KR102330738B1 - System and method for creating dynamic management area in inspection tool - Google Patents

Abstract

The defect inspection system includes an inspection subsystem and a controller communicatively coupled to the detector. The inspection subsystem includes an illumination source configured to generate a beam of illumination, a set of illumination optics for directing the beam of illumination to the sample, and a detector configured to collect illumination emitted from the sample. The controller includes a memory device and one or more processors configured to execute program instructions. The controller is configured to: define one or more management regions on a sample based on the one or more target patterns and design data of the sample stored in a memory device of the controller to determine one or more target patterns corresponding to one or more features on the sample; and identify the one or more defects within the one or more control areas of the sample based on the illumination collected by the detector.

Description

System and method for creating dynamic management area in inspection tool

preference

This application is filed May 28, 2015, with the inventors Vijayakumar Ramachandran, Vidyasagar Anantha, Philip Measor, and Rajesh Manepalli entitled "NOVEL AND EFFICIENT APPROACH FOR ON-TOOL DYNAMIC CARE AREA GENERATION USING DESIGN" Indian Provisional Patent Application No. 2681/CHE/2015, and filed on July 30, 2015, the inventors are Vijayakumar Ramachandran, Vidyasagar Anantha, Philip Measor, and Rajesh Manepalli, entitled "NOVEL AND EFFICIENT APPROACH FOR ON- Priority is claimed to U.S. Provisional Patent Application No. 61/198,911, "TOOL DYNAMIC CARE AREA GENERATION USING DESIGN," both of which are incorporated herein by reference in their entirety.

technical field

BACKGROUND This disclosure relates generally to defect inspection, and more particularly to care area generation on an inspection tool.

The inspection system identifies and classifies defects on a semiconductor wafer to create a group of defects on the wafer. A given semiconductor wafer may contain hundreds of chips, each chip containing thousands of components of interest, and each component of interest may have millions of instances on a given layer of chips. As a result, an inspection system may generate a vast number of data points (eg, hundreds of billions of data points for some systems) on a given wafer. In addition, increasingly shrinking device requirements lead to increased requirements for inspection systems. The requirements include the need for improved resolution and capacity needed to infer the root cause of an identified defect without sacrificing inspection speed or accuracy.

However, the use of design data associated with wafers typically impacts the overhead of the inspection process and thus throughput. For example, a utility for generating a region of interest based on design data may provide a large data file specifying various attributes of the region of interest that should be sent to the inspection tool. In addition, the inspection tool may need to register design data with the sample in order to correlate the design coordinates with the coordinates of the inspection tool.

Accordingly, it would be desirable to provide a system and method for treating a disadvantage as identified above.

A defect inspection system in accordance with one or more exemplary embodiments of the present disclosure is disclosed. In another exemplary embodiment, the system includes an inspection subsystem. In another exemplary embodiment, the inspection subsystem includes an illumination source configured to generate a beam of illumination. In another exemplary embodiment, the inspection subsystem includes a set of illumination optics for directing a beam of illumination to a sample. In another exemplary embodiment, the inspection subsystem includes a detector configured to collect illumination emitted from the sample. In another exemplary embodiment, the system includes a controller communicatively coupled to the detector. In another exemplary embodiment, the controller includes a memory device and one or more processors configured to execute program instructions. In another embodiment, the controller is configured to determine one or more target patterns corresponding to one or more features on the sample. In another embodiment, the controller is configured to define one or more care areas on the sample based on the design data of the sample and the one or more target patterns. In another exemplary embodiment, the design data of the sample is stored in a memory device of the controller. In another embodiment, the controller is configured to identify one or more defects within the one or more control areas of the sample based on the illumination collected by the detector.

A defect inspection system is disclosed in accordance with one or more exemplary embodiments of the present disclosure. In another exemplary embodiment, the system includes an inspection subsystem. In another exemplary embodiment, the inspection subsystem includes an illumination source configured to generate a beam of illumination. In another exemplary embodiment, the inspection subsystem includes a set of illumination optics for directing a beam of illumination to a sample. In another exemplary embodiment, the inspection subsystem includes a detector configured to collect illumination emitted from the sample. In another exemplary embodiment, the system includes a controller communicatively coupled to the detector. In another exemplary embodiment, the controller includes a memory device and one or more processors configured to execute program instructions. In another embodiment, the controller is configured to determine one or more target patterns corresponding to one or more features on the sample. In another embodiment, the controller is configured to determine the source pattern. In another exemplary embodiment, the source pattern approximates a subset of instances of one or more target patterns within the design data of the sample. In another exemplary embodiment, the design data of the sample is stored in a memory device of the controller. In another exemplary embodiment, the controller is configured to define a spatial relationship between a source pattern and at least one target pattern of a subset of instances of the one or more target patterns within the design data of the sample. In another exemplary embodiment, the controller is configured to identify one or more instances of the source pattern within the design data of the sample. In another exemplary embodiment, the controller is configured to: select within the design data of the sample based on one or more identified instances of the source pattern and a spatial relationship between the source pattern and at least one target pattern of a subset of the one or more instances of the target pattern. and identify a subset of instances of the one or more target patterns. In another exemplary embodiment, the controller is configured to define one or more management regions on the sample based on a subset of instances of the one or more target patterns. In another embodiment, the controller is configured to identify one or more defects within the one or more control areas of the sample based on the illumination collected by the detector.

The defect inspection method is a defect inspection method according to one or more exemplary embodiments of the present disclosure. In one exemplary embodiment, the method includes providing design data of the sample to the inspection system. In another exemplary embodiment, a method includes determining one or more target patterns. In another exemplary embodiment, the one or more target patterns include design data associated with one or more sample features to be inspected. In another exemplary embodiment, a method includes defining one or more management areas on a sample by the inspection system based on the design data of the sample and one or more target patterns. In another exemplary embodiment, the method includes identifying one or more defects within one or more control areas of the sample.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and for purposes of explanation only, and are not necessarily limiting of the invention as claimed. BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the general description, serve to explain the principles of the invention.

Various advantages of the present disclosure may be better understood by those skilled in the art by reference to the accompanying drawings, in which:
1 is a conceptual diagram illustrating an inspection system, in accordance with one or more embodiments of the present disclosure.
2 is a block diagram of an inspection tool of an inspection system illustrating use of design data to create a management area for inspection based on design data stored on the inspection tool, in accordance with one or more embodiments of the present disclosure.
3 is a flow diagram illustrating steps performed in a method for defect detection, in accordance with one or more embodiments of the present disclosure.
4 is a schematic diagram of design data illustrating the definition of an associated management area based on a source pattern, in accordance with one or more embodiments of the present disclosure.
5A is a conceptual diagram illustrating an optical inspection subsystem, in accordance with one or more embodiments of the present disclosure.
5B is a simplified schematic diagram of an inspection subsystem utilizing one or more particle beams, in accordance with one or more embodiments of the present disclosure.

Reference will now be made in detail to the disclosed subject matter, which is illustrated in the accompanying drawings.

Embodiments of the present disclosure relate to an inspection system with on-tool generation of a management area of a sample. In this regard, a control area, or a selected area of a sample of interest for examination, may be created directly on the examination tool. Additional embodiments of the present disclosure relate to on-tool identification of a management area based on identifying one or more instances of a target pattern of interest within design data of a sample stored on an inspection tool. For example, the target pattern may include design data associated with one or more sample features to be inspected. Additional embodiments of the present disclosure relate to storage and pre-processing of design data of a sample on an inspection system for efficient determination of a management area on an inspection tool. Another embodiment of the present disclosure relates to identification of a subset of instances of a target pattern within design data of a sample based on proximity to a source pattern within the design data. Accordingly, the creation of the management region may include retrieval of the sample's design data for combinations of target patterns of interest that are filtered to include instances of the target pattern that are proximate to the source pattern based on defined spatial relationships.

