This application is a National Stage of International patent application PCT/EP2016/067112, filed on Jul. 19, 2016, which claims priority to foreign European patent application No. EP 15306181.7, filed on Jul. 20, 2015, the disclosures of which are incorporated by reference in their entirety.
The invention relates to the field of micro- and nano-manufacturing, and in particular to that of direct-writing (or “maskless”) lithography, such as electron beam lithography (EBL). More precisely, the invention relates to a method for transferring a pattern onto a substrate by direct writing by means of a particle or photon beam using a spatially-dependent exposure dose (dose modulation), and also to a computer program product and an apparatus for carrying out such a method.
The expression “direct writing” will be used to designate all the techniques wherein the surface of a substrate is locally modified by directing a narrow or shaped particle or photon beam onto it, without making use of a mask. The meaning of this expression is not limited to the case where the substrate is a semiconductor wafer and also includes, inter alia, the writing of photolithography masks.
Electron beam (e-beam) lithography is the most commonly used technique for performing direct writing—or maskless—lithography. It allows achieving a spatial resolution of a few tens of nanometers or less, and is particularly well suited for manufacturing photolithography masks.
Electron beam 21 may be a narrow circular beam, in which case the pattern is projected onto the resist point by point, using raster or vector scanning. In industrial applications, however, it is often preferred to use “shaped beams”, which are larger and have a rectangular or triangular section. In this case, the pattern to be transferred onto the substrate is decomposed into a plurality of elementary shapes corresponding to the section of the beam. An elementary shape can then be transferred by a single shot—or a series of successive shots for a fixed position of the substrate—with a significant acceleration of the process.
In the real world, the dose actually received by the substrate surface does not fall abruptly at the edges of the beam spot, but it decreases smoothly. Moreover, electrons interacting with the resist and/or the substrate experience forward and backward scattering which broadens the dose distribution beyond the theoretical limits of the incident beam spot; in particular, backscattered electrons can travel by a distance of a few micrometers. The influence of the interactions of primary electrons with the substrate and the resist on the dose distribution is known as “proximity effects”.
On
The correction of proximity effects is essential for ensuring an accurate reproduction of the target pattern on the substrate. It requires the development of an accurate physical model including:
Once the physical model is calibrated, it is possible to proceed to the stage of correcting, or compensating, the electronic proximity effects (PEC). There are three possible types of correction:
The paper by Takayuki Abe et al. “High-Accuracy Proximity Effect Correction for Mask Writing”, Japanese Journal of Applied Physics, Vol. 46, No. 2, 2007, pp. 826-833 describes a commonly used method of performing dose correction modulation. According to the simplest form of this method, the normalized correction dose at a position r=(x,y) of the surface of the sample is given by:
where the integral is computed over the whole pattern to be transferred (or the relevant portion thereof) and the distribution g(r) of the energy deposited by backscattered electron satisfies the normalization condition ∫∫−∞+∞g(r)dr=1.
Typically, g(r) is a Gaussian distribution of standard deviation σb, typically truncated at 3σb, taking into account long-range effects (mainly backscattering):
g(r)=A·exp[(−(r−r′)2/σb2)] (eq. 2)
where A is a normalization constant.
If the pattern density is defined by:
Density=∫∫patterng(r−r′)·dr′2 (eq. 3)
then (eq. 1) can be rewritten in the simpler form:
It has been found that dose modulation is simpler to implement than geometry modulation, but less precise. The invention aims at overcoming this drawback of the prior art; more precisely it aims at improving the precision of the received dose modulation on one- and two-dimensional critical shapes (i.e. with narrow width, space or density) without increasing—or even reducing—its implementation complexity.
Document US 2014/077103 describes a method of performing direct writing using a charged particle beam, wherein different dose correction formulas are applied for elementary shapes situated inside the pattern or at its periphery.
Document US 2007/228293 describes a method of performing direct writing using a charged particle beam, wherein a dose correction factor is computed as a function of both a pattern density and of a parameter depending on the shape of the pattern.
