CN115855812B - Methods and apparatus for acquiring structured light field patterns, and methods and apparatus for classifying them. - Google Patents
Methods and apparatus for acquiring structured light field patterns, and methods and apparatus for classifying them.Info
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- CN115855812B CN115855812B CN202211458883.1A CN202211458883A CN115855812B CN 115855812 B CN115855812 B CN 115855812B CN 202211458883 A CN202211458883 A CN 202211458883A CN 115855812 B CN115855812 B CN 115855812B
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Abstract
本发明提出了一种结构光场图案的获取方法及装置、分类方法及装置，所述结构光场图案的获取方法，包括：获取第一结构光场；对所述第一结构光场进行投影成像处理，以获取第二结构光场；获取第一数据矩阵、以及第二数据矩阵；根据第一差值构建评价函数；通过调整所述第一数据矩阵内的像素值的大小，对所述第二结构光场进行迭代优化；当所述第一差值小于第一预设阈值或者所述迭代的次数等于第二预设阈值时，停止对所述第二结构光场进行所述迭代优化，并获取目标结构光场；获取优化结构光场图案。本发明在保证所述集成电路芯片不被破坏的前提下，提高集成电路芯片的缺陷检测的效率。
This invention proposes a method and apparatus for acquiring structured light field patterns, as well as a classification method and apparatus. The method for acquiring structured light field patterns includes: acquiring a first structured light field; performing projection imaging processing on the first structured light field to acquire a second structured light field; acquiring a first data matrix and a second data matrix; constructing an evaluation function based on a first difference; iteratively optimizing the second structured light field by adjusting the pixel values in the first data matrix; stopping the iterative optimization of the second structured light field and acquiring a target structured light field when the first difference is less than a first preset threshold or the number of iterations is equal to a second preset threshold; and acquiring an optimized structured light field pattern. This invention improves the efficiency of defect detection in integrated circuit chips while ensuring that the integrated circuit chip is not damaged.
Description
Technical Field
The present invention relates to the field of integrated circuit defect detection technologies, and in particular, to a method and apparatus for acquiring a structured light field pattern, and a method and apparatus for classifying the structured light field pattern.
Background
An integrated circuit (INTEGRATED CIRCUITS, IC) is an electronic circuit with specific functions, which is fabricated by using semiconductor technology to fabricate a plurality of electrical devices such as diodes, transistors, resistors, capacitors, etc. on a very small silicon die. With the continuous development of everything interconnection, 5G, intelligent equipment and national defense technology, the IC has become an important foundation for realizing informatization and intellectualization in various industries. With the progressive node of the international most advanced semiconductor process, the existing IC chip inspection technology and equipment will face more serious challenges, mainly that the size of the IC chip defect under the advanced process node has gradually approached tens of atoms. This measurement requirement far beyond the optical diffraction limit will be very weak in scattered signal intensity in the conventional optical detection mode and thus easily submerged in the background scattered noise. The current common super-resolution defect detection schemes are realized by scanning near-field optical microscope, multi-photon fluorescence microscope, atomic force microscope, transmission electron microscope, quantitative phase imaging microscope and X-ray laminated diffraction imaging technology, and the methods need to mark the defective position on the chip, have certain destructiveness and have low efficiency.
Therefore, the invention provides a method and a device for acquiring a structural light field pattern, and a method and a device for classifying the structural light field pattern, which can improve the defect detection efficiency of an integrated circuit chip on the premise of ensuring that the integrated circuit chip is not damaged.
Disclosure of Invention
The invention provides a method and a device for acquiring a structural light field pattern, and a method and a device for classifying the structural light field pattern, which are used for solving the technical problems of certain destructiveness and low efficiency in the prior art due to the fact that the defective position on a chip is required to be marked.
The invention provides a method for acquiring a light field pattern of a structure, which comprises the steps of S1, acquiring a light field of a first structure, wherein the light field of the first structure is a standard structure light field corresponding to a first target area of an integrated circuit to be detected, S2, performing projection imaging processing on the light field of the first structure to acquire a light field of a second structure, S3, acquiring a first data matrix related to pixel value distribution in the light field of the first structure, and acquiring a second data matrix related to pixel value distribution in the light field of the second structure, S4, constructing an evaluation function according to a first difference value, wherein the first difference value is a difference value of pixel values of the first data matrix and the second data matrix at a corresponding position in a second target area, S5, performing iterative optimization on the light field of the second structure by adjusting the size of the pixel values in the first data matrix, S6, and performing iterative optimization on the light field of the second structure when the first difference value is smaller than a first preset threshold or the number of times equal to a second preset threshold, S4, constructing an evaluation function according to the first difference value, and optimizing the light field of the second structure, and acquiring the light field pattern of the first structure, and optimizing the light field of the structure to be the target structure.
The method has the advantages that the method improves the iterative optimization of the second structure light field by adjusting the pixel value in the first data matrix so as to obtain the first structure light field in an ideal state or a near ideal state, and is convenient for obtaining an accurate defect classification result in the follow-up defect problem analysis.
