Classifications

• • G—PHYSICS
  • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
  • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
  • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
  • G03F7/70—Microphotolithographic exposure; Apparatus therefor
  • G03F7/70483—Information management; Active and passive control; Testing; Wafer monitoring, e.g. pattern monitoring
• • G—PHYSICS
  • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
  • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
  • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
  • G03F7/70—Microphotolithographic exposure; Apparatus therefor
  • G03F7/70483—Information management; Active and passive control; Testing; Wafer monitoring, e.g. pattern monitoring
  • G03F7/70491—Information management, e.g. software; Active and passive control, e.g. details of controlling exposure processes or exposure tool monitoring processes
  • G03F7/705—Modelling or simulating from physical phenomena up to complete wafer processes or whole workflow in wafer productions
• • G—PHYSICS
  • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
  • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
  • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
  • G03F7/70—Microphotolithographic exposure; Apparatus therefor
  • G03F7/70483—Information management; Active and passive control; Testing; Wafer monitoring, e.g. pattern monitoring
  • G03F7/70491—Information management, e.g. software; Active and passive control, e.g. details of controlling exposure processes or exposure tool monitoring processes
  • G03F7/70516—Calibration of components of the microlithographic apparatus, e.g. light sources, addressable masks or detectors
• • G—PHYSICS
  • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
  • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
  • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
  • G03F7/70—Microphotolithographic exposure; Apparatus therefor
  • G03F7/70483—Information management; Active and passive control; Testing; Wafer monitoring, e.g. pattern monitoring
  • G03F7/70605—Workpiece metrology
  • G03F7/70616—Monitoring the printed patterns
  • G03F7/70633—Overlay, i.e. relative alignment between patterns printed by separate exposures in different layers, or in the same layer in multiple exposures or stitching

Definitions

• the present invention relates generally to overlay measurement techniques, which are used in semiconductor manufacturing processes. More specifically, the present invention relates to analyzing overlay marks (also called overlay targets) used for measuring alignment ereor between different layers or different patterns on the same layer of a semiconductor wafer film stack.
• overlay marks also called overlay targets
• overlay or misregistration measurement In the process of manufacturing semiconductor integrated circuits, one of the critical metrology steps is overlay or misregistration measurement.
• the overlay measurement ideally quantifies the lateral displacement between two layers of the integrated circuit from their nominal, perfect alignment.
• the lateral displacement is called overlay enor or misregistration (herein refened to as overlay).
• overlay metrology is typically performed by a specialized optical instrument, overlay metrology tool, on test structures located either in the so-called scribe lines on the wafer or within the area of the integrated circuit itself. These test structures are called overlay targets.
• the overlay metrology tool reports, as the result of each measurement, two numbers, representing the overlay in two orthogonal directions in the plane of the wafer, labeled x and y.
• the overlay is measured on several locations on a wafer, and on several wafers of each processing lot.
• the results are used primarily for two purposes.
• One purpose of the overlay measurements is to facilitate decisions as to whether to pass or fail a given wafer lot (known as lot dispositioning), based on the overlay values or their combinations.
• Another purpose is to facilitate calculating what part of these errors was due to the non-ideal alignment or other functioning of the lithography stepper or scanner, and feeding this information back to the stepper or scanner to effect corrections (known as process control).
• This conection is determined using a stepper analysis program, based on stepper models.
• the reported overlay results may not be reliable in certain situations. That is, the measured overlay measurements may be affected by other factors besides misalignment of the target.
• the overlay measurement may be affected by background noise associated with the measured target.
• background may cause an overlay enor to be measured when the target is not misaligned.
• Systematic errors, such as asymmetry may also cause the measured overlay enor to be inaccurate.
• a target which has significant asymmetries, combined with a significant true overlay enor may result in zero measured overlay enor.
• the asymmetry enor may go unnoticed and steps to conect process problems leading to such asymmetry may go uninitiated and adversely affect yield.
• the present invention provides apparatus and methods for obtaining and analyzing various unique metrics or "target diagnostics" from one or more semiconductor overlay targets.
• an overlay target is measured to obtain two specific types of target diagnostic information, systematic enor metrics and random noise metrics.
• the systematic error metrics generally quantify asymmetries of the overlay target, while the random noise metrics quantify and/or qualify the spatial noise that is proximate to or associated with the overlay target.
• image information or intensity signals of an overlay target are provided or obtained from an overlay measurement tool.
• the overlay enor for the overlay target is generally obtained by analyzing the image information or the intensity signal(s) of the overlay target to determine overlay errors between two different layers of the overlay target.
• a systematic enor metric is also obtained from the overlay target by analyzing the image information or the intensity signal(s) of the overlay target to thereby quantify asymmetries of the target.
• the systematic enor metric may quantify the discrepancies between the sizes of two target areas which are designed to have a same size.
• the systematic error metric is obtained by obtaining an asymmetry value of portions of the overlay target which are designed to be symmetrical.
• a noise metric is further obtained from the overlay target by applying a statistical model to the image information or the intensity signal(s) of the overlay target. Noise metrics generally characterize the spatial noise associated with the overlay target, such as a grainy background.
• the unique target diagnostics information may then be used in various overlay and/or stepper analysis procedures, hi one embodiment, overlay errors, a plurality of systematic metrics, and a plurality of noise metrics for each overlay enor are obtained for a plurality of targets.
• a quantitative metric on a quality of the overlay enor may then be determined based on the systematic metrics and/or the noise metrics for such overlay enor.
• the quantitative metric is a confidence level for each overlay enor.
• Each overlay error and its quantitative metrics may then be analyzed to determine a characteristic associated with the overlay targets.
• confidence level information which is based on the systematic and/or noise metric may be used to identify "flyers" or unreliable overlay metrology results. For example, if the confidence level falls below a predetermined threshold, such as 60%, the associated overlay measurement may be identified as a flyer. In addition to determining whether to identify specific overlay measurements as flyers, the confidence levels may also be used to determine whether a different overlay measurement setup or recipe is to be used for the current overlay target or whether a alternative overlay target is to be used in place of the current overlay target.