It is recognized herein that an inspection tool may typically only inspect a subset of the surface of a sample for defects. The creation of a target area, or control area, of a sample to be inspected may greatly improve the accuracy of defect inspection by reducing spurious signals and noise, as well as the efficiency of defect detection by reducing the surface area being inspected. Control areas may also be defined to provide targeted inspection analysis, such as, but not limited to, analysis of specific defect types or analysis of specific pattern elements located throughout a sample. .

It is also recognized that design data of a sample (eg, physical placement of components on the sample, electrical connections between components on the sample, etc.) may be utilized to define a management area. However, the use of design data typically impacts the overhead of the inspection process and thus throughput. For example, a utility for creating a management area based on design data may include various attributes of the management area that must be transmitted to the inspection tool (eg, the location of each management area on the sample, the shape of each management area, and so on). In addition, the inspection tool registers the design data with the sample (eg, aligns, scales, or etc.) may be required.

Embodiments of the present disclosure relate to storing a preprocessed version of design data of a sample on an inspection tool. In this regard, a design-based management area may be created on the inspection tool using the preprocessed design data (eg, a local version of the preprocessed design data). Also, in some embodiments, design-based management areas may be created on the inspection tool without additional data transfer requirements. Additionally, the design-based ROI generated on the inspection tool may be automatically aligned with the coordinates of the inspection tool.

As used throughout this disclosure, the term “sample” generally refers to a substrate formed of a semiconductor or non-semiconductor material (eg, a wafer, or the like). For example, the semiconductor or non-semiconductor material may include, but is not limited to, single crystal silicon, gallium arsenide, or indium phosphide. A sample may include one or more layers. For example, such a layer may include, but is not limited to, a resist, a dielectric material, a conductive material, or a semiconducting material. Many different types of such layers are known in the art, and the term sample as used herein is intended to encompass a sample on which any type of such layer may be formed. One or more layers formed on the sample may or may not be patterned. For example, a sample may include a plurality of dies, each die having repeatable patterned features. The formation and processing of this layer of material may ultimately result in a finished device. Many different types of devices may be formed on a sample, and the term sample as used herein is intended to include a sample on which any type of device known in the art is being fabricated. Also, for purposes of this disclosure, the terms sample and wafer should be construed as being interchangeable. Also, for purposes of this disclosure, the terms patterned device, mask, and reticle should be interpreted as being interchangeable.

1 is a conceptual diagram illustrating an inspection system 100 , in accordance with one or more embodiments of the present disclosure. In one embodiment, the inspection system 100 includes an inspection subsystem 102 for detecting defects on the sample 110 .

It is noted herein that inspection subsystem 102 may be any type of inspection system known in the art suitable for detecting defects on sample 110 . For example, inspection subsystem 102 may include a particle beam inspection subsystem. Accordingly, the inspection subsystem 102 is configured to detect one or more defects based on detected radiation (eg, secondary electrons, backscattered electrons, luminescence, and the like) emanating from the sample 110 , such that: One or more particle beams (eg, electron beams, ion beams, or the like) may be directed at the sample 110 . As another example, inspection subsystem 102 may include an optical inspection subsystem. Accordingly, the inspection subsystem 102 detects one or more defects based on detected radiation (eg, reflected radiation, scattered radiation, diffracted radiation, luminescent radiation, or the like) emitted from sample 110 . Optical radiation may be directed to the sample 110 to be detectable.

Inspection subsystem 102 may operate in an imaging mode or a non-imaging mode. For example, in an imaging mode, an individual object (eg, a defect) is located within an illuminated spot on a sample (eg, a portion of a brightfield image, a darkfield image, a phase contrast image, or the like). as) may be decomposed. In a non-imaging mode of operation, the radiation collected by the one or more detectors may be associated with a single illuminated spot on the sample and may represent a single pixel of the image of the sample 110 . In this regard, an image of the sample 110 may be generated by acquiring data from an array of sample locations. In addition, the inspection subsystem 102 is configured to characterize the angular distribution of radiation from the sample 110 (eg, related to scattering and/or diffraction of the radiation by the sample 110 ) to characterize the radiation from the sample. It can also act as a scatterometry-based inspection system to be analyzed in this pupil plane.

In another embodiment, the inspection system 100 includes a controller 104 coupled to the inspection subsystem 102 . For example, the controller 104 may be communicatively coupled to the detector 522 . In this regard, the controller 118 may be configured to receive data, including but not limited to, inspection data from the inspection subsystem 102 . In another embodiment, the controller 118 includes one or more processors 108 . For example, the one or more processors 108 may be configured to execute a set of program instructions maintained in the memory device 108 or memory. The one or more processors 106 of the controller 104 may include any processing element known in the art. In this sense, the one or more processors 108 may include devices of any microprocessor type configured to execute algorithms and/or instructions. In addition, memory medium 108 may include any storage medium known in the art suitable for storing program instructions executable by one or more processors 108 associated therewith. For example, memory medium 108 may include non-transitory memory media. By way of further example, memory medium 108 may include, but is not limited to, read only memory, random access memory, magnetic or optical memory devices (eg, disks), magnetic tape, solid state drives, and the like. it doesn't happen It is also noted that the memory medium 108 may be housed in a common controller housing along with one or more processors 108 .

Inspection system 100 may detect defects associated with a sample using any inspection technique known in the art. For example, a defect on the sample 110 may include a measured characteristic of the sample (eg, generated by the inspection subsystem 102 , or the like), a measured characteristic of a reference sample (eg, die vs. compared to die-to-die (D2D) inspection, standard reference die (SRD) inspection, or the like). As another example, a defect on sample 110 may include comparing an inspection image of sample 110 to an image based on a design characteristic (eg, die-to-database (D2DB) inspection). may be detected by As another example, the inspection system 100 may include a virtual inspection system. In one embodiment, the controller 104 operates as a virtual inspector. In this regard, the controller 104 may detect one or more defects on the sample 110 by comparing the inspection data of the sample to persistent reference data (eg, one or more reference images). have. For example, one or more reference images may be stored on the inspection system 100 (eg, in the memory 108 ) and utilized for defect detection. In another embodiment, the controller 104 generates and/or receives a simulated inspection image based on design data associated with the sample 110 to act as a reference image for defect detection.

Inspection systems using design data are generally described in US Patent Application No. 2014/0153814, published Jun. 5, 2013, which is incorporated herein by reference in its entirety. Inspection systems that use persistent data (eg, stored data) are generally described in US Pat. No. 8,126,255, issued Feb. 28, 2012, which is incorporated herein by reference in its entirety. are integrated Inspection systems that use design data of samples to facilitate inspection are generally described in US Pat. No. 7,676,077, issued Mar. 9, 2010, and US Pat. No. 6,154,714, issued Nov. 28, 2000. , these patents are incorporated herein by reference in their entirety. Determination of the source of defects and failures is generally determined in U.S. Patent No. 6,920,596, issued July 19, 2005, U.S. Patent No. 8,194,968, issued June 5, 2015, and February 7, 2006 No. 6,995,393, which is incorporated herein by reference in its entirety. Device feature extraction and monitoring is generally described in US Pat. No. 8,611,639, issued Dec. 17, 2013. The use of dual energy electron flooding for neutralization of charged substrates is generally described in US Pat. No. 6,930,309, issued Aug. 16, 2005, which is incorporated herein by reference in its entirety. are integrated The use of reticles in inspection systems is generally covered by US Pat. No. 6,529,621, issued Mar. 4, 2003, US Pat. No. 6,748,103, issued Jun. 8, 2004, and Nov. 15, 2005. It is described in issued US Pat. No. 6,966,047, which is incorporated herein by reference in its entirety. Generating an inspection process or inspection target is generally described in US Pat. No. 6,691,052, issued Feb. 10, 2004, US Pat. No. 6,921,672, issued Jul. 26, 2005, and Feb. 7, 2012. US Patent No. 8,112,241 issued to , which is incorporated herein by reference in its entirety. Determination of critical regions of semiconductor design data is generally described in US Pat. No. 6,948,141, issued Sep. 20, 2005, which is incorporated herein by reference in its entirety.