Optionally, in the step S3, the first structural light field is divided into two parts, namely, a length a is divided into two parts in a horizontal direction and a length B is divided into two parts in a vertical direction, the second structural light field is divided into two parts in a horizontal direction and a length D is divided into two parts in a vertical direction, A, B, C, D are positive numbers, the ratio of C to a and the ratio of D to B are equal to the scaling factor of the projection imaging process, the pixel value distribution of each region after the first structural light field is divided into two parts is obtained to form the first data matrix, and the pixel value distribution of each region after the second structural light field is divided into two parts is obtained to form the second data matrix. The method has the advantages that the pixel value data of discrete distribution is conveniently obtained by dividing the first structure light field and the second structure light field so as to construct a data matrix of the pixel value distribution, and the ratio of C to A and the ratio of D to B are equal to the scaling factor of the projection imaging processing, so that the pixel values of the first structure light field and the second structure light field at corresponding positions can be directly compared so as to obtain an accurate comparison result.
Optionally, in the step S4, a ratio of the product of the A and the B to the perimeter of the first structure light field pattern is calculated, a pixel value distribution of the first structure light field and the second structure light field in a second target area is obtained, and an evaluation function is constructed according to a measurement window function, the first difference value and the ratio, wherein the measurement window function is used for obtaining an aggregation value of the first difference value. The method has the beneficial effects that an effective evaluation function is obtained, and the second structural light field is conveniently optimized through the evaluation function.
Optionally, in the step S5, the second structural light field is iteratively optimized by adjusting the size of the pixel values in the first data matrix and a multi-objective optimization algorithm based on conjugate gradients.
In a second aspect, the invention provides a method for classifying defects of an integrated circuit, which comprises the steps of guiding the optimized structure light field pattern obtained by the method according to any one of the first aspect into a reflection type amplitude type spatial light modulator to obtain a third structure light field, wherein the third structure light field is generated by the reflection type amplitude type spatial light modulator according to the optimized structure light field pattern, the pixel size of the reflection type amplitude type spatial light modulator is matched with the selection of the A and the B, aligning the third structure light field with the pattern of the integrated circuit to be classified, collecting a first far-field microscopic image under the illumination of the third structure light field, comparing the first far-field microscopic image with a second far-field microscopic image to obtain defects of the integrated circuit to be classified relative to the ideal integrated circuit, the second microscopic image is an ideal integrated circuit which is obtained under the illumination of the third structure light field and is an integrated circuit which has no defects, and classifying the defects according to the positions and types of the defects.
The method for classifying the integrated circuit defects has the advantages that the integrated circuit defects to be detected do not need to be marked and are not damaged while the defect detection accuracy and efficiency are ensured.
Optionally, the pixel size of the reflective amplitude type spatial light modulator is matched with the selection of the A and the B, and the method comprises the step that the A and the B are integer multiples of the pixel size of the reflective amplitude type spatial light modulator. The method has the beneficial effects that the light field structure beneficial to processing is conveniently obtained, so that the defect classification process is simplified.
Optionally, comparing the first far-field microscopic image with the second far-field microscopic image to obtain a defect of the integrated circuit to be tested relative to the ideal integrated circuit, wherein the defect comprises the steps of obtaining a position of the defect, namely a position inconsistent with a pixel value of the second far-field microscopic image in the first far-field microscopic image, and judging the type of the defect by combining the position of the defect and a shape formed by the position inconsistent with the pixel point. The method has the advantages that the method only needs to judge the inconsistent positions of the pixels and the shapes formed by the inconsistent positions of the pixels to obtain the positions and the types of the defects, and does not need to mark the chip, namely the method has no destructiveness while ensuring the accuracy of defect identification, and in addition, the efficiency and the automation are improved to a certain extent because the participation of testers is hardly needed in the defect classification process.
In a third aspect, the present invention provides an acquisition device for a structural light field pattern, configured to perform an acquisition method for a structural light field pattern according to any one of the embodiments of the first aspect, including an acquisition module, a projection processing module, an evaluation module, and an optimization module, where the acquisition module includes a first acquisition unit, a second acquisition unit, a third acquisition unit, a fourth acquisition unit, and a fifth acquisition unit, the first acquisition unit is configured to acquire a first structural light field, the first structural light field is a standard structural light field corresponding to a first target area of an integrated circuit to be tested, the projection processing module is configured to perform projection imaging processing on the first structural light field, the second acquisition unit is configured to acquire a second structural light field according to a result of the projection imaging processing on the first structural light field by the projection processing module, the third acquisition unit is configured to acquire a first data matrix related to a distribution of pixel values in the first structure, and to acquire a second data matrix related to a distribution of pixel values in the second structural light field, the projection processing module is configured to construct an evaluation function according to a first difference value, the first acquisition unit is configured to perform iterative optimization on the first data matrix and the second data matrix is smaller than the first data matrix and the second data matrix is configured to perform iterative optimization on the first data matrix and the second data matrix is smaller than the first data matrix and the first data matrix is configured to perform iterative optimization on the first data matrix is smaller than the first data matrix is configured to perform iterative optimization on the first data matrix, the fifth acquisition unit is used for acquiring an optimized structure light field pattern, wherein the optimized structure light field pattern is a structure light field pattern corresponding to the target structure light field.
