ESTIMATION METHOD OF THE LOCAL TOPOGRAPHY OF A SAMPLE BASED ON IMAGES FROM A SCRATCHING ELECTRON MICROSCOPE AND A MATHEMATICAL MODEL

Description

DOMAINE TECHNIQUE DE L'INVENTION

[0001] The technical field of the invention is that of estimating the local topography of samples by scanning electron microscopy, using a mathematical model.

[0002] The present invention relates to a method for estimating the local topography of a sample and in particular a method for estimating the local topography of a sample from scanning electron microscopy images and a mathematical model. ARRIERE-PLAN TECHNOLOGIQUE DE L'INVENTION

[0003] With a view to improving profitability, the industry is seeking to develop devices with non-planar architectures (FinFET, Tri-gate FinFET, Gate-all-around FET, etc.). It is also developing various technologies enabling the implementation of diverse functions, integrated on silicon, leading to potentially complex three-dimensional architectures (imagers, MEMS, photonics, 3D memories, etc.).

[0004] The development of these new architectures can only be done in parallel with nanometric metrology enabling dimensioning in three dimensions of space.

[0005] In optical proximity correction or OPC applications, it is necessary to accurately measure the critical dimension of each pattern in the sample in a robust manner; therefore, it can be useful to know the topography of the observed pattern in order to, for example, measure the critical dimensions at a constant height.

[0006] Several methods are commonly used to perform such measurements.

[0007] Such a measurement is performed, for example, by acquiring cross-sections of the sample, micro-machined using a focused ion probe, and then imaged by scanning or transmission electron microscopy. Although it provides accurate results, this method is time-consuming and causes local destruction of the sample being tested, making it unsuitable as a systematic quality control method in industry.

[0008] Another way to perform this measurement is to use an atomic force microscope which analyzes the sample point by point by scanning via a local probe, but this method has many disadvantages including reproducibility problems due to the rapid wear of the local probe, and slowness, which prevents its implementation at an industrial level on samples with a very large number of patterns.

[0009] It has also been proposed to use a scanning electron microscope capable of rapid acquisitions, coupled with a mathematical model to estimate the critical dimension by thresholding on a gray-level profile. However, such mathematical models are only suitable for a certain type of pattern with similar characteristics and cannot be generalized to patterns with varied characteristics.

[0010] There is therefore a need for a method to accurately measure the topography, and in particular the height and flank angle, of any type of pattern in a fast, non-destructive and reproducible manner.

[0011] US document 2006 / 210143 entitled "Method and apparatus for measuring shape of a specimen" is known from the prior art. RESUME DE L'INVENTION

[0012] The invention offers a solution to the problems mentioned above, by proposing a method for measuring the height and flank angle of all the patterns of a sample over a very wide variety of dimensional characteristics, and which can be implemented systematically at an industrial level.

[0013] A first aspect of the invention relates to a method for estimating the local topography of a sample comprising at least one pattern, the method comprising: for each motif of the sample: ∘ an acquisition step, by a scanning electron microscope, of a plurality of images of the motif, the images being taken with different angles of incidence; ∘ for each acquired image: a calculation step of a grey level profile along a given axis; a placement step of a plurality of primary descriptors on the calculated grey level profile; a calculation step of secondary descriptors from the primary descriptors; a use of a mathematical model to calculate primary topographic quantities from the secondary descriptors; ∘ a local topography estimation step of the motif consisting of using the mathematical model to calculate secondary topographic quantities from the primary topographic quantities and the previously calculated secondary descriptors.

[0014] Thanks to the invention, it is possible to quickly and accurately obtain, using the rapid image acquisition speed of a scanning electron microscope, the height and flank angle of each motif in a sample, and more generally, the topography of each motif in the sample, by using images at multiple angles of incidence and a mathematical model. The mathematical model allows for the initial determination of primary topographic measurements from a single image and, subsequently, secondary topographic measurements that can only be obtained from multiple images. It models the topography of the motif as a shape characterized by these primary and secondary topographic measurements.Furthermore, the use of the mathematical model once calibrated allows the topography of patterns with varying topographic sizes to be estimated with error rates close to those of the current reference methods previously presented.

[0015] In addition to the characteristics mentioned in the preceding paragraph, the method according to a first aspect of the invention may have one or more complementary characteristics from among the following, considered individually or according to all technically possible combinations.

[0016] According to one embodiment, the method according to a first aspect of the invention comprises a first step of calibrating the mathematical model from reference topographies.