• determining whether the overlay enor value is a flyer may include the following specific implementation steps: (1) determining a confidence level based on the systematic metric and the noise metric and (2) when the confidence level is out of predefined specification, defining the overlay enor value as a flyer. In a further aspect, analysis of the overlay enor value is halted when the target is defined as a flyer. In another aspect, operations (1) and (2) are repeated for an alternative target when an alternative target exists for the cunent overlay target and the current overlay target is defined as a flyer. In another implementation, operations (1) and (2) are repeated for a next target when a next target exists and there is no alternative target or the current overlay target is not defined as a flyer.
• operations (1) and (2) are repeated for a plurality of targets from a plurality of semiconductor wafers.
• the plurality of semiconductor wafers include a plurality of reference wafer lots.
• Statistical information regarding the target diagnostic information of the overlay targets is collected from the reference wafer lots.
• Operations (1) and (2) are then repeated for the overlay targets of a cunent wafer lot to thereafter analyze the target diagnostic data to determine whether the current wafer lot fails or passes based on the previously obtained statistical information. It may then be detennined whether a decision can be made as to whether a current wafer lot passes or fails based on the confidence levels conesponding to the current wafer lot. When it is detennined that a decision can be made, it is detennined whether the cunent wafer lot passes based on comparison of the cunent target diagnostic information from the current wafer lot to the statistical information from the reference wafer lots.
• the target diagnostic information is used to improve on the operation of a stepper tool that is used to place overlay targets and associated design structures on a plurality of wafers or wafer lots.
• a stepper analysis procedure includes determining whether the stepper tool which is used to place the overlay target, as well as the design structures, is misaligned.
• a stepper conection is calculated based on the overlay data, systematic enor metric, and noise metric. The stepper correction, of course, is then used to correct the current stepper misalignment.
• determining the stepper correction includes the following specific implementation steps: (1) obtaining an overlay enor value, a systematic error metric, and a noise metric for a plurality of overlay targets of a cunent wafer; (2) conecting the overlay error values by the systematic enor metrics; (3) weighting each overlay enor value based on a confidence level of the each overlay enor; and (4) determining the stepper conection based on the conected and weighted overlay error values. The stepper tool is then adjusted by the stepper conection.
• overlay enors may be analyzed along with the systematic enor metric and/or noise metric to correct for a DI/FI (development inspection/final inspection) bias
• the overlay error is obtained from a target at the DI stage (i.e., after photo-resist development and prior to a processing step, such as an ineversible etch process, being performed on the existing photo-resist pattern).
• a DI/FI bias associated with the overlay target is then predicted, where the DI/FI bias prediction is based on the systematic enor metric.
• the overlay error is adjusted by the predicted DIFI bias.
• the DI/FI bias value is predicted by obtaining the overlay error value and the systematic enor metric when the overlay target is in the re-workable DI stage and predicting the DI/FI bias value based on the systematic error metric.
• the overlay enor may then be adjusted according to such bias.
• the target diagnostic information may be used to determine whether a process excursion has occurred, for example, for a current wafer lot.
• Target diagnostic information is obtained for a plurality of targets on a plurality of product wafers. Determining whether a process excursion has occurred may be accomplished by (1) monitoring changes related to the systematic enor metrics or the noise metrics obtained from overlay targets on the plurality of product wafers and (2) when a significant change in the monitored metrics occurs, determining that a process excursion has occurred for the wafer or wafer lot associated with such significant change.
• a confidence level is determined for each overlay enor value based on the systematic and/or noise metrics, and the changes that are monitored include changes to the confidence level.
• the invention pertains to off-line root-cause-analysis.
• the application compares target metrics across field, across wafer, lot to lot, layer to layer, device to device, etc. to statistical variations of historical production lot-run and tool-qualification data.
• the system uses these comparisons as well as context information to identify the root cause of various identified behaviors.
• the statistical data, images, and/or line-scans of the images from which the data is taken can be made available for review and analysis.
• the invention pertains to a computer system for obtaining and analyzing various unique metrics or "target diagnostics" from one or more semiconductor overlay targets.
• the computer system has one or more processors and one or more memory. At least one of the processors and memory are adapted to perform one or more of the above described method operations.
• Figure 1A is a diagrammatic top view of an example target structure.
• Figure IB is a diagrammatic top view of an example target structure that is asymmetrical.
• Figure 1C is a diagrammatic top view of the target of Figure 1A with a noisy background.
• Figure 2 is a flowchart illustrating a procedure for obtaining target diagnostics, including systematic and noise metrics, in accordance with one embodiment of the present invention.
• Figure 3 is a flowchart illustrating a procedure for identifying flyer target data in accordance with one embodiment of the present invention.
• Figure 4 is a flowchart illustrating a procedure for determining the confidence level of a particular overlay target's data in accordance with a first embodiment of the present invention.
• Figure 5 is a flowchart illustrating a procedure for determining the confidence level of a particular overlay target's data in accordance with a second embodiment of the present invention.
• Figure 6 is a flowchart illustrating a procedure for determining the confidence level of a particular overlay target's data in accordance with a third embodiment of the present invention.
• Figure 7 is a flowchart illustrating a procedure for determining the confidence level of a particular overlay target's data in accordance with a fourth embodiment of the present invention.
• Figure 8 is a flowchart illustrating a lot disposition procedure in accordance with one embodiment of the present invention.
• Figure 9 is a flowchart illustrating a procedure for improving stepper correction in accordance with one embodiment of the present invention.
• Figure 10 is a flowchart illustrating the operation of Figure 10 of weighting the overlay measurements based on the diagnostic metrics in accordance with one embodiment of the present invention.
• Figure 11 is a flowchart illustrating a procedure for minimizing DF/FI bias in accordance with one embodiment of the present invention.
• Figure 12 is a flowchart illustrating a procedure for experimentally determining the weight values of Figure 11 in accordance with one embodiment of the present invention.