In a fourth aspect, the invention provides a classification device for integrated circuit defects, which is used for executing the classification method for integrated circuit defects according to the second aspect, and comprises a structural light field acquisition unit, an alignment unit, a defect acquisition unit and a defect classification unit, wherein the structural light field acquisition unit is used for guiding the optimized structural light field pattern acquired by the method according to any one of the first aspect into a reflection type amplitude spatial light modulator to acquire a third structural light field, the third structural light field is the structural light field generated by the reflection type amplitude spatial light modulator according to the optimized structural light field pattern, the pixel size of the reflection type amplitude spatial light modulator is matched with the selection of the A and the B and the scaling factor of equipment used for projection imaging processing, the alignment unit is used for aligning the third structural light field with the pattern of an integrated circuit to be detected, and collecting a first far-field microscopic image under the illumination of the third structural light field, the defect acquisition unit is used for comparing the first far-field microscopic image with a second far-field microscopic image to acquire a third structural light field, the third structural light field is the structural light field generated by the reflection type spatial light modulator, the pixel size of the reflection type spatial light modulator is the structural light field generated by the optimized structural light field pattern, the pixel size of the reflection type spatial light modulator is matched with the selection of the A and the B and the scaling factor of equipment used for projection imaging processing is used for classifying the defects according to the ideal image defects of the integrated circuit.
Advantageous effects concerning the above third to fourth aspects can be seen from the respective description in the above first or second aspects.
Drawings
FIG. 1 is a flowchart of an embodiment of a method for acquiring a structured light field pattern according to the present invention;
FIG. 2 is a flowchart of another embodiment of a method for acquiring a structured light field pattern according to the present invention;
FIG. 3 is a schematic diagram of a first target area in an integrated circuit under test according to the present invention;
FIG. 4 is a schematic representation of one embodiment of a far field microimage provided by the present invention;
FIG. 5 is a schematic diagram of an embodiment of a structured light field pattern and structured light field according to the present invention;
FIG. 6 is a schematic diagram of yet another embodiment of a structured light field pattern and structured light field provided by the present invention;
FIG. 7 is a flowchart of an embodiment of a method for classifying defects of an integrated circuit according to the present invention;
FIG. 8 is a flowchart of another exemplary method for classifying defects of an integrated circuit according to the present invention;
FIG. 9 is a schematic structural diagram of an embodiment of a structural light super-resolution defect detection system according to the present invention;
FIG. 10 is a schematic representation of yet another far field microscopy image embodiment provided by the present invention;
FIG. 11 is a schematic diagram of an embodiment of a device for acquiring a structured light field pattern according to the present invention;
Fig. 12 is a schematic diagram of an embodiment of a classification apparatus for integrated circuit defects according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present application are described below with reference to the accompanying drawings in the embodiments of the present application. In the description of embodiments of the application, the terminology used in the embodiments below is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include, for example, "one or more" such forms of expression, unless the context clearly indicates to the contrary. It should also be understood that in the following embodiments of the present application, "at least one", "one or more" means one or more than two (including two). The term "and/or" is used to describe an associative relationship of associative objects, and indicates that three relationships may exist, for example, a and/or B may indicate that a exists alone, while a and B exist together, and B exists alone, where A, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise. The term "coupled" includes both direct and indirect connections, unless stated otherwise. The terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated.
In embodiments of the application, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.
The invention provides a method and a device for acquiring a structural light field pattern, and a method and a device for classifying the structural light field pattern, which are used for solving the technical problems of certain destructiveness and low efficiency in the prior art due to the fact that the defective position on a chip is required to be marked.
Before describing the present invention, the structures in the integrated circuit are shown in brief description of fig. 3-6, and black part in fig. 10, which represent light field intensity of 0, and white part, which represent light field intensity of 1, and light field intensity of 1, which are attached to the drawings of the following description.
The invention provides a method for acquiring a light field pattern of a structure, which is shown in a figure 1, and comprises the following steps:
S101, acquiring a first structural light field, wherein the first structural light field is a standard structural light field corresponding to a first target area of an integrated circuit to be tested;
S102, performing projection imaging processing on the first structure light field to obtain a second structure light field;
S103, acquiring a first data matrix related to pixel value distribution in the first structure light field and acquiring a second data matrix related to pixel value distribution in the second structure light field;
S104, constructing an evaluation function according to a first difference value, wherein the first difference value is the difference value of pixel values of the first data matrix and the second data matrix at corresponding positions in a second target area;
S105, updating the first difference value and performing iterative optimization on the second structure light field by adjusting the pixel value in the first data matrix;
S106, stopping performing iterative optimization on the second structure light field and acquiring a current target structure light field when the first difference value is smaller than a first preset threshold value or the number of iterations is equal to a second preset threshold value, wherein the target structure light field is a first structure light field corresponding to the current second structure light field;
And S107, acquiring an optimized structure light field pattern, wherein the optimized structure light field pattern is the structure light field pattern corresponding to the current second structure light field.
