with the metrology system of the population of metrology systems relative to an average measured value of the parameter of interest across each of the two or more metrology systems used to measure a first inline production wafer of the plurality of inline production wafers; determining an updated offset value for the metrology system of the population of metrology systems based at least in part on the first measured deviation; and A correction value for the measurement of the parameter of interest by the metrology system is estimated based on the updated offset value and the current value of the measurement of the parameter of interest by the metrology system.

2. The method according to claim 1, further comprising: determining a second measurement deviation associated with the metrology system of the population of metrology systems relative to an average measurement value across each of two or more metrology systems used to measure a second inline production wafer of the plurality of inline production wafers; and An average of the measured deviations associated with the metrology system is determined based at least in part on the first measured deviation and the second measured deviation, wherein the updated offset value is based on the average of the measured deviations. The method according to claim 2 , wherein the average value of the measured deviations is determined as a mean or a median.

4. The method of claim 1 , wherein the estimate of the corrected value of the measurement of the parameter of interest by the metrology system is determined by adding a correction term to the measurement of the parameter of interest by the metrology system, wherein the correction term is the product of the updated offset value and a scaling factor. The method of claim 4 , wherein the scaling factor has a positive value less than or equal to 1.

6. The method according to claim 1, further comprising: The measured value of the parameter of interest associated with the measurement of the plurality of inline production wafers by the first metrology system of the metrology system cluster is adjusted based on an elapsed time between the measurement of the inline production wafer by the first and second metrology systems of the metrology system cluster.

7. The method according to claim 1, further comprising: The measured value of the parameter of interest associated with the measurement of the inline production wafer by the first metrology system of the metrology system cluster is adjusted based on a duration over which the measurement of the inline production wafer of the plurality of inline production wafers is performed by the first and second metrology systems of the metrology system cluster.

8. The method according to claim 1, further comprising: comparing the updated offset value of the metering system of the metering system group with an upper predetermined threshold and a lower predetermined threshold; If the updated offset value exceeds the upper predetermined threshold, then replacing the updated offset value by the upper predetermined threshold; and If the updated offset value is less than the lower predetermined threshold, the updated offset value is replaced by the lower predetermined threshold.

9. The method according to claim 1, further comprising: determining a difference between the updated offset value of the metrology system of the group of metrology systems and a current offset value of the metrology system; If the difference exceeds an upper predetermined threshold, replacing the updated offset value by the upper predetermined threshold; and If the difference is less than a lower predetermined threshold, the updated offset value is replaced by the lower predetermined threshold.

10. A system comprising: Multiple measurement systems, each including: an illumination source configured to provide an amount of illumination radiation to one or more structures disposed on an inline production wafer; a detector configured to receive an amount of collected radiation from the one or more structures in response to the amount of illuminating radiation and to generate a measurement signal indicative of the collected radiation; and One or more computing systems configured to: receiving a plurality of measurements from the plurality of measurement systems, wherein each of the plurality of measurements is a value of a parameter of interest characterizing the one or more structures disposed on each of a plurality of inline production wafers, wherein each of the plurality of inline production wafers is measured in a same process step of a semiconductor manufacturing process flow, wherein the plurality of measurements of the parameter of interest are associated with measurements of each of the plurality of inline production wafers by two or more measurement systems of the plurality of measurement systems, wherein a current value of the measurement of the parameter of interest by a metrology system of the cluster of metrology systems is based on a current offset value corresponding to the metrology system; determining a first measurement deviation associated with the measurement system of the plurality of measurement systems relative to an average measured value of the parameter of interest across each of the two or more measurement systems used to measure a first inline production wafer of the plurality of inline production wafers; determining an updated offset value for the measurement system of the plurality of measurement systems based at least in part on the first measured deviation; and A correction value for the measurement of the parameter of interest by the measurement system is estimated based on the updated offset value and the current value of the measurement of the parameter of interest by the metrology system.

