Abstract:
A method and system for analyzing a substrate including the step of scanning the substrate to produce an intensity signal which represents the topography of the wafer to a first order. Other contributions to the signal intensity may be chemical composition and electrical state of the scanned features on the substrate. The scanned signal is compared and correlated to a reference signal to assess the substrate. The present invention is also directed to a method of manufacturing a wafer using the method and system and improving the manufacturing quality of product.

Description:
FIELD OF THE INVENTION 
     The present invention relates generally to scanning electron microscopes and, more particularly, to a scanning electronic microscope processor for analyzing semiconductor devices and a method of manufacturing an integrated circuit. 
     BACKGROUND OF THE INVENTION 
     A large amount of activity in the microelectronics industry is directed toward developing methodologies for testing wafers during the manufacturing process. Typically, scanning electron microscopes (SEM) have been used in semiconductor manufacturing processes. Although the SEM is useful for providing some information regarding a semiconductor device that is scanned, it can be difficult for an operator to detect errors by simply viewing the waveform from the SEM. Usually, an operator operates a SEM in an automatic mode to measure critical line width. The measurement is derived from the intensity waveform produced by the SEM. The SEM is not utilized to extract processing variables from the topography of the wafer. The shape of the measured object is typically not considered. 
     In addition, cross-sections of wafers are performed to assess the quality of a wafer. Although this process may be useful, the process is destructive and time consuming. As a result, a small number of wafers are selected for testing. An alternative approach is to perform electrical tests at the end of wafer processing to determine if deficiencies exist and assess the quality of the semiconductor devices formed on the wafer. Although deficiencies may be found, the defects are not detected until the end of wafer processing. As a result, problems in the manufacturing process or with the equipment used during manufacturing may not be detected. Numerous defective wafers may be produced before problems with the manufacturing or measurement process can be corrected. 
     SUMMARY OF THE INVENTION 
     The present invention provides a method and system for analyzing the intensity profiles of a wafer including the step of scanning the wafer to produce a scanned signal. The scanned signal is preprocessed and compared to a reference signal to assess the wafer. The present invention is also directed to a method of manufacturing a wafer using the above method and system. 
     It is to be understood that both the foregoing general description and the following detailed description are exemplary, but are not restrictive, of the invention. 
    
