JP5638038B2 - Determination method and program - Google Patents

Description

The present invention relates to a determination method and a program to thus determine the value of the exposure parameters of the exposure device to the computer.

2. Description of the Related Art Conventionally, a projection exposure apparatus that exposes a reticle (mask) pattern to an object to be exposed such as a single crystal substrate for a semiconductor wafer or a glass substrate for a liquid crystal display (LCD) by a projection optical system has been used. To meet inexpensively supply the demand a large number of electronic devices, production of the device as a final product obtained from the object to be exposed (i.e., semiconductor chips such as LSI or VLSI, CCD, LCD, magnetic sensor, a thin film magnetic head) How to do it is necessary to increase the yield. Such a device manufacturing method includes, for example, processes such as exposure, development, and etching. Conventional exposure apparatuses perform exposure in consideration of not only the resolution for accurately resolving a reticle pattern on an object to be exposed but also the influence of other processes in the device manufacturing method.

  It is important to optimize exposure conditions and reticle patterns in order to improve resolution (see, for example, Patent Documents 2 and 3). The optimization of the reticle pattern is performed by, for example, optical proximity correction (OPC). As a general evaluation index of conventional resolution, line width (Critical Dimension: CD) uniformity is known (see, for example, Patent Documents 4 and 5). Patent Document 1 proposes a technique (Process Proximity Control: PPC) for correcting an etching error caused by pattern density in advance by adding it to a mask design. For efficient optimization, a simulation or a simulator may be used without actually exposing the object to be exposed.

  Other conventional techniques include, for example, Non-Patent Documents 1 and 2. Non-Patent Document 1 describes that a design of a via / chain, which is a test pattern, is made based on various design rules, and the quality of the design rules and OPC is judged by measuring resistance and the like.

JP 9-319067 A JP 2005-26701 A JP 2002-319539 A Japanese Patent Laid-Open No. 2003-257819 Japanese Patent Laid-Open No. 2005-094015

SPIE5379-15 Design rule optimization for 65-nm-node (CMOS5) BEOL using process and layout decomposition methodology Ever Seevinck, France J. et al. List, and JanLohstroh, "Static-Noise Margin Analysis of MOS SRAM Cells", IEEE Journal of Solid-State Circuits, Vol. SC-22, NO. 5, October 1987

  As the miniaturization progresses, the interaction between processes in the device manufacturing method cannot be ignored, and the yield management of only exposure using CD uniformity as an index cannot always improve the device yield. Whether a device as an electronic component is a good product or a defective product depends on the electrical characteristics of the device. A typical example of the electrical characteristic is a power supply voltage characteristic as a change in voltage with respect to the power supply of the device, but other characteristics such as durability, resistance, and capacitance may be used.

Examples of electrical characteristics include Static Noise Margin (SNM) (Non-Patent Document 2) in the case of SRAM (Static RAM), variations in _VTH at transistor gates, and the like. The electrical characteristics to be verified vary depending on the type of device.

  However, the evaluation index regarding the resolution does not necessarily correspond to the electrical characteristics. For example, the device may be a good product in terms of electrical characteristics even if the CD uniformity is poor, or the device may be a defective product in terms of electrical characteristics even if a predetermined CD uniformity is satisfied.

Accordingly, the present invention is the value of the exposure parameters for high yield manufacturing a device as a final product to provide a determination method and a program computer thus determined.

Method of determining the one aspect of the present invention is a determining method for thus determining the value of the exposure parameter in the computer of an exposure apparatus for exposing a pattern of a reticle onto the object to be exposed with light from a light source, the exposure parameters A step of setting a value of, and calculating an optical image of the pattern of the reticle using the set exposure parameter value, thereby obtaining an electrical characteristic of the pattern formed on the object to be exposed; Using the information representing the relationship between the electrical characteristics of the pattern formed on the object to be exposed and the exposure parameters, the set exposure is performed so that the required electrical characteristics satisfy the predetermined electrical characteristics. An adjustment step for adjusting the value of the parameter, wherein the adjustment step uses an optical simulation to calculate the value of the first exposure parameter depending on the optical system. And adjusting, characterized by a step of adjusting the value of the second exposure parameters that do not depend on the optical system without using an optical simulation.