2 is a block diagram of an inspection tool 202 of the inspection system 100 illustrating the definition of a management area on the inspection tool 202, in accordance with one or more embodiments of the present disclosure. In one embodiment, the inspection tool 202 includes one or more modules configured to perform one or more steps of the inspection tool 102 . For example, one or more modules of inspection tool 202 may, but need not, be implemented as one or more program instructions stored in memory 108 and executed by one or more processors 106 .

In another embodiment, the inspection tool 202 includes a design module 204 . For example, the design module 204 may include design data associated with one or more samples 110 to be inspected by the inspection tool 202 . In this regard, the management area may be created on the inspection tool 202 using design data associated with the sample 110 . It is noted herein that creating design-based management areas directly on the inspection tool 202 may facilitate efficient and dynamic creation of management areas. For example, the creation of a design-based management region on the inspection tool 202 may reduce data transfer (eg, region-of-interest definitions, or the like) between the inspection tool 202 and external systems. . In addition, the creation of a design-based management area on the inspection tool 202 may facilitate accurate alignment of coordinates associated with the design data and the sample and/or coordinates associated with the inspection tool 202 . For example, the design coordinates (eg, GDS coordinates, or the like) are adjusted such that the size and orientation of the design pattern in the design data matches the printed pattern on the sample as measured by the inspection tool 202 . (eg, scaled, rotated, or the like). The creation of a design-based management area on the inspection tool may facilitate accurate and efficient alignment of design and sample coordinate systems.

The term “design data” as used in this disclosure generally refers to the physical design of an integrated circuit and data derived from the physical design through complex simulations or simple geometric manipulations and Boolean operations. Further, an image of a reticle and/or a derivative thereof obtained by the reticle inspection system may be used as a proxy or substitutes for design data. This reticle image or derivative thereof may serve as a replacement for the design layout in any of the embodiments described herein that use design data. Design data and design data surrogates are described in US Pat. Nos. 7,676,007 to Kulkarni, issued Mar. 9, 2010; US Patent Application Serial No. 13/115,957 to Kulkarni, filed May 25, 2011; US Pat. No. 8,041,103 to Kulkarni, issued Oct. 18, 2011; and US Pat. No. 7,570,796 to Zafar et al., issued Aug. 4, 2009, all of which are incorporated herein by reference. The use of design data in directing the inspection process is also generally described in US Patent Application Serial No. 13/339,805 to Park, filed February 17, 2012, which is incorporated by reference in its entirety. is incorporated herein.

Design data may include properties of individual components and/or layers on sample 110 (eg, insulator, conductor, semiconductor, well, substrate, or the like), connectivity between layers on sample 110 , or sample 110 . ) and the physical layout of the components and connections (eg, wires) on it. In this regard, the design data may include a plurality of design pattern elements corresponding to printed pattern elements on the sample 112 .

Herein, design data may include what is known as a “floorplan” that includes placement information for pattern elements on sample 110 . It is also noted herein that this information may be extracted from the physical design of the chip, which is typically stored in GDSII or OASIS file format. Structural behavior or process design interactions may be a function of the context (environment) of the pattern element. By using the floorplan, the proposed analysis can identify pattern elements within the design data, such as polygons, that describe the features to be constructed on the semiconductor layer. In addition, the proposed method may provide not only coordinate information of these repeating blocks, but also context-sensitive data (eg, location of adjacent structures, or the like).

In one embodiment, the design data includes one or more graphical representations (eg, visual representations, symbolic representations, graphical representations, or the like) of pattern elements. For example, the design data may include a graphical representation of the physical layout of the component (eg, a description of one or more polygons corresponding to printed pattern elements fabricated on sample 110 ). The design data may also include one or more layers of the sample design (eg, one or more layers of printed pattern elements fabricated on the sample 110 ) or a graphical representation of connectivity between one or more layers. As another example, design data may include a graphical representation of electrical connectivity of components on sample 110 . In this regard, the design data may include a graphical representation of one or more circuits or sub-circuits associated with the sample. In another embodiment, the design data includes one or more image files comprising graphical representations of one or more portions of sample 110 .

In other embodiments, the design data includes one or more textual descriptions (eg, one or more lists, one or more tables, one or more databases, or the like) of the connectivity of the pattern elements of the sample 110 . For example, design data may include, but is not limited to, netlist data, circuit simulation data, or hardware description language data. A netlist is for providing a description of the connectivity of an electrical circuit including, but not limited to, a physical netlist, a logical netlist, an instance-based netlist, or a net-based netlist. It may include any type of netlist known in the art. The netlist may also include (eg, in a hierarchical configuration) one or more sub-netlists for describing circuits and/or sub-circuits on sample 110 . For example, netlist data associated with a netlist may include a list of nodes (eg, nets, wires between components of a circuit, or the like), a list of ports (eg, terminals, pins, connector, or the like), a description of the electrical component between the four (eg, a resistor, capacitor, inductor, transistor, diode, power supply, or the like), a value associated with the electrical component (eg, a resistor in ohms) resistance value, the voltage value in volts of the power supply, the frequency characteristic of the power supply, the initial condition of the component, or the like). In another embodiment, the design data may include one or more netlists related to a particular stage of a semiconductor process flow. For example, sample 110 may be inspected (eg, by system 100 ) at one or more intermediate points in a semiconductor process flow. Accordingly, the design data used to create the management region may be unique to the layout of the sample 110 at the current point in the semiconductor process flow. In this regard, a physical design layout in combination with a technology file (layer connectivity, respective electrical properties of the layers, and the like) to include only those components present on the wafer at certain intermediate points in the semiconductor process flow, or From any one of the netlists associated with the final layout of sample 110 , a netlist associated with a particular intermediate point in the semiconductor process flow may be derived (eg, may be extracted, or the like).

In another embodiment, the design module 204 of the inspection tool 202 executes step 206 of preprocessing the design data. It is noted herein that the design data may include data (eg, manufacturing data, or the like) that is unrelated to the determination of the management area of the inspection system 100 . Further, the design data may not be in a format suitable for efficient identification (eg, searching, matching, or the like) of pattern elements of interest within the design data. Accordingly, the preprocessed design data may include a preprocessed version of the design data to facilitate efficient creation of management areas on the inspection tool 202 . In this regard, the preprocessed design data may facilitate identification of one or more instances of a target pattern (eg, pattern element of interest, hot spot, or the like) within the design data. For example, the preprocessed design data may include an identifier of the target pattern, electrical properties of the target pattern, physical properties of the target pattern, or the target pattern and one or more additional patterns (eg, anchor pattern, source pattern, or the like); or searchable according to any combination of design data elements including, but not limited to, relationships between graphical representations of target patterns.

In other embodiments, design data (eg, raw design data, preprocessed design data, or a combination thereof) is stored by the inspection tool 202 . For example, the design data may be stored in the memory device 108 of the controller 104 . In other embodiments, the design data may be pre-processed external to the inspection system 100 and stored on the inspection tool 202 . In this regard, preprocessed design data associated with one or more samples may be communicated to the inspection tool 202 .

In another embodiment, the design module 204 executes analyzing the design data stored on the inspection tool 202 . In this regard, the design module 204 is configured to identify one or more instances of the target pattern within the design data of the sample (eg, by retrieving the preprocessed design data for the one or more instances of the target pattern, or the like). can also be identified. The design module 204 may also provide parameters of the identified instance of the target pattern necessary for creation of the management area, such as, but not limited to, the coordinates and/or shape of the identified target pattern.

In one embodiment, the inspection tool 202 includes a recipe module 210 . For example, the recipe module 210 may generate a recipe for one or more inspection steps by the inspection tool 202 . In this regard, the recipe may include a description of one or more management areas for inspecting defects, (eg, coordinates associated with design data, coordinates associated with samples and/or inspection subsystem 102 , or the like). It may include, but is not limited to, one or more registration operations (to align and/or scaling), one or more defect identification steps, or one or more defect classification steps. Additionally, the creation of a design-based management domain on the inspection tool 202 may facilitate an efficient multi-step inspection process (eg, for systematic defect discovery, or the like). In this regard, design data may be retrieved on the inspection tool 202 for different target patterns or combinations of target patterns in an iterative inspection analysis, without the need for data transfer to an external system.

