TW201706590A - System and method for dynamic care area generation on an inspection tool - Google Patents

Abstract

A defect inspection system includes an inspection sub-system and a controller communicatively coupled to the detector. The inspection sub-system includes an illumination source configured to generate a beam of illumination, a set of illumination optics to direct the beam of illumination to a sample, and a detector configured to collect illumination emanating from the sample. The controller includes a memory device and one or more processors configured to execute program instructions. The controller is configured to determine one or more target patterns corresponding to one or more features on the sample, define one or more care areas on the sample based on the one or more target patterns and design data of the sample stored within the memory device of the controller, and identify one or more defects within the one or more care areas of the sample based on the illumination collected by the detector.

Description

System and method for dynamic care area generation on inspection tools priority

This application claims that the application titled NOVEL AND EFFICIENT APPROACH FOR ON-TOOL DYNAMIC CARE AREA GENERATION USING DESIGN, the Indian interim patent application invented by Vijayakumar Ramachandran, Vidyasagar Anantha, Philip Measor and Rajesh Manepalli on May 28, 2015 No. 2681/CHE/2015; and the title of the application on July 30, 2015 is NOVEL AND EFFICIENT APPROACH FOR ON-TOOL DYNAMIC CARE AREA GENERATION USING DESIGN, invented by Vijayakumar Ramachandran, Vidyasagar Anantha, Philip Measor and Rajesh Manepalli The priority of US Provisional Patent Application No. 61/198, 911, the entire disclosure of which is incorporated herein by reference.

The present invention is generally directed to defect detection and, more particularly, to the creation of a care area on a test tool.

The inspection system identifies defects on the semiconductor wafer and classifies the defects to create a defect population on a wafer. A given semiconductor wafer can contain hundreds of wafers, each containing thousands of components of interest, and each component of interest can have millions of instances of a given layer of a wafer. Therefore, the inspection system can generate a large amount on a given wafer. Data points (for example, hundreds of billions of data points for some systems). In addition, the need to continuously shrink the device has led to an increase in demand for detection systems. The need includes the need for increased resolution and capacity required to infer the root cause of the identified defect without sacrificing detection speed or accuracy.

However, the use of design information associated with a wafer typically affects the additional consumption of a test procedure and therefore the throughput. For example, a utility for generating a care area based on design data can provide a large data archive of the various attributes of the designated care area (which must be transmitted to the inspection tool). In addition, a test tool may need to register the design data with the sample to correlate the design coordinates with the coordinates of the test tool.

Accordingly, it would be desirable to provide a system and method for addressing the shortcomings identified above.

A defect detection system is disclosed in accordance with one or more illustrative embodiments of the invention. In an illustrative embodiment, the system includes a detection subsystem. In another illustrative embodiment, the detection subsystem includes an illumination source configured to generate an illumination beam. In another illustrative embodiment, the detection subsystem includes a set of illumination optics to direct the illumination beam to the same. In another illustrative embodiment, the detection subsystem includes one of the detectors configured to collect illumination emitted from the sample. In another illustrative embodiment, the system includes a controller communicatively coupled to the detector. In another illustrative embodiment, the controller includes a memory device and one or more processors configured to execute the 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 one or more target patterns and design data for the sample. In another illustrative embodiment, the design data for the sample is stored in the memory device of the controller. In another embodiment, the controller is configured to identify the one or more care areas of the sample based on the illumination collected by the detector One or more defects.

A defect detection system is disclosed in accordance with one or more illustrative embodiments of the invention. In an illustrative embodiment, the system includes a detection subsystem. In another illustrative embodiment, the detection subsystem includes an illumination source configured to generate an illumination beam. In another illustrative embodiment, the detection subsystem includes a set of illumination optics to direct the illumination beam to the same. In another illustrative embodiment, the detection subsystem includes one of the detectors configured to collect illumination emitted from the sample. In another illustrative embodiment, the system includes a controller communicatively coupled to the detector. In another illustrative embodiment, the controller includes a memory device and one or more processors configured to execute the 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 a source pattern. In another illustrative embodiment, the source pattern is adjacent to a subset of the instances of the one or more target patterns within the design data for the sample. In another illustrative embodiment, the design data for the sample is stored in the memory device of the controller. In another illustrative embodiment, the controller is configured to define between the source pattern and at least one target pattern of the subset of the one or more target patterns within the design material of the sample A spatial relationship. In another illustrative embodiment, the controller is configured to identify one or more instances of the source pattern within the design material of the sample. In another illustrative embodiment, the controller is configured to be based on the one or more identified instances of the source pattern and the subset of the source pattern and the one or more target patterns A subset of the one or more target patterns within the design material of the sample is identified by a spatial relationship between the at least one target pattern. In another illustrative embodiment, the controller is configured to define one or more care areas on the sample based on the subset of the items of the one or more target patterns. In another illustrative embodiment, the controller is configured to identify one or more defects in the one or more care areas of the sample based on the illumination collected by the detector.

A defect detecting method is disclosed in accordance with one or more illustrative embodiments of the present invention. In an illustrative embodiment, the method includes providing the same design information to a detection system. In another illustrative embodiment, the method includes determining one or more target patterns. In another illustrative embodiment, the one or more target patterns include design material associated with one or more sample features to be detected. In another illustrative embodiment, the method includes defining, by the detection system, one or more care areas on the sample based on the one or more target patterns and the design data of the sample. In another illustrative embodiment, the method includes identifying one or more defects in the one or more care areas of the sample.

It is to be understood that both the foregoing general description The embodiments of the present invention are illustrated in conjunction with the description of the claims

100‧‧‧Detection system

102‧‧‧Detection subsystem

104‧‧‧ Controller

106‧‧‧ Processor

108‧‧‧Memory media/memory/memory device

110‧‧‧ sample

202‧‧‧Detection tools

204‧‧‧Design module

206‧‧‧Steps

208‧‧‧Analysis of design information

210‧‧‧Recipe module

212‧‧‧Steps

214‧‧‧ steps

216‧‧‧Steps

300‧‧‧ method

302‧‧‧Steps

304‧‧‧Steps

306‧‧‧Steps

308‧‧‧Steps

402‧‧‧Design materials

404‧‧‧ target pattern

406‧‧‧care area

408‧‧‧ source pattern

410‧‧‧Combined target pattern

412‧‧‧Specific examples of target patterns

414‧‧‧ vector

502‧‧‧Light source/particle source

504‧‧‧Lighting beam/particle beam

506‧‧‧Lighting path

508‧‧‧Optical components

510‧‧‧ lens

512‧‧‧sample stage

514‧‧‧beam splitter

516‧‧‧ Objective lens

518‧‧‧Collection path

520‧‧‧ lens

522‧‧‧Detector

524‧‧‧Particle focusing element

526‧‧‧ particle beam scanning element

528‧‧‧ particles

A person skilled in the art can better understand the many advantages of the present invention by referring to the accompanying drawings in which: FIG. 1 is a conceptual diagram illustrating one of the detection systems according to one or more embodiments of the present invention; A block diagram of one of the inspection tools of one of the detection systems of the present invention, illustrating the use of design data to generate a care area for detection based on design data stored on the inspection tool; FIG. 3 is a diagram A flow chart illustrating one of the steps performed in one of the methods for defect detection in accordance with one or more embodiments of the present invention; FIG. 4 illustrates the association of a source pattern based on one or more embodiments of the present invention. A schematic diagram of one of the design data of the care area; FIG. 5A is a conceptual diagram illustrating one of the optical detection subsystems in accordance with one or more embodiments of the present invention; and FIG. 5B is utilized in accordance with one or more embodiments of the present invention. Or multiple particle beams A schematic diagram of one of the detection subsystems.