  Further objects and other features of the present invention will become apparent from the preferred embodiments described below with reference to the accompanying drawings.

  According to the present invention, a device as a final product can be manufactured with a high yield.

It is a flowchart of the optimization algorithm of this invention. It is a flowchart for demonstrating the device manufacturing method of this invention. 3 is a detailed flowchart of Step 4 shown in FIG. 2. It is a schematic block diagram of the exposure system which performs the optimization method shown in FIG. It is a schematic block diagram of the modification of the exposure system shown in FIG. FIG. 4 is a circuit diagram of an SRAM as an example of a device manufactured in FIGS. 2 and 3. It is a graph explaining the characteristic of Static Noise Margin (SNM) of SRAM shown in FIG. FIG. 7 is a circuit diagram of the SRAM shown in FIG. 6 assuming an equivalent circuit of switching noise. It is a graph explaining the magnitude | size of SNM when Cell Ratio is changed. 7 is a cell structure of the SRAM shown in FIG. 11A to 11E show the configuration layers of the SRAM cell shown in FIG. FIG. 12A to FIG. 12D are diagrams showing the relationship between the degeneration of the gate / line end and the NA. FIGS. 13A to 13C are diagrams showing the relationship between the degeneration of the gate / line end and the exposure amount. FIG. 14A to FIG. 14B are diagrams of overlapping of the gate layer and the source-drain layer.

  Embodiments of the present invention will be described below with reference to the accompanying drawings. Here, FIG. 1 is a flowchart of the optimization algorithm of the present embodiment. FIG. 4 shows an exposure system 1 that executes the optimization algorithm shown in FIG. As shown in FIG. 4, the exposure system 1 includes a processing system 10 in an FAB (factory), input units 20a to 20c, a calculation system 30, and exposure apparatuses 40a to 40d.

The processing system 10 acquires reticle data and exposure conditions from the input units 20a to 20c, and selects an exposure apparatus suitable for each from the exposure apparatuses 40a to 40d. The exposure apparatuses 40a to 40d include a light source (ArF, KrF, EUV, etc.), an exposure method (scanner, stepper), illumination conditions (polarized illumination, effective light source, etc.), a projection optical system (lens system, catadio system, immersion system, etc.) ) And other data with different specifications and characteristics. Further, not only those data but also machine difference data in the same model exposure apparatus for those data is included. The processing system 10 acquires the characteristic data of these exposure apparatuses 40a to 40d in advance and stores them in a memory (not shown). The computing system 30 is a computer that executes the optimization algorithm shown in FIG. The arithmetic system 30 acquires the feature data of the selected exposure apparatus from the processing system, and optimizes the exposure parameters based on the electrical characteristics of the device as necessary. The processing system 10 acquires the exposure parameter optimization information from the calculation system 30 and sets it in the exposure apparatus.
(The FAB internal processing system and the computing system may be a single computer system inside or outside the FAB, or the computing system may be outside the FAB.)
Referring to FIG. 1, in the optimization algorithm of the present embodiment, first, a relationship between an exposure parameter for determining a mode for exposing an object to be exposed and an electrical characteristic obtained from the object to be exposed is acquired (step 1002). ). In this embodiment, the power supply voltage characteristic as a change in voltage with respect to the power supply of the device is used as the electrical characteristic.

  The exposure parameters include, for example, the numerical aperture (NA) of the projection optical system, exposure amount, focus, Zernike coefficient, pupil transmittance, effective light source distribution, telecentricity, polarization degree, polarization degree image height variation, slit profile, and light source wavelength. There are distribution, vertical magnification, horizontal magnification, shot rotation, eccentric distortion, and the like.