In another embodiment, the recipe module 210 may provide one or more target patterns (eg, one or more patterns of interest) associated with manufactured pattern elements on the sample 110 to be inspected by the inspection tool 202 in an inspection step. element, one or more hot spots, or the like). For example, the recipe module 210 may provide one or more target patterns based on one or more targets of an inspection run of the inspection tool 202 . For example, the recipe module 210 may provide a target pattern associated with a known defect type of interest.

In another embodiment, the recipe module 204 determines one or more target patterns in an automated process. For example, the recipe module 204 may analyze 208 the design data of the sample 110 based on (eg, physical layout, pattern size, proximity to other patterns, circuit complexity, or the like). ) may determine one or more target patterns that are likely to represent defects.

In another embodiment, determination of the target pattern is facilitated by the user. For example, the user may select one or more defect identifiers, one or more GDS coordinates, one or more design-based classification (DBC) clips, or one or more design-based grouping (DBG) bins ( bin) (eg, input to recipe module 210 ), including, but not limited to, inspection tool 202 . In this regard, the recipe module 210 may determine one or more target patterns based on user input. In another embodiment, the inspection tool 202 may provide a visual display associated with design data (eg, within a design view of the inspection tool 202 ). In this regard, a user may select one or more target patterns from a visual display of design data. For example, the visual display may be a graphical display in which design pattern elements of design data (eg, pattern elements related to the physical layout of components, pattern elements related to electrical connections between components, or the like) may be displayed. (eg, display of an image, or the like). As another example, the visual display may include a text-based display in which design data may be displayed. In another embodiment, a user may visualize design data (eg, on a graphical display) according to a coordinate system (eg, GDS coordinates) to determine and/or identify one or more target patterns. For example, a user may input coordinates (eg, into an input device of the inspection system 100 ) for visualizing and/or verifying design data at a particular location, for generation of a target pattern for inspection. have.

In another embodiment, the recipe module 210 executes step 214 of defining one or more management areas to be examined on the sample 110 . For example, the recipe module 210 may define one or more management areas based on one or more target patterns and design data stored on the inspection tool 202 . In one embodiment, the recipe module 210 interfaces with the design module 204 to analyze design data based on one or more determined target patterns. In this regard, the recipe module 210 may provide one or more target patterns to the design module 204 for pattern matching. In addition, the design module 204 may identify one or more instances of the target pattern within the design data, and, based on the identified instances of the target pattern, provide any parameters necessary for creation of the management area to the recipe module 110 . may provide. For example, the design module 204 may determine the location (eg, in design coordinates) of the identified instance of the target pattern, the shape of the identified instance of the target pattern, and the outline of the identified instance of the target pattern. , or the like may be provided.

In another embodiment, the recipe module 210 performs step 216 of identifying defects on the sample 110 . In this regard, the recipe module 210 may interface with the inspection subsystem 102 to perform defect inspection. The recipe module 210 may also analyze data received by the inspection subsystem 102 to determine the presence of one or more defects. Additionally, the recipe module 210 may characterize one or more defects. For example, a recipe module may, but need not, characterize a defect based on a DBC system, a DBG system, or the like. Recipe module 210 may also assign one or more defect identifiers to one or more characterized defects.

Herein, the steps described throughout this disclosure (eg, steps associated with a module of the inspection tool 202 , etc.) may be performed by a single controller 104 , or alternatively multiple controllers 104 . It is recognized that this may be done by It is also noted herein that one or more controllers 104 may be located proximate the inspection subsystem 102 . Additionally, one or more controllers 104 may be housed in a common housing with the inspection subsystem 102 . Additionally, any controller or combination of controllers may be individually packaged as a module suitable for integration into the complete inspection system 100 . For example, the first controller may be configured to perform steps associated with the design module 204 . One or more additional controllers may then be configured to perform the steps associated with the recipe module 210 . In this regard, one or more controllers 104 may be integrated into the inspection system 100 .

3 is a flow diagram illustrating steps performed in a method 300 for defect detection, in accordance with one or more embodiments of the present disclosure. Applicants note that the embodiments and enabling technologies previously described herein in the context of system 100 should be interpreted to extend to method 300 . It is also noted, however, that method 300 is not limited to the architecture of system 100 .

In one embodiment, method 300 includes providing 302 design data of the sample to an inspection system. For example, the design data may, but need not, be provided to the inspection system in the form of one or more data files (eg, GDSII files, OASIS files, or the like). In this regard, design data provided to the inspection system may be utilized to generate one or more design-based regions of interest for inspection.

In another embodiment, method 300 includes determining 304 one or more target patterns. In this regard, one or more target patterns of interest associated with fabricated features on a sample may be provided for inspection. For example, the target pattern may include one or more polygons (eg, a cross, a plus, an L-shaped, a T-shaped, a square, a rectangle, or between instances) representing features to be constructed on the semiconductor layer. one or more instances of other polygons with dimensions and spacing specified in .

In one embodiment, the one or more target patterns are determined based on the defect identifier. In this regard, one or more known defects or defect types associated with a defect identifier (e.g., an identifier used to classify one or more defects, or the like) can be determined (e.g., based on one or more previous inspection runs; based on one or more design characteristics, or the like) may be associated with one or more specific target patterns. Thus, the occurrence of a known defect or defect type may be characterized by providing a corresponding target pattern for inspection.

In other embodiments, one or more target patterns are determined based on previous inspection steps (eg, by inspection system 100 or additional inspection systems). For example, in systematic defect discovery, a first inspection run of the sample 110 or portion of the sample 110 may identify one or more manufactured components of the sample 110 prone to defects. In this regard, the first inspection run may determine one or more target patterns associated with the identified manufactured component on the sample 110 . The second inspection run may also include a recipe (eg, generated by the recipe module 210 ) for performing dedicated inspection of one or more target patterns identified from the first inspection run. In other embodiments, the one or more target patterns are determined according to a DBC or DBG process associated with a previous inspection step.

In other embodiments, the one or more target patterns are determined based on one or more coordinates (eg, GDS coordinates, or the like) of the target pattern on the sample. For example, one or more target patterns may be determined based on known coordinates of exemplary target patterns of interest associated with the design data. As another example, one or more target patterns may be determined based on known coordinates of an example manufactured component on sample 110 . Accordingly, one or more target patterns associated with an example manufactured component may be provided for inspection.

In another embodiment, the method 300 includes defining 308 one or more management areas on the sample by the inspection system based on the target pattern and design data of the sample. In this regard, step 308 may include defining one or more regions on the sample to be inspected. For example, a management area may include coordinates on a sample to be inspected (eg, in a coordinate system of an inspection system).

In another embodiment, the management area comprises one or more target areas on the sample for examination. For example, the first target area may include one or more instances of the first target pattern identified at step 304 , and the second target area may include one or more instances of the second target pattern identified at step 304 . may include, and may be, and the like. Also, the definition of one or more target regions may facilitate sensitive inspection of the sample 110 . For example, a target region may be defined to include samples with similar sensitivity levels. Accordingly, each target region may be inspected with a different sensitivity threshold such that the contrast of inspection data associated with the respective target region may be increased.

In another embodiment, step 306 is an instance of the target pattern determined in step 304 within design data (eg, preprocessed design data stored in memory device 108 of inspection system 100 ). includes identifying In this regard, each identified instance of the target pattern of interest may be included in the management area. Additionally, various target patterns of interest (eg, horizontal and/or vertical flips of target patterns, scaled versions of target patterns, rotated versions of target patterns, or the like) may be identified and managed in step 306 . It may be included in the area.