[0017] According to a first sub-emphasis, the reference topographies are obtained using at least one microscopy technique other than scanning electron microscopy.

[0018] According to an example of an embodiment of the first sub-embody above, the microscopy techniques can be chosen from transmission electron microscopy or atomic force microscopy.

[0019] Thus, the mathematical model is calibrated using topographic profiles from measurements made using microscopy techniques other than scanning electron microscopy.

[0020] According to a second sub-emphasis, the reference topographies are obtained by simulation.

[0021] Thus, the mathematical model is calibrated using topographies obtained by simulation, which allows for faster calibration and a wider diversity of patterns compared to the case where only images acquired by microscopy are used, which are slower to obtain and where it is difficult to control each parameter.

[0022] According to an embodiment compatible with the previous embodiment, the topography of a pattern is modeled using a trapezoid with rounded corners.

[0023] According to an example of an embodiment of the preceding embodiment, the rounded-corner trapezoid has a small base, a large base and two sides and can be characterized by the following eight topographical quantities: a right-hand bottom curvature, a left-hand bottom curvature, a right-hand top curvature, a left-hand top curvature, a height, a right-hand side angle, a left-hand side angle and a length at a given height.

[0024] Thus, the mathematical model estimates the topography of the pattern by determining topographic quantities specific to a trapezoid with rounded corners.

[0025] According to an embodiment compatible with the preceding embodiments, the primary descriptors are determined from particular values ​​of the derivative of the grey level profile along the given axis.

[0026] Thus, the primary descriptors correspond to positions where the levels of grey vary significantly, which generally correspond to the edges of a pattern.

[0027] According to an embodiment compatible with the preceding embodiments, a primary topographic quantity is a linear combination of the secondary descriptors and the angle of incidence of a single acquired image.

[0028] Thus, primary topographic quantities can be directly obtained from a single acquired image.

[0029] According to an embodiment compatible with the preceding embodiments, a secondary topographic quantity is a function of primary topographic quantities and the angles of incidence of several acquired images and possibly secondary descriptors of several acquired images.

[0030] Thus, secondary topographic quantities cannot be directly obtained from a single acquired image but from several images taken with different angles of incidence.

[0031] A second aspect of the invention relates to a computer program product comprising instructions which, when the program is executed by a computer, lead the computer to implement the steps of the method according to a first aspect of the invention except the acquisition steps.

[0032] A third aspect of the invention relates to a computer-readable recording medium comprising instructions which, when executed by a computer, cause the computer to carry out the steps of the method according to a first aspect of the invention except the acquisition steps.

[0033] The invention and its various applications will be better understood by reading the following description and examining the accompanying figures. BREVE DESCRIPTION DES FIGURES

[0034] The figures are presented for illustrative purposes only and are in no way limiting to the invention. There figure 1 represents a synoptic diagram of the steps of the method according to a first aspect of the invention. The figure 2 represents a model of the topography of a pattern in a sample, and the associated topographic quantities for a zero angle of incidence. figure 3 This represents a diagram of a scanning electron microscope imaging a sample at a certain angle of incidence. figure 4A represents an image of a sample acquired by a scanning electron microscope. figure 4B represents the greyscale profile of the image of the figure 4A along a given axis. The figure 4C represents the derivative of the grayscale profile of the figure 4B . There figure 5 represents a model of the topography of a pattern in a sample, and the associated topographic quantities for a zero angle of incidence on the left and for a non-zero angle of incidence on the right. DESCRIPTION DETAILLEE D'AU MOINS UN MODE DE REALISATION DE L'INVENTION

[0035] Unless otherwise specified, the same element appearing on different figures has a unique reference.

[0036] A first aspect of the invention relates to a method for estimating the local topography of a sample.

[0037] The term "local topography of a sample" refers to the configuration of the surface of the sample, in other words, the identification of the reliefs and hollows of the sample, called line or space in the field of microelectronics.

[0038] The term "estimating the local topography of a sample" refers to the process of approximately evaluating the local topography of the sample.

[0039] A sample of 301, represented at the figure 3 may include one or more 3010 patterns as shown on the figure 2 The topography of each 3010 pattern is, for example, modeled by a shape following certain contours of a trapezoid with rounded corners.

[0040] [ Fig 2 ] shows a model 200 of a pattern 3010 of sample 301 by a shape following certain contours of a trapezoid with rounded corners.

