WO2019162203A1

WO2019162203A1 - Method for determining a corrected dimensional parameter value relating to a feature formed by a lithographic process and associated apparatuses

Info

Publication number: WO2019162203A1
Application number: PCT/EP2019/053797
Authority: WO
Inventors: Sander Frederik WUISTER; Thomas I. Wallow
Original assignee: Asml Netherlands B.V.
Priority date: 2018-02-22
Filing date: 2019-02-15
Publication date: 2019-08-29
Also published as: TW201945853A

Abstract

A method of determining a corrected dimensional parameter value relating to a feature formed by a lithographic process, the corrected dimensional parameter value being corrected for a measurement effect on the dimensional parameter, the method including: performing a measurement to obtain at least two measurement values for the dimensional parameter; determining the measurement effect from the at least two measurement values; and determining the corrected dimensional parameter value from the determined measurement effect.

Description

METHOD FOR DETERMINING A CORRECTED DIMENSIONAL PARAMETER VALUE RELATING TO A FEATURE FORMED BY A LITHOGRAPHIC PROCESS AND

ASSOCIATED APPARATUSES

Cross-reference to related applications

[0001] This application claims priority of US application 62/634,190 which was filed on February 22, 2018, and which is incorporated herein in its entirety by reference.

Field

[0002] The present description relates to methods and apparatus for applying patterns to a substrate in a lithographic process.

[0003] A lithographic apparatus is a machine that applies a desired pattern onto a substrate, usually onto a target portion of the substrate. A lithographic apparatus can be used, for example, in the manufacture of integrated circuits (ICs). In that instance, a patterning device, which is alternatively referred to as a mask or a reticle, may be used to generate a pattern to be formed on an individual layer of, e.g., the IC. This pattern can be transferred onto a target portion (e.g. comprising part of, one, or several dies) on a substrate (e.g. a silicon wafer). Transfer of the pattern is typically via imaging onto a layer of radiation-sensitive material (resist) provided on the substrate. In general, a single substrate will contain a network of adjacent target portions that are successively patterned. Known lithographic apparatus include so-called steppers, in which each target portion is irradiated by exposing an entire pattern onto the target portion at one time, and so-called scanners, in which each target portion is irradiated by scanning the pattern through a radiation beam in a given direction (the “scanning”-direction) while synchronously scanning the substrate parallel or anti-parallel to this direction. It is also possible to transfer the pattern from the patterning device to the substrate by imprinting the pattern onto the substrate.

[0004] In order to monitor the lithographic process, parameters of the patterned substrate are measured. Parameters may include, for example, the overlay error between successive layers formed in or on the patterned substrate and/or critical linewidth or critical dimension (CD) of a structure on the substrate such as developed resist. This measurement may be performed on a product substrate and/or on a dedicated metrology target. There are various techniques for making measurements of the microscopic structures formed in lithographic processes, including the use of scanning electron microscopes and various specialized tools.

[0005] In performing lithographic processes, such as application of a pattern on a substrate or measurement of such a pattern, process control methods are used to monitor and control the process. Such process control techniques are typically performed to obtain corrections for control of the lithographic process. It would be desirable to improve, e.g., such process control methods.

[0006] In an aspect, there is provided a method of determining a corrected dimensional parameter value relating to a feature formed by a lithographic process, the corrected dimensional parameter value being corrected for a measurement effect on the dimensional parameter, the method comprising: performing a measurement to obtain at least two measurement values for the dimensional parameter; determining the measurement effect from the at least two measurement values; and determining the corrected dimensional parameter value from the determined measurement effect.

[0007] In an aspect, there is provided a computing apparatus comprising a processor, and being configured to perform a method as described herein.

[0008] In an aspect, there is provided a scanning electron microscopy inspection apparatus operable to image a plurality of features on a substrate, and comprising a computing apparatus as described herein.

[0009] In an aspect, there is provided a computer program comprising program instructions operable to perform a method as described herein when run on a suitable apparatus.

[0010] Further aspects, features and advantages, as well as the structure and operation of various embodiments of the invention, are described in detail below with reference to the accompanying drawings. It is noted that the invention is not limited to the specific embodiments described herein. Such embodiments are presented herein for illustrative purposes only. Additional embodiments will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein.