Reference will now be made in detail to the claims,

Embodiments of the present invention are directed to a detection system that produces the same care area on a tool. In this regard, a selection area for the care area or sample of interest can be generated directly on the detection tool. An additional embodiment of the present invention relates to identifying a care area on a tool based on one or more instances of a target pattern of interest within a design data identifying a sample stored on the testing tool. For example, a target pattern can include design material associated with one or more sample features to be detected. Additional embodiments of the present invention relate to the storage and pre-processing of a design data on a detection system for detecting an effective determination of a care area on a tool. A further embodiment of the invention relates to a subset of the examples of identifying a target pattern within the design data based on the proximity of a source pattern within the design data of the sample. Accordingly, the generation of the care area may include designing a combination of search samples based on a defined spatial relationship for one of the target patterns of interest filtered by the target pattern that is close to the source pattern.

It should be recognized herein that detection tools typically only detect a subset of one of the same surfaces for defects. The generation of the care area or the target area of the sample to be detected not only can significantly improve the efficiency of defect detection by reducing the detected surface area, but also can significantly improve the accuracy of defect detection by reducing spurious signals and noise. In addition, the care area can be defined to provide a target detection analysis such as, but not limited to, analysis of a particular defect type or analysis of a particular pattern element throughout one of the sample locations.

It should be further appreciated that the design data for the sample (eg, the physical layout of the components in the present, the electrical connections between the components on the sample, or the like) can be used to define the care area. However, the use of design data often affects the additional consumption of a test procedure and therefore the throughput. For example, a utility for generating a care area based on design data can provide a designation The large data files of the various attributes of the care area (eg, the location of each care area, the shape of each care area, and the like) must be transmitted to the inspection tool. In addition, a test tool may need to register the design data with the sample (eg, align, scale, or the like) such that the design coordinates (eg, graphic design system (GDS) coordinates or the like) and the coordinates of the test tool Interrelated.

Embodiments of the present invention are a pre-processed version of one of the design materials for storing a sample on a test tool. In this regard, a design-based care area can be generated using pre-processing design data (eg, a local version of the pre-processed design material) on the inspection tool. Moreover, in some embodiments, a design-based care area can be created on the inspection tool without further data transfer requirements. In addition, the design-based care area created on the inspection tool can be automatically aligned to the coordinates of the inspection tool.

As used throughout this disclosure, the term "sample" generally refers to a substrate formed from a semiconductor or non-semiconductor material (eg, a wafer or the like). For example, a semiconductor or non-semiconductor material can include, but is not limited to, single crystal germanium, gallium arsenide, and indium phosphide. A sample can include one or more layers. For example, such layers can include, but are not limited to, a photoresist, a dielectric material, a conductive material, and a half conductive 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 one of these layers can be formed. One or more layers formed on the same substrate may be patterned or unpatterned. For example, the same may include a plurality of dies, each having reproducible patterning features. The formation and processing of such material layers can ultimately result in a completed device. Many different types of devices can be formed in the same manner, 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. Moreover, for the purposes of the present invention, the terms sample and wafer should be interpreted as being interchangeable. Additionally, for the purposes of the present invention, the terms patterning device, mask, and reticle have been interpreted to be interchangeable.

1 is a conceptual diagram illustrating one of the inspection systems 100 in accordance with one or more embodiments of the present invention. In one embodiment, detection system 100 includes a detection subsystem 102 to Detecting the same defects on this 110.

It should be noted herein that detection subsystem 102 can be any type of detection system known in the art that is suitable for detecting defects on the same 110. For example, detection subsystem 102 can include a particle beam detection subsystem. Accordingly, detection subsystem 102 can direct one or more particle beams (eg, an electron beam, an ion beam, or the like) to sample 110 such that it can be based on detected radiation (eg, secondary electrons) emitted from the sample 110 , backscattered electrons, luminescence, or the like) detects one or more defects. As another example, detection subsystem 102 can include an optical detection subsystem. Accordingly, detection subsystem 102 can direct optical radiation to sample 110 such that one can be detected based on detected radiation (eg, reflected radiation, scattered radiation, diffracted radiation, luminescent radiation, or the like) emitted from the sample 110. Or multiple defects.

Detection subsystem 102 can operate in an imaging mode or a non-imaging mode. For example, in an imaging mode, individual objects (eg, defects) may be resolved within the illumination point on the sample (eg, as a bright field image, a dark field image, a phase contrast image, or the like). In a non-imaging mode of operation, the radiation collected by one or more detectors can be associated with a single illumination point on the sample and can represent a single pixel of one of the images of the sample 110. In this regard, an image of the sample 110 can be generated by obtaining data from an array of local locations. Moreover, detection subsystem 102 can operate as a detection system based on scatterometry, wherein the radiation from the sample is analyzed at a pupil plane to characterize the angular distribution of radiation from sample 110 (eg, with sample 110) Radiation scattering and/or diffraction associated).

In another embodiment, detection system 100 includes a controller 104 coupled to one of detection subsystems 102. For example, the controller 104 can be communicatively coupled to the detector 522. In this regard, the controller 104 can be configured to receive data including, but not limited to, detection data from the detection subsystem 102. In another embodiment, the controller 104 includes one or more processors 106. For example, the one or more processors 106 can be configured to execute a set of program instructions maintained in a memory device 108 or memory. One or more processors of one controller 104 106 can include any of the processing elements known in the art. In this regard, one or more processors 106 can include any microprocessor type device configured to perform algorithms and/or instructions. Moreover, the memory medium 108 can include any storage medium known in the art that is suitable for storing program instructions executable by the associated one or more processors 106. For example, the memory medium 108 can include a non-transitory memory medium. As an additional example, the memory medium 108 can include, but is not limited to, a read only memory, a random access memory, a magnetic or optical memory device (eg, a magnetic disk), a magnetic tape, a solid magnetic Disc players and the like. It should be further noted that the memory medium 108 can be housed in a common controller enclosure with one or more processors 106.

Detection system 100 can utilize any of the detection techniques known in the art to detect defects associated with the same. For example, by comparing the measured characteristics of the sample (eg, produced by the detection subsystem 102 or the like) with the measured characteristics of a reference sample (eg, die-to-die (D2D) detection, standard reference crystals) The particle (SRD) detection or the like) detects the same defect on the 110. As another example, the same defect on the 110 can be detected by comparing the image of one of the samples 110 with one of the images based on design characteristics (eg, die-to-database (D2DB) detection). As a further example, detection system 100 can include a virtual detection system. In one embodiment, controller 104 operates as a virtual detector. In this regard, the controller 104 can detect one or more defects on the sample 110 by comparing the detected data of the sample with the persistent reference data (eg, one or more reference images). For example, one or more reference images can be stored on detection system 100 (eg, in memory 108) and used for defect detection. In another embodiment, the controller 104 generates and/or receives a simulated detected image based on the design data associated with the sample 110 to operate as one of the reference images for defect detection.