[0041] A "trapezoid with rounded corners" is a classic trapezoid in which some corners have been replaced by rounded corners.

[0042] A "classical trapezoid" is defined as a quadrilateral with two opposite parallel sides of different lengths. The opposite parallel side with the shorter dimension is commonly called the lesser base (base 202), and the opposite parallel side with the longer dimension is commonly called the greater base (base 201). In a classic trapezoid, two sides meet at an angle.

[0043] In the following description, the two other sides of the classic trapezoid are called sides 203, that is, the sides connecting the smaller base 202 and the larger base 201. The lower end of a side 203 is the end of the side 203 connected to the larger base 201, and the upper end of a side 203 is the end of the side 203 connected to the smaller base 202. The width 2030 of a side 203 is the distance, along an axis parallel to the smaller base 202, between the upper and lower ends of the side 203. The angle 2031 of a side 203 is the value of the angle between the larger base 201 and the side 203.

[0044] The trapezoid is called a "rounded trapezoid" because each side 203 joins the smaller base 202 by forming a curve, rather than an angle as in classic trapezoids. In other words, the upper end of each side 203 is curved.

[0045] The structure of a trapezoid with rounded corners is therefore based on the structure of a classic trapezoid and certain topographical dimensions of this classic trapezoid can therefore be used to characterize the topography of the trapezoid with rounded corners, such as the length 2020 of the small base 202, the length 2010 of the large base 201, the width 2030 of side 203 and the angle 2031 of side 203.

[0046] On the figure 2 The small base 202 corresponds to the upper part of the pattern 3010 of the sample 301 and the large base 201 corresponds to the lower part of the pattern 3010 of the sample 301 located at the height at which the surface of the sample 301 would be if there were no pattern 3010. In other words, the height between the small base 201 and the large base 202 corresponds to the height 2000 of the pattern 3010.

[0047] The height 2000 of pattern 3010 can be positive or negative depending on whether pattern 3010 is a relief or a hollow.

[0048] Subsequently, the length of the pattern 3010 for a given height is called the "length of pattern 3010". The length of pattern 3010 is, for example, the length 2020 of the small base 201, that is to say the length of pattern 3010 at the height 2000 of pattern 3010, or the length 2010 of the large base 201, that is to say the length of pattern 3010 at zero height.

[0049] The motif 3010 of sample 301 is modeled by a curve 200, part of which follows certain contours of the rounded-corner trapezoid. More specifically, this curve 200 has a first part P1 following the sides 203 and the shorter base 202 of the rounded-corner trapezoid, as well as a second part P2 and a third part P3 located on either side of the first part P1 and extending along a plane containing the longer base 201. The junction between the first part P1 and the second part P2 of the curve 200 forms a curve at the lower end of one of the sides 203, and the junction between the first part P1 and the third part P3 of the curve 200 forms a curve at the lower end of the other side 203 of the rounded-corner trapezoid.

[0050] For simplicity, we can assume that curve 200 is symmetrical with respect to an axis passing through the midpoint of the smaller base 202 and the midpoint of the larger base 201. Thus, for example, the junctions between the first part P1 and the second part P2, and between the first part P1 and the third part P3 of curve 200, have the same rounded shape. Similarly, the junctions between each side 203 and the smaller base 202 have the same rounded shape, the angle 2031 of side 203 between the left side 203 and the larger base 201, and the angle 2031 of side 203 between the right side 203 and the larger base 201, have the same value, and the width 2030 of the right side 203 and the width 2030 of the left side 203 are the same.

[0051] The topography of this curve 200 can then be characterized by the following quantities: the length 2010, 2020 of the pattern 3010, the height 2000 of the pattern 3010, the value of the rounding between the first part P1 and the second part P2 of the curve 200 called the low curvature 2011, the value of the rounding between a flank 203 and the small base 202 called the high curvature 2021 and the angle 2031 of flank 203.

[0052] In a more complex case where the curve 200 does not have an axis of symmetry, the topography of the curve 200 can be characterized by the length 2010, 2020 of the pattern 3010, the height 2000 of the pattern 3010, the lower curvature 2011 right, the lower curvature 2011 left, the upper curvature 2021 right, the upper curvature 2021 left, the angle 2031 of flank 203 right and the angle 2031 of flank 203 left.

