Electrical computers and digital processing systems: memory – Addressing combined with specific memory configuration or... – Addressing cache memories
Reexamination Certificate
2001-09-10
2004-05-18
Siek, Vuthe (Department: 2643)
Electrical computers and digital processing systems: memory
Addressing combined with specific memory configuration or...
Addressing cache memories
C716S030000, C703S005000, C703S006000, C430S005000
Reexamination Certificate
active
06738859
ABSTRACT:
BACKGROUND OF THE INVENTION
In lithography, an exposure energy, such as ultraviolet light that is generated in an optical system, is passed from an aperture of the system through a mask (or reticle) and onto a target such as a silicon substrate. The mask typically may contain opaque and transparent regions formed in a predetermined pattern. The exposure energy exposes the mask pattern, thereby forming an aerial image of the mask. The aerial image is then used to form an image onto a layer of resist formed on the target. The resist is then developed for removing either the exposed portions of resist for a positive resist or the unexposed portions of resist for a negative resist. This forms a patterned substrate. A mask typically may comprise a transparent plate such as fused silica having opaque (chrome) elements on the plate used to define a pattern. A radiation source illuminates the mask according to well-known methods. The radiation transmitted through the mask and exposure tool projection optics forms a diffraction-limited latent image of the mask features on the photoresist. The patterned substrate can then be used in subsequent fabrication processes. In semiconductor manufacturing, such a patterned substrate can be used in deposition, etching, or ion implantation processes, to form integrated circuits having very small features.
In a manufacturing process using a lithographic projection apparatus, a pattern in a mask is imaged onto a substrate, which is at least partially covered by a layer of radiation-sensitive material (resist). Generally, lithographic patterning processes are understood by those who practice the profession. Information regarding exemplary processes may be obtained, for example, from the book “Microchip Fabrication: A Practical Guide to Semiconductor Processing”, Third Edition, by Peter van Zant, McGraw Hill Publishing Co., 1997 ISBN 0-07-067250-4.
As the size of lithographically fabricated structures decreases, and the density of the structures increases, the cost and complexity of designing masks additionally increases. One method of reducing costs of lithographic fabrication is by optimizing the lithographic design with a lithographic simulation step prior to the actual manufacturing step. One specific method of lithographic simulation is drawn to simulating the aerial image of the mask. The aerial image is defined as an intensity distribution of light just prior to reaching the resist on a surface of a substrate, when the substrate is exposed via the mask in an exposure apparatus. In order to simulate the aerial image, a layout of a mask and exposure conditions (non-limiting examples include NA: Numerical Aperture, &sgr; (sigma): Partial Coherence Factor) of the lithographic apparatus are typically required as input parameters.
Lithographic apparatus may employ various types of projection radiation, non-limiting examples of which include light, ultra-violet (“UV”) radiation (including extreme UV (“EUV”), deep UV (“DUV”), and vacuum UV (“VUV”)), X-rays, ion beams or electron beams. The following have been considered exemplary exposure sources. Light may generally refer to certain mercury emissions, i.e., wavelengths of 550 nm for the f-line, 436 nm for the g-line, and 405 mn for the h-line. Near-UV or UV generally typically refer to other mercury emissions, i.e., 365 nm for the i-line. DUV generally refers to excimer laser emissions, such as KrF (248 nm) and ArF (193 nm). VUV may refer to excimer laser F
2
, i.e., 157 nm, Ar
2
, i.e., 126 nm, etc. EUV may refer to 10-15 nm. This last portion of the electromagnetic spectrum is very close to “soft X-rays” but has been named as “EUV”, possibly to avoid the bad reputation of X-ray patterning. Soft X-rays may refer to 1-15 nm, which may typically be used in X-ray lithography.
Depending on the type of radiation used and the particular design requirements of the apparatus, the projection system may be for example, refractive, reflective or catadioptric, and may comprise vitreous components, grazing-incidence mirrors, selective multi-layer coatings, magnetic and/or electrostatic field lenses, etc; for simplicity, such components may be loosely referred to in this text, either singly or collectively, as a “lens”.
When the resist is exposed by the aerial image, there is an additional variable in that some of the exposure light is reflected back by the surface of the substrate, and then absorbed by the resist. Accordingly, not only the resist characteristics (regarding, for example, refractive index: Dill's A,B,C) but also parameters regarding the characteristics of the substrate (e.g., refractive index) should be included as input parameters for simulating the latent image.
The so-called Hopkins model treats the electric field forming the image typically as a scalar and assumes the object being imaged is sufficiently thin so that its effect on the incident field is represented by a multiplicative function. It is advantageous to perform the image formation analysis in the Fourier domain (frequency space) in order to deal with the pupil function of the imaging system rather than the amplitude response function, and with the angular distribution or “effective source” rather than with the mutual intensity.
There are several computer programs commercially available that calculate aerial images based on the Hopkins model. For example, the University of California at Berkeley, Department of Electrical Engineering and Computer Science, Berkeley, Calif., 94720, offers a program called SPLAT.
The Hopkins model is used to model the imaging of drawn design features under partially coherent illumination. A major problem in modeling aerial images under partially coherent illumination is the necessity to superimpose and add the effect of each individual illumination source that makes up the partially coherent source. In the Hopkins model, a two-dimensional by two-dimensional transmission cross-coefficient function (“TCC”) is pre-calculated, which captures all the effects of the lithographic projection apparatus, including NA, sigma, etc. As taught, for example in Born & Wolf, p. 603, once a TCC is known, systems with partially coherent illumination can be modeled by integrating the TCC over the Fourier transform of the transmission function for the geometrical layout feature under illumination.
Fundamentally, the TCC is a two-dimensional by two-dimensional correlation function with a continuous set of arguments. In practice, an assumption can be made that the feature patterns to be imaged are periodic in space. For such periodic patterns, the TCC has a large, but discrete, set of arguments. The TCC can then be represented as a matrix, with discrete columns and rows. For typical features interesting to the lithographer the size of this matrix is tremendous and restricts the scale and size of features that can be simulated. It is a purpose of any simulation algorithm based on the Hopkins model to reduce the size of this matrix by approximation, while retaining a reasonable degree of accuracy.
An exemplary projection lithography system is illustrated in
FIGS. 1A and 1B
. In
FIG. 1A
, light from illumination source
102
is focussed by condenser
104
. The condensed light passes through the mask
106
, then through the pupil
108
and onto the substrate
110
. As shown in
FIG. 1B
, substrate
110
may comprise a top anti-reflective coating
112
, a resist
118
, a bottom anti-reflective coating
117
, a top substrate layer
114
and a plurality of other substrate layers. As indicated in
FIG. 1B
, the focal plane may lie within the resist
118
.
In the past, several numerical techniques have been applied to reduce the size of the TCC to reasonable scales. In one instance singular value decomposition has been applied to decompose the TCC into its eigenspectrum, sort the resulting eigenvectors in decreasing magnitude of their eigenvalues, and only retain a finite number of eigenvectors in order to approximate the TCC. An exemplary method for optical simulation for the system of
FIG. 1A
, that uses the Hopkins model, is
ASML Masktools B.V.
Dimyan Magid Y
McDermott & Will & Emery
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