In this embodiment, the first structural light field may be designed by a tester according to a pattern distribution on the integrated circuit to be tested. The distribution of the data in the first data matrix should be consistent with the distribution of pixel values within the first structured light field and the distribution of the data in the second data matrix should be consistent with the distribution of pixel values within the second structured light field. The second target area refers to a randomly selected one of the first data matrix and the second data matrix, the local area corresponding to a position in the first data matrix coinciding with a position in the second data matrix. The first difference value is a difference value of all data of the first data matrix and the second data matrix in the second target area and the data occupying the same position.
According to the invention, the second structural light field is subjected to iterative optimization by adjusting the pixel values in the first data matrix, so that the first structural light field in an ideal state or a state close to the ideal state is obtained, and an accurate defect classification result is obtained in the subsequent defect problem analysis.
In some embodiments, the first structural light field is divided into a first structural light field at intervals of a length in a horizontal direction and a second structural light field at intervals of B length in a vertical direction, the second structural light field is divided into a second structural light field at intervals of C length in the horizontal direction and a third structural light field at intervals of D length in the vertical direction, A, B, C, D are positive numbers, the ratio of C to a and the ratio of D to B are equal to the scaling factor of the projection imaging process, the pixel value distribution of each region of the first structural light field after the division process is obtained to form the first data matrix, and the pixel value distribution of each region of the second structural light field after the division process is obtained to form the second data matrix. The method has the advantages that the pixel value data of discrete distribution is conveniently obtained by dividing the first structure light field and the second structure light field so as to construct a data matrix of the pixel value distribution, and the ratio of C to A and the ratio of D to B are equal to the scaling factor of the projection imaging processing, so that the pixel values of the first structure light field and the second structure light field at corresponding positions can be directly compared so as to obtain an accurate comparison result. Illustratively, the value of A is the length of the first structural light fieldPreferably, the value of A is the length of the first structural light fieldOr (b)
In some embodiments, a ratio of the product of the A and the B to the perimeter of the first structured light field pattern is calculated, a distribution of pixel values of the first structured light field and the second structured light field in a second target region is obtained, and the evaluation function is constructed according to a measurement window function, the first difference value and the ratio, wherein the measurement window function is used for obtaining an aggregate value of the first difference value. The method has the beneficial effects that an effective evaluation function is obtained, and the second structural light field is conveniently optimized through the evaluation function.
In some embodiments, the second structured light field is iteratively optimized by adjusting the size of pixel values within the first data matrix and a conjugate gradient based multi-objective optimization algorithm.
For more detailed description of the method for acquiring a structured light field pattern provided by the present invention, a specific example is described herein, and a flow chart thereof is shown in fig. 2, including:
s201, selecting a first target area on an integrated circuit to be tested;
Specifically, the pattern of the target area selected in the preferred embodiment is shown in fig. 3 (a), and is a two-dimensional rectangular grating circuit, in which the rectangular length and width are 500nm and 100nm respectively, and two typical defects, namely edge bridging as shown in fig. 3 (b) and middle breaking as shown in fig. 3 (c), are selected as defect objects in the integrated circuit to be tested. In some other embodiments, other common functional circuits in the integrated circuit may be used as the circuit structure to be tested, such as a one-dimensional line grating circuit and a logic gate circuit.
Further, in the preferred embodiment, when the selected integrated circuit structure is illuminated by using a common plane wave, far-field microscopic images collected by the detector are shown in (a), (b) and (c) in fig. 4, and are limited by diffraction limits, so that the far-field microscopic images cannot distinguish the type and the position of defects carried in the integrated circuit.
S202, acquiring a first structural light field, wherein the first structural light field is a standard structural light field corresponding to a first target area of an integrated circuit to be tested;
Specifically, according to the circuit structure to be tested (i.e. the first target area) selected in fig. 3 (a), the first structural light field shown in fig. 5 (a) is designed, and the structural light field is formed by a plurality of rectangular arrays with uniform sizes, and the length and width of a single rectangle are 100 times of the rectangular feature sizes in the circuit structure, namely 50 μm and 10 μm.
S203, performing projection imaging processing on the first structure light field to obtain a second structure light field;
s204, gridding the first structure light field and the second structure light field;
Illustratively, the first structural light field designed in (a) in fig. 5 is subjected to gridding treatment, namely, the first structural light field is divided into a plurality of equal parts at intervals of A length in the horizontal direction and B length in the vertical direction, so that the pixel value distribution of the first structural light field can be represented as a discretized data matrix, and subsequent numerical simulation calculation is conveniently unfolded. The A and the B are each 1 μm. And similarly, dividing the second structural light field every C length in the horizontal direction and every D length in the vertical direction, wherein the ratio of C to A and the ratio of D to B are equal to the scaling factor of the projection imaging processing.