[0053] The topography of a 3010 pattern can be more complex, such as a "T" shape, multiple slopes along the flank, or even curved flanks. Therefore, for shapes far removed from the rounded trapezoidal case, the model can be made more complex by incorporating higher orders for straight lines and a greater number of break points.

[0054] The calculation of the topographic quantities characterizing the model 200 therefore makes it possible to obtain the model 200 and thus to estimate the topography of each motif 3010 of the sample 301. These calculations are carried out using a mathematical model from images acquired by a scanning electron microscope, according to the steps of method 100 according to a first aspect of the invention.

[0055] A "mathematical model" is understood to be a set of equations that allow the calculation of the characteristic quantities of a model.

[0056] [ Fig 1 ] shows a synoptic diagram of the steps of method 100 according to a first aspect of the invention.

[0057] A first step 101 of the method 100 consists of calibrating the mathematical model using reference topographies. The mathematical model makes it possible to obtain topographic quantities characterizing the shape of the modeling 200 chosen to estimate the topography of a pattern 3010 of a sample 301, for example the topographic quantities of the curve 200 following certain contours of a trapezoid with rounded corners, such as its height 2000 or its side angle 2031 203.

[0058] At the beginning of the first step 101 of process 100, the mathematical model uses a set of parameters having default values ​​and the calibration of the mathematical model aims to modify the value of these parameters to minimize the errors between the topographic quantities obtained by the mathematical model and the topographic quantities obtained for the reference topographies of pattern 3010.

[0059] According to a first embodiment, the reference topographies are obtained using at least one microscopy technique other than scanning electron microscopy, such as transmission electron microscopy or TEM and atomic force microscopy or AFM.

[0060] According to a second embodiment, the reference topographies are obtained by numerical simulation.

[0061] It is possible to use reference topographies from the first embodiment and reference topographies from the second embodiment.

[0062] Each reference topography is coupled with a corresponding scanning electron microscopy image. For example, in the first embodiment, an image of a test pattern is acquired consecutively using a scanning electron microscope and another type of microscope, for example, an AFM microscope. For example, in the second embodiment, an image of a test pattern, for which a numerical simulation has been performed and whose topography is known, is acquired using a scanning electron microscope.

[0063] The first step 101 of method 100 consists of determining a first model, having the same shape as that from which the mathematical model allows obtaining the topographic quantities, which corresponds best with the reference topography found by the other microscopy technique or by numerical simulation, then to use the mathematical model on the corresponding image obtained by scanning electron microscopy and to adjust the mathematical model to obtain a second model as close as possible to the first model.

[0064] The term "adjusting the mathematical model" refers to performing an iterative calculation process to find the set of parameters for the mathematical model that minimizes the discrepancy between the topographic measurements obtained by the model and the topographic measurements considered closest to reality, corresponding to the measurements determined using another microscopy technique or by numerical simulation. In practice, this calculation process is implemented, for example, by a computer using one of the known algorithms for minimizing the discrepancy, such as the least squares method.

[0065] For the mathematical model to function on a wide variety of different patterns, this variety must be present in the reference topographies. Thus, if we want, for example, to be able to determine the height 2000 of 3010 patterns, the mathematical model must have been calibrated using reference topographies exhibiting a variety of different heights.

[0066] Once calibrated, the mathematical model is operational on any type of pattern, regardless of, for example, its height 2000 or its flank angle 2031, as long as the flank is geometrically visible on the electron microscopy images used for topology estimation.

[0067] A second step 102 of method 100 consists of acquiring a plurality of images of a pattern 3010 of the sample 301 whose topography is to be studied. The acquisitions are carried out using a scanning electron microscope with several different angles of incidence and possibly with other different image acquisition conditions such as electron acceleration or electron beam intensity.

[0068] [ Fig 3 ] shows a schematic representation of a scanning electron microscope 300 imaging a sample 301 with a certain angle of incidence 302.

[0069] On the figure 3 , sample 301 receives an electron beam from an electron gun 303, at an angle of incidence 302. Secondary electrons are re-emitted by sample 301 and intercepted by an imager 304. Depending on the angle of incidence 302, the image acquired by the imager 304 is different.

[0070] The variation in the angle of incidence is obtained either by tilting the sample or by deflecting the electron beam using magnetic coils.

[0071] The angle of incidence 302 is for example between 0° and 15° in the case where the electron beam is deflected.