An instance of the target pattern within the device data may be identified using any method known in the art. For example, step 306 may include retrieving design data for one or more instances of the target pattern to create one or more identified instances of the target pattern. In one embodiment, step 306 comprises a text-based search of design data. For example, text-based design data (eg, one or more lists, one or more tables, one or more databases, one or more data files, or the like) may be retrieved according to one or more characteristics of the target pattern. In another embodiment, step 306 includes an image-based retrieval of design data. For example, images such as, but not limited to, feature extraction techniques, convolution techniques, pattern matching techniques, spatial frequency analysis, transform techniques (eg, Hough transform techniques, or the like). One or more instances of the target pattern (or variations of the target pattern) may be discovered through a processing algorithm. Additionally, multiple design layers of design data (eg, corresponding to multiple layers of fabricated components on sample 110 ) may be individually searched for one or more instances of target patterns of interest.

In one embodiment, the target pattern may be identified using design data included in a design layout file such as OASIS or GDS. It is noted herein that the target pattern may vary in size and may be located at various levels of design data (eg, associated with various layers, dies, blocks, cells, or the like of sample 110 ). In this regard, target patterns of design data may be identified using known or observed design cell hierarchies. For example, the design cell hierarchy may be analyzed to identify target patterns in repeating groups within a given set of inspection data.

In other embodiments, the target pattern may be subjected to a design rule checking (DRC) process, optical rule checking (ORG), or failure analysis; FA) processes may be used to identify them. In another embodiment, the target pattern may be identified utilizing a process window qualification method (PWQ). Retrieving design data for one or more target patterns may be performed as described in the references set forth above by Kulkarni et al. and Zafar et al., incorporated supra by reference above.

In some embodiments, a target pattern may be identified on a semiconductor wafer utilizing data from electronic design automation (EDA) tools and other knowledge. Any such information about the design generated by the EDA tool may be used to identify repeating blocks. Further, the design data may be retrieved for one or more target patterns in any suitable manner. For example, retrieving design data for one or more target patterns may be performed as described in the supra-referenced patent applications by Kulkarni et al. and Zafar et al., incorporated supra by reference. In addition, the target pattern may be selected or identified using any other method or system described in this patent application.

In addition, design data may be analyzed to identify an appropriate target pattern for inspection based on a given inspection technique (eg, optical inspection, electron beam inspection, and the like).

It is recognized that the target pattern may be repeated through the die of sample 110 to form repeating blocks (or fields). In addition, cells of sample 110 may sometimes repeat through a given die with a different name or repeat with one name in multiple locations. In some embodiments, repeating cells are aligned on the same horizontal and/or vertical axis. In other embodiments, repeat cells are not aligned on the same horizontal and/or vertical axis.

In another embodiment, step 306 includes providing, at a location within the design data, a confidence metric associated with the identification of each instance of the target pattern of interest. In this regard, an instance of the target pattern in the device data may include an exact match (eg, a confidence metric of 100%, or the like) or a substantial match (eg, a confidence metric of less than 100%). It should be understood that any reliability metric in the art is within the spirit and scope of the present disclosure. For example, the confidence metric may range from 0 (no match) to 1 (complete match).

It is noted herein that a management area may be defined to include a subset of the identified instances of the target pattern. For example, the probability that a particular defect on a particular component of a device fabricated on sample 110 will lead to degradation in performance depends on a number of factors, such as, but not limited to, the presence of neighboring structures or the operating conditions of the particular component. may depend on the factors of

In one embodiment, step 306 involves defining, within the design data, one or more management regions that will contain instances of the target pattern proximate to the additional pattern (eg, source pattern, anchor pattern, or the like). include In this regard, the presence of the source pattern may act as a filter providing a subset of instances of the target pattern as a management area to be inspected.

4 is a schematic diagram of design data illustrating the definition of an associated management area based on a source pattern, in accordance with one or more embodiments of the present disclosure.

In one embodiment, the design data 402 includes multiple instances of the target pattern 404 . The design data 402 also includes a source pattern 408 that is proximate to a subset of instances of the target pattern 404 (eg, a particular instance 412 of the target pattern 404 ). For example, the source pattern may include one or more instances of a crossing, a cross, a plus shape, an L-shape, a T-shape, a square, a rectangle, or any other polygon having specific dimensions and spacing between the instances. may include, but are not limited to.

Step 306 also includes a management area 406 around a particular instance 412 of the target pattern 404 based on the spatial relationship between the particular instance 412 of the target pattern 404 and the source pattern 408 . may include a definition of For example, the spatial relationship between a particular instance 412 of the target pattern 404 and the source pattern 408 is a vector 414 between the particular instance 412 of the target pattern 404 and the source pattern 408 . may include, but is not limited to. In another embodiment, step 306 includes retrieving one or more instances of the source pattern within the design data and based on the spatial relationship between the particular instance 412 of the target pattern 404 and the source pattern 408 . , further identifying a subset of instances of the target pattern for inclusion within the management area (eg, a particular instance 412 of the target pattern 404 ). In another embodiment, step 306 includes retrieving an instance of the combined target pattern 410 that includes the source pattern 408 and the instance of the target pattern within the device data 402 , and at the same time the identified composite and defining a management area 406 around a subset of instances of the target pattern 404 that are associated with the target pattern 410 (eg, a particular instance 412 of the target pattern 404 ). Accordingly, the source pattern 408 may be utilized as part of the search phase, although not included within the associated management area 406 .

In another embodiment, the method 300 includes identifying 308 one or more defects within one or more managed areas of the sample. In this regard, the inspection system (eg, inspection system 100 ) inspects the control area of the sample defined in step 308 (eg, using illumination subsystem 101 ) for defects. . For example, data from the inspection subsystem 102 may be analyzed to determine the presence of one or more defects on the sample 112 associated with the management area defined in step 306 . In addition, the identified defects may be classified (eg, according to a defect identifier, DBC dip, DBG bin, or the like). In other embodiments, data associated with one or more identified defects may be provided to inspection system 100 and/or external systems (eg, as feed forward data, feedback data, or the like).

It is recognized herein that the steps described throughout this disclosure may be performed by a single controller 104 , or, alternatively, by multiple controllers 104 . It is also noted herein that one or more controllers 104 may be housed within a common housing or within multiple housings. In this manner, any controller or combination of controllers may be individually packaged as a module suitable for integration into the complete inspection system 100 . As a non-limiting example, the first controller may be configured to perform the step of identifying the set of lighting detection events based on the lighting signal received from the lighting sensor. Then, the one or more additional controllers may be configured to perform the following steps: identifying a set of radiation detection events based on one or more radiation signals received from the one or more radiation sensors, the set of radiation detection events; generating a set of coincidence events compared to the set of lighting detection events, and excluding the set of coincidence events from the set of lighting detection events to produce a set of identified features on the sample.

5A is a conceptual diagram of an inspection subsystem 102 configured as an optical inspection subsystem, in accordance with one or more embodiments of the present disclosure. In one embodiment, the inspection subsystem 102 includes an illumination source 502 . The illumination source 502 may include any illumination source known in the art suitable for generating an illumination beam 504 (eg, a beam of photons). For example, illumination source 502 includes a monochromatic light source (eg, a laser), a polychromatic light source having a spectrum comprising two or more discrete wavelengths, a broadband light source, or a wavelength-sweeping light source. may, but are not limited to. In addition, the illumination source 502 may include a white light source (eg, a broadband light source having a spectrum including visible wavelengths), a laser source, a free-form illumination source, a single-pole illumination source. It may be formed from, but is not limited to, a pole illumination source, a multi-pole illumination source, an arc lamp, an electrodeless lamp, or a laser sustained plasma (LSP) source. The illumination beam 504 may also be delivered via free space propagation or guided light (eg, optical fiber, light pipe, or the like).

In another embodiment, the illumination source 502 directs one or more illumination beams 504 to the sample 110 via an illumination pathway 506 . The illumination path 506 may include one or more lenses 510 . The illumination path 506 may also include one or more additional optical components 508 suitable for modifying and/or conditioning the one or more illumination beams 504 . For example, the one or more optical components 508 may include one or more polarizers, one or more filters, one or more beam splitters, one or more diffusers, one or more homogenizers, one or more apodizers, or one or more It may include, but is not limited to, a beam shaper. In one embodiment, the illumination path 506 includes a beam splitter 514 . In another embodiment, the inspection subsystem 102 includes an objective lens 516 that focuses one or more illumination beams 504 onto the sample 110 .