A detection system using design data is generally described in U.S. Patent Application Serial No. 2014/0153814, the entire disclosure of which is incorporated herein by reference. The use is generally described in U.S. Patent No. 8,126,255, issued Feb. 28, 2012. A detection system for continuous data (e.g., stored data) is incorporated herein by reference in its entirety. The detection system using the same design information to facilitate detection is generally described in U.S. Patent No. 7,676,077, issued March 9, 2010, and U.S. Patent No. 6,154,714, issued on Nov. 28, 2000. This is incorporated herein by reference. Defects and sources of failure are generally described in U.S. Patent No. 6,920,596, issued July 19, 2005, U.S. Patent No. 8,194,968 issued on Jun. 5, 2015, and U.S. Patent No. 6,995,393, issued on Feb. 7, 2006. The entire disclosures of these patents are hereby incorporated by reference. Device nature extraction and monitoring is generally described in U.S. Patent No. 8,611,639, issued December 17, 2013. The use of dual energy electron flooding for use in a charging substrate is generally described in U.S. Patent No. 6,930,309, issued to A.S. U.S. Patent No. 6,529,621 issued on Mar. 4, 2003, U.S. Patent No. 6,748,103 issued on Jun. 8, 2004, and U.S. Patent No. 6,966,047, issued on In the detection system, the entire contents of these patents are incorporated herein by reference. U.S. Patent No. 6,691,052, issued on Feb. 10, 2004, U.S. Patent No. 6,921,672, issued on Jul. 26, 2005, and U.S. Patent No. 8,112,241, issued on Feb. 7, 2012. The detection targets are incorporated herein by reference in their entirety. A key area for determining semiconductor design information is generally described in U.S. Patent No. 6,948,141, issued Sep. 20, 2005, which is incorporated herein in its entirety by reference.

2 is a block diagram of one of the inspection tools 202 of the detection system 100 in accordance with one or more embodiments of the present invention, illustrating the definition of the care area on the inspection tool 202. In one embodiment, the inspection tool 202 includes one or more modules configured to perform one or more steps of the inspection tool 202. For example, one or more modules of the inspection tool 202 can be implemented (but not necessarily) as being stored in the memory 108 and executed by the one or more processors 106.

In another embodiment, the inspection tool 202 includes a design module 204. For example, the design module 204 can include design data associated with one or more samples 110 to be detected by the inspection tool 202. In this regard, the design material associated with the sample 110 can be used on the inspection tool 202 to create a care area. It should be noted herein that the direct creation of a design-based care area on the inspection tool 202 can facilitate efficient and dynamic generation of the care area. For example, generating a design-based care area on the inspection tool 202 can reduce data transfer between the test tool 202 and an external system (eg, care area definition or similar data transfer). Moreover, generating a design-based care area on the inspection tool 202 can facilitate the precise alignment of the coordinates associated with the design material to the coordinates associated with the sample and/or the inspection tool 202. For example, a design coordinate (eg, a GDS coordinate or the like) may need to be adjusted (eg, scaled, rotated, or the like) such that the design pattern size and orientation of the design data match the sample, such as by the inspection tool 202. The printed pattern was measured. Producing a design-based care area on the inspection tool facilitates accurate and efficient alignment of the design and sample coordinate system.

The term "design data" as used in the present invention generally refers to the physical design of an integrated circuit and the data derived from the physical design through complex simulation or simple geometry and Boolean operations. In addition, an image of one of the reticle and/or its derivatives obtained by a reticle inspection system can be used as an agent or a number of agents for the design data. Such a reticle image or derivative thereof can be used in place of one of the design layouts for the design materials used in any of the embodiments described herein. U.S. Patent No. 7,676,007 issued to Kulkarni on March 9, 2010; U.S. Patent Application Serial No. 13/115,957, filed on May 25, 2011 by Kulkarni; issued by Kulkarni on October 18, 2011 Design documents and design information agents are described in U.S. Patent No. 8, 041,103, the disclosure of which is incorporated herein by reference. In addition, the design information is used in the guidance detection procedure as generally described in U.S. Patent Application Serial No. 13/339,805, filed on Feb. 17, 2012, which is incorporated herein by reference.

The design data may include characteristics of individual components and/or layers on a sample 110 (eg, an insulator, a conductor, a semiconductor, a well, a substrate, or the like), a connection between layers on the sample 110 A functional relationship or a physical layout of one of the components and connectors (eg, wires) on the sample 110. In this regard, the design material can include a plurality of design pattern elements corresponding to the printed pattern elements on the sample 110.

It should be noted herein that the design data may include information referred to as a "planar design" containing information on the placement of pattern elements on the sample 110. It should be further noted herein that this information can be extracted from an entity design that typically stores one of the wafers in GDSII or OASIS file format. Structural behavior or programming interactions can vary depending on the context (environment) of a pattern element. By using a planar design, the proposed analysis can identify pattern elements within the design data, such as polygons that describe the features to be constructed on a semiconductor layer. In addition, the proposed method can provide coordinate information of such repeating blocks as well as content context data (eg, the location of adjacent structures or the like).

In one embodiment, the design material includes one or more graphical representations of the pattern elements (eg, visual representations, symbolic representations, graphical representations, or the like). For example, the design material can include a graphical representation of one of the physical layouts of the components (eg, corresponding to a description of one or more polygons of the printed pattern elements made on the sample 110). In addition, the design material may include a graphical representation of one or more layers of the design (eg, one or more layers of the printed pattern elements fabricated on the sample 110) or a connection between one or more layers. As another example, the design material can include a graphical representation of one of the electrical connectivity capabilities of the components on the sample 110. In this aspect, the design material can include a graphical representation of one or more circuits or sub-circuits associated with the sample. In another embodiment, the design material includes one or more image files containing graphical representations of one or more portions of the sample 110.

In another embodiment, the design material includes one or more textual descriptions of the pattern elements of the sample 110 (eg, one or more lists, one or more tables, one or more databases, or the like) . For example, design data may include (but is not limited to) wiring comparisons Materials, circuit simulation data or hardware description language materials. The wiring comparison table may include any type of wiring comparison table described in the art for providing a connection capability of a circuit, including (but not limited to) a physical wiring comparison table, a logical wiring comparison table, and an example based Wiring checklist or network-based wiring checklist. In addition, a wiring comparison table may include one or more sub-wiring control tables (eg, in a hierarchical configuration) to describe circuits and/or sub-circuits on the same 110. For example, the wiring reference table data associated with a wiring checklist may include, but is not limited to, a list of nodes (eg, a network, wire, or the like between components of a circuit); a list (eg, Terminal, pin, connector, or the like; one of the electrical components between the networks (eg, resistors, capacitors, inductors, transistors, diodes, power supplies, or the like); associated with electrical components The value of the joint (for example, one of the resistance values of a resistor (in ohms), one of the voltage values of a power source (in volts), the frequency characteristic of a voltage source, the initial condition of the component, or the like). In another embodiment, the design data may include one or more wiring comparison tables associated with particular steps of a semiconductor program flow. For example, the same book 110 can be detected at one or more intermediate points in a semiconductor program flow (e.g., by system 100). Thus, at one of the current points in the semiconductor program flow, the design material used to create the care area can be dedicated to the layout of the sample 110. In this regard, it may be derived from a physical design layout that incorporates a technical file (layer connection capability, electrical properties of the layers, and the like) or a wiring comparison table associated with one of the final layouts of the same 110 (eg, Extracting or similar one of the wiring checklists associated with a particular intermediate point in a semiconductor program flow to include components present on the wafer only at a particular intermediate point in the semiconductor program flow.

