Optimization method, device and exposure apparatus for mask

Abstract

The application relates to the field of computer lithography, and discloses a mask optimization method and device and an exposure equipment, the method comprising the following steps: collecting a wavefront aberration parameter of an illumination light beam of a mask pattern transfer device; calculating a wavefront aberration of the illumination light beam according to the wavefront aberration parameter; calculating an image plane wavefront matrix of an imaging plane based on the wavefront aberration and a preset initial transmittance function; and optimizing the initial transmittance function according to the image plane wavefront matrix and a loss function of a preset imaging pattern to obtain a target transmittance function, which is used for optimizing the mask to compensate for the wavefront aberration. The wavefront aberration is compensated for in the process of designing the mask, the complex structure of the illumination system and the process of adjusting the wavefront aberration are avoided, the concept of holographic lithography is perfectly matched, and the light path complexity and technical realization difficulty of the holographic lithography are reduced.

Description

Technical Field

[0001] This invention relates to the field of computational lithography, and in particular to a method, apparatus, and exposure equipment for optimizing photomasks. Background Technology

[0002] With the development of science and technology, the structure of lithography machines has evolved through stages such as contact lithography, proximity lithography, scanning projection lithography, distributed projection lithography, and step-scan projection lithography. Projection lithography projects a mask pattern onto a wafer using a projection lens. Holographic lithography, however, is a novel lithography technology that exposes silicon wafers through holographic diffraction imaging. The mask in holographic lithography is created by calculating the image using algorithms and performing diffraction calculations on a known pattern. Due to the use of diffraction imaging, holographic lithography has strict requirements on the illumination beam; a key indicator reflected in the mask is the wavefront aberration of the illumination beam. Although the structure of holographic lithography is relatively simpler than traditional projection lithography, the requirements for wavefront aberration of the illumination beam remain stringent. Therefore, a method for compensating and correcting wavefront aberrations in holographic lithography is needed.

[0003] Currently, the control of wavefront aberration in holographic lithography primarily focuses on the illumination system. One solution involves using mechanical compensation mechanisms within the illumination system for wavefront aberration compensation and correction. However, while this method can compensate for some wavefront aberration, it places significantly higher demands on the manufacturing of the illumination system. This not only imposes stricter requirements on the lens manufacturing process but also presents a greater challenge to the structure of the mechanical compensation mechanism. The more demanding lens manufacturing processes and more complex mechanical structures will elevate the difficulty of holographic lithography to a new level.

[0004] Another way to address illumination wave aberrations in holographic lithography is by adding an adaptive optics device, a deformable mirror. However, this approach also increases the overall complexity of the optical path in holographic lithography. These complex deformable mirrors are typically expensive, and when used with a controller, they are bulky, requiring more mechanical space in the optical path, which significantly increases the complexity of holographic lithography. Fundamentally, the reason current lithography technologies choose holographic lithography is that its structure and optical path are simpler than projection lithography, and its illumination system is easier to manufacture, shifting the manufacturing burden from hardware to the computational algorithm and mask. Complex illumination systems and adaptive deformable mirrors contradict the original intention behind the development of holographic lithography technology.

[0005] In summary, existing techniques for compensating and correcting wavefront aberration in holographic lithography present technical challenges that increase the complexity of the optical path and the difficulty of implementation. Summary of the Invention

[0006] In view of this, embodiments of the present invention provide a method, apparatus and exposure equipment for optimizing a mask, in order to solve the technical problem that existing techniques for compensating and correcting wavefront aberration in holographic lithography increase the complexity of the optical path and the difficulty of implementation in holographic lithography.

[0007] In a first aspect, the present invention provides a method for optimizing a photomask, comprising:

[0008] Acquire wavefront aberration parameters of the illumination beam in the mask pattern transfer device;

[0009] The wavefront aberration of the illumination beam is calculated based on the wavefront aberration parameters.

[0010] The image plane wavefront matrix located on the imaging plane is calculated based on the wavefront aberration and the preset initial transmittance function.

[0011] The initial transmittance function is optimized based on the loss function of the image plane wavefront matrix and the preset imaging pattern to obtain the target transmittance function. The target transmittance function is used to optimize the mask to achieve wavefront aberration compensation.