  As will be described later, the electrical characteristics can be evaluated without using a Monte Carlo simulation or the like to actually complete the device. The electrical characteristics of the device tend to greatly affect the yield as the memory cell size is reduced in future miniaturization. The main factors affecting the electrical characteristics are as follows. That is, first, the amount of variation due to manufacturing factors may increase with respect to the design dimensions of the gate width and gate length. Second, since the gate size is small, variations in ion implantation dose may not be negligible. Third, variations in gate film thickness and gate film dielectric constant may not be negligible.

  On the other hand, some electrical characteristics are known to be associated with a specific evaluation index. For example, according to Non-Patent Document 1, the yield deteriorates due to line end shortening (LES) or the like. Here, “LES” refers to a phenomenon in which the tip of the line pattern is not resolved due to focus variation. LES occurs when the OPC cannot be sufficiently arranged due to the device layout. Regarding the relationship between LES and electrical characteristics, for example, when LES occurs in the gate layer, electrical characteristics including resistance change due to a change in gate length. Other phenomena of this type include line edge roughness (LER) related to SNM and side wall angle (SWA), which also affect the electrical characteristics because they change the shape of the circuit. It is common in the point to do.

  Step 1002 obtains the above relationship by, for example, measuring the electrical characteristics after creating an actual device by changing various exposure parameters. An embodiment of a device manufacturing method will be described with reference to FIGS. Here, FIG. 2 is a flowchart for explaining the manufacture of a semiconductor device (a semiconductor chip such as an IC or LSI, or a liquid crystal panel or a CCD). In step 1 (circuit design), a semiconductor device circuit is designed. In step 2 (reticle fabrication), a reticle on which the designed circuit pattern is formed is fabricated. On the other hand, in step 3 (wafer manufacture), a wafer is manufactured using a material such as silicon. Step 4 (wafer process) is called a pre-process, and an actual circuit is formed on the wafer by lithography using the prepared reticle and wafer. The next step 5 (assembly) is called a post-process, and is a process for forming a semiconductor chip using the wafer produced in step 4, and is a process such as an assembly process (dicing, bonding), a packaging process (chip encapsulation), or the like. including. In step 6 (inspection), the semiconductor device manufactured in step 5 undergoes inspections such as an operation confirmation test and a durability test. Through these steps, the semiconductor device is completed and shipped (step 7).

FIG. 3 is a detailed flowchart of the wafer process in Step 4 of FIG. In step 11 (oxidation), the surface of the wafer is oxidized. In step 12 (CVD), an insulating film is formed on the wafer surface. In step 13 (electrode formation), an electrode is formed on the wafer by vapor deposition or the like. In step 14 (ion implantation), ions are implanted into the wafer. In step 15 (resist process), a photosensitive material is applied to the wafer. Step 16 (exposure) uses the exposure apparatus to expose a reticle pattern onto the wafer. In step 17 (development), the exposed wafer is developed. In step 18 (etching), portions other than the developed resist image are removed. In step 19 (resist stripping), the resist that has become unnecessary after the etching is removed. In step 20 (electric characteristic measurement), the electric characteristics of the device are measured . By repeating these steps, multiple circuit patterns are formed on the wafer.

  Next, an exposure parameter as an initial state is set (step 1004). The exposure parameter set as the initial state may be set so as to maximize the exposure margin.

  Next, it is determined whether or not the device obtained from the set exposure parameters has a predetermined electrical characteristic (step 1006). Such a determination may be obtained by actually manufacturing a test chip and measuring the electrical characteristics of the test chip, or may be obtained by simulation. Such simulation can use, for example, Monte Carlo simulation for each layer of the device.

  Hereinafter, the SNM in the SRAM will be described. The SRAM is used as a cache memory for connecting the CPU and the DRAM to increase the speed and efficiency of the entire system because of its high processing speed. A DRAM requires a refresh operation at regular intervals to hold data, whereas an SRAM employs an electronic circuit called a “flip-flop”. Therefore, as long as the power is turned on, data can be held statically without refreshing.