More specifically, document JP 2012/212792 describes a method of performing direct writing using a charged particle beam, wherein the dose is computed by taking into account a line width and a pattern density. A “line width” is not easily defined for every kind of pattern.
An object of the present invention, achieving these aims, is a method for transferring a pattern onto a substrate by direct writing by means of a particle or photon beam, the method comprising:
characterized in that said step of producing a dose map includes:
According to particular embodiments of the invention
Another object of the invention is a computer program product comprising computer-executable code for causing a computer to produce a dose map, associating an emitted dose to each of a plurality of elementary shapes of a pattern to be transferred onto a substrate by direct writing by means of a particle or photon beam, by computing at least two metrics for each of said elementary shapes of the pattern, and determining the emitted dose associated to each of said elementary shapes of the pattern as a function of said metrics. The computer program product may further comprise computer-executable code for causing a computer to determine a relation between said metrics and an emitted dose by using numerical simulations or experimental tests to find optimal doses for a plurality of reference patterns, each being representative of a different set of values of said metrics, according to a predetermined optimality criterion. The computer program product may further comprising computer-executable code for carrying out a method as outlined above by causing a computer to drive a source of said particle or photon beam in order to expose said substrate according to said pattern with a spatially-dependent dose depending on said dose map.
Additional elementary shapes and advantages of the present invention will become apparent from the subsequent description, taken in conjunction with the accompanying drawings, wherein:
The invention will be described with reference to shaped-beam EBL (including variable-shaped beams), but it is not limited to this case. Generalization to vector or raster scan lithography or to other micro- or nano-manufacturing techniques involving particles (not necessarily electrons) or photon beams is straightforward. In the case of scanning beam lithography, the “elementary shapes” of the pattern for which the emitted dose has to be calculated are the projections on the substrate of the narrow particle or photon beam.
The present inventors have realized that the conventional (e.g. Abe's) approach to emitted Dose Modulation is not entirely satisfactory, especially for narrow patterns, because the emitted dose is only computed as a function of the density, and therefore only depends on a “long range” metric, without taking into account local or semi-local features of the pattern. The present invention overcomes this limitation by determining the dose as a function of both the density and the critical dimension of each shape. The idea at the basis of the invention is the following: an “optimal” dose is computed for each of a plurality of reference patterns, each characterized by at least two pattern metrics, one depending on very local (short range) features of the pattern and the other one depending in longer-range features. For instance, the metrics may be density and a critical dimension, or a long-range density and a short-range density. The reference patterns are chosen so that they sample the parameter plane (or, more generally, hyperplane) defined by these metrics. This way, a look-up table can be obtained relating (first metrics, second metrics) pairs to the corresponding optimal exposure doses. The look-up table is then used to determine the dose associated to each specific EBL shot, by direct reading or interpolation.
Contrarily to the methods of US 2014/077103 and US 2007/228293, according to the invention the optimal dose associated to a geometrical shape (or “shot”) of the pattern does not only depend on the shape itself, but on local features of the pattern situated in its proximity. The calibration process is much simpler than in the case of JP 2012/212792, as the dose is directly calculated from the PSFs.
As illustrated on
Defining the critical dimension for a non-trivial pattern is less straightforward. A possible way of doing it is illustrated on
where A(Di) is the area of the disk Di, χPattern is the indicator function of the pattern (χPattern=1 inside the pattern, 0 outside) and χDi is the indicator function of the ith disk (χDi=1 inside the disk Di, 0 outside). Clearly, OFi=1 when the disk is completely contained within an elementary shape of the pattern and OFi<1 when it stretches beyond the limits of such an elementary shape. The critical dimension of the elementary shape can then be defined as:
the index “i” taking the smallest value for which OFi<1.
This method of computing the critical dimension is not an essential feature of the invention, and alternative approaches can be devised.