[0012] This invention acquires wavefront aberration parameters, calculates the wavefront aberration of the illumination beam based on these parameters, calculates the image plane wavefront matrix located on the imaging plane based on the wavefront aberration and a preset initial transmittance function, optimizes the initial transmittance function based on the image plane wavefront matrix and a loss function of a preset imaging pattern to obtain the target transmittance function, and optimizes the mask based on the target transmittance function to achieve wavefront aberration compensation. The entire process does not require additional structures. By compensating for wavefront aberration during the mask design process, it avoids complex illumination systems and complex wavefront aberration adjustment processes, perfectly matching the concept of holographic lithography, reducing the optical path complexity and technical implementation difficulty of holographic lithography. It is a low-cost, high-precision, and simple-to-operate wavefront aberration compensation method.

[0013] Optionally, the step of calculating the image plane wavefront matrix located on the imaging plane based on the wavefront aberration and a preset initial transmittance function includes:

[0014] The holographic wavefront matrix is ​​calculated based on the wavefront aberration and the preset initial transmittance function.

[0015] The image plane wavefront matrix is ​​obtained by performing diffraction integration based on the holographic wavefront matrix and the diffraction transfer function.

[0016] In this method, the wavefront matrix of the image plane is calculated by considering wavefront aberrations. The wavefront matrix of the image plane calculated in this way is closer to the actual value, and the calculation result is more accurate.

[0017] Optionally, the step of calculating the holographic wavefront matrix based on the wavefront aberration and a preset initial transmittance function includes:

[0018] The wavefront matrix of the holographic surface is calculated using the following formula:

[0019] V(x,y,0)=W(·)T0(x,y)

[0020] In the formula, V(x,y,0) is the holographic wavefront matrix, W(·) is the wavefront aberration, and T0(x,y) is the initial transmittance function.

[0021] This method simplifies the calculation process of the holographic wavefront matrix and improves computational efficiency.

[0022] Optionally, the step of obtaining the image plane wavefront matrix by performing diffraction integration based on the holographic wavefront matrix and the diffraction transfer function includes:

[0023] The image plane wavefront matrix is ​​calculated using the following formula:

[0024]

[0025] In the formula, E(ξ,η,z) is the image plane wavefront matrix, and H(x,y,ξ,η,z) is the diffraction transfer function.

[0026] In this method, the wavefront matrix of the image plane is obtained by diffraction integration, which can more accurately predict the propagation of the beam during the photolithography process.

[0027] Optionally, before optimizing the initial transmittance function based on the loss function of the image plane wavefront matrix and the preset imaging pattern to obtain the target transmittance function, the following steps are included:

[0028] An iterative optimization algorithm is used to calculate the loss function of the image plane wavefront matrix and the preset imaging pattern;

[0029] Correspondingly, the initial transmittance function is optimized based on the loss function of the image wavefront matrix and the preset imaging pattern to obtain the target transmittance function, including:

[0030] An iterative optimization algorithm is used to iteratively optimize the initial transmittance function based on the loss function to obtain the target transmittance function.

[0031] In this approach, an iterative optimization algorithm can be used to gradually approximate the optimal transmittance function, thereby achieving more accurate wavefront aberration compensation.

[0032] Optionally, the iterative optimization algorithm is a gradient algorithm, a pixel flip algorithm, a VO algorithm, a Gerchberg-Saxton algorithm, a genetic algorithm, or simulated annealing.

[0033] This approach offers a variety of iterative optimization algorithms to choose from, allowing you to select the most suitable algorithm based on different application scenarios and requirements.

[0034] Optionally, the wavefront aberration parameter is the Zernike coefficient;

[0035] Correspondingly, the wavefront aberration parameters of the illumination beam after passing through the illumination system in the holographic lithography system are acquired, including:

[0036] The Zernike coefficient of the illumination beam after passing through the illumination system is acquired by a wavefront sensor positioned between the illumination system and the mask in holographic lithography.

[0037] In this approach, using the Zernike coefficient as a wavefront aberration parameter allows for a more accurate description and compensation of the beam's wavefront distortion.