• Figure 13 A is a flowchart illustrating a procedure for determining a process excursion and its root cause in accordance with a first embodiment of the present invention.
• Figure 13B is a flowchart illustrating a procedure for determining a process excursion and its root cause in accordance with a second embodiment of the present invention.
• FIG 14 is a simplified diagram of an overlay measurement system, in accordance with one embodiment of the present invention.
• FIG. 1A is a diagrammatic top view of an example target structure 100. As shown, the target 100 is formed from an inner box 104 and an outer box 102. The imier box 104 is typically formed in a different layer than the outer box 102. For example, at the Dl-stage the inner box 104 may be a resist pattern defining the Via2-layer, while outer box 102 is formed of features in a metal 2 layer.
• the inner box 104 is formed from a plurality of segments 104a through 104d which are arranged in a square pattern, while the outer box is formed from a plurality of segments 102a through 102d formed in a square pattern.
• the overlay enor is typically determined by finding a center of each box and comparing the two centers to obtain an overlay enor difference. This difference is typically expressed in x and y coordinates although the difference may be expressed in other forms, such as a vector.
• the inner box and outer box share a same center 106, indicating that there is no overlay enor between the inner and outer box. hi this case, the overlay enor would be 0,0.
• Figure IB is a diagrammatic top view of an example target structure 150 that is asymmetrical.
• the inner box 104 has a segment 104e that differs in width from the remaining segments 104b through 104d.
• this asymmetrical target 150 results in no overlay enor because the inner box 104 and outer box 102 share a same center 106, the target 150 is defective because of the asymmetry.
• This type of defect is refened to as a systematic enor.
• Systematic enors can be characterized per target, and they are often of systematic nature across the wafer. Systematic enors are typically due to target asymmetry, caused by process effects such as CMP polish, metal sputtering, or photoresist effects.
• Figure 1C is a diagrammatic top view of the target 100 of Figure 1A with a noisy background 160.
• the background noise is in the form of grains.
• the noise may be caused by any source of spatial noise in the image.
• the noise 160 may cause the apparent center of either the inner box 104 or the outer box 102 to shift in direction 167, for example.
• the resulting overlay enor may be caused by random noise instead of an actual overlay enor or a systematic error.
• These types of enors are refened to as random enors.
• the random enors are due to spatial noise caused by process effects such as graininess. These enors are characterized by the fact that their effect on targets across the wafer and even on a single target are statistical in nature.
• FIG. 2 is a flowchart illustrating a procedure 200 for obtaining target diagnostic metrics, including systematic and noise metrics, in accordance with one embodiment of the present invention.
• an overlay target is provided in operation 202.
• the overlay error is then obtained from the target in operation 204. That is, image information is obtained from the target and analyzed to obtain the overlay error, as described further below.
• the intensity signal or the image information may be analyzed to obtain the overlay error.
• the difference between a center for the inner box 104 and the outer box 102 is measured, and such difference is defined as the overlay enor.
• a systematic metric such as an asymmetry metric, is then obtained by comparing selective portions of the target to each other in operation 206.
• An asymmetry metric may be obtained using any suitable technique, hi one embodiment, portions of the target which are designed to be symmetrical with respect to each other are compared.
• the systematic enor metric is obtained through a comparison of the nominally symmetrical signal forms from the different parts of the target, e.g. comparison between the signal from the left outer bar and right outer bar.
• the overlay tool may have some asymmetry in its optics, it is advisable to measure the Asymmetry Metrics at two orientations of the wafer: 0° and 180°.
• the final systematic or asymmetry metric may be calculated as:
• Asymmetry(final) [Asy ⁇ nmetry(0 o )-Asymmetry(180°)]/2.
• the left inner bar 104e is compared to the right inner bar 104c to obtain an x-direction asymmetry metric for the inner part of the target.
• the left outer bar 102a may be compared with the right outer bar
• the top inner bar 104d may be compared to the bottom inner bar 104b to determine whether the target has a y-direction asymmetry metric.
• the outer top bar 102d may be compared with the outer bottom bar 102b to determine a y-direction asymmetry metric for the outer part of the target.
• These different x- and y-direction asymmetry metrics may then be combined into a final asymmetry metric.
• Specific techniques or algorithms for measuring the asymmetry of a target through comparison include Fourier-transform techniques, derivative (slope) techniques, overlap integral techniques, and center-of-gravity techniques.
• a random noise metric of the target is then obtained by applying a statistical model to the image information (or intensity signal) of the target in operation 208.
• the target diagnostic metrics or target diagnostics refer herein to one or more of the following metrics: the systematic metric, the random noise metric, or a combination of the two.
• An overlay and/or stepper analysis may then be performed based on the overlay metrology results and target diagnostic metrics in operation 210. The procedure then ends.
• the target diagnostics metrics may be used to analyze the overlay data to determine its accuracy and reliability. For instance, overlay data that contains a high noise metric value and/or a high asymmetry metric value may be identified as less reliable or unreliable and possibly thrown out from the overlay measurements that are collected from multiple targets prior to analysis of such overlay data. In a specific application, the target diagnostic metrics are used to determine a confidence level of the overlay enor. hi other applications, the overlay enor data may be weighted or qualified based on the noise and/or asymmetry metrics prior to processing of the overly data for various uses, such as determining a stepper conection, or determining whether a lot passes or fails a given specification.
• the target diagnostics data may be used to determine that a different overlay enor measurement setup (measurement type, measurement algorithm, etc.) or a different target is to be used when the target diagnostics metrics indicate that the current overlay data is unreliable.
• noise determination algorithms may be used: statistical algorithms, integrated noise algorithms, integrated derivative algorithms, signal-to-noise algorithms, or spectrum of noise algorithms.
• Target diagnostics may then be used to produce, in parallel with the overlay measurement described above, quantitative metrics on the quality of the measured overlay targets. These quantitative metrics may be used for any suitable purpose in relation to analysis of the overlay measurements, hi general, the target diagnostics are used together with the overlay measurements during overlay and stepper analysis procedures. Several example uses for the target diagnostics are described further below.