S205, constructing an objective function F to evaluate the difference of pixel value distribution of the first structure light field and the second structure light field;
specifically, after the first structural light field is reduced by the projection system, the theoretical feature size is 500nm long and 100nm wide, the theoretical resolution of the second structural light field obtained by performing the projection imaging processing is calculated to be 0.61×426 nm/0.95×270nm, so that the obtained second structural light field has obvious feature degradation compared with the first structural light field, as shown in (b) in fig. 5, an evaluation function F for evaluating the difference between the target light field, namely the first structural light field and the second structural light field is constructed: Wherein δx represents the a, δy represents the B, L represents the perimeter of the second target region corresponding to the first structural light field, w (x, y) represents a measurement window function for obtaining the aggregate value of the first difference value, T represents the pixel value of the first structural light field at the (x, y) position, and z represents the pixel value of the second structural light field at the (x, y) position.
Step S206, a multi-objective optimization algorithm based on conjugate gradient is established, the first difference value is updated by adjusting the pixel value in the first data matrix, iterative optimization is carried out on the second structure light field, when the first difference value is smaller than a first preset threshold value or the iterative times are equal to a second preset threshold value, the iterative optimization is stopped on the second structure light field, and a structure light field pattern corresponding to a target structure light field, namely the optimized structure light field pattern, is obtained, and the target structure light field is the first structure light field corresponding to the current second structure light field.
Specifically, gray values filled in each grid in the structural light field are adjusted by using a multi-objective optimization algorithm, the optimization objective is to minimize the value of the evaluation function F, and when the value of the evaluation function F is lower than a given value (difference) or the iteration number reaches an upper limit, the iterative optimization is stopped, and the obtained optimized structural light field pattern is shown in (a) in fig. 6.
Based on the method for acquiring the structured light field pattern in any one of the embodiments, the present invention provides a method for classifying defects of an integrated circuit, the flow of which is shown in fig. 7, including:
S701, importing the optimized structure light field pattern obtained by the method according to any one of the embodiments into a reflective amplitude type spatial light modulator to obtain a third structure light field, wherein the third structure light field is generated by the reflective amplitude type spatial light modulator according to the optimized structure light field pattern;
S702, aligning the third structure light field with a pattern of an integrated circuit to be tested, and collecting a first far-field microscopic image under the illumination of the third structure light field;
s703, comparing the first far-field microscopic image with a second far-field microscopic image to obtain defects of the integrated circuit to be tested relative to the ideal integrated circuit, wherein the second far-field microscopic image is a far-field microscopic image of the ideal integrated circuit obtained under the illumination of the third structural light field, and the ideal integrated circuit is an integrated circuit without defects;
and S704, classifying the defects according to the positions and the types of the defects to finish the classification of the defects.
In S703, the position where the pixel values are inconsistent is the position where the defect on the far-field microscopic image is located, and the type of the defect is determined by integrating the position and the shape formed by the position where the pixel values are inconsistent. Optionally, the intensity difference between the pixel values is also comprehensively considered when judging the type of the defect.
The method for classifying the integrated circuit defects has the advantages that the integrated circuit defects to be detected do not need to be marked and are not damaged while the defect detection accuracy and efficiency are ensured.
Optionally, the pixel size of the reflective amplitude-type spatial light modulator is matched with the selection of the A and the B, including that the A and the B are integer multiples of the pixel size of the reflective amplitude-type spatial light modulator. The method has the beneficial effects that the light field structure beneficial to processing is conveniently obtained, so that the defect classification process is simplified.
Optionally, comparing the first far-field microscopic image with the second far-field microscopic image to obtain a defect of the integrated circuit to be tested relative to the ideal integrated circuit, wherein the defect comprises the steps of obtaining a position of the defect, namely a position inconsistent with a pixel value of the second far-field microscopic image in the first far-field microscopic image, and judging the type of the defect by combining the position of the defect and a shape formed by the position inconsistent with the pixel point. The method has the advantages that the method only needs to judge the inconsistent positions of the pixels and the shapes formed by the inconsistent positions of the pixels to obtain the positions and the types of the defects, and does not need to mark the chip, namely the method has no destructiveness while ensuring the accuracy of defect identification, and in addition, the efficiency and the automation are improved to a certain extent because the participation of testers is hardly needed in the defect classification process.
For more detailed description of the method for classifying integrated circuit defects according to the present invention, a specific example is described herein, and the flow chart of the method is shown in fig. 8, and includes:
S801, a reflective amplitude type spatial light modulator is used, and a structured light super-resolution defect detection system is configured and built;
Specifically, referring to fig. 9, the structure of the structural light super-resolution defect detection system includes a 421nm laser light source 210, an illumination light path structure 220, a structural light modulation mechanism 230 (i.e. a reflective amplitude type spatial light modulator), a sample stage 240, a projection and imaging structure 250, and a signal light collection mechanism 260, which are sequentially arranged, wherein the optical axes of the first plane mirror 221, the second plane mirror 222 and the illumination light path are respectively 30 ° and 135 °, the zoom ratio of a conjugate lens system formed by an objective lens 251 and a tube lens 252 is greater than or equal to 100X, and the numerical aperture of the objective lens 251 is greater than or equal to 0.8. The reflection type amplitude type spatial light modulator is added in an incident light path, the light beam is firstly led into the reflection type amplitude type spatial light modulator by utilizing two plane reflectors, then the modulated structure light is turned back to an illumination light path, and the angle between the incident angle of the light beam and the normal line of the reflection type amplitude type spatial light modulator is 10 degrees. The light beam entering the beam splitter is parallel light, the illumination light path and the imaging light path share the same group of objective lens and tube lens, and the pixel arrays of the reflective amplitude type spatial light modulator and the detector are all on the focal plane of the tube lens. Alternatively, the magnification of the conjugate system of lens and tube mirror may be set to 100X, 150X, 200X, 500X. Light in the laser light source and light in the illumination light path belong to the visible light band.