[0038] Optionally, calculating the wavefront aberration of the illumination beam based on the wavefront aberration parameters includes:

[0039] The wavefront aberration of the illumination beam is calculated using the following formula:

[0040]

[0041] Where W(·) represents wavefront aberration, c nm Represents the Zernike coefficient. Let n denote a Zernike polynomial, where n ≥ m and nm is an even number, 0 ≤ ρ ≤ 1, and 0 ≤ θ < 2π.

[0042] In this method, the wavefront aberration of the illumination beam can be accurately calculated using the Zernike polynomial formula, providing accurate data support for subsequent compensation.

[0043] Secondly, the present invention provides a mask optimization apparatus, comprising:

[0044] The parameter acquisition module is used to acquire the wavefront aberration parameters of the illumination beam in the mask pattern transfer device;

[0045] An aberration calculation module is used to calculate the wavefront aberration of the illumination beam based on the wavefront aberration parameters.

[0046] The wavefront matrix calculation module is used to calculate the image plane wavefront matrix located on the imaging plane based on the wavefront aberration and the preset initial transmittance function.

[0047] The iterative optimization module is used to optimize the initial transmittance function based on the image plane wavefront matrix and the loss function of the preset imaging pattern to obtain the target transmittance function. The target transmittance function is used to optimize the mask to achieve wavefront aberration compensation.

[0048] Thirdly, the present invention provides an exposure apparatus, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the mask optimization method described in any one of the first aspects. Attached Figure Description

[0049] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart of a mask optimization method in an embodiment of the present invention;

[0051] Figure 2 This is a flowchart of another mask optimization method in an embodiment of the present invention;

[0052] Figure 3 This is a flowchart of another mask optimization method in an embodiment of the present invention;

[0053] Figure 4 A schematic diagram of the optical path for designing a mask in related technologies when wavefront aberrations are not considered.

[0054] Figure 5 This is a schematic diagram of the optical path for designing a mask when considering wavefront aberrations in an embodiment of the present invention;

[0055] Figure 6 This is a schematic diagram of the structure of the mask optimization device in an embodiment of the present invention;

[0056] Figure 7 This is a schematic diagram of the exposure device in an embodiment of the present invention. Detailed Implementation

[0057] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0058] Holographic lithography is a technique that uses the principles of interference and diffraction to record and reconstruct the true image of an object. It can record not only the amplitude information of light but also its phase information, thus providing depth information of the object. Holography was initially proposed by physicist Dennis Gabor, who in 1947 proposed a concept for recording information using the principle of interference and obtained the first hologram and its reconstructed image in 1948. Subsequently, with the development of science and technology, the development of high-performance computers, and the emergence of efficient numerical algorithms, it became possible to use computers for wavefront recording—this is known as computational holography. It involves computer-based wavefront recording, while the reconstruction process uses real illumination light for optical reconstruction.

[0059] Holographic lithography is essentially a part of computational lithography. It uses efficient computer algorithms to optimize a target pattern, i.e., an integrated circuit image, into a holographic mask. This holographic mask can then be manufactured using methods commonly used in the semiconductor industry. During the lithography process, the illumination system illuminates the mask according to the required light. The desired target pattern, i.e., the circuit pattern, can then be obtained on the silicon wafer behind the mask through exposure.

[0060] Compared to traditional projection lithography, although the requirements for the complexity of the optical system are lower in the context of holographic lithography, wavefront aberration is still a parameter that needs to be focused on.

[0061] Please see Figure 4 The principle of using holographic technology to obtain the target pattern of an integrated circuit in a photomask is as follows:

[0062] Let Ω denote the plane containing the object (integrated circuit design layout). o (x,y,0), the wavefront of an object can be represented in the form of complex amplitude of light as follows:

[0063]

[0064] Where A O The amplitude of the object wave. Let I be the phase of the object wave, and I be the imaginary unit. Let the plane at a distance Z from the object be the plane Ω containing the hologram. H (ξ,η,z), then the wavefront of the object wave propagating to this plane can be obtained by diffraction integral:

[0065]

[0066] Here, H(x,y,ξ,η,z) is the diffraction transfer function, which varies depending on the diffraction formula.