The illumination source 502 may direct one or more illumination beams 504 to the sample at any angle through the illumination path 506 . In one embodiment, as shown in FIG. 5A , the illumination source 502 directs one or more illumination beams 504 to the sample 110 at a normal angle of incidence. In another embodiment, the illumination source 502 directs one or more illumination beams 504 to the sample 110 at a non-normal incidence angle (eg, a glancing angle, a 45 degree angle, or the like).

In another embodiment, the sample 110 is placed on a sample stage 110 suitable for holding the sample 512 during injection. In another embodiment, the sample stage 512 is an actuatable stage. For example, the sample stage 512 may include one or more translation stages suitable for selectably translating the sample 110 along one or more linear directions (eg, the x-direction, the y-direction, and/or the z-direction). may include, but are not limited to. As another example, the sample stage 512 may include, but is not limited to, one or more rotation stages suitable for selectively rotating the sample 110 along a direction of rotation. As another example, the sample stage 512 may include a rotational stage and a translation stage suitable for selectively translating the sample along a linear direction and/or rotating the sample 110 along a rotational direction, although these is not limited to

In another embodiment, the illumination path 506 includes one or more beam scanning optics (not shown) suitable for scanning the illumination beam 504 across the sample 110 . For example, the one or more illumination passages 506 may include one or more electro-optic beam deflectors, one or more acousto-optic beam deflectors, one or more galvanometric scanners, one or more resonant scanners. , or any type of beam scanner known in the art, such as one or more polygonal scanners. In this way, the surface of the sample 110 may be scanned in an r-theta pattern. It is also noted that the illumination beam 504 may be scanned according to any pattern on the sample. In one embodiment, the illumination beam 504 is split into one or more beams such that more than one beam may be scanned simultaneously.

In another embodiment, the inspection subsystem 102 includes one or more detectors 522 (eg, one or more photo detectors, one more photon detectors, etc.). The collection passageway 518 is provided by an objective lens 516, including but not limited to, one or more lenses 520, one or more filters, one or more polarizers, one or more beam blocks, or one or more beam splitters. It may include multiple optical elements for directing and/or modifying the collected illumination. It is noted herein that the components of the collection passage 518 may be oriented in any position relative to the sample 110 . In one embodiment, the collection passageway includes an objective lens 516 oriented perpendicular to the sample 110 . In another embodiment, collection passageway 518 includes multiple collection lenses oriented to collect radiation from the sample at multiple solid angles.

In one embodiment, the inspection system 100 comprises a brightfield inspection system. For example, a brightfield image of sample 110 , or a portion of sample 110 , is projected onto detector 522 (eg, by objective lens 516 , one or more lenses 520 , or the like). It may be projected. In another embodiment, the inspection system 100 includes a dark field inspection system. For example, the inspection system 100 may be one for directing the illumination beam 504 to the sample 110 at a large angle of incidence such that an image of the sample on the detector 112 is related to scattered and/or diffracted light. It may include the above components (eg, annular beam block, dark field objective 516, or the like). In another embodiment, the inspection system 100 includes an oblique angle inspection system. For example, the inspection system 100 may direct the illumination beam 504 to the sample at an off-axis angle to provide contrast for defect inspection. In another embodiment, the inspection system 100 includes a phase contrast inspection system. For example, the inspection system 100 may include one or more phase plates and/or beams to provide phase contrast between diffracted and undiffracted light from the sample to provide contrast for defect inspection. blocks (eg, annular beam blocks, or the like). In other embodiments, the inspection system 100 may include a luminescence inspection system (eg, a fluorescence inspection system, a phosphorescence inspection system, or the like). For example, the inspection system 100 may direct an illumination beam 504 having a first wavelength spectrum to the sample 110 , which is emitted from the sample 110 (eg, one of the samples 110 ). It may include one or more filters to detect one or more additional wavelength spectra (emitted from one or more defects on one or more components and/or sample 110 ). In another embodiment, the inspection system includes one or more pinholes positioned in a confocal position such that the system 100 may operate as a confocal inspection system.

5B is a simplified schematic diagram of an inspection subsystem configured as a particle beam inspection subsystem in accordance with one or more embodiments of the present disclosure. In one embodiment, the illumination source 502 comprises a particle source configured to generate a particle beam 504 . Particle source 502 may include any particle source known in the art suitable for generating particle beam 504 . As a non-limiting example, the particle source 502 may include, but is not limited to, an electron gun or an ion gun. In another embodiment, the particle source 502 is configured to provide a variable energy to the particle beam 504 . For example, a particle source 502 comprising an electron source may provide an accelerating voltage in the range of 0.1 kV to 30 kV, but is not limited thereto. As another example, a particle source comprising an ion source may, but need not, provide the ion beam with an energy value in the range of 1-50 keV to the ion beam.

In another embodiment, the inspection subsystem 102 includes two or more particle beam sources 502 (eg, electron beam sources or ion beam sources) for generation of two or more particle beams 504 .

In another embodiment, the illumination path 506 includes one or more particle focusing elements 524 . For example, the one or more particle focusing elements 524 may include, but are not limited to, one or more particle focusing elements forming a single particle focusing element or a complex system. In another embodiment, the objective lens 516 of the system 100 is configured to direct the particle beam 504 to the sample 110 . Further, the one or more particle focusing elements 524 and/or the objective lens 516 may be of any type known in the art including, but not limited to, electrostatic, magnetic, single potential, or dual potential lenses. Particle lenses may be included. Inspection subsystem 102 may also include, but is not limited to, one or more electronic deflectors, one or more apertures, one or more filters, or one or more astigmatism stigmators.

In another embodiment, the electronic inspection subsystem 102 includes one or more particle beam scanning elements 526 . For example, the one or more particle beam scanning elements may include, but are not limited to, one or more scanning coils or deflectors suitable for controlling the position of the beam with respect to the surface of the sample 110 . no. In this regard, one or more scanning elements may be utilized to scan the particle beam 504 across the sample 110 in a selected pattern.

In another embodiment, the inspection subsystem includes a detector 522 that images or otherwise detects particles 528 emitted from the sample 110 . In one embodiment, the detector 522 includes an electron collector (eg, a secondary electron collector, a backscattered electron detector, or the like). In other embodiments, the detector 522 is coupled to a photon detector (eg, a photo detector, an x-ray detector, a photomultiplier tube (PMT) detector) for detecting electrons and/or photons from the sample surface. ringed scintillating elements, or the like). In a general sense herein, detector 522 may include any device or combination of devices known in the art for characterizing a sample surface or bulk using particle beam 504 . For example, detector 522 can detect reverse scattered electrons, Auger electrons, transmitted electrons or photons (eg, x-rays emitted by the surface in response to incident electrons, cathodic emission of sample 108 ). , or the like) may include any particle detector known in the art that is configured to collect.

In another embodiment, the inspection system 100 includes a voltage contrast imaging (VCI) system. Herein, an inspection system utilizing a particle beam (eg, an electron beam, an ion beam, or the like), due to its high achievable spatial resolution, detects defect mechanisms on a semiconductor sample (eg, a random logic chip, or the like). It may be particularly useful for detection and/or identification. For example, a particle beam may be utilized within an inspection system to image a sample (eg, by capturing secondary electrons, backscattered electrons, or the like emitted from the sample). Additionally, structures on the sample (eg, patterned semiconductor wafers) may exhibit a charging effect in response to excitation by the particle beam. The charging effect may include a modification of the number of electrons (eg, secondary electrons) captured by the system and thus the VCI signal strength. In this regard, a voltage contrast imaging (VCI) system may generate a high-resolution image of a sample in which the intensity of each pixel of the image provides data regarding the electrical properties of the sample at the pixel location. For example, an insulating structure and/or a structure that is not connected to a ground source (eg, not grounded) may cause depletion of particles (eg, secondary electrons, ions, or the like) induced by the particle beam. A charge (eg, a positive or negative charge) may be generated in response to . Thus, the induced charge may deflect the trajectory of the secondary electron and reduce the signal strength captured by the detector. Conversely, a grounded structure may not generate a charge and thus exhibit a strong signal (eg, may appear bright in the associated VCI image). Further, the signal strength of the capacitive structure may be a function of the scan rate and/or the energy of the particle beam. In this regard, the VGI image may include a grayscale image in which the grayscale value of each pixel provides data regarding the relative electrical characteristics of its location on the wafer. In another embodiment, the inspection system 100 includes one or more components (eg, one or more electrodes) configured to apply one or more voltages to one or more locations of the sample 108 . In this regard, system 100 may generate active voltage contrast imaging data.