Brief Description of the Drawings

[0011] Embodiments of the invention will now be described, by way of example, with reference to the accompanying drawings in which:

[0012] Figure 1 depicts a lithographic apparatus together with other apparatuses forming a production facility for, e.g., semiconductor devices;

[0013] Figure 2 schematically depicts two examples of stochastic variation, wherein Figure 2A schematically depicts line edge roughness (LER) and Figure 2B schematically depicts line width roughness (LWR);

[0014] Figure 3 shows a graph of dose E against position x, illustrating the concept of a blurred ILS;

[0015] Figure 4 illustrates the effect of resist shrinkage and CD change due to SEM metrology, showing in Figure 4A an aerial image interacting with a resist layer, in Figure 4B the after development imaged structure in resist and in Figure 4C the same structure as shown in Figure 4B after measurement using SEM metrology;

[0016] Figure 5 is a plot of CD against SEM dose for a particular feature; and [0017] Figure 6 is a flowchart of a method according to an embodiment of the invention.

Detailed Description

[0018] Before describing embodiments of the invention in detail, it is instructive to present an example environment in which embodiments of the present invention may be implemented.

[0019] Figure 1 at 200 shows a lithographic apparatus LA as part of an industrial production facility implementing a high-volume, lithographic manufacturing process. In the present example, the manufacturing process is adapted for the manufacture of semiconductor products (e.g., integrated circuits) on substrates W such as semiconductor wafers. The skilled person will appreciate that a wide variety of products can be manufactured by processing different types of substrates in variants of this process. The production of semiconductor products is used purely as an example which has great commercial significance today.

[0020] Within the lithographic apparatus (or“litho tool” 200 for short), a measurement station MEA is shown at 202 and an exposure station EXP is shown at 204. A control unit LACU is shown at 206. In this example, each substrate visits the measurement station and the exposure station to have a pattern applied. In an optical lithographic apparatus, for example, a projection system is used to transfer a product pattern from a patterning device MA onto the substrate using conditioned radiation and a projection system. This is done by forming an image of the pattern in a layer of radiation- sensitive resist material.

[0021] The term“projection system” used herein should be broadly interpreted as encompassing any type of projection system, including refractive, reflective, catadioptric, magnetic, electromagnetic and electrostatic optical systems, or any combination thereof, as appropriate for the exposure radiation being used, or for other factors such as the use of an immersion liquid or the use of a vacuum. The patterning MA device may be a mask or reticle, which imparts a pattern to a radiation beam transmitted or reflected by the patterning device. Well-known modes of operation include a stepping mode and a scanning mode. As is well known, the projection system may cooperate with support and positioning systems for the substrate and the patterning device in a variety of ways to apply a desired pattern to many target portions across a substrate. Programmable patterning devices may be used instead of reticles having a fixed pattern. The radiation for example may include electromagnetic radiation in the deep ultraviolet (DUV) or extreme ultraviolet (EUV) wavebands. The present disclosure is also applicable to other types of lithographic process, for example imprint lithography and direct writing lithography, for example by electron beam.

[0022] The lithographic apparatus control unit LACU controls all the movements and

measurements of various actuators and sensors to receive substrates W and reticles MA and to implement the patterning operations. LACU also includes signal processing and data processing capacity to implement desired calculations relevant to the operation of the apparatus. In practice, control unit LACU will be realized as a system of many sub-units, each handling the real-time data acquisition, processing and control of a subsystem or component within the apparatus.

[0023] Before the pattern is applied to a substrate at the exposure station EXP, the substrate is processed at the measurement station MEA so that various preparatory steps may be carried out. The preparatory steps may include mapping the surface height of the substrate using a level sensor and/or measuring the position of alignment marks on the substrate using an alignment sensor. The alignment marks are arranged nominally in a regular grid pattern. However, due to inaccuracies in creating the marks and also due to deformations of the substrate that occur throughout its processing, the marks deviate from the ideal grid. Consequently, in addition to measuring position and orientation of the substrate, the alignment sensor in practice measures in detail the positions of many marks across the substrate area, if the apparatus is to print product features at the correct locations with very high accuracy. The apparatus may be of a so-called dual stage type which has two substrate tables, each with a positioning system controlled by the control unit LACU. While one substrate on one substrate table is being exposed at the exposure station EXP, another substrate can be loaded onto the other substrate table at the measurement station MEA so that various preparatory steps may be carried out. The substrate tables can be exchanged between the stations EXP and MEA. The measurement of alignment marks is therefore very time-consuming and the provision of two substrate tables enables a substantial increase in the throughput of the apparatus. If a position sensor is not capable of measuring the position of the substrate table while it is at the measurement station as well as at the exposure station, a second position sensor may be provided to enable the positions of the substrate table to be tracked at both stations.