  A general circuit diagram of the SRAM is shown in FIG. At the time of writing data in the SRAM, first, when the state of the word line WL is set to H (High: voltage is applied), the states of the NMOS transistors Qn3 and Qn4 are turned on. In this state, when the state of the bit line line BL1 is set to H and the state of BL2 is set to L (Low: no voltage is applied), the switches of the NMOS transistor Qn2 and the PMOS transistor Op1 are turned on. In this way, “1” is written to the left node and “0” is written to the right node. If the state of BL1 is L and the state of BL2 is H, “0” is written to the left node and “1” is written to the right node.

  At the time of data retention in the SRAM, the state of the word line WL is set to L, thereby turning off the states of Qn3 and Qn4 and maintaining the write information as long as Vcc is maintained (as long as the power is maintained). The The reason why the write information is maintained is that charges are accumulated by the SRAM cell acting as a capacitor.

  At the time of reading data in the SRAM, the state of the word line WL is again set to H, whereby the states of Qn3 and Qn4 are turned on. In the state of the left node “1” and the right node “0”, a voltage is applied to BL1, and data can be read by detecting the voltage. This voltage is detected by a sense amplifier circuit. The sense amplifier is a circuit for amplifying the voltage from the memory cell. Although not specifically shown in FIG. 6, the sense amplifier is arranged on the bit line line BL. The SRAM memory cell can be regarded as a very small capacitor, and the voltage read to the bit line is as small as several hundred mV. Therefore, it is necessary to amplify this voltage and amplify it to a level at which it can be handled as a digital level. A circuit that performs the amplification is a sense amplifier.

  In this manner, data is written, held, and read from the SRAM cell. However, when reading data from the SRAM, noise is generated in the SRAM cell because the switches of Qn3 and Qn4 are switched on at the moment when the state of the word line WL is set to H. Even if the state of the left node “1” and the right node “0” is originally detected due to noise, the state of the left node “0” and the right node “1” may be erroneously detected.

  There is SNM as an index of robustness against such readout noise. FIG. 7 is a graph representing the SNM of the SRAM. The curve shown in FIG. 7 is said to be a spectacle characteristic or a butterfly curve. This butterfly curve is expressed mathematically by considering the physical effect of each transistor of Qn1, Qn2, Qn3, Qn4, Op1, and Op2 so that the sum of the inflow current and the outflow current at ND1 becomes equal (Kirchhoff's law). Can be requested.

When the voltage of ND1 in FIG. 6 is V _A and the voltage of ND2 is V _B , the stable point 1 represents the state of the left node “0” and the right node “1”, and the stable point 2 represents the left node “ 1 ”and right node“ 0 ”.

When holding data, the voltage characteristics at the node are at some stable point. When the word line WL is changed from “L → H” in the stable point 1 state, the voltage V _A at the node 1 and the voltage V _{B at the} node 2 instantaneously attempt to transition to the stable point 2 state. Return to state. When the SNM is large, it is easy to return to the stable point 1 state, and when the SNM is small, it is difficult to return to the stable point 1. In addition, when the SNM is small, there is a possibility that the sense amplifier is erroneously detected by changing from the stable point 1 to the stable point 2 due to the influence of sudden charged particles. Therefore, the SRAM device is better when the SNM is larger.

  The model formula of SNM is described in detail in Non-Patent Document 2. According to Non-Patent Document 2, the SNM is derived from Equation (1) from Kirchhoff's equation and transistor characteristics in an SRAM cell in which an equivalent circuit of noise is arranged as shown in FIG.

Here, r in Equation 1, called the Cell Ratio, the driver transistor is a (gate width) / (gate length) beta _d, an access transistor (gate width) / (gate length) beta _a It is the one divided by. Driver transistors refer to Qn1 and Qn2 in FIG. Access transistors refer to Qn3 and Qn4 in FIG.