In other embodiments, the inspection system 100 may include a display (not shown). In another embodiment, the display is communicatively coupled to the controller 104 . For example, the display may be communicatively coupled to one or more processors 104 of the controller 101 . In this regard, the one or more processors 106 may display one or more of the various results of the present invention on a display.

The display device may include any display device known in the art. In one embodiment, the display device may include, but is not limited to, a liquid crystal display (LCD). In other embodiments, the display device may include, but is not limited to, an organic light-emitting diode (OLED) based display. In other embodiments, the display device may include, but is not limited to, a CRT display. Those skilled in the art will recognize that a variety of display devices may be suitable for implementation in the present invention and that the particular selection of a display device will depend on a variety of factors including, but not limited to, form factor, cost, and the like. It should be recognized that there may be In a general sense, any display device that can be integrated with a user interface device (eg, a touchscreen, bezel mounted interface, keyboard, mouse, trackpad, and the like) is contemplated for implementation in the present invention. Suitable.

In other embodiments, the inspection system 100 may include a user interface device (not shown). In one embodiment, the user interface is communicatively coupled to one or more processors 106 of the controller 104 . In other embodiments, a user interface device may be utilized by the controller 104 to accept selections and/or instructions from a user. In some embodiments further described herein, a display may be used to display data to a user. The user may then enter selections and/or instructions (eg, user selection of an examination area) in response to examination data displayed to the user via the display device.

A user interface device may include any user interface known in the art. For example, a user input device may include a keyboard, keypad, touch screen, lever, knob, scroll wheel, track ball, switch, dial, sliding bar, scroll bar, slide, handle, touch pad, paddle, steering wheel. , a joystick, a bezel input device, or the like. In the case of a touch screen interface device, those skilled in the art should recognize that a number of touch screen interface devices may be suitable for implementation in the present invention. For example, the display device may be integrated with a touch screen interface such as, but not limited to, a capacitive touch screen, a resistive touch screen, a surface acoustic based touch screen, an infrared based touch screen, or the like. . In a general sense, any touchscreen interface that can be integrated with the display portion of the display device 105 is suitable for implementation in the present invention. In other embodiments, the user interface may include, but is not limited to, a bezel mounted interface.

5A and 5B, together with the corresponding description above, are provided herein for illustrative purposes only and should not be construed as limiting. It is contemplated that many equivalent or additional configurations may be utilized within the scope of the present invention.

The subject matter described herein sometimes exemplifies different other components that are included in, or connected to, other components. It should be understood that the architecture so depicted is merely exemplary, and that many other architectures may be implemented that achieve the same functionality. In a conceptual sense, any arrangement of components to achieve the same functionality is effectively "related" such that the desired functionality is achieved. Thus, any two components herein that are combined to achieve a particular functionality, regardless of architecture or intermediate component, may be viewed as "related" to each other such that the desired functionality is achieved. Likewise, any two components so related may also be viewed as being “connected” or “coupled” to each other to achieve a desired functionality, and any two components that may be so related are also can be seen as "coupleable" to each other to achieve the functionality of Specific examples of what may be coupled include physically interactable and/or physically interacting components and/or wirelessly interactable and/or wirelessly interacting components and/or logically interactable and and/or logically interacting components.

It is believed that the present disclosure and many of its attendant advantages will be understood by the foregoing description, in the form, construction and arrangement of components, without departing from the disclosed subject matter or sacrificing all of the significant advantages of the disclosed subject matter. It will be apparent that various modifications may be made. The form described is for illustrative purposes only, and it is the intention of the following claims to encompass and include such modifications. It should also be understood that the invention is defined by the appended claims.

Claims (47)