[0067] After the object wave is transmitted to the holographic surface, the complex amplitude distribution of the object wave's optical field is obtained. To convert this into a physically realized light intensity distribution, a reference beam needs to be introduced and positioned at the holographic surface Ω. H The wavefront matrix of (ξ,η,z) is:

[0068]

[0069] Where A r For the reference wave amplitude, φ r Let I be the reference wave phase and I be the imaginary unit. The interference between the two waves, recorded on a medium, forms a hologram.

[0070] According to the Gabor holographic principle, the reference light on the holographic surface Ω can be obtained. H Light intensity distribution over (ξ,η,z):

[0071] I(ξ,η)=|Ω H (ξ,η,z)+R(ξ,η,z)| 2

[0072] After normalization, the transmittance distribution of the holographic surface can be obtained as follows:

[0073] T(ξ,η)=I(ξ,η) / I max

[0074] Among them, I max The maximum light intensity is given, thus yielding a transmittance distribution with a value of [0.1]. After obtaining the transmittance distribution, the transmittance is approximated by machining holes of different sizes at different locations on the mask, thus obtaining the holographic mask. The size of the openings is determined by the equipment.

[0075] Compared to traditional projection lithography, holographic lithography has a relatively simple structure, but it still has very strict requirements regarding the wavefront aberration of the illumination beam. In related technologies, to eliminate the influence of wavefront aberration, one solution is to use a mechanical compensation mechanism in the illumination system for wavefront aberration compensation and correction. Another solution is to add an adaptive optics device, a deformable mirror, to address the wavefront aberration problem in holographic lithography. Both methods increase the complexity of the illumination system, which contradicts the original intention of developing holographic lithography technology.

[0076] Based on this, embodiments of the present invention provide a method for optimizing a photomask for use in an exposure device. It should be noted that the executing entity can be a terminal, client, or server. The server can be a single server or a server cluster composed of multiple servers. In this embodiment, the terminal can be a smartphone, personal computer, tablet computer, or other smart hardware device. A photomask pattern transfer device is used to form specific devices on a silicon wafer, such as a lithography machine.

[0077] This invention provides a method for optimizing a mask. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here. Figure 1 This is a flowchart of a holographic mask optimization method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0078] Step S101: Collect the wavefront aberration parameters of the illumination beam in the mask pattern transfer device.

[0079] Specifically, in a mask pattern transfer device, the laser emitted by the laser is collimated into a collimated beam after being expanded and collimated by an illumination system. For example... Figure 2 As shown, a wavefront sensor is placed behind the collimated beam, and the wavefront aberration parameters of the illumination beam after passing through the illumination system are collected by the wavefront sensor.

[0080] In one example, the wavefront aberration parameter is the Zernike coefficient.

[0081] Step S102: Calculate the wavefront aberration of the illumination beam based on the wavefront aberration parameters.

[0082] Specifically, after obtaining the wavefront aberration parameters, further analysis and calculation are performed to obtain the wavefront aberration of the beam.

[0083] Step S103: Calculate the image plane wavefront matrix located on the imaging plane based on wavefront aberration and a preset initial transmittance function.

[0084] The initial transmittance function is the basis for designing the mask. In one example, the preset initial transmittance function is:

[0085] T0(x,y)=I0(x,y) / I max

[0086] Among them I max I0(x,y) represents the maximum light intensity, and I0(x,y) represents the preset initial light intensity distribution. The preset initial transmittance function T0(x,y) can be randomly set to an initial value.

[0087] The image plane wavefront matrix represents the distribution of light beam propagation onto the image plane. Based on wavefront aberrations and a preset initial transmittance function, the image plane wavefront matrix can be calculated while taking wavefront aberrations into account, making it more accurate and facilitating subsequent optimization of the mask.

[0088] Step S104: Optimize the initial transmittance function based on the image plane wavefront matrix and the loss function of the preset imaging pattern to obtain the target transmittance function. The target transmittance function is used to optimize the mask to achieve wavefront aberration compensation.

[0089] The preset image pattern is the pattern that you actually want to focus on on the imaging surface.

[0090] The loss function characterizes the deviation between the currently calculated image wavefront matrix and the preset imaging requirements. By introducing the loss function, if the loss function is greater than the preset value, the initial transmittance function is increased or decreased according to the preset gradient, thereby optimizing the initial transmittance function and making the image wavefront matrix closer to the preset imaging pattern.