In another embodiment, the design module 204 of the inspection tool 202 performs one of the pre-processing design data steps 206. It should be noted herein that the design data may include information (eg, manufacturing materials or the like) that is unrelated to the determination of the care area of the detection system 100. In addition, the design material may not be in one of the formats suitable for effective identification (eg, search, match, or the like) of the pattern elements of interest within the design material. Therefore, the design data of the pretreatment can include One version of the data is pre-processed to facilitate efficient generation of the care area on the inspection tool 202. In this regard, the pre-processed design material may facilitate identification of one or more of the target patterns (eg, target elements of interest, hotspots, or the like) within the design data. For example, the pre-processed design material may be searched according to any combination of design data elements, including but not limited to one of the target pattern identifiers, one of the target patterns, one of the target patterns, one of the target patterns, or one of the target patterns. One of a relationship between one or more additional patterns (eg, an anchor pattern, a source pattern, or the like) or a graphical representation of one of the target patterns.

In another embodiment, the design information (eg, original design data, pre-processed design data, or a combination thereof) is stored by the inspection tool 202. For example, the design data can be stored in one of the memory devices 108 of the controller 104. In another embodiment, the design data may be pre-processed outside of the inspection system 100 and stored on the inspection tool 202. In this regard, pre-processed design material associated with one or more samples can be transmitted to the inspection tool 202.

In another embodiment, the design module 204 performs one of the steps of analyzing the design data stored on the inspection tool 202. In this aspect, the design module 204 can identify one or more instances of one of the target patterns within the same design data (eg, by searching for pre-processed design material or the like for an instance of one or more target patterns) By). In addition, the design module 204 can provide parameters of the identified instances of the target pattern required to produce the care 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 can generate a recipe for one or more detection steps by the inspection tool 202. In this aspect, a formulation can include, but is not limited to, one or more care zones for defect detection, one or more registration operations (eg, aligning and/or scaling the coordinates associated with the design material) One of the one or more defect identification steps or one or more defect classification steps is described to the coordinates and similarities associated with the sample and/or detection subsystem 102. In addition, creating a design-based care area on the inspection tool 202 facilitates an efficient multi-step detection procedure (for example, for system defect discovery or similar). In this regard, the search design data can be searched and analyzed on the inspection tool 202 for different target patterns or combinations of target patterns without the need to transfer the data to an external system.

In another embodiment, the recipe module 210 performs one or more target patterns (eg, one or more concerns) associated with the manufacturing pattern elements on the sample 110 to be detected by the inspection tool 202 in a detection step. Step 212 of one of a pattern element, one or more hotspots or the like. For example, the recipe module 210 can provide one or more target patterns based on one or more of the purposes of detecting one of the inspection tools 202. For example, recipe module 210 can provide a target pattern associated with a known type of defect of interest.

In another embodiment, the recipe module 210 determines one or more target patterns in an automated process. For example, the recipe module 210 can analyze the design data 208 of the sample 110 to determine one or more target patterns that may exhibit defects (eg, based on physical layout, pattern size, proximity to other patterns, circuit complexity, or the like). Related characteristics).

In another embodiment, the determination of the target pattern is facilitated by a user. For example, a user may provide input to one of the inspection tools 202 (eg, to one of the recipe modules 210), including but not limited to one or more defect identifiers, one or more GDS coordinates, one or Multiple design-based classification (DBC) fragments or one or more design-based grouping (DBG) frequency bins. In this regard, the recipe module 210 can determine one or more target patterns based on user input. In another embodiment, the inspection tool 202 can provide a visual display associated with the design material (eg, within one of the design views of the inspection tool 202). In this regard, the user can select one or more target patterns from the visual display of the design data. For example, the visual display can include a graphical display (eg, a display of one image or the like) in which design pattern elements of the design material can be displayed (eg, pattern elements associated with the physical layout of the components, and between the components) The pattern element associated with the electrical connector or the like). As another example, a visual display can include a text-based display in which design material can be displayed. In another embodiment, a user may be based on a standard system (eg, The GDS coordinates) (eg, on a graphical display) visualize design data to determine and/or confirm one or more target patterns. For example, a user may enter coordinates (eg, into one of the input devices of detection system 100) to visualize and/or confirm design data at a specified location to generate a target pattern for detection.

In another embodiment, the recipe module 210 performs a step 214 of defining one or more care areas to be detected on the sample 110. For example, the recipe module 210 can define one or more care 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 can provide one or more target patterns to the design module 204 for pattern matching. In addition, the design module 204 can identify one or more instances of the target pattern within the design data and provide any parameters needed to generate the care area to the recipe module 210 based on the identified instances of the target pattern. For example, the design module 204 can provide the location of the identified instance of the target pattern (eg, in design coordinates), the shape of the identified instance of the target pattern, the contour of the identified instance of the target pattern, or the like.

In another embodiment, the recipe module 210 performs one of the steps 216 of identifying defects on the sample 110. In this regard, the recipe module 210 can interface with the detection subsystem 102 to perform defect detection. Additionally, the recipe module 210 can analyze the data received by the detection subsystem 102 to determine the presence of one or more defects. Additionally, the recipe module 210 can characterize one or more defects. For example, a recipe module can (but need not) be characterized based on a DBC system, a DBG system, or the like. In addition, recipe module 210 can assign one or more defect identifiers to one or more characterized defects.

It should be appreciated herein that the steps described throughout this disclosure (e.g., steps associated with modules of detection tool 202 or the like) may be implemented by a single controller 104 or alternatively by multiple controllers 104. It should be further noted herein that one or more controllers 104 can be positioned proximate to detection subsystem 102. Additionally, the one or more controllers 104 and detectors can be The systems 102 are housed together in a common housing and, in addition, any controller or combination of controllers can be individually packaged into one module suitable for integration into a complete inspection system 100. For example, a first controller can be configured to perform the steps associated with design module 204. Next, one or more additional controllers can be configured to perform the steps associated with recipe module 210. In this regard, one or more controllers 104 can be integrated into the detection system 100.

3 is a flow chart illustrating one of the steps performed in a method 300 for defect detection in accordance with one or more embodiments of the present invention. Applicants should note that the embodiments and enabling techniques previously described herein in the context of system 100 should be construed as extending to method 300. However, it should be further noted that the method 300 is not limited to the architecture of the system 100.

In one embodiment, method 300 includes the step 302 of providing one of the design data to a detection system. For example, design data may (but need not) be provided to a detection 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 detection system can be utilized to generate one or more design-based care areas for testing.

In another embodiment, method 300 includes a step 304 of determining one or more target patterns. In this aspect, one or more of the target patterns of interest associated with the manufacturing features on the sample can be provided for detection. For example, the target pattern may include one or more polygons representing features to be constructed on a semiconductor layer (eg, one or more instances of a cross, plus, L, T, square, rectangle, or other polygon) , with specific dimensions and spacing between the items).

In one embodiment, one or more target patterns are determined based on the defect identifier. In this regard, one or more known defects or types of defects associated with a defect identifier (eg, an identifier or similar to one or more defect classifications) may be associated with one or more particular target patterns Associated (eg, based on one or more previous detection passes, based on one or more design characteristics or the like). Thus, the occurrence of a known defect or type of defect can be characterized by providing a corresponding target pattern for detection.

In another embodiment, one or more target patterns are determined based on a previous detection step (eg, by detection system 100 or an additional detection system). For example, in a system defect discovery, the first detection run of one of the present 110 or a portion of the sample 110 can identify one or more manufacturing components of the sample 110 that are susceptible to defects. In this aspect, the first detection stroke can determine one or more target patterns associated with the identified manufacturing components on the sample 110. Additionally, a second test pass can include a recipe (eg, generated by recipe module 210) to perform a dedicated detection of one of the one or more target patterns from the first test pass. In another embodiment, one or more target patterns are determined based on a DBC or a DBG program associated with a previous detection step.

