Radiant energy – Calibration or standardization methods
Reexamination Certificate
2003-05-19
2004-08-03
Nguyen, Kiet T. (Department: 2881)
Radiant energy
Calibration or standardization methods
C250S310000
Reexamination Certificate
active
06770868
ABSTRACT:
FIELD
This invention relates to the field of instrumentation. More particularly, this invention relates to improved data output from an electron microscope.
BACKGROUND
In the integrated circuit industry, electron microscopes are central to microstructural analysis of integrated circuit components. The quality of the finished integrated circuit is highly dependent on the measurement and control of an integrated circuit's critical dimensions. Thus, it is very important to ensure that the critical dimension measurements received from the electron microscope are precise and accurate.
Typically, in critical dimension analysis of an integrated circuit component the electron microscope measures the apparent width of a structure when determining its dimensions. The apparent width of the structure is compared to critical dimension specifications in order to determine the compliance of the integrated circuit component.
Unfortunately, there seem to be disadvantages to using the typical apparatus and method, as the apparent width of a structure as reported by the measurement tool is often different from the actual width of the structure. In addition, the discrepancy between the actual width and the apparent width of the structure seems to fluctuate from sample to sample, and even from day to day. Thus, the integrity of the data derived from such measurements is often called into question, and is difficult to rely on.
In an effort to overcome this problem, some have used a calibration piece having a structure with a known size. The calibration piece is loaded into the measurement tool and measured at regular intervals, such as once each day. The difference between the apparent width and the actual width of the structure on the calibration piece is used as a correction factor for other measurements. Unfortunately, even this procedure tends to not have the desired accuracy in all situations.
Similarly, calibration pieces have been used that are optimized for viewing on an electron microscope, such as tin-on-gold resolution standards. These are used to verify the proper functioning of the electron microscope, and to measure the inherent resolution of the electron microscope. Unfortunately, because the interaction between the electron beam and the calibration piece is very different on such standards in comparison with the interaction between the electron beam and the semiconductor samples to be measured, the data produced is unfortunately of limited use in calibrating the scanning electron microscope for use as a measurement tool.
What is needed, therefore, is a system to improve the precision and accuracy of measurement data obtained from an electron microscope during critical dimension review of an integrated circuit component.
SUMMARY
The above and other needs are met by a system for determining an actual measurement of physical properties of a structure on a sample using a measurement tool with a calibration standard having measurement sites. A first site on the calibration standard with a first known metric is measured with the measurement tool to produce a first measurement. A calibration factor for the measurement tool is computed by comparing the first measurement to the first known metric. The structure on the sample is then measured using the measurement tool to produce a precursor measurement. This precursor measurement is adjusted with the calibration factor to produce an intermediate measurement. Then the intermediate measurement is adjusted with the sample composition data to produce the actual measurement.
Thus, rather than naively processing the scan data from the measurement tool to produce a measurement result, a model is preferably applied of both (1) how the electron optics perform, including their deviations from ideality, and (2) how the incident electrons interact with the structure on the sample to produce secondary and backscattered electrons. The properties of the electron optical system are preferably derived from both an analytical model of the optical system and from the measurement data taken on the calibration standard. The actual physical properties of the sample to be measured are then preferably determined using an analytical model of the interaction of the incident beam with the sample and the properties of the electron optical system as determined above. The physical properties are preferably determined by iteratively changing some of the sample parameters that are input to the sample interaction model, such as, but not limited to, feature width, height, sidewall angle, and degree of crystallinity, while other sample parameters are preferably kept constant, such as, but not limited to sample material, etc., to produce an analytically derived profile that most faithfully reproduces the empirically observed profile from the sample measurement. In this sense, the present system preferably goes beyond merely determining a correction factor to be applied to the measurement.
In this manner the system described herein provides improved measurement data by correcting the apparent width of a structure by both a calibration factor, which accounts for any drift in the properties of the measurement tool, and by sample structural and composition data, which accounts for measurement differences due to different materials and structures being measured. By calibrating the measurement tool in this manner, the precision and accuracy of the measurement tool is improved. The calibration standard is preferably of a similar composition of the structure to be measured, allowing for correct measurements of structures consisting of a wide range of materials.
Most preferably, the first site is a previously measured site. Preferably, a newly measured site on the calibration standard with a second known metric is also measured with the measurement tool to produce a second measurement. In this embodiment, the second measurement is also compared to the second known metric, and this information is also used in the computation of the calibration factor.
In various preferred embodiments, the measurement tool is preferably an electron microscope, and most preferably a scanning electron microscope.
Thus, rather than merely producing and using a single calibration factor, one or more properties of the electron optical system are preferably determined, which may include incident spot size, collection angles for secondary and backscattered electrons, depth of focus, etc. These properties are preferably used as the inputs to the optical system model used in the sample measurement. Determining these properties from the calibration sample measurement preferably involves the use of known properties of the sample, such as material or nominal feature dimensions, and the use of the sample interaction model described above.
One purpose of using multiple calibration sites is to preferably distinguish between variations in the calibration scan data, which variation can arise from three different sources, being: 1) variation in the measurement tool over time, 2) variation in the properties of one measurement site to another, and 3) variation due to modification of a single measurement site due to interaction with the measurement tool. The source of the variation is preferably determined by using the measurement results from a single calibration standard, as measured at multiple sites on the calibration standard, and the calibration data gathered from previous readings of calibration standards.
This information can be used to simultaneously determine, for example, that the width of a feature is systematically increased by one nanometer each time it is measured, that the size of the irradiated spot has decreased by a tenth of a nanometer since the last calibration, and that the two added measurement sites on the calibration standard deviate from the nominal size by 0.2 and −0.1 nanometers respectively. The determination of each of these example determinations is subject to some statistical uncertainty, which can be determined from the data.
The calibration factor is preferably computed by averag
Bevis Christopher F.
Clapper David E.
Luedeka Neely & Graham P.C.
Nguyen Kiet T.
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