[0091] After obtaining the target transmittance function, holes of different sizes are processed at different positions on the mask to approximate the target transmittance function, thus obtaining the holographic mask.

[0092] This invention discloses a mask optimization method. By acquiring wavefront aberration parameters, calculating the image plane wavefront matrix located on the imaging plane based on the wavefront aberration and a preset initial transmittance function, optimizing the initial transmittance function based on the image plane wavefront matrix and a loss function of a preset imaging pattern to obtain a target transmittance function, and then optimizing the mask based on the target transmittance function to achieve wavefront aberration compensation. The entire process does not require additional structures. By compensating for wavefront aberration during the mask design process, it avoids complex illumination systems and complex wavefront aberration adjustment processes, perfectly matching the concept of holographic lithography. It reduces the optical path complexity and technical implementation difficulty of holographic lithography, and is a low-cost, high-precision, and simple-to-operate wavefront aberration compensation method.

[0093] In one embodiment, the wavefront aberration parameter is the Zernike coefficient;

[0094] Correspondingly, in step S102, the wavefront aberration parameters of the illumination beam after passing through the illumination system in the holographic lithography system are acquired, including:

[0095] Step S1021: The Zernike coefficient of the illumination beam after passing through the illumination system is acquired by a wavefront sensor positioned between the illumination system and the mask in the holographic lithography.

[0096] In one example, the light emitted by the laser, after passing through the illumination system, becomes a beam that satisfies the requirements of the mask. The actual wavefront of the beam after the illumination system is detected using a wavefront sensor, yielding the Zernike coefficients of the actual wavefront. The Zernike coefficients are a set of orthogonal polynomials over a circular domain and can be used to characterize wave aberrations.

[0097]

[0098] Where W(·) represents wavefront aberration, c nm Represents the Zernike coefficient. Let n denote a Zernike polynomial, where n ≥ m and nm is an even number, 0 ≤ ρ ≤ 1, and 0 ≤ θ < 2π.

[0099] The Zernike polynomial can be further expressed as:

[0100]

[0101] It is an nth power polynomial in ρ, containing ρ n ,ρ n-2 ,…,ρ m item.

[0102] In practical use, Multiplying by a normalization factor, the normalized Zernike polynomial is expressed as follows:

[0103]

[0104] After normalization, the orthogonality of circular domains is as follows:

[0105]

[0106] Calculate the coefficient c using orthogonality. nm :

[0107]

[0108] In one example, the meaning and expression of the first fifteen Zernike polynomials are shown in Table 1:

[0109] Table 1. Meaning and Expression of the First Fifteen Zernike Polynomials

[0110]

[0111] In this embodiment of the invention, Zernike coefficients are used as wavefront aberration parameters, which can more accurately describe and compensate for the wavefront distortion of the beam. Furthermore, the wavefront aberration of the illumination beam can be accurately calculated using Zernike polynomials, providing accurate data support for subsequent compensation.

[0112] In one embodiment, step S103, calculating the image plane wavefront matrix located on the imaging plane based on wavefront aberration and a preset initial transmittance function, includes:

[0113] Step S1031: Calculate the holographic wavefront matrix based on the wavefront aberration and the preset initial transmittance function;

[0114] Specifically, the holographic wavefront matrix is ​​calculated using the following formula:

[0115] V(x,y,0)=W(·)T0(x,y)

[0116] In the formula, V(x,y,0) is the holographic wavefront matrix, W(·) is the wavefront aberration, and T0(x,y) is the initial transmittance function.

[0117] This calculation formula simplifies the calculation process of the holographic wavefront matrix and improves computational efficiency.

[0118] Step S1032: Obtain the image plane wavefront matrix by performing diffraction integration based on the holographic wavefront matrix and the diffraction transfer function.

[0119] like Figure 5 As shown, the image plane wavefront matrix represents the wavefront matrix of the object wave propagating to the image plane. It can be calculated using diffraction integrals, and the calculation formula is as follows:

[0120]

[0121] In the formula, E(ξ,η,z) is the image plane wavefront matrix, H(x,y,ξ,η,z) is the diffraction transfer function, and V(x,y,0) is the holographic plane wavefront matrix.