In another embodiment, one or more target patterns are determined based on one or more coordinates (eg, GDS coordinates or the like) of one of the target patterns. For example, one or more target patterns can be determined based on known coordinates of an exemplary target pattern of interest associated with the design material. As another example, one or more target patterns can be determined based on known coordinates of one of the exemplary fabrication components on sample 110. Accordingly, one or more target patterns associated with the illustrative manufacturing components can be provided for inspection.

In another embodiment, the method 300 includes the step 306 of delineating one or more care areas on the sample based on the target pattern and the design data of the sample by the detection system. In this regard, step 306 can include defining one or more regions on the sample to be detected. For example, a care area may contain coordinates on a sample to be detected (eg, in a coordinate system of a detection system).

In another embodiment, a care area includes one or more target areas on the sample for detection. For example, a first target area may include identifying one or more of the first target patterns in step 304, and a second target area may include identifying one or more of the second target patterns in step 304. Examples, and similar. Moreover, the definition of one or more target regions may facilitate sensitive detection of the sample 110. For example, the target area can be defined to include samples having similar sensitivity levels. Therefore, a different sensitivity threshold can be The value detects each target area such that a comparison of the detected data associated with each target area can be increased.

In another embodiment, step 306 includes identifying one or more instances of the target pattern determined in step 304 within the design data (eg, the pre-processed design data stored in the memory device 108 of the detection system 100). In this regard, each identified instance of the target pattern of interest may be included in a care area. Additionally, variations in the target pattern of interest (eg, one of a target pattern horizontally and/or vertically flipped, one of the target patterns being scaled, a rotated version of a target pattern, or the like) may be identified in step 306 It is included in a care area.

Any of the methods known in the art can be used to identify instances of the target pattern within the device data. For example, step 306 can include searching for design material for one or more of the target patterns to generate one or more identified instances of the target pattern. In one embodiment, step 306 includes one of the design materials based on a text search. For example, text-based design data may be searched for based on one or more characteristics of a target pattern (eg, one or more lists, one or more tables, one or more databases, one or more data files, or the like) ). In another embodiment, step 306 includes one of the design data based on the image search. For example, an image processing algorithm (such as, but not limited to) a feature extraction technique, a convolution technique, a pattern matching technique, a spatial frequency analysis, a transform technique (eg, a Hough transform technique or Similarly)) Find one or more instances of a target pattern (or one of the target patterns changes). In addition, multiple design layers of design data (eg, corresponding to multiple layers of the fabrication components on sample 110) may be individually searched for one or more instances of the target pattern of interest.

In one embodiment, the design pattern contained in a design layout file (such as OASIS or GDS) can be used to identify the target pattern. It should be noted herein that the size of the target pattern can vary and can be located at various levels of the design data (eg, associated with various layers, grains, blocks, cells, or the like of the sample 110). In this regard, a known or The observed design unit hierarchy identifies the target pattern in the design data. For example, a design unit hierarchy can be analyzed to identify a target pattern in a repeating group within a given set of test data.

In another embodiment, a design rule check (DRC) program, an optical rule check (ORC), or a fault analysis (FA) program can be utilized to identify the target pattern to identify a target pattern that is critical to device performance. In another embodiment, a program window qualification test (PWQ) can be utilized to identify the target pattern. Searching for design data for one or more target patterns can be performed as described by Kulkarni et al. and Zafar et al., as described in the above references, which are incorporated herein by reference.

In some embodiments, information from electronic design automation (EDA) tools and other knowledge can be utilized on the semiconductor wafer to identify the target pattern. Any such information about the design produced by an EDA tool can be used to identify duplicate blocks. Additionally, the design material can be searched for one or more target patterns in any suitable manner. Searching for design data for one or more target patterns can be performed, for example, as described by Kulkarni et al. and Zafar et al. in the above-referenced patent application, which is incorporated herein by reference. Additionally, the target pattern can be selected or identified using any of the other methods or systems described in this patent application.

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

It will be appreciated that the target pattern can be repeated throughout the same pattern of grains 110 to form a repeating block (or field). In addition, units of the same 110 may sometimes be repeated with different names throughout a given die or may be repeated at multiple locations with one name. In some embodiments, the repeating units are aligned to the same horizontal and/or vertical axis. In other embodiments, the repeating units are not aligned to the same horizontal and/or vertical axis.

In another embodiment, step 306 includes providing a confidence metric associated with the identification of each instance of the target pattern of interest to a location within the design material. In this regard, loading An instance of one of the target patterns within the data may include an exact match (eg, 100% one confidence measure or the like) or a substantial match (eg, less than 100% one confidence measure). It should be understood that any measure of confidence in the art is within the spirit and scope of the present invention. For example, a confidence measure can range from 0 (unmatched) to 1 (exact match).

It should be noted herein that the care area may be defined to include a subset of the identified instances of the target pattern. For example, the likelihood that a particular defect on one of the particular components of a device on a sample 110 will degrade one of the performances may depend on a number of factors, such as, but not limited to, the presence of an adjacent structure or the operating conditions of a particular component. .

In one embodiment, step 306 includes defining an instance of one or more care areas to include a target pattern of an additional pattern (eg, a source pattern, an anchor pattern, or the like) within one of the design materials. In this aspect, the presence of a source pattern can operate as a filter to provide a subset of the instances of the target pattern as the care area to be detected.

4 is a schematic diagram illustrating design data defining an associated care area based on a source pattern in accordance with one or more embodiments of the present invention.

In one embodiment, the design material 402 includes a plurality of instances of the target pattern 404. In addition, the design material 402 includes a source pattern 408 that is adjacent to a subset of the instance of the target pattern 404 (eg, one of the target instances 404 of a particular instance 412). For example, a source pattern can include, but is not limited to, one or more of an intersection, a cross, a plus, an L, a T, a square, a rectangle, or any other polygon, having a particular size between the items and spacing.

Moreover, step 306 can include defining a care area 406 around a particular instance 412 of the target pattern 404 based on a spatial relationship between the particular instance 412 of the target pattern 404 and the source pattern 408. For example, a spatial relationship between a particular instance 412 of the target pattern 404 and the source pattern 408 can include, but is not limited to, a vector 414 between the particular instance 412 of the target pattern 404 and the source pattern 408. In another embodiment, step 306 includes an example of searching for one or more instances of the source pattern within the design material and further identifying the target pattern based on the spatial relationship between the particular instance 412 of the target pattern 404 and the source pattern 408. a subset of items (for example, The specific example item 412) of the standard pattern 404 is included in a care area. In another embodiment, step 306 includes searching for an instance of the combined target pattern 410 including one of the source pattern 408 and one of the target patterns within the device profile 402, while surrounding the target pattern associated with the identified composite target pattern 410. A subset of the 404 instances (eg, the particular instance 412 of the target pattern 404) defines a care area 406. Thus, source pattern 408 can be used as part of a search step and is not included in associated care area 406.

In another embodiment, method 300 includes a step 308 of identifying one or more defects in one or more of the care areas. In this regard, the detection system (eg, detection system 100) detects the care area of the sample defined in step 308 for the defect (eg, using illumination subsystem 101). For example, data from detection subsystem 102 can be analyzed to determine the presence of one or more defects on sample 110 associated with the care area defined in step 306. In addition, the identified defects can be classified (eg, based on defect identifiers, DBC segments, DBG frequencies, or the like). In another embodiment, material associated with one or more identified defects may be provided (eg, as feed forward data, feedback material, or the like) to detection system 100 and/or an external system.