[0072] To obtain an estimate of a 203 flank, for example, a minimum of two images taken at two different 302 angles of incidence is required. However, for a significant improvement in accuracy, it is advisable to provide at least three images, for example at a zero 302 angle of incidence, at a low 302 angle of incidence, and at the largest 302 angle of incidence achievable by the equipment.

[0073] In the case of a model 200 based on a trapezoid with rounded corners, the value of the width 2030 of a side 203 varies according to the angle of incidence 302.

[0074] On the figure 2 , the width 2030 of the left flank 203 and the width 2030 of the right flank 203 are shown for an angle of incidence 302 zero.

[0075] [ Fig 5 On the figure 5 , the width 2030 of the left side 203 is shown for a zero angle of incidence 302 and the width 2030 of the right side 203 is shown for a non-zero angle of incidence 302.

[0076] The number of images acquired is not multiplied by the number of 3010 patterns in the sample; two images of the same area taken at different angles of incidence will, for example, be able to estimate all the flanks of 3010 patterns visible on both images.

[0077] The third 103, fourth 104, fifth 105 and sixth 106 steps of method 100 are performed for each image acquired during the second step 102 of method 100.

[0078] The third step 103 of method 100 consists, for a previously acquired image, of calculating a grey level profile along a given axis 1021.

[0079] [ Fig 4A ] represents a 1020 image of a 3010 pattern from a 301 sample acquired by a scanning electron microscope.

[0080] A 1020 image has two dimensions: one dimension along a horizontal axis and one dimension along a vertical axis. The 1021 axis is parallel to the axis of the 1020 image, which allows for a non-invariant grayscale profile.

[0081] On the figure 4A The 1021 axis is parallel to the horizontal axis. Indeed, all image axes parallel to the vertical axis produce an invariant greyscale profile.

[0082] The 1021 axis is then, for example, the horizontal axis passing through the center of the image.

[0083] [ Fig 4B ] represents the 1030 grayscale profile of the 1020 image of the figure 4A along axis 1021.

[0084] A 1030 grayscale profile represents a grayscale level based on a position. A 1030 grayscale profile along a 1021 axis represents the grayscale level of each point in the image located on the 1021 axis as a function of its position on the 1021 axis.

[0085] Grey levels have a value between 0 and X, with 0 corresponding to black and X to white. The value of X can vary depending on the convention. For example, X could be 1 or 255.

[0086] On the figure 4B , the 1030 grey level profile shows peaks at positions corresponding to the bright areas of the 1020 image located on the 1021 axis.

[0087] The fourth step 104 of method 100 consists of placing primary descriptors A,B,C,D,E on the previously calculated grey level profile 1030.

[0088] The primary descriptors A, B, C, D, E correspond, for example, to particular values ​​of the derivative of the 1030 profile of grey levels.

[0089] [ Fig 4C ] represents the 1031 derivative of the 1030 grayscale profile of the 1020 image of the figure 4A along axis 1021, represented at the figure 4B .

[0090] On the figure 4C, for the left peak, the primary descriptor A corresponds to the first position for which the derivative 1031 goes from a zero value to a positive value, the primary descriptor B corresponds to the position for which the derivative 1031 is maximum, the primary descriptor C corresponds to the intermediate position for which the derivative 1031 goes from a positive value to a negative value, the primary descriptor D corresponds to the position for which the derivative 1031 is minimum and the primary descriptor E corresponds to the last position for which the derivative 1031 goes from a negative value to a zero value.For the right-hand peak, primary descriptor A corresponds to the last position for which the derivative 1031 goes from a negative value to a zero value, primary descriptor B corresponds to the position for which the derivative 1031 is minimal, primary descriptor C corresponds to the intermediate position for which the derivative 1031 goes from a positive value to a negative value, primary descriptor D corresponds to the position for which the derivative 1031 is maximal and primary descriptor E corresponds to the first position for which the derivative 1031 goes from a zero value to a positive value.

[0091] The primary descriptors A, B, C, D, E can also correspond to positions for which the grey level value or its derivative 1031 have passed a certain threshold.

[0092] Additional primary descriptors responding to different rules could be added to enrich the mathematical model.

[0093] Step five 105 of method 100 consists of calculating secondary descriptors and step six 106 consists of calculating primary topographic quantities from the secondary descriptors using the mathematical model.

[0094] The primary topographic quantities are the topographic quantities of the model 200 that can be calculated using only the secondary descriptors and the angle of incidence 302, the acquired image 1020 being studied and possibly other image-taking conditions.