FIG. 9 shows the result of Monte Carlo simulation of the SNM in the case of r = 2, 3, and 4. Even if r is fixed, the SNM value varies depending on the power supply voltage V _DD and the inverter characteristics k and q. Therefore, it is necessary to perform simulation by varying the power supply voltage and the inverter characteristics. is there. In FIG. 9, it is shown that the cell ratio of 4 has a larger SNM and is excellent as a device.

Another example of electrical characteristics is _VTH variation. V _TH refers to a gate threshold voltage, and when the voltage applied to the gate exceeds the threshold voltage, the source and drain become conductive. Different values of _VTH within the cell affect device yield. By managing such V _TH, but it is possible to improve the yield of the device, V _TH changes due to various factors of the manufacturing process. Taking the cell circuit of the SRAM shown in FIG. 6 as an example, Qn1 and Qn2, Op1 and Op2, as Qn3 and Qn4, in a transistor having the same characteristics on design, the yield in the case where the gate threshold voltage _{V TH} varies Deterioration occurs. Such variations in V _TH, the gate film thickness and ion implantation amount, not only the factors other than the exposure apparatus, such as a gate electrode material, variations in the gate width and gate length, the exposure apparatus such as a superposition of between the upper and lower layers It has been found that factors also have a significant effect.

  FIG. 10 shows the structure of the SRAM cell 100. The SRAM cell 100 shown in the figure includes an element isolation layer, source-drain layers (101a-b, 102a-b), gate layers (103a-b), contact layers, wiring layers (105a-b, 106a-) indicated by dotted lines. 11A shows the gate layer, FIG. 11B shows the element isolation layer, FIG. 11C shows the contact layer, and FIG. 11D shows the source-drain layer. 11E shows a wiring layer, generally, a source-drain layer and a gate layer are formed after the element isolation layer is formed, and the wiring layer and the contact layer are formed according to the structure of the device.

  Returning to FIG. 1 again, when step 1006 determines that the predetermined electrical characteristic is not obtained, the exposure parameter set in step 1004 is adjusted based on the relationship obtained in step 1002 (step 1008).

  In this embodiment, as in step 1008, not the mask pattern but the exposure parameters (exposure conditions) are adjusted. As described above, since each device has an electrical characteristic to be verified, it is preferable to optimize exposure of an object to be exposed so that the electrical characteristic to be verified by each device is improved. In this regard, as in Non-Patent Document 1, it is conceivable to optimize the reticle pattern based on the electrical characteristics of the device. However, optimization of the reticle pattern (using OPC or PPC) alone is not necessarily sufficient for improving the device yield because the characteristics of the exposure apparatus and the manufacturing errors of the reticle are not taken into consideration. Even if reticle pattern optimization is performed in consideration of specific exposure apparatus differences, it is difficult to apply an exposure apparatus other than a specific exposure apparatus, and the flexibility of apparatus operation is deteriorated. Therefore, by optimizing the exposure conditions, it is necessary to improve the yield in the former case and to improve the flexibility of the apparatus operation in the latter case.

For example, when adjusting the exposure parameter of the gate layer so that the variation of _{VTH in} the SRAM cell is minimized, one of the electrical characteristics managed in the device is the gate threshold voltage _VTH . In particular, in the same type of transistors in the same cell, the difference in _VTH is a cause of cell failure. In the exposure process, _VTH is managed by paying attention to the size effects such as the gate length, gate width, gate area, and junction area with the source / drain layer, so that an exposure condition for reducing the variation is required. . An example of an exposure condition that reduces the variation in size effect is to suppress the amount of degeneration of the line end due to defocus by adjusting the NA of the projection optical system and the effective light source shape of the modified illumination. FIG. 12 is a qualitative diagram of NA, focus, and line end. A portion indicated by a dotted line in the gate layer shown in FIG. 12A is shown in FIG.