• overlay metrology occasionally produces an abnormally high measurement result, e.g. 500nm for a process where typical values are well below lOOnm. These results are called “flyers", and their removal from the data is important, as they corrupt the decisions that are based on the data set. Some of them may be removed by simple thresholding of the overlay value, but this reduces the confidence level of the decisions.
• the quality of the target is evaluated, and the targets are automatically labeled as flyers or unreliable targets when the quality or confidence level falls below a pre-set quantity. The decision may be done without regard to the actual overlay value of these targets.
• the data from the flyer targets may then be disregarded in the metrology process, and the flyer targets may also be automatically replaced by data from alternative targets and/or alternate metrology methods or algorithms.
• FIG. 3 is a flowchart illustrating a procedure 400 for identifying flyers within the target diagnostic data in accordance with one embodiment of the present invention.
• an image grab of a target is performed in operation 402.
• Overlay enor and target diagnostics metrics are then determined in operation 404. That is, an overlay error, a systematic metric, and a noise metric are determined as described above.
• the confidence level of the target diagnostic metrics is then determined in operation 406. It is then determined whether the confidence level is out of specification in operation 408.
• a stored selection variable is set "on” in operation 410. For instance, a user may have set the store variable to "on” so as to store images conesponding to measurements for which the target metrics are out of specification for later review and analysis. If the store selection variable is set "on”, an image may be stored in operation 411. Otherwise, storing of the image is skipped. Operations 410 and 411 are optional: and the image may be stored automatically without a user selecting whether to turn on or turn off such storing feature. The target is then identified and reported as a flyer in operation 412. It then may be optionally determined whether an alternative site exists in operation 414.
• the metrology recipe may include an alternative target site when the initial site proves to be out of specification.
• the alternative site is proximate to the out-of-spec or rejected site. If there is an alternative site, the overlay metrology tool then goes to the alternative site operation 426. The procedure 400 is then repeated in operation 402, where an image is grabbed of the alternative site.
• the overlay metrology of the current wafer is terminated, and overlay and/or stepper analysis may then be performed on the good target diagnostics metrics in operation 418 and the procedure ends. If there is a next site, the tool moves to the next site in operation 424. The procedure 400 is then repeated for the next target site in operation 402, where an image grab is performed on the next site. When the confidence level is not out of specification for the cunent target, the cunent target is determined to be good and the results are added to a overlay database in operation 420. The specification for flyer may also be recalculated based on the new target diagnostic data in operation 422. It is then determined whether there is a next target site in operation 416. If there is a next target, the procedure repeats for the next target. If there is not a next target, the procedure ends.
• the specification may be recalculated when it is determined that the confidence levels for several product wafers have drifted up to higher confidence levels or down to lower confidence levels.
• an initial specification may require that the confidence level be over 70%.
• the confidence level for hundreds of consecutive targets start reaching average values of over 90%, the confidence level requirement may be altered to 85%.
• the specification may be recalculated to be within 3 standard deviations of the mean target diagnostic metric value. That is, expectations regarding a targets quality may increase or decrease over time as new targets are designed and new processes emerge. Additionally, if several flyers are identified consecutively, the flyers may then be examined to determine a new specification or to adjust the process.
• FIG. 4 is a flowchart illustrating a procedure 500 for determining the confidence level of particular overlay data in accordance with a first embodiment of the present invention.
• a set of calibration wafers are run in operation 502.
• the weight values for the target diagnostic metric are estimated from the data in operation 504.
• the data is generally raw overlay and metrics values.
• the product wafers are then run in operation 506.
• a total target uncertainty (TTU) is then calculated for the current target in operation 508.
• TTU is defined as, for example, the target of Figures 1A ⁇ 1C:
• the units may be any unit of measurement, such as nm.
• the TTU value is determined, it is then determined whether the TTU is above a predetermined threshold in operation 510. If the TTU is not above the threshold, the target is determined to be good in operation 514. If the TTU is above the threshold, the target is defined as a flyer in operation 512. This procedure may then be repeated for each target by going to the next target in operation 516.
• FIG. 5 is a flowchart illustrating a procedure 600 for determining a confidence level in accordance with a second embodiment of the present invention.
• the operations 602-606 are similar to the operations 502-506 of Figure 4.
• a relative target uncertainty (RTU) value is calculated for the current target in operation 608.
• the confidence level result is relative to the overlay budget or some other variable, and translated to a relative notation, such as a %.
• RTU may be defined relative to the TTU value and a Reference Value as:
• the Reference Value is generally determined by the overlay budget or some other representative process value. After the RTU value is determined, it is then determined whether the RTU value is less than a predetermined threshold in operation 610. If the RTU is not less than the threshold, the target is good in operation 614. If the RTU is less than the threshold, the target is a flyer in operation 612. One then may then go to the next target in operation 616.
• FIG. 6 is a flowchart illustrating a procedure 700 for determining a confidence level in accordance with a third embodiment of the present invention.
• This third embodiment is similar to the RTU, but the result is relative to the stepper model residuals.
• the stepper model residuals are generally defined as the difference between the raw overlay data and the values predicted by the stepper model.
• Operations 702-706 are similar to the operations 502-506 of Figure 4. However, after a set of product wafers are run in operation 706, a stepper model and the residuals for a current wafer are calculated in operation 707. A model relative target uncertainty (MRTU) value is then calculated for the cunent target in operation 708 by:
• the target is good in operation 714. If the MRTU is less than the threshold, the target is a flyer in operation 712. One may then go to the next target in operation 718.
• FIG. 7 is a flowchart illustrating a procedure 800 for determining a confidence level with a fourth embodiment of the present invention, hi general terms, this technique is based on the relative accuracy of the cunent target metric with respect to calibration data. Calibration wafers (lot, set of lots) are run and means of the metrics are calculated. Then for the cunent run, the relative accuracy of the metric is calculated. And at the final step, the results are added to the calibration data and means are recalculated.