[0122] By calculating the wavefront matrix of the image plane using diffraction integrals, the propagation results of the beam during the photolithography process can be predicted more accurately.

[0123] In one embodiment, before step S104 optimizes the initial transmittance function based on the image wavefront matrix and the loss function of the preset imaging pattern to obtain the target transmittance function, the following steps are included:

[0124] An iterative optimization algorithm is used to calculate the loss function of the image plane wavefront matrix and the preset imaging pattern;

[0125] Correspondingly, step S104 includes:

[0126] Step S1041: The initial transmittance function is iteratively optimized using an iterative optimization algorithm based on the loss function to obtain the target transmittance function.

[0127] Specifically, a loss function is introduced into the iterative optimization algorithm, which represents the deviation between the currently calculated image wavefront matrix and the preset imaging requirements.

[0128] Please see Figure 3 If the loss function is greater than the preset value, the initial transmittance function is increased or decreased according to the preset gradient, and the process returns to step S1031 to recalculate. If the loss function is less than or equal to the preset value, it means that the initial transmittance function at this time meets the optimization conditions, and the initial transmittance function at this time is taken as the target transmittance function.

[0129] For example, the iterative optimization algorithm described above can be a gradient algorithm, a pixel flip algorithm, a VO algorithm, a Gerchberg-Saxton algorithm, a genetic algorithm, or simulated annealing.

[0130] It should be understood that those skilled in the art can choose the most suitable algorithm based on different application scenarios and needs.

[0131] After obtaining the target transmittance function, a holographic mask can be obtained by processing holes of different sizes at different positions on the mask. The mask obtained by the method is then compensated based on wavefront aberrations. An iterative optimization algorithm can be used to gradually approximate the optimal transmittance function, thereby achieving more accurate wavefront aberration compensation.

[0132] An optimization method for a photomask according to an embodiment of the present invention compensates for wavefront errors during the photomask design process using an algorithm, avoiding complex illumination systems and complex wavefront aberration adjustment processes, perfectly matching the concept of holographic lithography.

[0133] The mask optimization method of this invention does not require additional mechanical structures and will not increase the complexity of the optical path of the entire holographic lithography. It is a low-cost, high-precision, and simple-to-operate wavefront aberration compensation method.

[0134] The embodiments of the present invention use Zernike coefficients as wavefront aberration parameters, which can more accurately describe and compensate for the wavefront distortion of the beam. Furthermore, the wavefront aberration of the illumination beam can be accurately calculated using Zernike polynomials, providing accurate data support for subsequent compensation.

[0135] The embodiments of the present invention employ an iterative optimization algorithm that can gradually approximate the optimal transmittance function, thereby achieving more accurate wavefront aberration compensation.

[0136] This invention also provides a mask optimization device, such as... Figure 6 As shown, the device includes:

[0137] The parameter acquisition module 601 is used to acquire the wavefront aberration parameters of the illumination beam in the mask pattern transfer device;

[0138] The aberration calculation module 602 is used to calculate the wavefront aberration of the illumination beam based on the wavefront aberration parameters.

[0139] The wavefront matrix calculation module 603 is used to calculate the image plane wavefront matrix located on the imaging plane based on the wavefront aberration and the preset initial transmittance function.

[0140] The iterative optimization module 604 is used to optimize the initial transmittance function based on the image plane wavefront matrix and the loss function of the preset imaging pattern to obtain the target transmittance function. The target transmittance function is used to optimize the mask to achieve wavefront aberration compensation.

[0141] This invention discloses a mask optimization device that collects wavefront aberration parameters, calculates the wavefront aberration of the illumination beam based on these parameters, calculates the image plane wavefront matrix located on the imaging plane based on the wavefront aberration and a preset initial transmittance function, optimizes the initial transmittance function based on the image plane wavefront matrix and a loss function of a preset imaging pattern to obtain a target transmittance function, and optimizes the mask based on the target transmittance function to achieve wavefront aberration compensation. The entire process does not require additional structures. By compensating for wavefront aberration during the mask design process, it avoids complex illumination systems and complex wavefront aberration adjustment processes, perfectly matching the concept of holographic lithography, reducing the optical path complexity and technical implementation difficulty of holographic lithography. It is a low-cost, high-precision, and simple-to-operate wavefront aberration compensation method.