Step S802, guiding the optimized structure light field pattern obtained by the embodiment into a reflection type amplitude type spatial light modulator in an incident light path, and transferring the structure light field generated by the reflection type amplitude type spatial light modulator to an object plane of an objective lens through a tube lens and the objective lens to obtain a third structure light field;
Specifically, the pixel size of the reflective amplitude-type spatial light modulator is 1 μm consistent with the sizes of the a and the B, and the structural light field of the incident light beam projected to the object plane of the objective lens after being shaped by the reflective amplitude-type spatial light modulator is shown in fig. 6 (B). Alternatively, the sizes of the A and the B are equal to the pixel size of the reflective amplitude type spatial light modulator or the integral multiple of the pixel size of the reflective amplitude type spatial light modulator, and the sizes of the pixels of the reflective amplitude type spatial light modulator can be flexibly adjusted.
Step 803, performing spatial position matching on a third structural light field and a pattern of an integrated circuit to be tested in an object plane, and collecting a first far-field microscopic image under the illumination of the third structural light field;
Specifically, the sample to be measured is placed on a precision displacement stage, the displacement stage is adjusted so that the structural light field on the object plane of the objective lens and the circuit structure to be measured are matched in spatial position, the far-field microscopic image collected by the detector 260 is shown in fig. 10, fig. 10 (a) is a far-field microscopic image of a perfect integrated circuit without defects, fig. 10 (b) is a far-field microscopic image of an integrated circuit with edge bridging defects, and fig. 10 (c) is a far-field microscopic image of an integrated circuit with intermediate fracture defects. Further, the integrated circuit to be tested is far larger than the third structural light field, and the position of the third structural light field can be adjusted so that the third structural light field is aligned with the integrated circuit to be tested respectively to obtain corresponding far-field microscopic images.
Step S804, comparing a second far-field microscopic image with the first far-field microscopic image collected by the detector to finish the positioning and classification of the integrated circuit defects, wherein the second far-field microscopic image is a far-field microscopic image of an ideal integrated circuit obtained under the illumination of the third structural light field. The ideal integrated circuit should be consistent with the design goals of the integrated circuit under test, except that the integrated circuit under test may be defective, but the ideal integrated circuit is not.
Specifically, the second far-field microscopic image and the first far-field microscopic image selected in the preferred embodiment are compared, so that the defect characterization effect is better, and the defect types and positions of edge bridging and middle fracture can be intuitively reflected. Moreover, the invention can detect any nano-level defects.
Further, in order to meet the measurement requirements of integrated circuits with more complex functions and layouts, far-field microscopic images of the integrated circuits with defects and defects are subjected to differential processing, so that the contrast ratio of the defects is improved, the missing detection of the defects is avoided, the difficulty in positioning and classifying the defects through an algorithm or direct observation is reduced, and the defects in a large-area measurement area can be rapidly and accurately positioned and classified.
The structured light microscopic detection technology adopts a structured light field corresponding to the integrated circuit structure to illuminate the region to be detected of the sample, and the special illumination mode can inhibit the intensity of a scattered field generated by the inherent pattern and the non-defect region, but does not influence the intensity of the scattered field corresponding to the defect. The signal to noise ratio of weak scattering signals corresponding to the integrated circuit defects is improved, so that weak scattering fields generated by the small defects can be detected. Typical structured light microscopic measurement systems generally select a reflective amplitude type spatial light modulator to generate a required structured light field, and reduce and project the first structured light field onto an object plane of an objective lens through a conjugate lens group formed by the objective lens and the objective lens, after the structured light field is spatially matched with a corresponding circuit structure on an integrated circuit, a reflected scattered field is amplified and imaged to a detector image plane through the objective lens and the objective lens, so as to obtain a super-resolution far-field microscopic image of the integrated circuit to be measured, and defects can be positioned and classified by comparing the far-field microscopic image and the super-resolution far-field microscopic image of an ideal integrated circuit.