• a set of calibration wafers are run in operation 802, and the means of the metrics for the calibration wafers are then calculated in operation 803.
• the weights are then estimated based on the data in operation 804.
• a set of product wafers are then run in operation 806.
• a calibration relative confidence level (CRCL) value is then calculated for the current target in operation 808.
• the CRCL may be defined as for example, the target of Figures 1A-1C as:
• A,B...G are weights; the CunentAsymOutX and Y are the asymmetry between the pair of outer X bars (or boxes) and between the pair of outer Y bars (or boxes), respectively; CunentAsymlnnX and Y are the asymmetry between the pair of inner X bars (or boxes) and between the pair of inner Y bars (or boxes), respectively; and the Calibration values are the conesponding calibration values for the same.
• a default value for the weights equal to 1 may be initially used.
• the CRCL may be also defined as ,the target of Figures 1 A ⁇ 1C as
• the units of the values is [%]. The range of the value is from 0% to 100%.
• the default values for A,...,F are one's, and the default value for S is 3.
• the CunentAsymOutX and Y are the asymmetry between the pair of outer X bars (or boxes) and between the pair of outer Y bars (or boxes), respectively;
• CurrentAsymlnnX and Y are the asymmetry between the pair of inner X bars (or boxes) and between the pair of inner Y bars (or boxes), respectively.
• the CRCL After the CRCL is determined, it is then determined whether the CRCL value is less than a predetermined threshold in operation 810. If the CRCL value is not less than the threshold, the target is good in operation 814. The calibration values are also updated in operation 816. New values are added to the historical data (database) and then means, sigmas and cumulative distributions are recalculated on the data with new values. If the CRCL value is less than the threshold, the target is a flyer in operation 812. One may then go to the next target in operation 818 and repeat operations 808- 816. Increasing the Confidence of a Lot's Pass/Fail Decision
• Overlay metrology after the lithography step may be used for providing one of the indicators for passing or failing a wafer lot.
• a pass/fail decision may be done based on subjective judgment, often after additional overlay metrology.
• target diagnostics such as a systematic enor and/or noise metric from the overlay targets and by converting the results into confidence levels relating to each overlay result, a more intelligent, and possibly further automated, decision for pass/fail becomes possible.
• an automated decision process may take place, based on the specific confidence level results.
• Figure 8 is a flowchart illustrating a lot disposition procedure 900 in accordance with one embodiment of the present invention.
• each product wafer or product wafer lot may be rated as passing or failing based on this procedure.
• overlay measurements are performed for a particular product wafer lot in operation 902.
• the target diagnostic metrics e.g., systematic and noise metrics
• This procedure may include one of two loops: a wafer-level loop ("Wafer Auto") where flyer targets are identified and/or alternative sites measured (e.g., as described for Figure 3) or alternative measurement types or algorithms are performed in operation 910, and a lot-level loop (“Lot Auto") as illustrated by operation 912 for adding more wafers to the lot.
• the wafer-level loop may take place while a given wafer is being measured.
• the target diagnostics indicate in real-time whether the target is acceptable. If the target is not acceptable, a real-time decision may be made to measure an alternate target, which has been designated already in the recipe set-up phase.
• the data that results from measuring a given wafer is all good data (provided that the wafer contains a sufficient number of good targets).
• a flyer target may also simply be removed from the target diagnostic data for a particular wafer without measurement of an alternative target or implementation of an alternative measurement algorithm. The procedures described above for removing flyers from the target diagnostics data and using alternative targets may be implemented. In some cases, this wafer-level loop is not possible due to the constraints of the specific user, hi these cases, a lot-level strategy may be used, where an indication is given after each wafer or lot measurement on the quality of the measurement. This quality indication is again based on the confidence levels given by the target diagnostics.
• a decision is taken - either by the overlay tool, a supervisory system, or a user - whether to measure additional wafers of the same lot. All this may take place while the lot is still on the overlay metrology tool, thus avoiding unnecessary logistical overhead of unloading, storing, retrieving and reloading a lot.
• the lot-level loop and the wafer-level loop may be implemented together or alone. That is, the wafer-level loop may be implemented without the lot- level loop, and visa versa.
• the target diagnostics may then be analyzed to detennine overlay statistics and confidence levels in operation 906.
• the statistics may include any suitable overlay statistical data compiled from results of measuring overlay targets from multiple wafers or wafer lots. This statistical information may later be utilized to determine whether a particular wafer lot passes or fails.
• the statistical information includes a mean of the measured overlay enors, as well as a standard deviation, from a plurality of targets and product wafers.
• the statistical information may also include a maximum overlay enor value.
• the maximum overlay error may be determined directly from the overlay error data (by selecting the maximum measured overlay enor data point) or determined by extrapolating from the overlay enor data (e.g., by a polynomial curve fit to the measured overlay error data).
• the confidence levels may be determined in any suitable manner, for example, as described above.
• a decision may be made regarding a cunent lot's fail or pass status in operation 908. This determination is accomplished by analyzing the confidence levels. For instance, if the overlay enor data indicates that the lot passes but the confidence levels fall below a predetermined specification (e.g., 60%), steps may be taken to increase the confidence levels of the current overlay enor data. In the illustrated embodiment, when it is determined that a decision cannot be made as to the status of the cunent wafer lot (e.g., the confidence level is too low), in operation 912 more wafers are added to the lot on which overlay measurement are then performed (later in operations 902).
• a predetermined specification e.g. 60%
• the current lot passes, based on its overlay values, in operation 914. For instance, it is determined whether the current overlay enors for the cunent lot are within three standard deviations of the overlay enor mean determined from previous lot overlay data. In an alternative implementation, it is determined whether the cunent lot's overlay enor maximum exceeds the determined overlay enor maximum. If the cunent overlay error exceeds the maximum or is greater than three standard deviations from the overlay mean, it is determined that the current lot fails. Otherwise, it is determined that the cunent lot passes. If the cunent lot does not pass, it is reported as failing in operation 918. Otherwise, the current lot is reported as passing in operation 916.