[0095] In the example of curve 200 following certain contours of a trapezoid with rounded corners, the primary topographic quantities are the lower curvatures 2011, the high curvatures 2021 and the widths 2030 of flank 203.

[0096] Each primary topographic quantity is, for example, a linear combination of secondary descriptors defined as a linear or non-linear function of several primary descriptors A, B, C, D, E of the same acquired image 1020 and the corresponding angle of incidence 302.

[0097] A secondary descriptor is for example |AB| which corresponds to a distance or e -|AB|< corresponding to a probability of electron exit.

[0098] The primary topographic quantities are calculated by the mathematical model from the secondary descriptors, the calibration step 101 having made it possible to adjust the constant coefficients of each linear combination by minimizing the differences between the topographic quantities obtained from a given reference topography and the topographic quantities provided by the mathematical model.

[0099] The high curvatures 2021 depend, for example, on |DE| and the angle of incidence 302. The low curvatures 2011 depend, for example, on |AB| and the angle of incidence 302. Each width 2030 of sidewall 203 depends, for example, on |DB|, the angle of incidence 302, the corresponding high curvature 2021 and low curvature 2011.

[0100] At the end of the sixth step 106 of method 100, the primary topographic quantities are obtained for each image 1020 acquired in the acquisition step 102.

[0101] For example, if three 1030 images were acquired in step 102 of acquisition in the case of a model 200 whose shape follows certain contours of a symmetrical rounded-corner trapezoid, at the end of the sixth step 106 of method 100, nine primary topographic quantities are obtained: three low curvatures 2011, three high curvatures 2021 and three flank widths 2030 203.

[0102] A seventh step 107 of the method 100 consists of calculating secondary topographic quantities from the primary topographic quantities and corresponding incidence angles 302, and possibly secondary descriptors and other image-taking conditions of several acquired images 1020.

[0103] Secondary topographic quantities are the topographic quantities of the 200 modeling that cannot be calculated using a single acquired 1020 image.

[0104] In the example of the 200 model based on a symmetrical rounded-corner trapezoid, the secondary topographic quantities are the 2020 length of pattern 3010, the 2000 height of pattern 3010 and the 2031 angle of flank 203.

[0105] A secondary topographic quantity is, for example, a function of primary topographic quantities and incidence angles, and possibly other image acquisition conditions. A secondary topographic quantity is, for example, a function of secondary descriptors and previously calculated primary topographic quantities.

[0106] Secondary topographic quantities are calculated by the mathematical model, with calibration step 101 allowing the constant coefficients of each function to be adjusted by minimizing the differences between the topographic quantities obtained from a given reference topography and the topographic quantities provided by the mathematical model.

[0107] The height 2000 and the angle 2031 of flank 203 depend, for example, on several widths 2030 of flank 203 and the corresponding angles of incidence 302. The length 2020 of the pattern 3010 depends, for example, on the secondary descriptor |D-D'| and the angle 2031 of flank 203, where D' is the primary descriptor of the right peak and D the primary descriptor of the left peak.

[0108] At the end of step 107 of method 100, the primary and secondary topographic dimensions are obtained for the pattern 3010 imaged in acquisition step 102. The topography of pattern 3010 from sample 301 is thus estimated, this estimate corresponding to model 200, whose topographic dimensions are known. For example, in the case of model 200 based on a rounded trapezoid, step 107 consists of providing the curve 200 that follows certain contours of the rounded trapezoid, corresponding to the previously calculated topographic dimensions.

[0109] The estimation of the topography of the entire sample 301 can, for example, be done by carrying out steps 102 to 107 of method 100 for each pattern 3010 of the sample 301.

[0110] In the case of a 200 model based on a trapezoid with rounded corners symmetrical with respect to an axis passing through the midpoint of the small base 202 and the midpoint of the large base 201, the mathematical model used includes, for example, the following equations to calculate the primary topographic quantities from a first image 1020: 2011 1 = w 0 + w 1 A − B 2021 1 = w 2 + w 3 C − E 2 + w 4 D − E 2030 1 = w 5 + w 6 B − D − e − B − D + w 7 2011 1 × 302 1 With : 2011 1 , the lower curvature of pattern 3010 corresponding to the first image 1020; 2021 1 , the upper curvature of pattern 3010 corresponding to the first image 1020; 2030 1 , the flank width of pattern 3010 corresponding to the first image 1020; 302 1 , the angle of incidence with which the first image 1020 is taken; A, B, C, D, E , the primary descriptors corresponding to the first image 1020; w 0 , w 1 , w 2 , w 3 , w 4 , w 5 , w 6 , parameters obtained during calibration.