[0024] Within the production facility, apparatus 200 forms part of a“litho cell” or“litho cluster” that also contains a coating apparatus 208 configured to apply photosensitive resist and/or one or more other coatings to substrates W for patterning by the apparatus 200. At an output side of apparatus 200, a baking apparatus 210 and developing apparatus 212 are provided for developing the exposed pattern into a physical resist pattern. Between all of these apparatuses, substrate handling systems take care of supporting the substrates and transferring them from one piece of apparatus to the next. These apparatuses, which are often collectively referred to as the track, are under the control of a track control unit which is itself controlled by a supervisory control system SCS, which also controls the lithographic apparatus via lithographic apparatus control unit LACU. Thus, the different apparatus can be operated to, for example, maximize throughput and/or processing efficiency. Supervisory control system SCS receives recipe information R which provides in great detail a definition of the steps to be performed to create each patterned substrate and can receive information 252 from the control unit LACU.

[0025] Once the pattern has been applied and developed in the litho cell, patterned substrates 220 are transferred to other processing apparatuses such as are illustrated at 222, 224, 226. A wide range of processing steps is implemented by various apparatuses in a typical manufacturing facility. For the sake of example, apparatus 222 in this embodiment is an etching station, and apparatus 224 performs a post-etch annealing step. Further physical and/or chemical processing steps are applied in one or more further apparatuses 226. Numerous types of operation can be required to make a real device, such as deposition of material, modification of surface material characteristics (oxidation, doping, ion implantation etc.), chemical-mechanical polishing (CMP), and so forth. The apparatus 226 may, in practice, represent a series of different processing steps performed in one or more apparatuses. As another example, apparatus and processing steps may be provided for the implementation of self- aligned multiple patterning, to produce multiple smaller features based on a precursor pattern laid down by the lithographic apparatus.

[0026] As is well known, the manufacture of semiconductor devices involves many repetitions of such processing, to build up device structures with appropriate materials and patterns, layer-by-layer on the substrate. Accordingly, substrates 230 arriving at the litho cluster may be newly prepared substrates, or they may be substrates that have been processed previously in this cluster or in another apparatus entirely. Similarly, depending on the required processing, substrates 232 on leaving apparatus 226 may be returned for a subsequent patterning operation in the same litho cluster, they may be destined for patterning operations in a different cluster, or they may be finished products to be sent for dicing and packaging.

[0027] Each layer of the product structure typically involves a different set of process steps, and the apparatuses used at each layer may be completely different in type. Further, even where the processing steps to be applied are nominally the same, in a large facility, there may be several supposedly identical machines working in parallel to perform the steps on different substrates. Small differences in set-up or faults between these machines can mean that they influence different substrates in different ways. Even steps that are relatively common to each layer, such as etching (apparatus 222) may be implemented by several etching apparatuses that are nominally identical but working in parallel to maximize throughput. In practice, moreover, different layers require different etch processes, for example chemical etches, plasma etches, according to the details of the material to be etched, and special requirements such as, for example, anisotropic etching.

[0028] The previous and/or subsequent processes may be performed in other lithography apparatuses, as just mentioned, and may even be performed in different types of lithography apparatus. For example, one or more layers in the device manufacturing process which are very demanding in one or more parameters such as resolution and/or overlay may be performed in a more advanced lithography tool than one or more other layers that are less demanding. Therefore one or more layers may be exposed in an immersion type lithography tool, while one or more others are exposed in a‘dry’ tool. One or more layers may be exposed in a tool working at DUV wavelengths, while one or more others are exposed using EUV wavelength radiation.

[0029] In order that the substrates that are exposed by the lithographic apparatus are exposed correctly and consistently, it is desirable to inspect exposed substrates to measure one or more properties such as overlay error between subsequent layers, line thickness, critical dimension (CD), etc. Accordingly a manufacturing facility in which the litho cell is located also typically includes a metrology system which receives one or more or all of the substrates W that have been processed in the litho cell. Metrology results are provided 242 directly or indirectly to the supervisory control system SCS. If errors are detected, adjustments 266 may be made to, e.g., exposures of subsequent substrates, especially if the metrology can be done soon and fast enough that other substrates of the same batch are still to be exposed. Also, already exposed substrates may be stripped and reworked to improve yield, or discarded, thereby avoiding performing further processing on substrates that are known to be faulty. In a case where only some target portions of a substrate are faulty, further exposures can be performed only on those target portions which are good.