• stepper corrections In conventional calculations of stepper corrections, all overlay values are treated equally.
• the confidence levels may be converted into weights, for weighing the influence of each overlay value in the stepper correction calculation process. In this way, overlay values whose quality is lower, have less of an influence on the final stepper conections, and in this way the confidence that the user can have on the calculated stepper conections will increase.
• FIG 9 is a flowchart illustrating a procedure 1000 for improving stepper conection in accordance with one embodiment of the present invention.
• overlay measurements and target diagnostic metrics are collected or provided from a wafer in operation 1002.
• the overlay measurements may then be conected by the asymmetry metrics in operation 1004. This is done in the cases, where it can be demonstrated that a conection based on the asymmetry metrics gives a truer overlay value, such as in conecting for DI/FI bias.
• Example techniques for conecting the DF/FI bias are further described below with respect to Figures 11 and 12.
• the overlay measurements are also weighted based on the confidence level or similar metrics in operation 1006.
• each overlay measurement is weighted based on a determined confidence level (e.g., as determined using any of the techniques described above). For instance, confidence levels between 50 and 60% are given a weight value of 0.2; confidence levels between 61 and 70% are given a weight of 0.4; etc.
• Function f can be either a continuous or discrete function.
• a stepper conection may then be detennined based on the weighted overlay measurements in operation 1008. The stepper conections are then used for process control including being passed on to the stepper, e.g., via a host computer or cell controller, where the stepper corrections may be implemented, in operation 1110. The procedure then ends.
• FIG 10 is a flowchart illustrating a calibration procedure for obtaining an estimate for the weights used in the operation 1006 of Figure 9.
• one or more targets are fonned, e.g., on one or more wafers, in a stepper operation 1101.
• the DI overlay values and target diagnostic metrics are then obtained from the target(s) in operation 1102.
• Confidence levels of the DI overlay values are then calculated, e.g., as described above, in operation 1106.
• an initial function f and a set of coefficients a ⁇ a n are determined in operation 1105. Weights are then calculated based on this initial function f, coefficients, and calculated confidence levels in operation 1107. The weights are then used to calculate weighted stepper conections in operation 1108.
• a process (such as an etch process) may be performed in operation 1103. This process may be performed in parallel to determining the weighted stepper conection.
• FI overlay values are then obtained from the targets post process in operation 1104.
• the FI overlay values and the weighted stepper corrections are then used to simulate overlay distribution at FI (A) in operation 1109.
• the overlay data at FI and the difference between the actual stepper settings in the lithography (from operation 1101) and the settings indicated by the weighted stepper corrections (from operation 1108) are used to simulate the change in overlay data at FI had the weighted stepper conections been implemented at the lithography stage.
• An overlay distribution (B) is also calculated based on the obtained FI overlay values in operation 1114.
• a and B are compared in operation 1108, and it is then determined whether A is better than B in operation 1113. In other words, it is determined whether the determined stepper conection will likely result in an improved overlay distribution, as compared with the current stepper settings and resulting distribution.
• the distribution may be evaluated using any suitable criteria. By way of examples, the evaluation may be based on Total Modeled Enor TME, maximum overlay, or maximum + 3 ⁇ overlay. If A is better than B, it is then determined whether the stepper conection is good enough in operation llll. In one example, the distributions of the simulated FI overlay is compared to the true FI overlay and to a criterion of "good" distribution. If the stepper correction needs to be improved or A is not better than B, the coefficients ai, a , ..., aw and/or the function is adjusted (if needed) to improve the distribution in operation 1112.
• any standard method for optimizing model weights such as linear least squares method may be used.
• the calibration method can be used both for an initial calibration for a new process, as well as periodic re- calibrations.
• the DI/FI Bias refers to the difference of overlay as measured on the same wafer and same target location in two instances of time during the process: The first time is the so-called DI (Develop Inspect or After Develop or Photo) overlay, the second is the so-called FI (Final Inspection or After Etch or Etch) overlay.
• DI Develop Inspect or After Develop or Photo
• FI Fluor Inspection or After Etch or Etch
• This difference is due to a distortion of the overlay mark, with the major contributions coming from process effects before and up to the lithography step. Since many of these process effects on the overlay targets manifest themselves as asymmetry, they can be characterized using the target diagnostics asymmetry metrics. These metrics can be correlated to the DI/FI Bias, and in this way used for predicting the DI/FI Bias and correcting for it.
• Finding the true overlay at the DI stage is preferable, since then the wafer may be easily reworked, e.g., by stripping and reapplying the photoresist.
• FIG 11 is a flowchart illustrating a procedure for conecting for DF/FI bias in accordance with one embodiment of the present invention.
• one or more targets are fonned by a stepper in operation 1202.
• Overlay measurements are then obtained after the resist has been exposed and developed (DI) in operation 1204.
• Target diagnostics are also obtained in operation 1206.
• x and y asymmetry values are obtained.
• a DI/FI bias is determined based on the target diagnostics and overlay metrics in operation 1208. For example, a formula calculating a conected overlay measurement may be in the form of:
• x and y are the DI overlay measurements and a x and a y are the measured x and y asymmetries, respectively.
• the weights w x and w y may be selected initially with default values, such as 1, or determined experimentally through a calibration procedure detailed below.
• the overlay values from the DF stage may then be corrected by such determined DF/FI bias in operation 1210.
• the conected overlay values may then be used for any suitable overlay analysis procedures, such as lot deposition and stepper conections as described herein.
• Figure 12 is a flowchart illustrating an example procedure for experimentally determining the weights w x and w y of Figure 11.
• one or more wafers are exposed and developed in track to form overlay targets in operation 1252.
• DI overlay values and target diagnostic metrics are then collected from the wafers in operation 1254.
• the DI/FI bias prediction is determined for each measurement location based on initial values for the weights (1260) in operation 1256.
• the initial weight values are determined in operation 1258.
• the corrected DI overlay values are calculated by conecting the initial DI overlay by the DI FI bias predictions in operation 1261 Meanwhile, the wafers have proceeded through the process step, e.g., an etching process, in operation 1262, and overlay values are then collected at the FI stage in operation 1264.