    
     BRIEF DESCRIPTION OF THE DRAWING 
     The invention is best understood from the following detailed description when read in connection with the accompanying drawing. It is emphasized that, according to common practice in the semiconductor industry, the various features of the drawing are not to scale. On the contrary, the dimensions of the various features are arbitrarily expanded or reduced for clarity. Included in the drawing are the following figures: 
     FIG. 1 is a block diagram of scanning electron microscope system  100  according to the present invention; 
     FIGS. 2-5 are flow chart diagrams for illustrating the operation of the scanning electron microscope system  100  shown in FIG. 1; 
     FIGS. 6-22 are graphs illustrating the operation of the scanning electron microscope system  100 ; and 
     FIG. 23 is a SEM picture of a metal line on a wafer illustrating an alternative embodiment. 
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Overview 
     The present invention is directed to a scanning electron microscope system that measures and analyzes the surface topology of a wafer during the manufacturing process. In other words, the present invention analyzes the shape of the scanned features. The surface topology is measured using a scanning electron microscope which produces intensity values in an array, an intensity profile. The intensity profile may then be processed using signal processing techniques and compared to standard waveforms from, for example, a standardized wafer which has been processed in the same manner. The standard waveforms are waveforms representing known shapes of scanned features. Differences and errors in the wafer are manifested in the measured topology and may be detected by the comparison. Errors in the measurement, i.e. focus and sharpness, by the SEM may also be determined. If the measured intensity topology can not be matched to the standard waveforms, it may be stored for further analysis. As a result, process monitoring may be improved and fatal errors in the wafers may be detected before further processing. Further, the above process may be implemented without adding additional steps to the manufacturing process because scanning electron microscopes are already used during processing. 
     Description of the Exemplary Embodiments 
     Referring now to the drawing, wherein like reference numerals refer to like elements throughout, FIG. 1 is a scanning electron microscope (SEM) system  100 . The SEM system  100  includes a scanning electron microscope (SEM)  150  for scanning a wafer  120  or a substrate having a surface feature and producing a wafer waveform signal y i (t). An exemplary wafer waveform signal y i (t) for a resist line is shown in FIG.  6 . The SEM  150  is, for example, Model 8820 available from Hitachi, 3100 North 1 st  Street, San Jose, Calif. 95134 USA. The SEM  150  is coupled to a processor  110 . 
     The processor  110  receives the wafer waveform signal y i (t) and detects errors and deficiencies in the wafer  120  by analyzing the wafer waveform signal y i (t). In addition, the processor  110  may detect deviations in the manufacturing process such as variations between tools. This process may be performed in-line during the manufacturing process. “In-line during the manufacturing process” means during the process of forming circuitry on the wafer  120 . Consequently, process errors and degraded quality in, for example, the lithography and etching processes may be detected before manufacture of the devices is completed. Measurement errors, such as charging, may also be detected. Measurement errors can cause unnecessary reworks or scrap. 
     In this way, adjustments may be made in the manufacturing line to correct, for example, tool drift and tool-to-tool matching for SEMs, steppers, and etchers. This allows problems such as SEM charging, stepper out of focus, and over etch errors to be detected and corrected. Further, defective wafers may be detected and removed prior to further processing. In addition, wafer characterization may be performed to determine profile degradation across a wafer. As a result, the cost of the manufacturing process may be decreased while increasing the quality of the wafers  120  produced. 
     The SEM system  100  also includes a database  125  for storing reference data. The SEM system  100  may also include a tool or tools  130  that may be automatically or manually adjusted in response to the analysis performed by the SEM system  100 . The components shown in FIG. 1 may be combined into one or more components and may be implemented in hardware or software. The operation of SEM system  100  is described below with reference to FIGS. 2-5. In addition, the process shown in FIGS. 2-5 is illustrated using the example shown in FIGS. 6-22. 
     At step  200 , shown in FIG. 2, the SEM  150  acquires the wafer waveform signal y i (t). An exemplary wafer waveform signal y i (t) for a charged resist line is shown in FIG.  7 . FIG. 8 is a diagram corresponding to a portion of the waveform shown in FIG.  7 . At step  205 , the processor  110  generates a processed waveform signal p 22 (t) from the wafer waveform signal y i (t) by implementing an auto-correlation operation. 
     Step  205  is described in greater detail below with reference to FIG.  3 . At step  300 , the processor  110  processes the wafer waveform signal y i (t) using, for example, equation (1) below to produce a converted waveform signal Y i (jw). 
     
       
           F[y   i ( t )]= Y   i ( jw )  (1) 
       
     
     F[ ] denotes any Fourier Transform. Equation (1) implements, for example, a Fast Fourier Transform (FFT). FIG. 9 is an exemplary converted waveform Y i (jw) for the wafer waveform signal y i (t) shown in FIG.  8 . At step  305  the converted waveform signal Y i (jw) is filtered using a low pass filter as is shown in equation (2) below to produce a filtered waveform signal Y f (jw). 
     
       
         Φ[ Y   i ( jw )]= Y   f ( jw )  (2) 
       
     
     For example, the filter implemented by equation (2) may pass a quarter (¼) or less of the components of the converted waveform signal Y i (jw). The high frequency components are removed to reduce the systematic noise in the wafer waveform signal y i (t). Other filters may be used. FIG. 10 is the filtered waveform signal Y f (jw) corresponding to the converted waveform signal Y i (jw) shown in FIG.  9 . 
     At step  310  an auto-correlation operation is performed to produce a wafer auto-correlation signal R 22 (jw) from the filtered waveform signal Y f (jw) using equation (3) below. 
     
       
           R   22 ( jw )= Y   f ( jw ) Y   f *( jw )  (3) 
       
     
     In equation (3), the “*” indicates a complex conjugate. An exemplary wafer auto-correlation signal R 22 (jw) is shown in FIG.  11 . At step  315 , an inverse transform is performed to produce a transformed signal r 22 (t) using equation (4) below.                  r   22          (   t   )       =         F     -   1            [       R   22          (     j                 w     )       ]       N             (   4   )                                
     In equation (4), N is the total number of pixels that would be used for display i ng the waveform or the total number of input quantities (samples). For example, an exemplary transformed signal r 22 (t) is shown in FIG.  12 . 
     At step  320  the maximum value MAX 22  of the transformed signal r 22 (t) is determined at a phase or lag equal to zero (0) as is shown in equation (5) below. 
     