Based on the method for acquiring the structured light field pattern according to any one of the embodiments, the present invention provides a device for acquiring the structured light field pattern, as shown in fig. 11, for executing the method for acquiring the structured light field pattern according to any one of the embodiments, including an acquisition module, a projection processing module 1102, an evaluation module 1103, and an optimization module 1104; the acquisition module comprises a first acquisition unit 11011, a second acquisition unit 11012, a third acquisition unit 11013, a fourth acquisition unit 11014 and a fifth acquisition unit 11015, wherein the first acquisition unit 11011 is used for acquiring a first structural light field which is a standard structural light field corresponding to a first target area of an integrated circuit to be detected, the projection processing module 1102 is used for carrying out projection imaging processing on the first structural light field, the second acquisition unit 11012 is used for acquiring a second structural light field according to the result of the projection imaging processing on the first structural light field by the projection processing module, the third acquisition unit 11013 is used for acquiring a first data matrix related to pixel value distribution in the first structural light field and acquiring a second data matrix related to pixel value distribution in the second structural light field, the evaluation module 1103 is used for constructing an evaluation function according to a first difference value which is a pixel value of the first data matrix and the second data matrix in a corresponding position of the second target area, the first difference value is used for optimizing the first difference value and the second data matrix when the first difference value is smaller than the first threshold value and the second threshold value is smaller than or equal to the first threshold value, the iterative optimization of the second structural light field is stopped, the fourth obtaining unit 11014 is configured to obtain a target structural light field, where the target structural light field is a first structural light field corresponding to the current second structural light field, and the fifth obtaining unit 11015 is configured to obtain an optimized structural light field pattern, where the optimized structural light field pattern is a structural light field pattern corresponding to the target structural light field.
All relevant contents of each step related to the above method embodiment may be cited to the functional description of the corresponding unit module, which is not described herein.
Based on the classification method of integrated circuit defects in any one of the embodiments, the invention provides a classification device of integrated circuit defects, as shown in fig. 12, comprising a structural light field acquisition unit 1201, an alignment unit 1202, a defect acquisition unit 1203 and a defect classification unit 1204, wherein the structural light field acquisition unit 1201 is used for guiding the optimized structural light field pattern in any one of the embodiments into a reflective amplitude type spatial light modulator to acquire a third structural light field, the third structural light field is the structural light field generated by the reflective amplitude type spatial light modulator according to the optimized structural light field pattern, the pixel size of the reflective amplitude type spatial light modulator is matched with the selection of the A and the B and the scaling factor of a device for projection imaging processing, the alignment unit 1202 is used for aligning the third structural light field with the pattern of an integrated circuit to be classified, and collecting a first far-field microscopic image 1203 under the illumination of the third structural light field, the defect acquisition unit is used for comparing the first far-field microscopic image with a second far-field microscopic image to acquire the third structural light field, the pixel size of the reflective amplitude type spatial light modulator is the structural light field generated by the reflective amplitude type spatial light modulator, the pixel size of the reflective amplitude type spatial light modulator is matched with the image of the structural light field generated by the optimized structural light field pattern, the image is the image of the integrated circuit is different from the ideal image of the integrated circuit defect classification device, and the ideal defect classification device is classified as the ideal defect type defect in the integrated circuit is classified as the ideal defect type defect.
All relevant contents of each step related to the above method embodiment may be cited to the functional description of the corresponding unit module, which is not described herein.
The foregoing is merely a specific implementation of the embodiment of the present application, but the protection scope of the embodiment of the present application is not limited to this, and any changes or substitutions within the technical scope disclosed in the embodiment of the present application should be covered in the protection scope of the embodiment of the present application. Therefore, the protection scope of the embodiments of the present application shall be subject to the protection scope of the claims.
Claims (9)
1. A method for acquiring a structured light field pattern, comprising:
s1, acquiring a first structural light field, wherein the first structural light field is a standard structural light field corresponding to a first target area of an integrated circuit to be tested;
S2, performing projection imaging processing on the first structure light field to obtain a second structure light field;
s3, acquiring a first data matrix related to pixel value distribution in the first structure light field and acquiring a second data matrix related to pixel value distribution in the second structure light field;
s4, constructing an evaluation function according to a first difference value, wherein the first difference value is a difference value of pixel values of the first data matrix and the second data matrix at corresponding positions in a second target area;
s5, updating the first difference value and performing iterative optimization on the second structure light field by adjusting the pixel value in the first data matrix;
S6, stopping performing iterative optimization on the second structure light field and acquiring a target structure light field when the first difference value is smaller than a first preset threshold value or the number of iterations is equal to a second preset threshold value, wherein the target structure light field is a first structure light field corresponding to the current second structure light field;
s7, acquiring an optimized structure light field pattern, wherein the optimized structure light field pattern is a structure light field pattern corresponding to the target structure light field.
2. The method according to claim 1, wherein in S3, the first structural light field is divided into a plurality of lengths a in a horizontal direction and a plurality of lengths B in a vertical direction, the second structural light field is divided into a plurality of lengths C in a horizontal direction and a plurality of lengths D in a vertical direction, the A, B, C, D are positive numbers, and the ratio of C to a and the ratio of D to B are equal to the zoom ratio of the projection imaging process;
Acquiring pixel value distribution of each region after dividing the first structural light field to form the first data matrix;
And acquiring pixel value distribution of each region of the second structural light field after the division processing so as to form the second data matrix.
3. The method of claim 2, wherein in S4, calculating a ratio of the product of a and B to the perimeter of the first structured light field pattern;
acquiring pixel value distribution of the first structural light field and the second structural light field in a second target area;
and constructing an evaluation function according to a measurement window function, the first difference value and the ratio, wherein the measurement window function is used for acquiring an aggregate value of the first difference value.