[0030] Accordingly, shown in Figure 1 is a metrology apparatus 240 which is provided for making measurements of parameters of one or more of the products at desired stages in the manufacturing process. A common example of a metrology station in a modem lithographic production facility is a scatterometer, for example a dark-field scatterometer, an angle-resolved scatterometer or a spectroscopic scatterometer, and it may be applied to measure properties of the developed substrates at 220 prior to etching in the apparatus 222. Using metrology apparatus 240, it may be determined, for example, that a performance parameter such as overlay or critical dimension (CD) does not meet specified accuracy requirements in the developed resist. Prior to the etching step, the opportunity exists to strip the developed resist and reprocess a substrate 220 through the litho cluster. The metrology results 242 from the apparatus 240 can be used to maintain accurate performance of the patterning operations in the litho cluster, by supervisory control system SCS and/or control unit LACU making small adjustments over time, thereby reducing or minimizing the risk of products being made out-of-specification, and requiring re-work.

[0031] Another example of a metrology station is a scanning electron microscope (SEM), otherwise referred to as an electron beam (e-beam) metrology device, which may be included in addition to, or as an alternative to, a scatterometer. As such, metrology apparatus 240 may comprise an e-beam or SEM metrology device, either alone or in addition to a scatterometer. E-beam and SEM metrology devices have an advantage of measuring features directly (i.e., they directly image the features), rather than the indirect measurement techniques used in scatterometry (where parameter values are determined from reconstruction from and/or asymmetry in diffraction orders of radiation diffracted by the structure being measured). A disadvantage with e-beam or SEM metrology devices is their measurement speed, which is much slower than scatterometry, limiting their potential application to specific offline monitoring processes.

[0032] Additionally, metrology apparatus 240 and/or other metrology apparatuses (not shown) can be applied to measure properties of the processed substrates 232, 234, and incoming substrates 230. The metrology apparatus can be used on the processed substrate to determine values of a parameter such as overlay or CD.

[0033] Lithographic projection apparatuses typically project a patterned (i.e., by a patterning device) image at a point immediately above the substrate, and then ultimately into the resist. The projected image is called the aerial image, which comprises a distribution of radiation intensity as a function of spatial position in the image plane. The aerial image is the source of the information that is exposed into the resist, forming a gradient in dissolution rates that enables the three-dimensional resist image to appear during development.

[0034] Stochastic induced failure predictions are typically made based on measurement of the variation of a dimensional parameter, such as CD (so called local CD uniformity (LCDU)), line edge position (so called line edge roughness (LER)), or linewidth (so called linewidth roughness (LWR)). Accurate measurement of the number of failures is cumbersome, as low failure rates (e.g., of the order of 1 per million to 1 per billion) can be expected in an optimized process. Therefore, failure predictions are based on stochastic LCDU, LER or LWR predictions which rely on relatively few measurements. In particular, stochastics tend to be driven by optical contrast and more specifically, the image log slope (ILS). The ILS is the gradient of the logarithm of the aerial image intensity /:

[0035] Since variations in the resist edge positions (linewidths) are typically expressed as a percentage of the nominal linewidth, the position coordinate x can be normalized by multiplying the ILS by the nominal linewidth w to obtain what is referred to as the normalized ILS (NILS):

d Ini

NILS -w

dx

[0036] The concept of using an ILS for stochastic induced failure predictions is described in, for example, PCT patent publications WO2015/121127 and WO2016/128392, the contents of which are incorporated herein in their entireties by reference.

[0037] Stochasticity can be of significance for extreme ultraviolet (EUV) lithography, as features are smaller relative to lithography techniques using lower energy exposure radiation, as is the number of photons in the exposure radiation (because of their higher energy). EUV radiation is

electromagnetic radiation having a wavelength within the range of 5-20 nm; for example within the range of 13-14 nm. EUV radiation with a wavelength of less than 10 nm could be used, for example within the range of 5-10 nm (e.g., 6.7 nm or 6.8 nm). Such radiation is termed extreme ultraviolet radiation or soft x-ray radiation. Possible sources for EUV radiation include, for example, laser- produced plasma sources, discharge plasma sources, or sources based on synchrotron radiation provided by an electron storage ring.