[0142] In one embodiment, the wavefront matrix calculation module 603 includes:

[0143] The holographic wavefront matrix calculation module is used to calculate the holographic wavefront matrix based on the wavefront aberration and the preset initial transmittance function.

[0144] The image plane wavefront matrix calculation module is used to obtain the image plane wavefront matrix by performing diffraction integration based on the holographic wavefront matrix and the diffraction transfer function.

[0145] In one embodiment, the holographic wavefront matrix calculation module includes:

[0146] The wavefront matrix of the holographic surface is calculated using the following formula:

[0147] V(x,y,0)=W(·)T0(x,y)

[0148] In the formula, V(x,y,0) is the holographic wavefront matrix, W(·) is the wavefront aberration, and T0(x,y) is the initial transmittance function.

[0149] In one embodiment, the image plane wavefront matrix calculation module includes:

[0150] The image plane wavefront matrix is ​​calculated using the following formula:

[0151]

[0152] In the formula, E(ξ,η,z) is the image plane wavefront matrix, and H(x,y,ξ,η,z) is the diffraction transfer function.

[0153] In one embodiment, the iterative optimization module 604 includes:

[0154] The loss function calculation module is used to calculate the image plane wavefront matrix and the loss function for preset imaging requirements using an iterative optimization algorithm;

[0155] The transmittance function optimization module is used to iteratively optimize the initial transmittance function based on the loss function to obtain the target transmittance function.

[0156] In one embodiment, the iterative optimization algorithm is a gradient algorithm, a pixel flip algorithm, a VO algorithm, a Gerchberg-Saxton algorithm, a genetic algorithm, or simulated annealing.

[0157] In one embodiment, the wavefront aberration parameter is the Zernike coefficient;

[0158] Correspondingly, the parameter acquisition module 601 includes:

[0159] The Zernike coefficient acquisition module is used to acquire the Zernike coefficient of the illumination beam after it has passed through the illumination system by a wavefront sensor positioned between the illumination system and the mask in holography.

[0160] In one embodiment, the aberration calculation module 602 includes:

[0161] The wavefront aberration of the illumination beam is calculated using the following formula:

[0162]

[0163] Where W(·) represents wavefront aberration, c nm Represents the Zernike coefficient. Let n denote a Zernike polynomial, where n ≥ m and nm is an even number, 0 ≤ ρ ≤ 1, and 0 ≤ θ < 2π.

[0164] This invention also provides a schematic diagram of the structure of an exposure device, as shown in the embodiment of the invention. Figure 7 As shown, the exposure apparatus includes one or more processors 10, a memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise as required. The processors can process instructions executed within the exposure apparatus, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interface). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple exposure apparatuses can be connected, each providing some of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system).Figure 7 Take a processor 10 as an example.

[0165] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0166] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0167] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the exposure equipment. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transient memory, such as at least one disk storage device, flash memory device, or other non-transient solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, which can be connected to the exposure equipment via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0168] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0169] The exposure apparatus also includes an input device 30 and an output device 40. The processor 10, memory 20, input device 30, and output device 40 can be connected via a bus or other means. Figure 7 Taking the example of a connection between China and Israel via a bus.

[0170] Input device 30 can receive input digital or character information, and generate key signal inputs related to user settings and function control of the exposure device, such as a touch screen, keypad, mouse, trackpad, touchpad, indicator, one or more mouse buttons, trackball, joystick, etc. Output device 40 may include display devices, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibration motors). The aforementioned display devices include, but are not limited to, liquid crystal displays, light-emitting diodes, displays, and plasma displays. In some alternative embodiments, the display device may be a touch screen.