It will be appreciated herein that the steps described throughout this disclosure may be implemented by a single controller 104 or alternatively a plurality of controllers 104. It should be further noted herein that one or more controllers 104 can be housed in a common housing or in multiple housings. In this manner, any controller or combination of controllers can be individually packaged as one suitable for integration into one of the complete inspection systems 100. By way of a non-limiting example, a first controller can be configured to perform the step of identifying a set of illumination detection events based on receiving one of the illumination signals from the illumination sensor. Next, the one or more additional controllers can be configured to perform the steps of: identifying a set of radiation detection events based on receiving one or more radiation signals from the one or more radiation sensors; comparing the set of radiation detections The event and the set of illumination detection events to generate a set of coincident events; and excluding the set of coincident events from the set of illumination detection events to produce a set of identified features on the sample.

5A is a conceptual diagram of a detection subsystem 102 configured as one of an optical detection subsystem in accordance with one or more embodiments of the present invention. In one embodiment, detection subsystem 102 includes an illumination source 502. The illumination source 502 can comprise any illumination source known in the art to be suitable for generating an illumination beam 504 (eg, a photon beam). For example, the illumination source 502 can include, but is not limited to: a monochromatic source (eg, a laser); a polychromatic source having one of two or more discrete wavelengths; a broadband source; A wavelength sweeps the light source. Moreover, the illumination source 502 can be, but is not limited to, a white light source (eg, having a broadband source comprising one of the visible wavelengths), a laser source, a free form illumination source, a monopolar illumination source, A multi-pole illumination source, an arc lamp, an electrodeless lamp or a laser sustaining plasma (LSP) source is formed. In addition, illumination beam 504 can be delivered via free space or guided light (eg, an optical fiber, a light pipe, or the like).

In another embodiment, illumination source 502 directs one or more illumination beams 504 to sample 110 via an illumination path 506. Illumination path 506 can include one or more lenses 510. Moreover, the illumination path 506 can include one or more additional optical components 508 that are adapted to modify and/or adjust one or more illumination beams 504. For example, one or more optical components 508 can include, but are not limited to, one or more polarizers, one or more filters, one or more beam splitters, one or more diffusers, one or more A homogenizer, one or more apodizer or one or more beam shapers. In one embodiment, illumination path 506 includes a beam splitter 514. In another embodiment, detection subsystem 102 includes an objective lens 516 to focus one or more illumination beams 504 onto sample 110.

Illumination source 502 can direct one or more illumination beams 504 to the sample at any angle via illumination path 506. In one embodiment, as shown in FIG. 5A, illumination source 502 directs one or more illumination beams 504 to sample 110 at a normal incidence angle. In another embodiment, the illumination source 502 directs one or more illumination beams 504 to the sample 110 at an illegal incident angle (eg, a glancing angle, a 45 degree angle, or the like).

In another embodiment, the sample 110 is positioned to hold the sample during scanning One of the sample carriers 512 is 110. In another embodiment, the sample stage 512 is an actuatable stage. For example, the sample stage 512 can include, but is not limited to, one or more of the samples 110 that are selectively translatable along one or more linear directions (eg, the x-direction, the y-direction, and/or the z-direction) Pan the stage. By way of another example, the sample stage 512 can include, but is not limited to, one or more rotating stages that are adapted to selectively rotate the sample 110 along a direction of rotation. By way of another example, the sample stage 512 can include, but is not limited to, a sample that is adapted to selectively translate the sample along a linear direction and/or rotate the sample 110 in a rotational direction. Pan the stage.

In another embodiment, illumination path 506 includes one or more beam scanning optics (not shown) adapted to cause illumination beam 504 to scan across sample 110. For example, one or more illumination paths 506 can include any type of beam scanner known in the art such as, but not limited to, one or more electric beam deflectors, one or more acoustic beam deflectors, one or more An galvanometer scanner, one or more resonant scanners, or one or more polygon scanners. In this way, the surface of the same 110 can be scanned in the r-θ pattern. It should be further noted that the illumination beam 504 can be scanned according to any pattern on the sample. In one embodiment, the illumination beam 504 is divided into one or more beams such that one or more beams can be scanned simultaneously.

In another embodiment, the detection subsystem 102 includes one or more detectors 522 (eg, one or more optical detectors, one or more photon detectors, or the like), and the detectors are grouped The state is extracted from the sample 110 by a collection path 518. The collection path 518 can include a plurality of optical elements for directing and/or modifying illumination collected by the 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 stops or one or more beam splitters. It should be noted herein that the components of the collection path 518 can be oriented in any position relative to the sample 110. In one embodiment, the collection path includes an objective lens 516 oriented normal to the sample 110. In another embodiment, collection path 518 includes a plurality of collection lenses that are oriented to collect radiation from the sample at a plurality of solid angles.

In one embodiment, detection system 100 includes a bright field detection system. For example, the sample 110 or one of the portions of the sample 110 can be projected onto the detector 522 (eg, by the objective lens 516, one or more lenses 520, or the like). In another embodiment, detection system 100 includes a dark field detection system. For example, the detection system 100 can include one or more components (eg, an annular beam stop, a dark field objective 516, or the like) to direct the illumination beam 504 to the sample 110 at a large angle of incidence such that the detector The image of the sample on 522 is associated with scattering and/or diffracted light. In another embodiment, the detection system 100 includes a tilt angle detection system. For example, the detection system 100 can direct the illumination beam 504 to the sample at an off-axis angle to provide a contrast for defect detection. In another embodiment, the detection system 100 includes a phase contrast detection system. For example, the detection system 100 can include one or more phase plates and/or beam stops (eg, an annular beam stop or the like) to provide a phase contrast between the diffracted and undiffracted light from the sample, This provides a comparison for defect detection. In another embodiment, the detection system 100 can include a luminescence detection system (eg, a fluorescence detection system, a phosphorescence detection system, or the like). For example, the detection system 100 can direct an illumination beam 504 having a first wavelength spectrum to the sample 110 and include one or more filters to detect emission from the sample 110 (eg, from one or more of the samples 110) One or more additional wavelength spectra of the component and/or one or more defects on the sample 110. In another embodiment, the detection system includes positioning at a confocal position such that the system 100 is operable as one or more pinholes of a confocal detection system.

5B is a simplified schematic diagram of one of the detection subsystems configured as a particle beam detection subsystem in accordance with one or more embodiments of the present invention. In one embodiment, illumination source 502 includes a particle source configured to generate a particle beam 504. Particle source 502 can comprise any particle source known in the art to be suitable for generating a particle beam 504. By way of non-limiting example, particle source 502 can include, but is not limited to, an electron gun or an ion gun. In another embodiment, particle source 502 is configured to provide a particle beam 504 having one tunable energy. For example, a particle source 502 comprising an electron source can be, but is not limited to, provided at 0.1 kV to 30 kV. One of the ranges accelerates the voltage. As another example, a particle source comprising an ion source can, but need not, provide an ion beam having one of the energy values in the range of 1 keV to 50 keV.

In another embodiment, detection subsystem 102 includes two or more particle beam sources 502 (eg, an electron beam source or an ion beam source) for generating two or more particle beams 504.

In another embodiment, illumination path 506 includes one or more particle focusing elements 524. For example, the one or more particle focusing elements 524 can include, but are not limited to, a single particle focusing element or one or more particle focusing elements forming a composite system. In another embodiment, one of the objective lenses 516 of the system 100 is configured to direct the particle beam 504 to the sample 110. Additionally, one or more particle focusing elements 524 and/or objective lens 516 can comprise any type of particle lens known in the art including, but not limited to, an electrostatic, magnetic, single potential or bipotential lens. Moreover, detection subsystem 102 can include, but is not limited to, one or more electronic deflectors, one or more apertures, one or more filters, or one or more astigmatism correctors.