A defect inspection system comprising:
inspection sub-system - the inspection subsystem comprising:
an illumination source configured to generate a beam of illumination;
a set of illumination optics for directing the beam of illumination to a sample; and
a detector configured to collect illumination emitted from the sample; and
a controller communicatively coupled to the detector
including,
The controller includes a memory device and one or more processors configured to execute program instructions, wherein the program instructions cause the one or more processors to:
store design data of a sample in the memory device of the controller, the design data being pre-processed to include a searchable data set suitable for identifying a pattern of interest in the design data, the design data comprising: registered with the inspection subsystem to provide the location of the identified pattern of interest in the coordinates of the inspection subsystem;
determine one or more target patterns as patterns of interest corresponding to one or more features on the sample;
define one or more care areas on the sample based on identifying instances of the one or more target patterns within design data stored in the memory device of the controller; and
identify one or more defects in one or more controlled areas of the sample based on illumination collected by the detector while inspecting the one or more controlled areas using the inspection subsystem;
A defect inspection system that is constituted. According to claim 1,
identifying the one or more instances of the one or more target patterns in the design data of the sample comprises:
generating a composite search pattern, wherein the composite search pattern includes a source pattern and a target pattern of at least one of the one or more target patterns;
identifying one or more instances of the complex search pattern within the design data of the sample; and
identifying one or more instances of the one or more target patterns within the design data of the sample based on the one or more identified instances of the composite search pattern.
Including, defect inspection system. The method of claim 1 , wherein identifying instances of the one or more target patterns within the design data of the sample comprises:
and retrieving design data for the one or more target patterns to create one or more identified instances of the one or more target patterns. The method of claim 1 , wherein defining the one or more management areas comprises:
identifying instances of the one or more target patterns within the design data;
determining a confidence score for each instance of the one or more target patterns in the design data, wherein the confidence score is a measure of the similarity between the identified instances of the one or more target patterns and the one or more target patterns in the design data. Lim -;
defining instances of the one or more target patterns in design data having a confidence score higher than a selected confidence score as the one or more management domains;
A defect inspection system comprising a. The method of claim 1 , wherein defining one or more management regions on the sample comprises:
defining one or more target regions, wherein the one or more target regions include at least one instance of at least one of the one or more target patterns, and the management region includes the one or more target regions; and
defining an inspection sensitivity for each of the one or more target regions;
A defect inspection system comprising a. 6. The defect inspection system of claim 5, wherein the inspection sensitivity of each of the one or more target regions is individually adjustable. According to claim 1,
wherein the one or more target patterns include one or more target patterns identified by at least one of a design-based classification process or a design-based binning process. According to claim 1,
wherein the one or more target patterns include one or more target patterns associated with one or more known defect types. According to claim 1,
wherein the one or more target patterns include one or more target patterns identified by a previous defect inspection process. According to claim 1,
Determining the one or more target patterns comprises:
and determining the one or more target patterns by a user. 11. The method of claim 10,
Determining the one or more target patterns by the user comprises:
and selecting one or more instances of the one or more target patterns from the design data of the sample. 12. The method of claim 11,
selecting the one or more instances of the one or more target patterns from the design data of the sample comprises:
and selecting the one or more instances of the one or more target patterns from a visual display of the design data of the sample. According to claim 1,
Defining the one or more management areas comprises:
and determining one or more coordinates associated with one or more instances of the one or more target patterns within the design data of the sample. The method of claim 1 , wherein the one or more processors are further configured to execute program instructions, the program instructions causing the one or more processors to:
determine one or more additional target patterns as patterns of interest based on the one or more identified defects;
define one or more additional management regions on the sample based on identifying an instance of the one or more additional target patterns within design data stored in the memory device of the controller;
identifying one or more additional defects within the one or more additional management areas based on inspection using the virtual inspection system;
defect inspection system. According to claim 1,
wherein the design data includes at least one of a physical layout of the sample or an electrical layout of the sample. According to claim 1,
and providing the one or more management areas for use in a subsequent inspection process. According to claim 1,
and classifying one or more identified defects based on the design data of the sample. According to claim 1,
wherein the beam of illumination comprises at least one of a beam of photons or a beam of particles. 19. The method of claim 18,
wherein the beam of particles comprises at least one of a beam of electrons or a beam of ions. According to claim 1,
wherein the set of illumination optics comprises at least one of photonic optics or particle optics. According to claim 1,
wherein the detector comprises at least one of a photon detector or a particle detector. According to claim 1,
and the controller is located proximate to the inspection subsystem. According to claim 1,
and at least a portion of the controller and the inspection subsystem are located within a common housing. The method of claim 1 , wherein determining the one or more target patterns comprises:
and providing one or more coordinates associated with one or more instances of the one or more target patterns within the design data of the sample. The method of claim 1 , wherein the one or more processors are further configured to execute program instructions, the program instructions causing the one or more processors to:
determine one or more additional target patterns as patterns of interest based on the one or more identified defects;
define one or more additional management regions on the sample based on identifying an instance of the one or more additional target patterns within design data stored in the memory device of the controller;
identify one or more additional defects within the one or more additionally managed areas based on illumination collected by the detector while inspecting the one or more additionally managed areas using the inspection subsystem;
defect inspection system. The defect inspection system of claim 1 , wherein the inspection system is a virtual inspection system. A defect inspection system comprising:
inspection subsystem - the inspection subsystem comprises:
an illumination source configured to generate a beam of illumination;
a set of illumination optics for directing the beam of illumination to a sample; and
a detector configured to collect illumination emitted from the sample; and
a controller communicatively coupled to the detector
including,
The controller includes a memory device and one or more processors configured to execute program instructions, wherein the program instructions cause the one or more processors to:
determine one or more target patterns corresponding to one or more features on the sample;
determine a source pattern, wherein the source pattern approximates a subset of instances of the one or more target patterns in the design data of the sample, the design data of the sample stored in the memory device of the controller;
define a spatial relationship between the source pattern and at least one target pattern of the subset of instances of the one or more target patterns within the design data of the sample;
identify one or more instances of the source pattern within the design data of the sample;
within the design data of the sample, based on the spatial relationship between the source pattern and the at least one target pattern of the subset of instances of the one or more target patterns, and the one or more identified instances of the source pattern. identify the subset of instances of the one or more target patterns;
define one or more management regions on the sample based on the subset of instances of the one or more target patterns; and
identify one or more defects within the one or more control areas of the sample based on the illumination collected by the detector;
A defect inspection system comprising: A defect inspection method comprising:
storing the design data of the sample in a memory device of the inspection system, wherein the design data is preprocessed to include a searchable data set suitable for identifying a pattern of interest within the design data, the design data comprising: Registered to provide coordinates to the coordinates of the inspection subsystem -;
determining, using one or more processors of the inspection system, one or more target patterns as patterns of interest corresponding to one or more features on the sample;
defining, using one or more processors of the inspection system, one or more management areas on the sample by the inspection system based on identifying instances of the one or more target patterns within the design data of the sample;
inspecting one or more managed areas of the sample with the inspection system by illuminating the one or more managed areas with a beam of illumination and collecting illumination emitted from the sample with a detector; and
identifying, using one or more processors of the inspection system, one or more defects within the one or more control areas of the sample based on illumination collected by the detector;
A defect inspection method comprising a. 29. The method of claim 28,
The step of defining the one or more management areas comprises:
determining a source pattern, the source pattern proximate to a subset of instances of the one or more target patterns within the design data of the sample;
defining a spatial relationship between the source pattern and at least one target pattern of the subset of instances of the one or more target patterns within the design data of the sample;
identifying one or more instances of the source pattern within the design data of the sample; and
within the design data of the sample, based on the spatial relationship between the source pattern and the at least one target pattern of the subset of instances of the one or more target patterns, and the one or more identified instances of the source pattern. identifying the subset of instances of the one or more target patterns;
That comprising a, defect inspection method. 29. The method of claim 28,
identifying instances of the one or more target patterns within the design data of the sample,
and retrieving design data for the one or more target patterns to create the identified instances of the one or more target patterns. 31. The method of claim 30,
The step of defining the one or more management areas comprises:
identifying instances of the one or more target patterns within the design data;
determining a confidence score for each instance of the one or more target patterns in the design data, wherein the confidence score is between the one or more target patterns in the design data and the one or more identified instances of the one or more target patterns. It is a measure of similarity -;
defining instances of the one or more target patterns in design data having a confidence score higher than a selected confidence score as the one or more management domains;
A defect inspection method comprising a. 29. The method of claim 28,
The one or more target patterns,
and one or more target patterns identified by at least one of a design-based classification process or a design-based binning process. 29. The method of claim 28,
The one or more target patterns,
and one or more target patterns identified by a previous defect inspection process. 29. The method of claim 28,
Determining the one or more target patterns comprises:
determining the one or more target patterns by a user. 35. The method of claim 34,
Determining the one or more target patterns by a user comprises:
and selecting one or more instances of the one or more target patterns from the design data of the sample. 36. The method of claim 35,
selecting the one or more instances of the one or more target patterns from the design data of the sample comprises:
and selecting one or more instances of the one or more target patterns from the visual display of the design data of the sample. 34. The method of claim 33,
determining one or more additional target patterns as patterns of interest based on the one or more identified defects;
defining one or more additional management regions on the sample based on identifying instances of the one or more additional target patterns within design data stored in a memory device of a controller; and
identifying one or more additional defects within the one or more additional management areas based on inspection using the virtual inspection system;
Defect inspection method further comprising. 34. The method of claim 33,
The design data includes at least one of a physical layout of the sample or an electrical layout of the sample. 34. The method of claim 33,
and providing the one or more management areas for use in a subsequent inspection process. 29. The method of claim 28,
and classifying one or more identified defects based on the design data of the sample. A defect inspection system comprising:
inspection subsystem - the inspection subsystem comprises:
an illumination source configured to generate a beam of illumination;
a set of illumination optics for directing the beam of illumination to a sample; and
a detector configured to collect illumination emitted from the sample; and
a controller communicatively coupled to the detector
including,
The controller includes a memory device and one or more processors configured to execute program instructions, wherein the program instructions cause the one or more processors to:
determine one or more target patterns as patterns of interest corresponding to one or more features on the sample;
create a complex search pattern, wherein the complex search pattern comprises at least one target pattern and a source pattern of the one or more target patterns;
define one or more management areas on the sample based on identifying one or more instances of the complex search pattern within the design data of the sample, the design data of the sample being stored in the memory device of the controller;
identify one or more defects in one or more controlled areas of the sample based on illumination collected by the detector while inspecting the one or more controlled areas using the inspection subsystem;
A defect inspection system that is constituted. 42. The method of claim 41, wherein identifying instances of the one or more target patterns within the design data of the sample comprises:
and retrieving design data for the one or more target patterns to create one or more identified instances of the one or more target patterns. 42. The method of claim 41, wherein defining the one or more management areas comprises:
identifying instances of the one or more target patterns in the design data;
determine a confidence score for each instance of the one or more target patterns in the design data, wherein the confidence score is a measure of the degree of similarity between the identified instances of the one or more target patterns and the one or more target patterns in the design data. to do;
defining, as the one or more management areas, instances of the one or more target patterns in design data having a confidence score higher than a selected confidence scorer;
A defect inspection system comprising a. 42. The method of claim 41, wherein the one or more target patterns include:
and one or more target patterns identified by a previous defect inspection process. 42. The method of claim 41,
Determining the one or more target patterns comprises:
and determining the one or more target patterns by a user. 46. The method of claim 45, wherein determining the one or more target patterns by the user comprises:
and selecting one or more instances of the one or more target patterns from the design data of the sample. 47. The method of claim 46, wherein selecting one or more instances of the one or more target patterns from the design data of the sample comprises:
and selecting the one or more instances of the one or more target patterns from a visual display of the design data of the sample.

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