[0038] Imaging, using a lithographic projection apparatus, will result in a stochastic variation in one or more parameters, such as pronounced line width roughness (LWR) and/or local CD variation in small two-dimensional features such as holes. The stochastic variation may be attributed to factors such as photon shot noise, photon- generated secondary electrons, photon absorption variation, photon-generated acids in the resist, etc. In the case of EUV lithography, the small sizes of features for which EUV is called for further compound this stochastic variation. The stochastic variation in smaller features is a significant factor in production yield and justifies inclusion in a variety of optimization processes of the litho cell.

[0039] Under the same radiation intensity, a lower exposure time of each substrate leads to higher throughput of a lithographic projection apparatus but stronger stochastic effect. The photon shot noise in a given feature under a given radiation intensity is proportional to the square root of the exposure time. The desire to lower exposure time for the purpose of increasing the throughput exists in lithography using EUV and other radiation wavelengths. Therefore, the methods and apparatuses described herein that consider the stochastic effect in an optimization process are not limited to EUV lithography.

[0040] The throughput can also be affected by the total amount of radiation directed to the substrate. In some lithographic projection apparatuses, a portion of the radiation (e.g., pupil fill ratio) from the source is sacrificed in order to achieve desired shapes of the source. Typically, a higher (N)ILS is obtained if the pupil fill ratio is lower, and as such there is a trade-off.

[0041] Figure 2A schematically depicts an example stochastic effect in the form of line edge roughness (LER). Assuming all conditions are identical in three exposures or simulations of exposure of an edge 903 of a feature on a design layout, the resist images 903 A, 903B and 903C of the edge 903 may have slightly different shapes and locations. Locations 904 A, 904B and 904C of the resist images 903 A, 903B and 903C may be measured by averaging the resist images 903 A, 903B and 903C, respectively, as represented by averages 902A, 902B and 902C respectively. LER of the edge 903 may be a measure of the spatial distribution of the locations 904 A, 904B and 904C. For example, the LER may be a 3s of the spatial distribution (assuming the distribution is a normal distribution). The LER may be derived from many exposures or simulations of the edge 903.

[0042] Figure 2B schematically depicts line width roughness (LWR). Assuming all conditions are identical in three exposures or simulations of exposure of a long rectangle feature 910 with a width 911 on a design layout, the resist images 910A, 910B and 910C of the rectangle feature 910 may have slightly different widths 911A, 91 IB and 911C, respectively. LWR of the rectangle feature 910 may be a measure of the distribution of the widths 911 A, 911B and 911C. For example, the LWR may be a 3s of the distribution (assuming the distribution is a normal distribution). The LWR may be derived from many exposures or simulations of the rectangle feature 910. In the context of a short feature (e.g., a contact hole), the widths of its images are not well defined because long edges are not available for averaging their locations. A similar quantity, LCDU, may be used to characterize this stochastic variation. The LCDU is a 3s of the distribution (assuming the distribution is a normal distribution) of measured CDs of images of the short feature.

[0043] The essence of stochastics relates to the absorbed dose, which fluctuates due to the limited number of (absorbed) photons. This is practically reflected in CD variations from feature to feature and/or over the length of a feature. As such, stochastic variation as described herein may comprise a measure of the variation of any dimensional parameter, and as such may comprise a line edge roughness (LER), a line width roughness (LWR), an LCDU, a hole LCDU, a circle edge roughness (CER), an edge placement error (EPE), or a combination selected therefrom.

[0044] In an embodiment, a design variable of the optimization process may comprise an ILS (e.g., more specifically a blurred ILS (ILS_B)), dose and/or image intensity (e.g., aerial image intensity). The blurred ILS (ILS_B) is the image log slope ILS (or normalized ILS) having a spatial blur applied thereto (e.g., by convolution with a Gaussian distribution), such that a blurred ILS has less contrast/slope than the unblurred aerial image. The spatial blur may represent blur of a resist image due to diffusion of a chemical species generated in a resist layer by exposure to radiation.