  Generally, in the case of a critical layer, a high NA condition is used to improve the pattern transfer performance. Here, FIG. 12C is a diagram showing the LES in the best focus and defocus states for a large NA. FIG. 12D is a diagram showing LES in the best focus and defocus states for a small NA. Referring to FIG. 12C and FIG. 12D, the CD becomes clear at the best focus with a large NA and unclear at a small NA. On the other hand, LES becomes large in defocus with a large NA, and LES becomes small in defocus with a small NA. In future miniaturization, emphasizing the yield from the viewpoint of electrical characteristics rather than the pattern transfer performance leads to a direct yield improvement. In this case, the NA may be reduced.

In another embodiment, the gate layer exposure conditions are optimized to maximize the SNM in the SRAM cell structure. In Formula 1, it is known that r and V _TH which are Cell Ratios affect SNM. Since parameters such as V _DD are determined by design values, when improving the SNM in the exposure process, attention is paid to the r value which is V _TH and Cell Ratio of the driver transistor. Therefore, since the improvement of the SNM in the exposure process focuses on the _VTH and the r value, it is necessary to reset the exposure conditions focusing on the size effect of the driver transistor. The cell ratio r is the ratio of the β value of the driver transistor Qn2 to the β value of the access transistor Qn4.

  An example of an exposure condition considering the gate size effect for improving the SNM will be described. The gate length of the driver transistor can be adjusted by adjusting the exposure amount. Parts shown by dotted lines of the gate layer shown in FIG. 13A are shown in FIG. 13B and FIG. 13C. More specifically, FIG. 13B shows the LES in the best focus and defocus state for a large exposure amount, and FIG. 13C shows the LES in the best focus and defocus state for a small exposure amount.

As shown in FIGS. 13B and 13C, the gate length can be shortened by increasing the exposure amount with the allowable LES amount as the upper limit, so that the V _TH of the driver transistor is reduced, and the Cell Ratio is reduced. And SNM can be improved. Note that the Cell Ratio varies depending on the exposure amount because the positional relationship of the patterns is different and thus the exposure amount sensitivity of the access transistor and the driver transistor is different.

Yet another embodiment, in the SRAM cell, such as variations in SNM and V _TH, resets the such exposure conditions to improve the two electrical characteristics at the same time. In this case, as described above, to reduce the exposure amount in consideration of the LES amount, not a good device when variations in even V _TH a case of increasing the Cell Ratio large. Therefore, it is necessary to set the exposure amount in consideration of the variation amount of the size effect of the driver transistor.

If a plurality of exposure parameters are related to the electrical characteristics, Step 1008 selects an exposure parameter having the greatest variation or the greatest influence on the predetermined electrical characteristics when changed among the plurality of exposure parameters. For example, a _VTH Monte Carlo simulation is performed by slightly changing the exposure parameters to verify how the electrical characteristics deteriorate, and the influence of the exposure parameters on the electrical characteristics is also stored as the relationship of step 1002. It is possible to effectively correct the electrical characteristics by correcting the exposure parameters having a large influence.

Here, it is assumed that the influence of the distortion of the exposure parameter is large. Note that the qualitative reason that distortion affects V _TH is that when there is an overlay error between the source-drain layer and the gate layer, there is a difference in the amount of ions existing in the active region. It becomes a variation factor of _TH . FIG. 14B shows a pair of portions indicated by dotted lines in FIG. In such a case, to reduce overlay errors by adjusting at a priority to distortion aberration in the aberration adjustment to tolerate the presence of other aberrations projection optical system can reduce the variation in V _TH. It is also possible to indirectly change the distortion parameter by adjusting the NA of the projection optical system or adjusting the effective light source shape.

  It should be noted that the SRAM cell structure as shown in FIG. 10 is difficult to adopt after the 90 nm node because the overlap between the gate line and the active region has a great influence on the circuit characteristics. However, it should be noted that the concept of the above-described embodiment can also be applied to the fine node.