The POI may be the geometrical center of a shaped spot, constituting an “elementary shape” of the pattern; in general, shape PF is constituted by a plurality of adjacent, or partially overlapping, shots. By applying the methods described above with reference to
Spacing depends on both the critical dimension and the pattern density. The look-up table could also express the optimal dose as a function of critical dimension and spacing, or of pattern density and spacing, instead of using critical dimension and density. Indeed, the look-up table could be based on any two functions of critical dimension and pattern density (provided they are not simply proportional to each other). It is also possible to take into account additional parameters by using a multidimensional look-up table.
The inventive method is typically implemented by executing a suitable program on a computer. Said computer may directly drive the EBL apparatus (cf. computer or processor 40 on
The invention has been described with reference to a particular embodiment, but is not limited to it.
For example, the reference patterns, or at least some of them, may not necessarily be one-dimensional (i.e. line) gratings; admissible reference patterns may include bi-dimensional gratings (e.g. regular dot patterns, or grids), or even non-grating pattern, e.g. issued from real designs.
Critical dimension and pattern density are only two of the possible metrics which can be used to compute the optimal emitted dose. Other metrics may be used for this purpose, such as SPACE (defined above); other suitable metrics are described in the following papers:
It is also possible to use two (or more) densities calculated using different ranges.
The optimal emitted dose may be computed as a function a plurality (i.e. two or more) of said metrics. For instance, the critical dimension may be replaced by a short range density defined as:
Short range density=∫∫patterngSR(r−r′)·dr′ (eq. 7)
where
gSR(r)=ASR·exp[(−(r−r′)2/σa2)] (eq. 8)
ASR being a normalization constant and σa a parameter smaller than σb and typically of the same order of magnitude of the short-range PSF radius α, i.e. 0.1·α≤σa≤10·α. Using a small value for σa improves the accuracy of the method, but may lead to high dose values, and therefore to long writing processes. Conversely, large σa values reduce the maximum dose value and therefore accelerate writing, but at the expense of accuracy (which may be improved using geometric proximity correction without adverse effects on writing speed).
A look-up table constitutes a useful tool for representing the relation between a given set of values of the metrics and the corresponding optimal emitted dose, but there are alternatives. For example, it is possible to determine the coefficients of a multi-variable polynomial function expressing the dose as a function of the metrics, storing these coefficients in a computer memory and using them for calculating the optimal emitted dose instead of reading it from a pre-computed table.
It is also possible to separately compute a first component of the emitted dose as a function of a first metrics and a second component of the emitted dose as a function of a second metrics, and to combine them.
Moreover, dose modulation may serve other purposes than maximizing the similarity between a reference and a transferred pattern. Said similarity may be ensured using geometry modulation, and dose modulation may then be used to optimize other suitable criteria—i.e. for reducing the exposition time, minimizing the simulation error, reducing the roughness of the edges of the elementary shapes, etc.
Number | Date | Country | Kind |
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15306181 | Jul 2015 | EP | regional |
Filing Document | Filing Date | Country | Kind |
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PCT/EP2016/067112 | 7/19/2016 | WO | 00 |
Publishing Document | Publishing Date | Country | Kind |
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WO2017/013085 | 1/26/2017 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
9224577 | Schiavone et al. | Dec 2015 | B2 |
20050273753 | Sezginer | Dec 2005 | A1 |
20070114463 | Nakasugi | May 2007 | A1 |
20070228293 | Ogasawara | Oct 2007 | A1 |
20120211675 | Tu | Aug 2012 | A1 |
20130275098 | Tortai et al. | Oct 2013 | A1 |
20140059503 | Belledent | Feb 2014 | A1 |
20140077103 | Matsumoto | Mar 2014 | A1 |
Number | Date | Country |
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2 952 963 | Dec 2015 | EP |
2012-212792 | Nov 2012 | JP |
Number | Date | Country | |
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20180204707 A1 | Jul 2018 | US |