[0045] Ligure 3 illustrates how a blurred ILS ILS_B can be used to translate local dose variations into local CD (or another stochastic parameter) variations. It shows a plot of dose E against position x, the curve representing the absorbed dose within the resist. Due to the limited number of photons, the absorbed dose obeys Poissonian statistics, resulting in an intrinsic local dose variation O_dose, which in turn results in a variation in the number of photons absorbed by the resist <N_ph>. The blurred ILS ILS_B comprises a combination of the ILS defined by the aerial image and this local dose variation Od_ose. The blurred ILS ILS_B translates the local dose variation Od_ose into a resultant local CD variation LCDU, shown here as a CD variation range describing a circular feature CL, although this is equally applicable to any feature. The LCDU (in nm) will depend on the blurred ILS ILS_B and the number of photons absorbed by the resist <N_ph> according to:

LCDU (N_ph) ILS_B scales with the local dose variation

[0046] An issue with the approach described, is that the blurred ILS is typically determined from CD measurements which are performed using scanning electron microscopy (SEM) techniques. The problem with this is that the very act of measuring CD in resist, e.g., after development (after development inspection ADI), results in a measurement effect, more specifically a change in the measured CD. This is because electrons of the electron beam used to measure in SEM are absorbed and interact with the resist (outgassing reaction), resulting in shrinkage of the resist. In particular, the CD of line features measured using SEM techniques tend to decrease (narrow) as a result of the SEM measurement and, conversely, the CD of hole or trench features tend to increase (widen) as a result of the SEM measurement. As a result, there is a fundamental difference between the position where the aerial image crosses the substrate (and determines the CD) and the CD measured by the SEM.

[0047] This effect is illustrated in Ligure 4. Ligure 4A shows the position of aerial image AI, which defines the (normalized) ILS, with respect to a resist layer R during exposure. Ligure 4B shows the developed feature in resist R’ following a development step. The critical dimension CD_ADI of this feature R’ is the true ADI critical dimension. The aerial image AI is shown for reference only and would not be present at this stage of processing. Ligure 4C shows the developed feature in resist R’’ following a SEM metrology step to measure the CD. The critical dimension CDSEM of this feature R’’ is not the true ADI CD, but rather there is a CD difference ACD between CDADI and CDSEM (i.e., a measurement effect). The CD difference ACD is purely the result of the SEM inspection.

[0048] With increased SEM dose the resist CD will reduce. This dependence on dose is cumulative, and therefore the ultimate CD will depend on the number of SEM measurements performed and resultant image frames obtained, as obtaining each frame subjects the resist to a further SEM dose.

The change in CD will depend, for example, on characteristics of the resist, the SEM dosage and the SEM voltage. Figure 5 is a graph of measured CD (y axis) against SEM dose ESEM (X axis), showing an example shrink curve SC for a given feature (e.g., a trench or hole feature).

[0049] The measured CD is therefore not representative of the CD after development. Because CD and the ILS are fundamentally coupled, this means that the ILS determined from the measured CD is not representative of the true, after-development ILS. This makes stochastic failure predictions based on this measured ILS inaccurate. Since both the CD difference due to measurement (which can be anything up to 15 nm) and the CD-ILS dependence vary per feature, an incorrect ILS is almost always obtained.

[0050] It is therefore proposed to determine the effect on CD (or other dimensional parameter) due to SEM measurement (ACD) and correct for this CD measurement effect in the CD measurements. The corrected CD measurements (i.e., an estimation of the CD obtained after development) can then be used to determine the ILS (e.g., the normalized or blurred ILS), which in turn can be used to make stochastic failure predictions with improved accuracy.

[0051] The CD measurement effect may be determined in different ways. The simplest way is to obtain a plurality of SEM frames (images) of the same feature. Typically with a SEM tool, each frame is stored separately, and therefore a CD value for a feature can be determined per frame. In an embodiment where only two frames are obtained, it may be assumed that the CD measurement effect is substantially linear (i.e., relates to the linear part of the shrink curve SC of Figure 5). As such the CD difference determined from the two (successive) frames may be assumed to be the same as the CD difference between the CD in the first frame and the unknown, after-development (pre-inspection) CD that is being estimated. By measuring more frames, the estimate can be made more accurate, as the shrink curve is actually typically more exponential than linear. For example, if there are a sufficient number of frames, the dependence of CD on SEM dose (i.e., a curve such as that of Figure 5) can be modelled. The model can then be used to more accurately estimate the CD measurement effect, and therefore the after-development CD, of similar features (for example, assuming that the other relevant variables e.g., resist type, SEM voltage etc. are maintained the same).