  The diffractive optical element is effective in forming a desired effective light source shape. When the diffractive optical element is used, the effective light source shape includes an error due to a manufacturing error of the diffractive optical element. In such a case, the electrical characteristics can be improved by using another diffractive optical element. The electrical characteristics can be improved by selecting an optimum diffractive optical element for the combination of mask data and exposure apparatus.

In this case, as shown in FIG. 5, an exposure system 1A is used. The exposure system 1A differs from the exposure system 1 in that it includes input units 50a to 50c. The input unit 50a to 50c inputs the effective light source shape data processing system 10 A. The effective light source shape is formed by a diffractive optical element.

If there are multiple electrical characteristics, step 1006 selects an electrical characteristic that most affects the yield of the device among the multiple electrical characteristics. In other words, weighting is performed based on the degree of contribution of each electrical characteristic to the final yield. For example, in the case of determining the outer σ is the maximum radius of the effective light source shape, the outer σ best to improve SNM, optimum outer σ is present to improve the V _TH. The relationship between the SRAM device structure of FIG. 6 and the electrical characteristics is determined by the V _TH of the transistors Qn4, Qn2, and Op1 and the Cell Ratio r in the case of SNM. V _TH is determined by the gate length, gate width, area, etc. of the transistor. Therefore, there are optimum gate shapes and exposure conditions for each electrical characteristic. Therefore, when there are a plurality of electrical characteristics, the outer σ is determined by performing weighting based on which greatly affects the final yield.

Here, it is assumed that the direction of the SNM affect device yield than V _TH. In this case, step 1008 adjusts the exposure parameters to improve the SNM most.

  As an embodiment in which the weighting is performed based on the contribution of each electrical characteristic to the final yield, the weighting can be performed according to the defective ratio of the electrical characteristics of the transistors Qn1 and Qn2 in the SRAM cell.

  When a plurality of exposure parameters are related to the predetermined electrical characteristic as a function, an exposure parameter having the greatest influence is selected from the plurality of exposure parameters. Specifically, the parameter having the largest value when the set exposure parameter value is substituted into the differential function obtained by differentiating the function is selected (step 1008).

  It is assumed that the electrical characteristic is SNM, and in step 1002, NA, the annular ratio (external σ) of annular illumination, and spherical aberration are related. In this case, NA is varied, and the relationship (function) SNM = f (NA) between NA and SNM is calculated by simulation. Similarly, the relationship (function) SNM = f (outside σ) and SNM = f (spherical aberration) of each of the annular ratio and spherical aberration and SNM are calculated by simulation while varying the annular ratio and spherical aberration.

  Next, these three functions are differentiated by NA, zone ratio, and spherical aberration, respectively, and three differential functions d (SNM) / d (NA), d (SNM) / d (outside σ), d (SNM) / d (spherical aberration) is obtained. Next, the NA, outer σ, and spherical aberration values set in step 1004 are substituted into these differential functions to obtain those having a large differential value. If the differential value is large in the order of NA> outside σ> spherical aberration, NA is selected as an exposure parameter and optimized. Even if the NA is optimized, if the SNM is out of the predetermined range again in step 1006 fed back, the outside σ is optimized while the NA is maintained at the optimum value. Even if the outer σ is optimized, if the SNM is again outside the predetermined range in step 1006 which is fed back, the spherical aberration is optimized while maintaining the NA and the outer σ at the optimum values. The exposure parameters can be efficiently optimized by adjusting in order from the parameter having the greatest influence on the SNM.

In step 1008, an exposure parameter that depends on the optical system (illumination optical system and projection optical system) is adjusted using optical simulation, and an exposure parameter that does not depend on the optical system is adjusted without using optical simulation. You may have. Here, the optical simulation is one process of simulation necessary for simulating the electrical characteristics of the device from the object to be exposed.