11. The system of claim 10, wherein the one or more computing systems are further configured to: determining a second measurement deviation associated with a measurement system of the plurality of measurement systems relative to an average measurement value across each of two or more measurement systems used to measure a second inline production wafer of the plurality of inline production wafers; and An average of the measured deviations associated with the measurement system is determined based at least in part on the first measured deviation and the second measured deviation, wherein the updated offset value is based on the average of the measured deviations.

12. The system of claim 11, wherein the average of the measured deviations is determined as a mean or a median.

13. The system of claim 10 , wherein the estimate of the corrected value of the measurement of the parameter of interest by the measurement system is determined by adding a correction term to the measured value of the parameter of interest by the measurement system, wherein the correction term is the product of the updated offset value and a scaling factor. The system of claim 13 , wherein the scaling factor has a positive value less than or equal to 1.

15. The system of claim 10, wherein the one or more computing systems are further configured to: The measured value of the parameter of interest associated with the measurement of the plurality of inline production wafers by the first measurement system of the plurality of measurement systems is adjusted based on an elapsed time between measurements of the inline production wafer by a first measurement system and a second measurement system of the plurality of measurement systems.

16. The system of claim 10, wherein the one or more computing systems are further configured to: The measured value of the parameter of interest associated with the measurement of the inline production wafer by the first measurement system of the plurality of measurement systems is adjusted based on a duration over which the measurement of the inline production wafer of the plurality of inline production wafers is performed by a first measurement system and a second measurement system of the plurality of measurement systems.

17. The system of claim 10, the computing system further configured to: comparing the updated offset value of the measurement system of the plurality of measurement systems with an upper predetermined threshold and a lower predetermined threshold; If the updated offset value exceeds the upper predetermined threshold, then replacing the updated offset value by the upper predetermined threshold; and If the updated offset value is less than the lower predetermined threshold, the updated offset value is replaced by the lower predetermined threshold.

18. The system of claim 10, the computing system further configured to: determining a difference between the updated offset value of the measurement system of the plurality of measurement systems and a current offset value of the measurement system; If the difference exceeds an upper predetermined threshold, replacing the updated offset value by the upper predetermined threshold; and If the difference is less than a lower predetermined threshold, the updated offset value is replaced by the lower predetermined threshold.

19. An offset calibration tool comprising: one or more processors of a computing system; and A non-transitory computer-readable medium storing computer-readable instructions that, when executed by the one or more processors, cause the computing system to: receiving a plurality of measurements of a parameter of interest characterizing one or more structures disposed on a plurality of inline production wafers, wherein each of the plurality of inline production wafers is measured at a same process step of a semiconductor manufacturing process flow, wherein the plurality of measurements of the parameter of interest are associated with measurements of each of the plurality of wafers by two or more metrology systems of a metrology system cluster, wherein current values ​​of the measurements of the parameter of interest by a metrology system of the metrology system cluster are based on current offset values ​​corresponding to the metrology systems; determining a first measurement deviation associated with the metrology system of the population of metrology systems relative to an average measured value of the parameter of interest across each of the two or more metrology systems used to measure a first inline production wafer of the plurality of inline production wafers; determining an updated offset value for the metrology system of the population of metrology systems based at least in part on the first measured deviation; and A correction value for the measurement of the parameter of interest by the metrology system is estimated based on the updated offset value and the current value of the measurement of the parameter of interest by the metrology system.

20. The offset calibration tool of claim 19, the computer readable instructions, when executed by the one or more processors of the computing system, cause the computing system to: determining a second measurement deviation associated with the metrology system of the population of metrology systems relative to an average measurement value across each of two or more metrology systems used to measure a second inline production wafer of the plurality of inline production wafers; and An average of the measured deviations associated with the metrology system is determined based at least in part on the first measured deviation and the second measured deviation, wherein the updated offset value is based on the average of the measured deviations.

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