[0052] Figure 6 is a flowchart describing an exemplary method using this concept. In step 1700, a feature is formed on a substrate and at step 1705, the CD, or other relevant dimensional parameter of the feature, is measured on at least two frames using a SEM. At step 1710, a corrected CD value is determined based on the measured CD values of the previous step. The corrected CD value comprises an estimate of the after-development CD, before measurement. This step may use any of the methods proposed in the previous paragraph. In step 1715, an image intensity metric is determined from the corrected CD values. The image intensity metric may comprise an ILS, a normalized ILS, a blurred ILS or a blurred normalized ILS, for example. At step 1720, a value of the stochastic variation (e.g., LER or LCDU) is determined from the ILS, from which stochastic induced failure predictions can be made.

[0053] The embodiments may further be described using the following clauses:

1. A method of determining a corrected dimensional parameter value relating to a feature formed by a lithographic process, the corrected dimensional parameter value being corrected for a measurement effect on the dimensional parameter, the method comprising:

performing a measurement to obtain at least two measurement values for the dimensional parameter; determining the measurement effect from the at least two measurement values; and

determining the corrected dimensional parameter value from the determined measurement effect.

2. The method of clause 1, wherein each of the at least two measurement values relate to the same feature.

3. The method of clause 1 or clause 2, wherein performing the measurement is performed using scanning electron microscopy metrology.

4. The method of any preceding clause, wherein each of the at least two measurement values are determined from a different frame of an image of the feature.

5. The method of any preceding clause, wherein the measurement effect is a change in the dimensional parameter caused by performing the measurement.

6. The method of any preceding clause, wherein the dimensional parameter is critical dimension, line edge position or linewidth.

7. The method of any preceding clause, wherein determining the measurement effect comprises determining the difference from two of the at least two measurement values, and attributing this difference to the measurement effect.

8. The method of any of clauses 1 to 6, wherein determining the measurement effect comprises modelling the variation of the dimensional parameter with a measurement parameter.

9. The method of clause 8, wherein the measurement parameter comprises measurement dose.

10. The method of any preceding clause, comprising using the corrected dimensional parameter value to determine an image intensity metric relating to an aerial image for forming the feature.

11. The method of clause 10, wherein the image intensity metric comprises an image log slope.

12. The method of clause 11, wherein the image log slope is normalized and/or blurred such that it comprises a normalized image log slope, a blurred image log slope or a blurred normalized image log slope.

13. The method of any of clauses 10 to 12, comprising using the image intensity metric to determine a stochastic variation. 14. The method of clause 13, wherein the stochastic variation comprises a line edge roughness (LER), a line width roughness (LWR), a LCDU, a hole LCDU, a circle edge roughness (CER) and/or an edge placement error (EPE).

15. The method of clause 13 or clause 14, comprising using the stochastic variation to predict a stochastic variation induced failure rate.

16. A computing apparatus comprising a processor, and being configured to perform the method of any preceding clause.

17. A scanning electron microscopy inspection apparatus operable to image one or more features on a substrate, and comprising the computing apparatus of clause 16.

18. A computer program comprising program instructions operable to perform the method of any of clauses 1 to 15 when run on a suitable apparatus.

19A non- transient computer program carrier comprising the computer program of clause 18.

[0054] The terms“radiation” and“beam” used in relation to the lithographic apparatus encompass all types of electromagnetic radiation, including ultraviolet (UV) radiation (e.g., having a wavelength of or about 365, 355, 248, 193, 157 or 126 nm) and extreme ultra-violet (EUV) radiation (e.g., having a wavelength in the range of 5-20 nm), as well as particle beams, such as ion beams or electron beams.

[0055] The term“lens”, where the context allows, may refer to any one or combination of various types of optical components, including refractive, reflective, magnetic, electromagnetic and electrostatic optical components.

[0056] The foregoing description of the specific embodiments fully reveals the general nature of embodiments of the invention that others can, by applying knowledge within the skill of the art, readily modify and/or adapt for various applications such embodiments, without undue

experimentation and without departing from the general concept of the present invention. Therefore, such adaptations and modifications are intended to be within the meaning and range of equivalents of the disclosed embodiments, based on the teaching and guidance presented herein. It is to be understood that the phraseology or terminology herein is for the purpose of description by example, and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by the skilled artisan in light of the teachings and guidance.

