Abstract: This disclosure is directed to solutions of detecting and classifying wafer defects using machine learning techniques. The solutions take only one coarse resolution digital microscope image of a target wafer, and use machine learning techniques to process the coarse SEM image to review and classify a defect on the target wafer. Because only one coarse SEM image of the wafer is needed, the defect review and classification throughput and efficiency are improved. Further, the techniques are not distractive and may be integrated with other defect detecting and classification techniques.

Abstract: A semiconductor wafer defect detection system captures test images of a semiconductor wafer. The system analyzes the test images with an analysis model trained with a machine learning process. The analysis model generates simulated integrated circuit layouts based on the test images. The system detects defects in the semiconductor wafer by comparing the simulated integrated circuit layouts to reference integrated circuit layouts.

Abstract: A process tube device can detect the presence of any external materials that may reside within a fluid flowing in the tube. The process tube device detects the external materials in-situ which obviates the need for a separate inspection device to inspect the surface of a wafer after applying fluid on the surface of the wafer. The process tube device utilizes at least two methods of detecting the presence of external materials. The first is the direct measurement method in which a light detecting sensor is used. The second is the indirect measurement method in which a sensor utilizing the principles of Doppler shift is used. Here, contrary to the first method that at least partially used reflected or refracted light, the second method uses a Doppler shift sensor to detect the presence of the external material by measuring the velocity of the fluid flowing in the tube.

Abstract: Some implementations described herein provide techniques and apparatuses for a semiconductor processing tool including an electrostatic chuck having a voltage-regulation system to regulate an electrical potential throughout regions of a semiconductor substrate positioned above the electrostatic chuck. The voltage-regulation system may determine that an electrical potential within a region of the semiconductor substrate does not satisfy a threshold. The voltage-regulation system may, based on determining that the electrical potential throughout the region does not satisfy the threshold, position one or more electrically-conductive pins within the region. While positioned within the region, the one or more electrically-conductive pins may change the electrical potential of the region.

Abstract: A semiconductor wafer defect detection system captures test images of a semiconductor wafer. The system analyzes the test images with an analysis model trained with a machine learning process. The analysis model generates simulated integrated circuit layouts based on the test images. The system detects defects in the semiconductor wafer by comparing the simulated integrated circuit layouts to reference integrated circuit layouts.

Abstract: In a method of inspection of a semiconductor substrate a first beam of light is split into two or more second beams of light. The two or more second beams of light are respectively transmitted onto a first set of two or more first locations on top of the semiconductor substrate. In response to the transmitted two or more second beams of light, two or more reflected beams of light from the first set of two or more first locations are received. The received two or more reflected beams of light are detected to generate two or more detected signals. The two or more detected signals are analyzed to determine whether a defect exists at the set of the two or more first locations.

Abstract: Some implementations described herein provide techniques and apparatuses for a semiconductor processing tool including an electrostatic chuck having a voltage-regulation system to regulate an electrical potential throughout regions of a semiconductor substrate positioned above the electrostatic chuck. The voltage-regulation system may determine that an electrical potential within a region of the semiconductor substrate does not satisfy a threshold. The voltage-regulation system may, based on determining that the electrical potential throughout the region does not satisfy the threshold, position one or more electrically-conductive pins within the region. While positioned within the region, the one or more electrically-conductive pins may change the electrical potential of the region.

Abstract: In a method of inspection of a semiconductor substrate a first beam of light is split into two or more second beams of light. The two or more second beams of light are respectively transmitted onto a first set of two or more first locations on top of the semiconductor substrate. In response to the transmitted two or more second beams of light, two or more reflected beams of light from the first set of two or more first locations are received. The received two or more reflected beams of light are detected to generate two or more detected signals. The two or more detected signals are analyzed to determine whether a defect exists at the set of the two or more first locations.

Abstract: Some implementations described herein provide techniques and apparatuses for a semiconductor processing tool including an electrostatic chuck having a voltage-regulation system to regulate an electrical potential throughout regions of a semiconductor substrate positioned above the electrostatic chuck. The voltage-regulation system may determine that an electrical potential within a region of the semiconductor substrate does not satisfy a threshold. The voltage-regulation system may, based on determining that the electrical potential throughout the region does not satisfy the threshold, position one or more electrically-conductive pins within the region. While positioned within the region, the one or more electrically-conductive pins may change the electrical potential of the region.

Abstract: A process tube device can detect the presence of any external materials that may reside within a fluid flowing in the tube. The process tube device detects the external materials in-situ which obviates the need for a separate inspection device to inspect the surface of a wafer after applying fluid on the surface of the wafer. The process tube device utilizes at least two methods of detecting the presence of external materials. The first is the direct measurement method in which a light detecting sensor is used. The second is the indirect measurement method in which a sensor utilizing the principles of Doppler shift is used. Here, contrary to the first method that at least partially used reflected or refracted light, the second method uses a Doppler shift sensor to detect the presence of the external material by measuring the velocity of the fluid flowing in the tube.