• the FI and corrected DI overlay values are compared in operation 1266 and it is determined whether the two values are close enough in operation 1268. For example, it is determined whether the difference between the two values is less than a predetermined difference value. Said in another way, it is determined whether the predicted DF/FI bias value matches the real DF/FI bias value.
• the DI/FI bias prediction model weights are accepted and used in further overlay measurements and the weight calibration procedure 1250 ends. If it is determined that the two sets of overlay values are not sufficiently close, the weights (1260) are adjusted in operation 1270 and a new set of calculations (operations 1256 and 1261) and comparison (operation 1266) are performed based on the adjusted weight values (1260).
• the flowchart of Figure 12 shows an iterative procedure for determining the weights, although any other commonly known method for determining the best solution for model coefficients may be used (e.g., linear least squares method).
• the calibration procedure may also be used both for determining the weights at the start of a new process, as well as for periodic re-calibrations of the weights.
• the metrics of target diagnostics may be used to monitor process changes. Reference levels may be set up, and excursions from these reference levels beyond a pre-set distance will trigger a warning or automated fault detection signal to the operator and/or host/APC (advanced process control) system. The values and locations of values beyond pre-set levels can be presented on a wafer map. Trends of the metrics may then be used by the APC system.
• Figure 13 A is a flowchart illustrating a procedure 1300 for determining a process excursion in accordance with a first embodiment of the present invention.
• target diagnostic metrics including asymmetry and noise metrics, are obtained from a number of targets in operation 1302. These targets may originate from different wafers.
• Statistics based on one or more of the target diagnostics metrics are then determined in operation 1304. For example, a systematic and/or noise metric mean and standard deviation may be determined for the targets fabricated so far. In another example, an average confidence level and standard deviation may be detennined.
• any of the metrics for a cunent wafer is above a predefined threshold based on the determined statistics in operation 306. For example, it is determined whether a particular lot's noise metric is more than 3 ⁇ above the average noise metric. Alternatively, it is determined whether the current systematic enor metric is significantly higher than (e.g., greater than 3 ⁇ ) the average systematic enor. In other examples, it is determined whether a cunent confidence levels are within statistical range of an average confidence level, h an alternative implementation, it is simply determined whether a metric or confidence level is above a predefined threshold without determining statistical information from a set of wafers. The threshold may be determined experimentally or theoretically.
• an alert may be generated regarding a process excursion in operation 1308.
• the excursion may have occurred for a single process for a single wafer or for a set of processes for an entire wafer or wafer lot. The process then ends or alternatively an automated recovery process is initiated.
• Figure 13B is a flowchart illustrating a procedure 1330 for determining a process excursion in accordance with a second embodiment of the present invention.
• target diagnostic metrics are determined from a wafer in operation 1332.
• the metrics are then plotted on a wafer map in operation 1334.
• a visual inspection of the wafer map is then performed in operation 1336. It is then manually determined whether an excursion has occurred in operation 1338. For instance, noise or systematic metric excursions for a particular wafer portion may be identified visually on such wafer map.
• wafer maps from a number of lots may be displayed side by side to identify a wafer having a deviant metric.
• confidence levels may be plotted in a wafer map and deviations may be conelated to a process excursion, hi general, any qualitative or quantitative change of the target diagnostic metric distribution on the wafer map If an excursion has occuned, an alert regarding the process excursion is generated in operation 1340 and the procedure then ends. Procedures for conecting the process excursion may then be implemented.
• context information (1305) is correlated with each target and its target diagnostic metrics.
• the context information may include any suitable information useful in determining root cause, such as process identity, lot identity, wafer identity, process tool operation settings, etc.
• the root cause of such excursion may then be determined based on the correlated context information (e.g., in operation 1310 and 1342). That is, it is determined which context information is associated with the excursion, and such context information is identified as the root cause.
• a particular process tool may be associated with the excursion and identified as a root cause.
• the target metrics are used to identify the subset of measurements which do not meet a pre-defined specification (e.g. measurements of poor or suspect quality).
• the metrology signal image, scan, etc.
• the metrology signal is stored and presented for further analysis: manual inspection, further signal processing, etc. From this information, further root cause analysis can occur.
• Figure 14 is a simplified diagram of an overlay measurement system or metrology tool 1420 that may be used to measure overlay in any of the marks described above via imaging.
• Imaging is a very developed technology with large user acceptance, and components that are readily available to the user. As is generally well known, imaging is an effective way to collect a large amount of information at any one time. That is, all points within the mark may be observed simultaneously. Furthermore, imaging allows a user to see what is actually being measured on the wafer. The dimensions of various components are exaggerated to better illustrate this embodiment.
• the overlay measurement system 1420 is ananged to determine overlay error, systematic metrics, and noise metrics via one or more overlay targets 1422 disposed on a wafer 1424.
• the overlay targets 1422 are positioned within the scribe lines of the wafer 1424.
• scribe lines are the areas of the wafer used for sawing and dicing the wafer into a plurality of dies. It should be noted, however, that this is not a limitation and that the position of the targets may vary according to the specific needs of each device design. For example, the designer of the semiconductor device may choose to insert overlay targets inside the area of the active devices.
• the overlay measurement system 1420 includes an optical assembly 1426 and a computer system 1428 having a processor and one or more memory devices.
• the optical assembly 1426 is generally ananged to capture the images of the overlay target 1422.
• the computer is generally ananged to calculate the relative displacement and target diagnostics of the elements of the overlay target from the captured images.
• the optical assembly 1426 includes a light source 1430 (e.g., incoherent or coherent, although incoherent is generally preferred) arranged to emit light 1432 along a first path 1434.
• the light 1432 is made incident on a first lens 1435, which focuses the light 1432 onto a fiber optic line 1436 configured to pass the light 1432 there through.
• a second lens 1438 which is arranged to image the end of the optical fiber 1436 to a suitable optical plane in the optical system, such as the entrance pupil of the objective lens 1444.