4. A method of acquiring a structured light field pattern according to claim 3, characterized in that in S5 the second structured light field is iteratively optimized by adjusting the size of the pixel values within the first data matrix and a conjugate gradient based multi-objective optimization algorithm.
5. A method for classifying defects in an integrated circuit, comprising:
Introducing the optimized structure light field pattern obtained by the method of any one of claims 1-4 into a reflective amplitude type spatial light modulator to obtain a third structure light field, wherein the third structure light field is a structure light field generated by the reflective amplitude type spatial light modulator according to the optimized structure light field pattern, the pixel size of the reflective amplitude type spatial light modulator is matched with the selection of A, B, wherein A is a length interval for dividing the first structure light field in the horizontal direction, B is a length interval for dividing the first structure light field in the vertical direction, and the pixel value distribution of each region of the first structure light field after the division is formed into the first data matrix;
Aligning the third structure light field with the pattern of the integrated circuit to be tested, and collecting a first far-field microscopic image under the illumination of the third structure light field;
Comparing the first far-field microscopic image with a second far-field microscopic image to obtain defects of the integrated circuit to be tested relative to the ideal integrated circuit, wherein the second far-field microscopic image is a far-field microscopic image of the ideal integrated circuit obtained under the illumination of the third structural light field, and the ideal integrated circuit is an integrated circuit without defects;
and classifying the defects according to the positions and the types of the defects to finish the classification of the defects.
6. The method of claim 5, wherein the pixel size of the reflective amplitude-type spatial light modulator is matched to the selection of A and B, and wherein A and B are integer multiples of the pixel size of the reflective amplitude-type spatial light modulator.
7. The method of claim 5, wherein comparing the first far-field microscopy image to a second far-field microscopy image to obtain defects of the integrated circuit under test relative to the ideal integrated circuit comprises:
acquiring the position of the defect, wherein the position of the defect is the position in the first far-field microscopic image, which is inconsistent with the pixel value of the second far-field microscopic image;
And judging the type of the defect by combining the position of the defect and the shape formed by the positions with inconsistent pixel values.
8. An acquisition device of a structural light field pattern, characterized in that the acquisition device is used for executing the acquisition method of the structural light field pattern according to any one of claims 1-4, and comprises an acquisition module, a projection processing module, an evaluation module and an optimization module;
The acquisition module comprises a first acquisition unit, a second acquisition unit, a third acquisition unit, a fourth acquisition unit and a fifth acquisition unit;
The first acquisition unit is used for acquiring a first structural light field, wherein the first structural light field is a standard structural light field corresponding to a first target area of the integrated circuit to be tested;
the projection processing module is used for carrying out projection imaging processing on the first structure light field, and the second acquisition unit is used for acquiring a second structure light field according to the result of the projection imaging processing on the first structure light field by the projection processing module;
The third acquisition unit is used for acquiring a first data matrix related to pixel value distribution in the first structure light field and acquiring a second data matrix related to pixel value distribution in the second structure light field;
The evaluation module is used for constructing an evaluation function according to a first difference value, wherein the first difference value is a difference value of pixel values of the first data matrix and the second data matrix at corresponding positions in a second target area;
The optimization module is used for updating the first difference value and carrying out iterative optimization on the second structure light field by adjusting the pixel value in the first data matrix, and stopping carrying out iterative optimization on the second structure light field when the first difference value is smaller than a first preset threshold value or the iterative times are equal to a second preset threshold value, wherein the fourth acquisition unit is used for acquiring a target structure light field which is a first structure light field corresponding to the current second structure light field;
The fifth acquisition unit is configured to acquire an optimized structure light field pattern, where the optimized structure light field pattern is a structure light field pattern corresponding to the target structure light field.
9. An integrated circuit defect classification device, which is used for executing the integrated circuit defect classification method according to any one of claims 5-7, and comprises a structural light field acquisition unit, an alignment unit, a defect acquisition unit and a defect classification unit;
The structure light field acquisition unit is used for guiding the optimized structure light field pattern acquired by the method of any one of claims 1-4 into a reflection type amplitude type spatial light modulator to acquire a third structure light field, wherein the third structure light field is the structure light field generated by the reflection type amplitude type spatial light modulator according to the optimized structure light field pattern, the pixel size of the reflection type amplitude type spatial light modulator is matched with the selection of A, B and the zoom magnification of equipment used for projection imaging processing, wherein A is the length interval for dividing the first structure light field in the horizontal direction, B is the length interval for dividing the first structure light field in the vertical direction, and the pixel value distribution of each region of the first structure light field after the division processing forms the first data matrix;
The alignment unit is used for aligning the third structural light field with the pattern of the integrated circuit to be tested and collecting a first far-field microscopic image under the illumination of the third structural light field;
The defect acquisition unit is used for comparing the first far-field microscopic image with a second far-field microscopic image so as to acquire defects of the integrated circuit to be tested relative to the ideal integrated circuit, the second far-field microscopic image is a far-field microscopic image of the ideal integrated circuit acquired under the illumination of the third structural light field, and the ideal integrated circuit is an integrated circuit without defect problems;
the defect classification unit is used for classifying the defects according to the positions and the types of the defects so as to finish classification of the defects.
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