Abstract: In a method of inspection of a semiconductor substrate a first beam of light is split into two or more second beams of light. The two or more second beams of light are respectively transmitted onto a first set of two or more first locations on top of the semiconductor substrate. In response to the transmitted two or more second beams of light, two or more reflected beams of light from the first set of two or more first locations are received. The received two or more reflected beams of light are detected to generate two or more detected signals. The two or more detected signals are analyzed to determine whether a defect exists at the set of the two or more first locations.

Abstract: An apparatus for inspecting a semiconductor substrate includes a rotatable base configured to support a substrate, and a nozzle arm includes a nozzle and a light monitoring device. The light monitoring device includes a laser transmitter and an array of light sensors arranged in the nozzle arm and facing the substrate. The light monitoring device is configured to transmit a laser pulse towards the substrate, wherein the laser pulse impinges on the substrate, receive a reflected laser pulse from the substrate, calculate whether one or more light sensors received the laser pulse, and calculate a distance between the light monitoring device and the substrate using the turnaround time for determining a process quality on the substrate.

Abstract: Methods and systems for diagnosing a semiconductor wafer are provided. A plurality of raw images are captured with a tilt angle from the semiconductor wafer according to graphic data system (GDS) information regarding a layout of a target die, by an inspection apparatus. A first image-based comparison is performed on the plurality of raw images, by a determining circuitry, to obtain a defect image in the plurality of raw images. A second image-based comparison is performed on a reference image and the defect image, so as to classify a defect type of an image difference in the defect image, by the determining circuitry. The number of the plurality of raw images is greater than 2.

Abstract: This disclosure is directed to solutions of detecting and classifying wafer defects using machine learning techniques. The solutions take only one coarse resolution digital microscope image of a target wafer, and use machine learning techniques to process the coarse SEM image to review and classify a defect on the target wafer. Because only one coarse SEM image of the wafer is needed, the defect review and classification throughput and efficiency are improved. Further, the techniques are not distractive and may be integrated with other defect detecting and classification techniques.

Abstract: Methods and systems for diagnosing a semiconductor wafer are provided. A plurality of raw images of the semiconductor wafer are obtained according to GDS information regarding a layout of a target die, by an inspection apparatus. A first image-based comparison is performed on the raw images, so as to provide a comparison result, by a determining circuitry. The comparison result indicates whether an image difference is present between the images. One of the raw images having the image difference is assigned as a defect image. A second image-based comparison is performed on a reference image and the defect image, so as to classify a defect type of the image difference, by the determining circuitry. The layout of the target die includes a circuit with a duplicate layout formed by a plurality of same cells. The number of the plurality of raw images is greater than 2.

Abstract: A method of manufacturing a semiconductor device includes: receiving a workpiece on which the semiconductor device is manufactured; causing a nozzle to dispense a fluid toward a surface of the workpiece external to the nozzle, wherein the nozzle includes a first channel and a second channel that allow the fluid to flow through; emitting light, by a light source, from within the nozzle toward the surface while the nozzle is dispensing the fluid; receiving light reflected from the surface by a light sensor, the light source and the light sensor being disposed within the nozzle and opposite to each other, and the emitted light and the reflected light adapted to be contained within the fluid; and examining a status of the reflected light. The emitted light and the reflected light propagate in a direction parallel to a longitudinal axis of each of the first channel and the second channel.

Abstract: This disclosure is directed to solutions of detecting and classifying wafer defects using machine learning techniques. The solutions take only one coarse resolution digital microscope image of a target wafer, and use machine learning techniques to process the coarse SEM image to review and classify a defect on the target wafer. Because only one coarse SEM image of the wafer is needed, the defect review and classification throughput and efficiency are improved. Further, the techniques are not distractive and may be integrated with other defect detecting and classification techniques.

Abstract: A method of monitoring a fluid includes: applying the fluid from within a nozzle to a surface of a wafer outside of the nozzle; emitting light, by a light source, from the nozzle to the surface; receiving light reflected from the surface by a light sensor and causing the reflected light to propagate into the nozzle; and determining whether a variation of the fluid occurs according to the reflected light.

Abstract: Methods for enhancing a surface topography of a structure formed on a substrate are provided. In one example, the method includes performing a polishing process on a substrate having a shallow trench isolation structure and a diffusion region, performing a surface topography enhancing process to enlarge a defect in at least one of the shallow trench isolation structure and the diffusion region, inspecting at least one of the shallow trench isolation structure and the diffusion region to detect the enlarged defect, and adjusting a parameter of the polishing process in response to detecting the enlarged defect.

Abstract: A method includes disposing a semiconductor substrate over a chuck. The chuck has a plurality of holes therein. The semiconductor substrate has a first surface facing the chuck and a second surface opposite thereto. A liquid layer is formed flowing over a top surface of the chuck by supplying liquid to the top surface of the chuck through the holes of the chuck. The semiconductor substrate is moved toward the chuck such that the first surface of the semiconductor substrate is in contact with the liquid layer and the liquid layer flows between the first surface of the semiconductor substrate and the top surface of the chuck.