       
         MAX 22   =r   22 ( t )( t =0)  (5) 
       
     
     At step  325 , the transformed signal r 22 (t) is normalized according to equation (6) below to produce the auto-correlation waveform signal p 22 (t).                  P   22          (   t   )       =         r   22          (   t   )         Max   22               (   6   )                                
     An exemplary auto-correlation signal p 22 (t) is shown in FIG. 13 where the transformed signal r 22 (t) is normalized. The result is a function of probability densities for a lag of t. This is shown for completeness, but is not necessary for further processing. The maximum value MAX 22  is, for example, 332.164. 
     Returning to FIG. 2, at step  210  the wafer waveform signal y i (t) is compared to a standard waveform signal x i (t) using the auto-correlation signal p 22 (t). The standard waveform signal x i (t) is used as a bench mark to determine whether other wafers  120  have deficiencies and satisfy quality standards and to detect variations in the manufacturing process. The standard waveform signal x i (t) is derived from a scan of a standard wafer (not shown). The standard wafer is a wafer that satisfies the desired manufacturing criteria for producing the wafer  120 . In other words, the wafer  120  is acceptable if the wafer  120  is within a specified range of the standard wafer. The process for deriving the standard auto-correlation signal p 11  is the same as the process for producing the wafer auto-correlation signal p 22  except the process is performed on a scanned signal rather than standard wafer. The process for deriving the standard auto-correlation signal p 11  is shown in FIG. 4. A description of FIG. 4 is omitted for the sake of brevity. 
     FIGS. 14-19 are exemplary waveforms corresponding to the process steps shown in FIG.  4 . FIG. 14 is an exemplary standard waveform signal x i (t) for a resist line on the standard wafer. The resist line is not charged. FIG. 15 is an exemplary converted waveform X i (jw) for the wafer waveform signal x i (t) shown in FIG.  14 . FIG. 16 is the filtered waveform signal X f (jw) corresponding to the converted waveform signal X i (jw) shown in FIG.  15 . FIG. 17 is the wafer auto-correlation signal R 11 (jw) for the filtered waveform signal X f (jw) shown in FIG.  16 . The transformed signal r 11 (t) of the auto-correlation signal R 11 (jw) is shown in FIG.  18 . Finally, FIG. 19 shows the standard auto-correlation waveform signal p 11 (t) corresponding to the transformed signal r 11 (t) shown in FIG.  18 . The maximum value MAX 11  used to produce the standard waveform signal p 11 (t) shown in FIG. 12 is 551.405. 
     Returning to FIG. 2, at step  215 , the processor  110  determines whether the comparison waveform signal p 12  is within a predetermined range. Step  215  is described in greater detail in FIG.  5 . At step  500 , a cross-correlation signal R 12 (jw) is generated from the wafer converted waveform signal y f (jw) and the standard converted waveform signal x f (jw), calculated in earlier steps, using equation (6) below. 
     
       
           R   12   =X   f ( jw ) Y   f *( jw )  (6) 
       