In another embodiment, detection subsystem 102 includes one or more particle beam scanning elements 526. For example, the one or more particle beam scanning elements can include, but are not limited to, one or more scanning coils or deflectors adapted to control one of the positions of the beam relative to the surface of the sample 110. In this aspect, the one or more scanning elements can be used to cause the particle beam 504 to scan across the sample 110 in a selected pattern.

In another embodiment, the detection subsystem includes a detector 522 to image or otherwise detect particles 528 emitted from the sample 110. In one embodiment, detector 522 includes an electron collector (eg, a secondary electron collector, a backscattered electron detector, or the like). In another embodiment, the detector 522 includes a photon detector (eg, a photodetector, an x-ray detector, a scintillation element coupled to a photomultiplier tube (PMT) detector, or the like). For detecting electrons and/or photons from the surface of the sample. In general, it should be appreciated herein that detector 522 can comprise any device or combination of devices known in the art for utilizing a particle beam 504 to characterize the same surface or block. E.g, The detector 522 can include configurations known in the art to collect backscattered electrons, Auger electrons, transmitted electrons, or photons (eg, x-rays emitted by the surface in response to incident electrons, Any particle detector of cathodoluminescence or the like of sample 110.

In another embodiment, detection system 100 includes a voltage contrast imaging (VCI) system. It should be appreciated herein that a detection system utilizing a particle beam (eg, an electron beam, an ion beam, or the like) can be attributed to detecting and/or identifying a semiconductor sample (eg, a random number) due to a high achievable spatial resolution. Defective mechanisms on logic chips or the like are especially useful. For example, a particle beam can be utilized within a detection system to image the same image (e.g., by drawing secondary electrons, backscattered electrons, or the like emitted from the sample). Moreover, the structure on the same (eg, a patterned semiconductor wafer) can exhibit a charging effect in response to excitation using a particle beam. The charging effect can 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 can produce a high resolution image of the same, wherein the intensity of each pixel of the image provides information about 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, ungrounded) can generate a charge (eg, a positive charge or a negative charge) in response to the depletion of particles caused by the particle beam. Thus, the induced charge deflects the orbit of the secondary electrons and reduces the signal strength drawn by a detector. Conversely, the ground structure may not generate a charge and thus may exhibit a strong signal (eg, appearing bright in an associated VCI image). In addition, the signal strength of the capacitive structure can vary depending on the scanning speed and/or energy of the particle beam. In this aspect, a VCI image can include a grayscale image in which the grayscale value of each pixel provides information about the electrical characteristics of the location on the wafer. In a further embodiment, detection 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 sample 110. In this regard, system 100 can generate an effective voltage versus imaging data.

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

The display device can comprise any display device known in the art. In an embodiment, the display device can include, but is not limited to, a liquid crystal display (LCD). In another embodiment, the display device can include, but is not limited to, an organic light emitting diode (OLED) based display. In another embodiment, the display device can 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 choice of display device may depend on various factors including, but not limited to, apparent size, cost, and the like. In a general sense, any display device that can be integrated with a user interface device (e.g., touch screen, panel mount interface, keyboard, mouse, track pad, and the like) is suitable for implementation in the present invention.

In another embodiment, detection system 100 can include a user interface device (not shown). In one embodiment, the user interface device is communicatively coupled to one or more processors 106 of the controller 104. In another embodiment, the user interface device can be utilized by the controller 104 to accept selections and/or instructions from a user. In some embodiments further described herein, the display can be used to display material to a user. Then, a user can input a selection and/or an instruction in response to the detection data displayed to the user via the display device (eg, one of the detection areas is user selected).

The user interface device can include any of the user interfaces known in the art. For example, the user interface can include (but is not limited to): keyboard, keypad, touch screen, lever, knob, scroll wheel, trackball, switch, dial, slider, roller, slider, handle, touch Pad, pedal, steering wheel, joystick, panel input device or the like. In the case of a touch screen interface device, those skilled in the art will recognize that a large number of touch screen interface devices can be adapted for implementation in the present invention. For example, the display device can be combined with a touch screen interface (such as but not limited to a capacitive touch screen, a resistive touch screen, a table based) The touch screen of the surface acoustic wave, an infrared-based touch screen or the like) is integrated. In a general sense, any touch screen interface that can be integrated with the display portion of display device 105 is suitable for implementation in the present invention. In another embodiment, the user interface can include, but is not limited to, a panel mounting interface.

It should be noted that Figures 5A and 5B and the corresponding description above are provided for illustration only and are not to 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 illustrates different components contained within or connected to other components. It should be appreciated that such depicted architectures are merely illustrative, and in fact many other architectures that achieve the same functionality can be implemented. In a conceptual sense, any configuration of components that achieve the same functionality is effectively "associated" to achieve the desired functionality. Accordingly, any two components herein combined to achieve a particular functionality can be seen as "associated" with each other such that the desired functionality is achieved without regard to the architecture or the intermediate components. Similarly, any two components so associated are also considered to be "connected" or "coupled" to each other to achieve the desired functionality, and any two components that can be so associated are also considered to be "coupled" to To achieve each other's desired functionality. Specific examples of coupling may include, but are not limited to, physical and/or physical interaction components and/or wirelessly interactive and/or wireless interactive components and/or logically interactive and/or logically interactive components.

It is believed that the invention, as well as its numerous advantages, are in the <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; </ RTI> <RTIgt; The description is for illustrative purposes only, and the following claims are intended to cover and cover such modifications. In addition, it is to be understood that the invention is defined by the scope of the accompanying claims.

102‧‧‧Detection subsystem

104‧‧‧ Controller

106‧‧‧ Processor

108‧‧‧Memory media/memory/memory device

110‧‧‧ sample

Claims (47)