• the light 1432 then continues on its path until it reaches a beam splitter cube 1440, which is arranged to direct the light onto a path 1442.
• the light 1432 continuing along path 1442 is made incident on an objective lens 1444, which relays the light 1432 onto the wafer 1424.
• the light 1432 which reflects off of the wafer 1424, is then collected by the objective lens 1444.
• the reflected light 1432 that is collected by the objective lens 1444 generally contains an image of a portion of the wafer 1424, as for example, the image of the overlay target 1422.
• the objective lens 1444 manipulates the collected light in a manner that is optically reverse in relation to how the incident light was manipulated. That is, the objective lens 1444 re-images the light 1432 and directs the light 1432 towards the beam splitter cube 1440.
• the beam splitter cube 1440 is ananged to direct the light 1432 onto a path 1446.
• the light 1432 continuing on path 1446 is then collected by a tube lens 1450, which focuses the light 1432 onto a camera 1452 that records the image of the wafer 1424, and more particularly the image of the target 1422.
• the camera 1452 may be a charge couple device (CCD), a two-dimensional CCD, or linear CCD array.
• CCD charge couple device
• the camera 1452 transforms the recorded image into electrical signals, which are sent to the computer 1428.
• the computer 1428 After receiving the electrical signals, the computer 1428 performs analysis using algorithms that calculate the overlay enor and target diagnostics of the image as described above. Analysis algorithms for determining overlay enor are described in greater detail below.
• the system 1420 further includes a frame grabber 1454 that works with the computer 1428 and the camera 1452 to grab images from the wafer 1424.
• the frame grabber 1454 is shown as a separate component, it should be noted that the frame grabber 1454 may be part of the computer 1428 and/or part of the camera 1452.
• the function of the frame grabber 1454 is generally to convert the signals from camera 1452 into a form usable by the computer 1428.
• the overlay metrology event is divided into two functions - target acquisition and image grab. During target acquisition, the frame grabber 1454 and computer 1428 cooperate with a wafer stage 1456 to place the target in focus and to position the target as closes as possible to the center of the field of view (FOV) of the metrology tool.
• FOV field of view
• the frame grabber grabs a plurality of images (e.g., not the images used to measure overlay) and the stage moves the wafer between these grabs until the target is conectly positioned in the X, Y and Z directions.
• the X&Y directions generally correspond to the field of view (FOV) while the Z direction generally corresponds to the focus.
• the second of these two functions is implemented (e.g., image grab).
• the frame grabber 1454 makes a final grab or grabs so as to capture and store the conectly positioned target images, i.e., the images that are used to determine overlay and target diagnostics.
• Various algorithms may then be used to determine the registration enor between various layers of a semiconductor wafer. For example, a frequency domain based approach, a space domain based approach, Fourier transform algorithms, zero-crossing detection, conelation and cross-conelation algorithms and others may be used.
• Algorithms proposed for determining overlay and target diagnostic metrics, such as asymmetry, via the marks described herein can generally be divided into a few groups. For instance, one group may relate to phase retrieval based analysis. Phase retrieval based analysis, which is often refened to as frequency domain based approaches, typically involves creating one dimensional signals by collapsing each of the working zones by summing pixels along the lines of the periodic structure. Examples of phase retrieval algorithms that may be used are described in U.S. Patent No. 6,023,338 issued to Bareket, U.S. Patent Application No. 09/603,120 (Attorney Docket No. KLA1P026) filed on une 22, 2000, and U.S. Patent Application No. 09/654,318 (Attorney Docket No. KLA1P029) filed on September 1 , 2000, all of which are incorporated herein by reference.
• phase retrieval algorithm decomposes signals into a set of harmonics of the basic signal frequency. Quantitative comparison of different harmonics' amplitudes and phases provide important information concerning signals' symmetry and spectral content, h particular, the phase difference between the 1st and 2nd or higher harmonics of the same signal (calibrated with their amplitudes) measures the degree of the signal asymmetry.
• the major contributions to such asymmetry come from the optical misalignment and illumination asymmetry in the metrology tool (tool induced shifts), as well as process induced structural features (wafer induced shifts).
• Comparing this misregistration between the phases of the 1st and the 2nd harmonics for the signals acquired from different parts of the field of view on the same process layer may provide independent information about optical abenations of the metrology tool. Finally, comparing these misregistrations from measurements at a given orientation with those obtained after rotating the wafer 180 degrees allows separation of the tool induced and wafer induced shifts due to asymmetry.
• Wavelet analysis Yet another phase retrieval algorithm that may be used is Wavelet analysis.
• Wavelet analysis is somewhat similar to that described in the section above, however, now a dynamic window is moved across the one dimensional signal and the phase estimation is carried out in a more localized way. This is particularly of interest with use in the case of a chirped periodic structure.
• Another group may relate to intensity conelation based methods.
• This approach the centers of symmetry for each process layer is found separately by calculating the cross covariance of one signal with the reversed signal from the opposite part of the mark, from the same process layer. This technique is similar to techniques used today with regards to box in box targets.
• overlay measurement tool may be any of a number of suitable and known imaging or metrology tools arranged for resolving the critical aspects of overlay marks formed on the surface of the wafer.
• overlay measurement tool may be adapted for bright field imaging microscopy, darkfield imaging microscopy, full sky imaging microscopy, phase contrast microscopy, polarization contrast microscopy, and coherence probe microscopy. It is also contemplated that single and multiple image methods may be used in order to capture images of the target.
• CPM single grab coherence probe microscopy
• CPM single grab coherence probe microscopy
• AFM Atomic Force Microscope
• the system's configuration for practicing techniques of the present invention may employ one or more memories or memory modules configured to store data, program instructions for the general-purpose inspection operations and/or the inventive techniques described herein.
• the program instructions may control the operation of an operating system and/or one or more applications, for example.
• the memory or memories may also be configured to store images of targets, overlay enor values, target diagnostic metrics, and confidence levels, as well as values for particular operating parameters of the inspection system.

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