Data processing: measuring – calibrating – or testing – Measurement system – Dimensional determination
Reexamination Certificate
2001-09-28
2004-03-30
Barlow, John (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system
Dimensional determination
C702S166000
Reexamination Certificate
active
06714892
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates generally to the field of metrology and more particularly to the measurement of very small features on the surface of a microelectronics substrate.
Quality control for the production of microelectronic devices, such as integrated circuit features formed on semiconductor substrate wafers, often depends upon the accurate measurement of the dimensions of various features formed over the substrate surface. Accurate measurement of the topography of the surface of the substrate facilitates not only a pass/fail inspection routine, but also provides a basis for feedback control of upstream processes and feed forward control of downstream processes.
The desire for precise measurement of the surface topography of a microelectronics device must be tempered by the cost and time involved in obtaining such information. At one extreme, destructive examination of a semi-conductor wafer may reveal precise dimensional information at the expense of a useable wafer and many hours of delay time.
The size of semiconductor devices continues to decrease and the metrology used to measure such devices must respond accordingly. There are many types of both optical and electron based metrology tools available, such as scanning electron microscope (SEM), focused ion beam microscope, focused x-ray microscope and focused optical microscopes including near-field scanning optical microscopy. As the size of devices has decreased, optical imaging metrology for critical dimensions has been abandoned. The scanning electron microscope currently plays a major role for metrology in the semiconductor manufacturing industry. Modem 157 nm lithography technology pushes the limits of top down critical dimension scanning electron microscopes (CDSEM). The technology critical dimension nodes of 120 nm and 100 nm lithography will require more precision and accuracy than the SEM appears to be able to provide while utilizing current technologies.
The critical dimension scanning electron microscope utilizes algorithms based upon the intensity of line scan profiles of images to extract the apparent width of features. While the CDSEM offers quick and repeatable measurements of the intensity profiles of features, it remains difficult to establish the exact morphology of the feature from a top down plan view perspective. This is, in part, due to the extensive electron beam interactions within the specimen. That is, the CDSEM will measure the intensity of the secondary electron signal from pixel to pixel across the sample surface. If a particular feature is flat, e.g. the top of a feature or the bottom of a trench, then the secondary electron signal will be constant as long as the surface material remains constant. When the interaction volume that intersects with the surface area of the material changes, the intensity of the secondary electrons that escape from the surface will also change. This topographic effect results in edge effects that blur the image at locations of morphology change. This blurring produces an uncertainty in the critical dimension measurement. While the shape of the intensity profiles respond to drastic changes in morphology, more subtle changes may be lost within the intensity profiles. When intensity profiles are averaged down a plurality of scan lines, additional feature information may be lost.
A CDSEM is used to develop a top down image as shown in
FIGS. 1A and 1B
. These images represent an intensity of secondary electrons across the plane of the substrate surface I(x, y).
FIG. 1A
is an SEM image for a semiconductor wafer I-line metal photoresist having a normal morphology, and
FIG. 1B
is an SEM image for a similar photoresist having an abnormal morphology. An amplitude modulated waveform P(x) may be constructed as a function of this topographic information by averaging I(x, y) over N number of lines using Equation 1:
P
(
x
)
=
∑
y
=
1
N
I
(
x
,
y
)
N
(
1
)
FIGS. 2A and 2B
illustrate the function P(x) as an amplitude modulated waveform representing the average intensity developed from the normal and abnormal photoresist lines of
FIGS. 1A and 1B
respectively. Known algorithms may be applied to these waveforms to identify critical dimensions, such as the width of the line at 50% wall height, as identified by dashed lines in
FIGS. 2A and 2B
. Many processes in the semiconductor industry have relied upon this single parameter characterization of the SEM data. Note, however, that single parameter characterization of the data may fail to discern a difference between normal and abnormal morphologies, for example, when both structures have the same critical dimension of 0.684 &ugr;m as illustrated in
FIGS. 2A and 2B
.
Multiple parameter characterization (MPC) refers to the use of functions or groups of measurements where a singular discrete measurement can no longer effectively represent the data. MPC is being developed in many different forms for application to scanning electron microscope data in an attempt to address the shortcomings of single parameter characterization, as described above. The shape and scale of the amplitude modulated waveform P(x) can be described through multiple parameters.
FIG. 3
illustrates an amplitude modulated waveform P(x) divided into two portions. The distance between the left and right regions of the waveform in solid lines defines a width measurement W and the distance between the left and right regions of the waveform in dashed lines defines a line space measurement S. At discrete intervals along the height of these regions a measurement may be taken for the width and line space, then plotted as a function of height, as shown in FIG.
4
. Curve W
N
-S
N
represents the MPC of the normal morphology of
FIGS. 1A and 2A
. Curve W
A
-S
A
represents the MPC of the abnormal morphology of
FIGS. 1B and 2B
. Here the difference between the normal and abnormal morphologies is readily apparent. Other derived MPC values may be used to illustrate deviations from normal profiles, such as roughness measured as the 3-sigma value of the difference between the maximum and minimum critical dimension values along a line profile. Roughness may be useful for illustrating the abnormal photoresist profile known as scumming, where the resist removal fails to clear the resist between developed photoresist lines.
A database of MPC curves such as shown in
FIG. 4
may be established for a particular device/process. Preset process margin templates may be established to define acceptable ranges for the MPC values for the evaluation of subsequently manufactured devices. While this quality control procedure is much improved when compared to single parameter evaluation of inspection data, it suffers from the shortcomings of any database driven system. Such shortcomings include a heavy reliance on numeric processing and a resultant lack of speed and a lack of flexibility that requires the establishment of an entirely new database each time a change is made to the process/device.
Another technique for nondestructively examining microelectronics devices is scanning probe microscopy (SPM). SPM includes various techniques of metrology wherein a probe tip is used to study the surface topography or properties of the surface of a substrate. One such device is the atomic force microscope (AFM). Another such device is the stylus nanoprofilometer (SNP) which has emerged recently as a potential tool for critical dimension metrology for both masks and 157 nm integrated circuit technology. An SNP probe tip makes contact with the substrate with only a small force at only discrete pixel points, thus minimizing the probe wear problems associated with atomic force microscopy, where a probe tip continuously touches, or nearly touches, the surface between points. The SNP probe tip is then retracted from the surface a distance sufficient to clear vertical features, moved horizontally a preset distance, and then moved back toward the surface. The vertical resolution is currently 0.3 nm or less. The distance between pixels dete
Houge Erik Cho
McIntosh John Martin
Plew Larry E.
Agere Systems Inc.
Barlow John
Beusse Brownlee Wolter Mora & Maire P.A.
Maire David G.
Washburn Douglas N
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