A defect detection system comprising: a detection subsystem comprising: an illumination source configured to generate an illumination beam; a set of illumination optics for directing the illumination beam to the same; and a detector configured to collect illumination emitted from the sample; and a controller communicatively coupled to the detector, the controller including a memory device and configured to execute one of the program instructions or a plurality of processors configured to cause the one or more processors to: determine one or more target patterns corresponding to one or more features on the sample; based on the one or more target patterns And the design data of the sample defines one or more care areas on the sample, wherein the design data of the sample is stored in the memory device of the controller; and based on the illumination collected by the detector Identifying one or more defects in the one or more care areas of the sample. The defect detection system of claim 1, wherein the defining the one or more care areas on the sample comprises: identifying one or more of the one or more target patterns in the design material of the sample. The defect detection system of claim 2, wherein the one or more instances of the one or more target patterns in the design data identifying the sample comprise: generating a composite search pattern, wherein the composite search pattern includes a source a pattern and at least one target pattern of the one or more target patterns; identifying one or more instances of the composite pattern in the design material of the sample; and The one or more instances of the one or more target patterns within the design material of the sample are identified based on the one or more identified instances of the composite pattern. The defect detection system of claim 2, wherein the one or more processors are further configured to execute program instructions to cause the one or more processors to: pre-process the design data of the sample by the detection system to facilitate Identifying the one or more instances of the one or more target patterns within the design material of the sample. The defect detection system of claim 2, wherein the one or more instances of the one or more target patterns in the design data identifying the sample comprise: searching for the design data for the one or more target patterns to generate One or more identified instances of the one or more target patterns. The defect detection system of claim 5, wherein the one or more identified instances of the one or more target patterns comprise the one or more associated with the one or more target patterns and the one or more target patterns One or more credibility scores for one of a plurality of identified instances. The defect detection system of claim 1, wherein the defining the one or more care areas on the sample comprises: defining one or more target areas, wherein the one or more target areas comprise at least the one or more target patterns At least one instance of one of the plurality of care areas comprising the one or more target areas. The defect detecting system of claim 7, wherein the detecting the one or more care areas for the defect comprises: detecting the one or more target areas, wherein one of the one or more target areas can be individually adjusted for detection sensitivity . The defect detection system of claim 1, wherein the one or more target patterns comprise: one or more target patterns identified by at least one of a design-based classification or a design-based binning program . The defect detection system of claim 1, wherein the one or more target patterns comprise one or more target patterns associated with one or more known defect types. The defect detection system of claim 1, wherein the one or more target patterns comprise one or more target patterns identified by a previous defect detection program. The defect detecting system of claim 1, wherein determining the one or more target patterns comprises: determining the one or more target patterns by a user. The defect detection system of claim 12, wherein the determining, by the user, the one or more target patterns comprises: selecting one or more of the one or more target patterns from the design material of the sample. The defect detection system of claim 13, wherein the one or more instances of selecting the one or more target patterns from the design material of the sample comprises: selecting the one or one visual display from the design material of the sample The one or more instances of the plurality of target patterns. The defect detecting system of claim 1, wherein determining the one or more target patterns comprises: providing one or more associated with one or more of the one or more target patterns in the design material of the sample Coordinates. The defect detection system of claim 15 wherein the one or more coordinates associated with the one or more instances of the one or more target patterns within the design material of the sample comprises: providing the one or more A graphical data system coordinate of the one or more instances of the plurality of target patterns. The defect detecting system of claim 1, wherein the detecting system is a virtual detecting system. The defect detection system of claim 1, wherein the design data comprises: at least one of a physical layout of one of the samples or an electrical layout of the sample. The defect detection system of claim 1, further comprising: providing the one or more care areas for use in a subsequent detection procedure. The defect detection system of claim 1, further comprising: classifying one or more identified defects based on the design data of the sample. The defect detecting system of claim 1, wherein the illumination beam comprises: at least one of a photon beam or a particle beam. The defect detecting system of claim 21, wherein the particle beam comprises: at least one of an electron beam or an ion beam. The defect detection system of claim 1, wherein the set of illumination optics comprises at least one of photonic optics or particle optics. The defect detection system of claim 1, wherein the detector comprises: at least one of a photon detector or a particle detector. The defect detection system of claim 1, wherein the controller is positioned proximate to the optical subsystem. The defect detection system of claim 1, wherein the controller and at least a portion of the optical subsystem are positioned within a common housing. A defect detection system comprising: a detection subsystem comprising: an illumination source configured to generate an illumination beam; a set of illumination optics that directs the illumination beam to the same; and a detection And configured to collect illumination from the sample; and a controller communicatively coupled to the detector, the controller including a memory device and configured to execute one or more of the program instructions A processor, the program instructions configured to cause the one or more processors: Determining one or more target patterns corresponding to one or more features on the sample; determining a source pattern, wherein the source pattern is adjacent to one of the one or more target patterns in the design data of the sample The set, wherein the design data of the sample is stored in the memory device of the controller; the subset of the instance of the one or more target patterns defining the source pattern and the design data of the sample a spatial relationship between the at least one target pattern; identifying one or more of the source patterns in the design material of the sample; the one or more identified instances based on the source pattern and the source pattern and The spatial relationship between the at least one target pattern of the subset of the one or more target patterns identifying the subset of the one or more target patterns in the design data of the sample Defining one or more care areas on the sample based on the subset of the one or more target patterns; identifying the one or more of the samples based on the illumination collected by the detector One or more defects in the care area . A defect detecting method includes: providing the same design data to a detecting system; determining one or more target patterns, wherein the one or more target patterns include a design associated with one or more sample features to be detected Information; defining, by the detection system, one or more care areas on the sample based on the one or more target patterns and the design data of the sample; and identifying one of the one or more care areas of the sample Or multiple defects. The defect detection method of claim 28, wherein the one or more care areas on the sample are defined to include: Identifying one or more of the one or more target patterns in the design material of the sample. The defect detection method of claim 29, wherein the one or more instances of the target patterns in the design data identifying the sample comprise: determining a source pattern, wherein the source pattern is within the design data of the sample a subset of the one or more target patterns; defining between the source pattern and the at least one target pattern of the subset of the one or more target patterns in the design material of the sample a spatial relationship; identifying one or more instances of the source pattern in the design material of the sample; and the one or more identified instances based on the source pattern and the design of the source pattern and the sample The spatial relationship between the at least one target pattern of the subset of the one or more target patterns in the data identifies the subset of the instance of the one or more target patterns. The defect detection method of claim 29, further comprising: pre-processing the design data of the sample to facilitate identifying the one or more instances of the one or more target patterns within the design data of the sample. The defect detecting method of claim 29, wherein the one or more instances of the one or more target patterns in the design data identifying the sample comprise: one or more instances of the one or more target patterns The item searches the design data to generate one or more identified instances of the target pattern. The defect detection method of claim 32, further comprising: calculating one of a similarity between the one or more target patterns and the one or more identified instances of the one or more target patterns Or multiple credibility scores. The defect detection method of claim 28, wherein the one or more care areas on the sample are defined to include: Defining one or more target regions, wherein the one or more target regions comprise at least one instance of at least one target pattern of the one or more target patterns, wherein the care regions comprise the one or more target regions. The defect detecting method of claim 34, wherein detecting the one or more care areas of the sample for the defect comprises: detecting the one or more target areas, wherein one of the one or more target areas can be individually adjusted for detection sensitivity . The defect detection method of claim 28, wherein the one or more target patterns comprise: one or more target patterns identified by at least one of a design-based classification or a design-based parallel image program. The defect detection method of claim 28, wherein the one or more target patterns comprise one or more target patterns associated with one or more known defect types. The defect detecting method of claim 28, wherein the one or more target patterns comprise: one or more target patterns identified by a previous defect detecting program. The defect detecting method of claim 28, wherein determining the one or more target patterns comprises: determining the one or more target patterns by a user. The defect detecting method of claim 39, wherein determining, by the user, the one or more target patterns comprises: selecting one or more of the one or more target patterns from the design material of the sample. The defect detecting method of claim 40, wherein the one or more instances of selecting the one or more target patterns from the design material of the sample comprises: selecting the one or one visual display from the design material of the sample One or more instances of multiple target patterns. The defect detecting method of claim 28, wherein the one or more target pattern packages are determined Included: providing one or more coordinates associated with one or more of the one or more target patterns within the design material of the sample. The defect detection method of claim 42, wherein the one or more coordinates associated with the one or more instances of the one or more target patterns in the design material of the sample comprises: providing the one or more A graphical data system coordinate of the one or more instances of the plurality of target patterns. The defect detecting method of claim 28, wherein the detecting system is a virtual detecting system. The defect detection method of claim 28, wherein the design material comprises: at least one of a physical layout of one of the samples or an electrical layout of the sample. The defect detection method of claim 28, further comprising: providing the one or more care areas for use in a subsequent detection procedure. The defect detection method of claim 28, further comprising: classifying the one or more identified defects based on the design data of the sample.