[0057] A computer program may be configured to provide any of the above described methods. The computer program may be provided on a computer readable medium. The computer program may be a computer program product. The product may comprise a non-transitory computer usable storage medium. The computer program product may have computer-readable program code embodied in the medium configured to perform the method. The computer program product may be configured to cause at least one processor to perform some or all of a method described herein.

[0058] Various methods and apparatus are described herein with reference to block diagrams or flowchart illustrations of computer-implemented methods, apparatus (systems and/or devices) and/or computer program products. It is understood that a block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by computer program instructions that are performed by one or more computer circuits. These computer program instructions may be provided to a processor circuit of a general purpose computer circuit, special purpose computer circuit, and/or other programmable data processing circuit to produce a machine, such that the instructions, which execute via the processor of the computer and/or other programmable data processing apparatus, transform and control transistors, values stored in memory locations, and other hardware components within such circuitry to implement the functions/acts specified in the block diagrams and/or flowchart block or blocks, and thereby create means (functionality) and/or structure for implementing the functions/acts specified in the block diagrams and/or flowchart block(s).

[0059] Computer program instructions may also be stored in a computer-readable medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instructions which implement the functions/acts specified in the block diagrams and/or flowchart block or blocks.

[0060] A tangible, non-transitory computer-readable medium may include an electronic, magnetic, optical, electromagnetic, or semiconductor data storage system, apparatus, or device. More specific examples of the computer-readable medium would include the following: a portable computer diskette, a random access memory (RAM) circuit, a read-only memory (ROM) circuit, an erasable programmable read-only memory (EPROM or Flash memory) circuit, a portable compact disc read only memory (CD-ROM), and a portable digital video disc read-only memory (DVD/Blu-ray).

[0061] The computer program instructions may also be loaded onto a computer and/or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer and/or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions/acts specified in the block diagrams and/or flowchart block or blocks.

[0062] Accordingly, the present disclosure may be embodied in hardware and/or in software (including firmware, resident software, micro-code, etc.) that runs on a processor, which may collectively be referred to as "circuitry," "a module" or variants thereof.

[0063] It should also be noted that in some alternate implementations, the functions/acts noted in the blocks may occur out of the order noted in the flowcharts. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Moreover, the functionality of a given block of the flowcharts and/or block diagrams may be separated into multiple blocks and/or the functionality of two or more blocks of the flowcharts and/or block diagrams may be at least partially integrated. Finally, other blocks may be added/inserted between the blocks that are illustrated.

[0064] The breadth and scope of the present invention should not be limited by any of the above- described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.

Claims

CLAIMS:

performing a measurement to obtain at least two measurement values for the dimensional parameter;

determining the measurement effect from the at least two measurement values; and determining the corrected dimensional parameter value from the determined measurement effect.

2. The method of claim 1, wherein each of the at least two measurement values relate to the same feature.

3. The method of claim 1 , wherein performing the measurement is performed using scanning electron microscopy metrology.

4. The method of claim 1, wherein each of the at least two measurement values are determined from a different frame of an image of the feature.

5. The method of claim 1 wherein the measurement effect is a change in the dimensional parameter caused by performing the measurement.

6. The method of claim 1, wherein the dimensional parameter is critical dimension, line edge position or linewidth.

7. The method of claim 1, wherein determining the measurement effect comprises determining the difference from two of the at least two measurement values, and attributing this difference to the measurement effect.

8. The method of claim 1, wherein determining the measurement effect comprises modelling the variation of the dimensional parameter with a measurement parameter.

9. The method of claim 8, wherein the measurement parameter comprises measurement dose.

10. The method of claim 1, comprising using the corrected dimensional parameter value to determine an image intensity metric relating to an aerial image for forming the feature.

11. The method of claim 10, wherein the image intensity metric comprises an image log slope, and / or wherein the image log slope is normalized and/or blurred such that it comprises a normalized image log slope, a blurred image log slope or a blurred normalized image log slope.

12. The method of claim 10 , comprising using the image intensity metric to determine a stochastic variation, and / or wherein the stochastic variation comprises a line edge roughness (LER), a line width roughness (LWR), a LCDU, a hole LCDU, a circle edge roughness (CER) and/or an edge placement error (EPE).

13. The method of claim 12, comprising using the stochastic variation to predict a stochastic variation induced failure rate.

14. A computing apparatus comprising a processor, and being configured to perform the method of claim 1.

15. A computer program comprising program instructions operable to perform the method of claim 1 when run on a suitable apparatus.