[0171] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for optimizing a photomask, characterized in that, include: Acquire wavefront aberration parameters of the illumination beam in the mask pattern transfer device; The wavefront aberration of the illumination beam is calculated based on the wavefront aberration parameters, using the following formula: in, Indicates wavefront aberration. Represents the Zernike coefficient. Representing the Zernike polynomial, and It is an even number. , ; The image plane wavefront matrix located on the imaging plane is calculated based on the wavefront aberration and the preset initial transmittance function. The initial transmittance function is optimized based on the loss function of the image plane wavefront matrix and the preset imaging pattern to obtain the target transmittance function. The target transmittance function is used to optimize the mask to achieve wavefront aberration compensation. The step of calculating the image plane wavefront matrix based on the wavefront aberration and a preset initial transmittance function includes: The holographic wavefront matrix is ​​calculated based on the wavefront aberrations and the preset initial transmittance function. The calculation formula is as follows: In the formula, For the holographic wavefront matrix, For wavefront aberration, The initial transmittance function is given, and the holographic surface is the plane at a distance from the object, which is the plane containing the hologram. Based on the holographic wavefront matrix and the diffraction transfer function, the image wavefront matrix is ​​obtained by diffraction integration, and the calculation formula is as follows: In the formula, For the image plane wavefront matrix, The diffraction transfer function; The process, before optimizing the initial transmittance function based on the loss function of the image wavefront matrix and the preset imaging pattern to obtain the target transmittance function, includes: An iterative optimization algorithm is used to calculate the loss function between the image plane wavefront matrix and the preset imaging pattern. The loss function characterizes the deviation between the currently calculated image plane wavefront matrix and the preset imaging requirements. Correspondingly, the initial transmittance function is optimized based on the loss function of the image wavefront matrix and the preset imaging pattern to obtain the target transmittance function, including: An iterative optimization algorithm is used to iteratively optimize the initial transmittance function based on the loss function to obtain the target transmittance function.

2. The method for optimizing a photomask according to claim 1, characterized in that, The iterative optimization algorithm is a gradient algorithm, pixel flip algorithm, VO algorithm, Gerchberg-Saxton algorithm, genetic algorithm, or simulated annealing.

3. The method for optimizing a photomask according to claim 1, characterized in that, The wavefront aberration parameter is the Zernike coefficient; Correspondingly, the wavefront aberration parameters of the illumination beam after passing through the illumination system in the holographic lithography system are acquired, including: The Zernike coefficient of the illumination beam after passing through the illumination system is acquired by a wavefront sensor positioned between the illumination system and the mask in holographic lithography.

4. A mask optimization device, characterized in that, include: The parameter acquisition module is used to acquire the wavefront aberration parameters of the illumination beam in the mask pattern transfer device; The aberration calculation module is used to calculate the wavefront aberration of the illumination beam based on the wavefront aberration parameters. The calculation formula is as follows: in, Indicates wavefront aberration. Represents the Zernike coefficient. Representing the Zernike polynomial, and It is an even number. , ; The wavefront matrix calculation module is used to calculate the image plane wavefront matrix located on the imaging plane based on the wavefront aberration and the preset initial transmittance function. An iterative optimization module is used to optimize the initial transmittance function based on the image plane wavefront matrix and the loss function of the preset imaging pattern to obtain a target transmittance function. The target transmittance function is used to optimize the mask to achieve wavefront aberration compensation. The wavefront matrix calculation module includes: The holographic wavefront matrix calculation module is used to calculate the holographic wavefront matrix based on wavefront aberrations and a preset initial transmittance function. The calculation formula is as follows: In the formula, For the holographic wavefront matrix, For wavefront aberration, The initial transmittance function is given, and the holographic surface is the plane at a distance from the object, which is the plane containing the hologram. The image plane wavefront matrix calculation module is used to obtain the image plane wavefront matrix by performing diffraction integrals based on the holographic wavefront matrix and the diffraction transfer function. The calculation formula is as follows: In the formula, For the image plane wavefront matrix, The diffraction transfer function; The iterative optimization module includes: The loss function calculation module is used to calculate the loss function between the image plane wavefront matrix and the preset imaging requirements using an iterative optimization algorithm. The loss function characterizes the deviation between the currently calculated image plane wavefront matrix and the preset imaging requirements. The transmittance function optimization module is used to iteratively optimize the initial transmittance function based on the loss function to obtain the target transmittance function.

5. An exposure apparatus used in chip fabrication processes, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the mask optimization method according to any one of claims 1 to 3.

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