     
     “*” indicates the complex conjugate. FIG. 20 is an exemplary cross-correlation signal R 12 (jw) of the processed waveform signal p 22  and the standard waveform signal p 11 . 
     At step  505 , the cross-correlation signal R 12 (jw) is converted to the time domain using equation (7) below to produce the unnormalized cross-correlation signal r 12 (t).                  r   12          (   t   )       =         F     -   1            [       R   12          (     j                 w     )       ]       N             (   7   )                                
     N is the same value for both signals. FIG. 21 is the unnormalized cross-correlation signal r 12 (t) corresponding to the cross-correlation signal R 12 (jw) shown in FIG.  20 . 
     At step  510 , the unnormalized cross-correlation signal r 12 (t) is normalized according to equation (8) below.                  p   12          (   t   )       =         r   12          (   t   )         Max   func               (   8   )                                
     The value Max func  is defined in equation (9) below.                Max     func                  =     {           Max   11               if                   Max   22       &lt;       Max   11                   and                 to                                          compare                 shape                 and                 amplitude               Max   22               if                   Max   11       &lt;       Max     22                     and                 to                                          compare                 shape                 and                 amplitude             or                             Max   22     ·     Max   11               if                 only                 to                 compare                 shape                     (   9   )                                
     FIG. 22 shows the normalized signal p 12 (t) normalized using a Max func  of 551.405 (Max 11 ). Amplitude is not considered in this case. The shape of the waveforms are only compared if there are scaling errors present, such as those caused by a degradation in the SEM  150  or when the SEM  150  is not matched to the SEM that measured the standardized wafer. At step  515 , the maximum value p max  of the comparison waveform signal p 12 (t) is determined. The maximum value p max  for the normalized signal p 12 (t) shown in FIG. 22 is 0.767. Phase errors (picture offsets) which may occur in the SEM  150  are eliminated. As a result, the wafer waveform signal y i (t) may later be compared to a standard waveform signal x i (t) without this possible source of error. 
     At step  520 , the processor  110  determines whether the comparison waveform signal p 12 (t) is within specification. For example, if the absolute value of the maximum value p max  is greater than 0.9 and less than 1 (0.90&lt;) |p max |&lt;1), the wafer  120  is considered acceptable. In a production line arrangement, one or more wafers  120  may be tested to determine if an entire lot is acceptable. Otherwise, the lot may be rejected. Typically, acceptable wafers  120  have been found to have a maximum value p max  between 0.95 and 1 (0.95&lt;|p max |&lt;1). 
     Returning to FIG. 2, at step  220 , the lot or tools  130  are indicated as passing if the maximum value p max  is within the specified range. Otherwise, at step  230 , the wafer waveform signal y i (t) is compared to data stored in database  125  using the same methods described earlier to determine what error has occurred and how the error may be corrected. The database  125  includes data and/or instructions for modifying the production process to eliminate the errors. At step  235 , the processor  110  provides instructions to the tools  130 , equipment, etc. using the data from the database  125  to correct the errors. In addition, the lot of wafers is disposed of is appropriate. Alternatively, the information may be provided to an operator via a user interface (not shown). The operator makes adjustments to the manufacturing process or measurement in response to the information. 
     At step  240 , if there is no corresponding instructions for correcting the error, the error and the associated data are stored in the database  125  for future analysis and comparison. For example, the wafer waveform signal y i (t), the comparison waveform signal p 12 , and/or any of the other signals produced or used during the analysis of the wafer  120  may be stored. 
     Although the above exemplary embodiment utilized a one dimensional waveform, a multi-dimensional process may be used or multiple waveforms may be compared. In addition, regions of the intensity topology may be averaged, summed, or in general signal processed, and compared. Further, the orientation of a feature may be analyzed. In this case, the wafer may be rejected if the feature does not have the proper orientation. The particular comparison that is chosen is dependent upon the particular feature to be analyzed. 
     For example, consider FIG. 23 which is a picture of a metal line  710  formed on a substrate. One process for determining the roughness of the edge  700  of the line  710  is to compare multiple average intensities in the y-direction. An average intensity is derived by averaging intensity values of a segment  720  extending in the x-direction. If the edge  700  varies, i.e. has bulges or inflections, the average intensity varies. Variations in the edge  700  may be detected and compared to an expected or standard edge profile. The average intensities may be considered to form a waveform signal y i (t) extending in the y-direction. This waveform signal y i (t) may be processed using the process shown in FIG.  2 . 
     The above invention is not limited to comparing the intensity profile in the x or y-directions or in straight lines. The selected comparison may include comparisons which traverse the wafer in a manner suitable to assess the particular feature. For example, the pattern may be selected to correspond to the edge of a feature which is not solely oriented in the x and y-directions. 
     Although the invention has been described with reference to exemplary embodiments, it is not limited to those embodiments. Rather, the appended claims should be construed to include other variants and embodiments of the invention which may be made by those skilled in the art without departing from the true spirit and scope of the present invention.