[0111] The mathematical model used includes, for example, the following equations to calculate secondary topographic quantities from the first image and a second image: 2000 = w 8 + w 9 2030 2 − 2030 1 tan 302 2 − tan 302 1 2031 = w 10 + w 11 2030 2 − 2030 1 2030 1 tan 302 2 − 2030 2 tan 302 1 2020 = w 12 + w 13 E l − E r + w 14 D l − D r + w 15 e − tan 90 − 2031 With : 2000, the height of pattern 3010; 2030 1, the side width of pattern 3010 corresponding to the first image 1020 and 2030 2, the side width of pattern 3010 corresponding to the second image 1020; 302 1, the angle of incidence with which the first image 1020 is taken and 302 2, the angle of incidence with which the second image 1020 is taken; 2031, the side angle of pattern 3010; 2020, the length 2020 of the small base 202 of pattern 3010; Di, E l are the primary descriptors for the left peak of the 1031 derivative of the 1030 grey level profile of the first 1020 image or the second 1020 image and D r , E r are the primary descriptors for the right peak of the first 1020 image or the second 1020 image; w 8 , w 9 , w 10 , w 11 , w 12 , w 13 , w 14 , w 15 are the parameters obtained during calibration.

Claims

1. A method (100) for estimating local topography of a sample (301) including at least one pattern (3010), the method (100) comprising: - for each pattern (3010) of the sample (301): ∘ a step (102) of acquiring, by a scanning electron microscope (300), a plurality of images (1020) of the pattern (3010), the images (1020) being taken at different angles of incidence (302); ∘ for each image (1020) acquired: ▪ a step (103) of calculating a grey level profile (1030) along a given axis (1021); ▪ a step (104) of placing a plurality of primary descriptors (A, B, C, D, E) on the greyscale profile (1030) calculated; ▪ a step (105) of calculating secondary descriptors from the primary descriptors (A, B, C, D, E); ▪ a step (106) of using a mathematical model to calculate primary topographic quantities (2011, 2021, 2030) from the secondary descriptors; ∘ a step (107) of estimating local topography of the pattern (3010) consisting in using the mathematical model to calculate secondary topographic quantities (2031, 2020, 2000) from the primary topographic quantities (2011, 2021, 2030) and the secondary descriptors previously calculated.

2. The method according to claim 1, characterised in it includes a first step (101) of calibrating the mathematical model from reference topographies.

3. The method according to claim 2, characterised in that the reference topographies are obtained using at least one microscopy technique different from scanning electron microscopy.

4. The method according to claim 3, characterised in that the microscopy techniques can be selected from transmission electron microscopy or atomic force microscopy.

5. The method according to claim 2, characterised in that the reference topographies are obtained by digital simulation.

6. The method according to any of the preceding claims, characterised in that the topography of a pattern (3010) is modelled using a trapezium with rounded corners.

7. The method according to claim 6, characterised in that the trapezium with rounded corners includes a small base (202), a large base (201) and two flanks (203) and can be characterised by the following eight topographical quantities: a right low curvature (2011), a left low curvature (2011), a right high curvature (2021), a left high curvature (2021), a height (2000), a right flank angle (2031), a left flank angle (2031) and a length (2010, 2020) at a given height.

8. The method according to any of the preceding claims, characterised in that the primary descriptors (A,B,C,D,E) are determined from particular values of the derivative (1031) of the grey level profile (1030) along the given axis (1021).

9. The method according to any of the preceding claims, characterised in that a primary topographic quantity (2011, 2021, 2030) is a linear combination of secondary descriptors and the angle of incidence (302) of a single image (1020) acquired.

10. The method according to any of the preceding claims, characterised in that a secondary topographic quantity (2031, 2020, 2000) is a function of primary topographic quantities (2011, 2021, 2030) and angles of incidence (302) of several images (1020) acquired and optionally secondary descriptors of several images (1030) acquired.

11. A computer program product comprising instructions which, when the program is executed by a computer, cause the same to implement the steps of the method (100) according to any of the preceding claims except for the acquisition steps.

12. A computer-readable recording medium comprising instructions which, when executed by a computer, cause the same to implement the steps of the method (100) according to any of claims 1 to 10 except for the acquisition steps.