Lithographic apparatus can be used, for example, in the manufacture of integrated circuits (ICs). In such a case, the mask may contain a circuit pattern corresponding to an individual layer of the IC, and this pattern can be imaged onto a target portion (e.g., comprising one or more dies) on a substrate (silicon wafer) that has been coated with a layer of radiation-sensitive material (resist). In general, a single wafer will contain a whole network of adjacent target portions that are successively irradiated via the projection system, one at a time. In one type of lithographic projection apparatus, each target portion is irradiated by exposing the entire mask pattern onto the target portion in one go; such an apparatus is commonly referred to as a wafer stepper. In an alternative apparatus, commonly referred to as a step-and-scan apparatus, each target portion is irradiated by progressively scanning the mask pattern under the projection beam in a given reference direction (the “scanning” direction) while synchronously scanning the substrate table parallel or anti-parallel to this direction. Since, in general, the projection system will have a magnification factor M (generally >1), the speed V at which the substrate table is scanned will be a factor M times that at which the mask table is scanned. More information with regard to lithographic devices as described herein can be gleaned, for example, from U.S. Pat. No. 6,046,792, incorporated herein by reference.
In a manufacturing process using a lithographic projection apparatus, a mask pattern is imaged onto a substrate that is at least partially covered by a layer of radiation-sensitive material (resist). Prior to this imaging step, the substrate may undergo various procedures, such as priming, resist coating and a soft bake. After exposure, the substrate may be subjected to other procedures, such as a post-exposure bake (PEB), development, a hard bake and measurement/inspection of the imaged features. This array of procedures is used as a basis to pattern an individual layer of a device, e.g., an IC. Such a patterned layer may then undergo various processes such as etching, ion-implantation (doping), metallization, oxidation, chemo-mechanical polishing, etc., all intended to finish off an individual layer. If several layers are required, then the whole procedure, or a variant thereof, will have to be repeated for each new layer. Eventually, an array of devices will be present on the substrate (wafer). These devices are then separated from one another by a technique such as dicing or sawing, whence the individual devices can be mounted on a carrier, connected to pins, etc.
For the sake of simplicity, the projection system may hereinafter be referred to as the “optics;” however, this term should be broadly interpreted as encompassing various types of projection systems, including refractive optics, reflective optics, and catadioptric systems, for example. The radiation system may also include components operating according to any of these design types for directing, shaping or controlling the projection beam of radiation, and such components may also be referred to below, collectively or singularly, as a “lens.” Further, the lithographic apparatus may be of a type having two or more substrate tables (and/or two or more mask tables). In such “multiple stage” devices the additional tables may be used in parallel, or preparatory steps may be carried out on one or more tables while one or more other tables are being used for exposures. Twin stage lithographic apparatus are described, for example, in U.S. Pat. No. 5,969,441, incorporated herein by reference.
The photolithographic masks referred to above comprise geometric patterns corresponding to the circuit components to be integrated onto a silicon wafer. The patterns used to create such masks are generated utilizing CAD (computer-aided design) programs, this process often being referred to as EDA (electronic design automation). Most CAD programs follow a set of predetermined design rules in order to create functional masks. These rules are set by processing and design limitations. For example, design rules define the space tolerance between circuit devices (such as gates, capacitors, etc.) or interconnect lines, so as to ensure that the circuit devices or lines do not interact with one another in an undesirable way. A critical dimension of a circuit can be defined as the smallest width of a line or hole or the smallest space between two lines or two holes. Thus, the CD determines the overall size and density of the designed circuit.
Due to an accuracy requirement for optical proximity correction (OPC) at very low k1 (<0.4), more accurate representation of the performance of the exposure tool in simulations has become critical to accommodate the reduction of device pattern dimensions. As is known, the modeling of complex optical imaging and patterning processes often relies on empirical models with adjustable parameters that have to be calibrated using measured data. Such empirical models are used in photolithography and advanced imaging applications, including optical proximity correction (OPC) of layouts in photolithography, post-OPC layout verification, die-to-database photomask pattern inspection, etc. The empirical models of the imaging process have adjustable parameters that are optimized, or “calibrated”, using measured data. In other words, the adjustable parameters are adjusted until the simulated imaging result matches the actual imaging result (i.e., the measured data) within some predefined error criteria. In case of OPC in lithographic patterning, the calibration data may be, for example, CD SEM measurements of patterns from semiconductor wafers. In case of mask inspection, the calibration data may be, for example, images of the mask measured on the inspection tool.
Although physically based models of lithographic patterning are well understood, their use in modeling full-chip designs is limited by available computation time and resources. Consequently, less complicated and more efficient empirical patterning models are typically used in OPC applications. As noted, empirical models have adjustable parameters that are optimized, or “calibrated”, using measured patterns and/or critical dimension (CD) information from semiconductor wafers patterned with the lithographic process of interest. Since each empirical model does not completely capture the physics of the patterning process, its usefulness depends on how well it can match the observed measurements and predict the process behavior.
Currently, in existing prior art imaging models, the resist performance is modeled by only considering the optical intensity at given points within the resist. This can be done, for example, by convolving the optical intensity with known curves, such as a Gaussian curve, so as to model the performance of the resist. However, this approach wholly neglects the non-linear effects of the resist, which are dependent, for example, on the pattern and resist type. As such, the current imaging model techniques do not accurately model the resist performance and thereby exhibit an inherent error with respect to modeling resist performance. As the design requirements continue to become more demanding, there is a continuing need for the simulation models to be more accurate.
Accordingly, there exists a need for a modeling process which considers and models actual resist performance so as to produce a simulation model capable of producing simulation results exhibiting increased accuracy relative to the actual imaging performance.