  In general, the optical simulation has a heavy calculation load. Accordingly, the simulation time for verifying the electrical characteristics by changing the NA, the effective light source shape, and the aberration parameter requires a long calculation time. On the other hand, for optical image calculation, parameters related to the determination of the slice level, focus position, and overlay, such as the scanning direction and rotation of the wafer / mask stage, are related to parameters and exposure conditions after the optical image is determined. It is. Once the optical image is calculated, the relationship between the electrical characteristics with respect to the parameters of the exposure amount, the overlay, and the light source wavelength can be easily obtained by processing and reusing the optical image.

The “ exposure parameter independent of the optical system” includes an exposure parameter capable of approximately obtaining an optical image by superimposing optical images. For example, parameters of light source wavelength distribution, chromatic aberration, and stage vibration (MSDz). When the light source has a wavelength distribution, the best focus position of each wavelength is shifted. By superimposing defocused images having a reference wavelength, an optical image having a wavelength distribution or the like can be formed. Since such a superposition of optical images has a small calculation load, parameter adjustment such as wavelength distribution may be adjusted after optical simulation for determining parameters depending on the optical system such as illumination shape and aberration.

  By obtaining optimal values such as NA, illumination shape, aberration, etc., which are exposure parameters depending on the optical system, by simulation for improving SNM, and then obtaining optimum values such as Dose, focus position, etc., which are parameters independent of the optical system. Efficient parameter setting is possible.

  Returning again to FIG. 1, after step 1008, the process returns to step 1006. If step 1006 determines that it has predetermined electrical characteristics, exposure is started with the set exposure parameters (step 1010).

  As mentioned above, although preferable embodiment of this invention was described, it cannot be overemphasized that this invention is not limited to these embodiment, A various deformation | transformation and change are possible within the range of the summary.

  For example, the parameters of the exposure apparatus can be determined based on LES, SWA, LER, etc., which are closely related to electrical characteristics.

1, 1A exposure system

Claims (9)

The pattern of the reticle using light from a light source to a determination method for thus determining the value of the exposure parameter in the computer of an exposure apparatus for exposing the object to be exposed,
Setting the value of the exposure parameter;
Calculating an optical image of the pattern of the reticle using the set exposure parameter value to obtain an electrical characteristic of the pattern formed on the object to be exposed;
Using the information representing the relationship between the electrical characteristics of the pattern formed on the object to be exposed and the exposure parameters, the set exposure is performed so that the required electrical characteristics satisfy the predetermined electrical characteristics. An adjustment step for adjusting the value of the parameter,
The adjustment step includes
Adjusting the value of the first exposure parameter depending on the optical system using optical simulation;
Adjusting the value of the second exposure parameter independent of the optical system without using an optical simulation.   The determination method according to claim 1, wherein the second exposure parameter is a parameter of stage vibration.   3. The determination method according to claim 1, wherein, in the step of obtaining the electrical characteristics, an electrical characteristic that most influences the yield of the device is obtained from a plurality of electrical characteristics. In the step of determining the electrical characteristics, a plurality of the electrical characteristics are determined,
2. The exposure parameter value is adjusted by performing weighting based on a contribution degree of each electrical characteristic of the plurality of electrical characteristics to a yield of the device in the adjusting step. 4. The determination method according to any one of 3.   5. The exposure parameter value that most affects the electrical characteristics among the plurality of exposure parameters is adjusted when a plurality of exposure parameters are related to the electrical characteristics. The determination method according to any one of the above.   When a plurality of exposure parameters are related to the electrical characteristics, the adjustment step includes adjusting an exposure parameter value having the largest variation with respect to the electrical characteristics when the plurality of exposure parameters are changed. The determination method according to claim 1, wherein the determination method is a characteristic.   When a plurality of exposure parameters are related to the electrical characteristics as a function, in the adjustment step, the set exposure parameter value is set to a differential function obtained by differentiating the function among the plurality of exposure parameters. 6. The determination method according to claim 1, wherein the exposure parameter value having the largest value when substituted is adjusted.   The determination method according to any one of claims 1 to 7, wherein the exposure parameter is an effective light source distribution of the light that illuminates the reticle.   A program for executing the determination method according to any one of claims 1 to 8 by a computer.