Systems and methods are described for determining whether liquid remains on a wafer surface following a scanning operation. A system embodiment includes, but is not limited to, a first system configured for positioning adjacent a transfer line coupled with a scanning nozzle to dispense fluid onto a wafer surface and to recover the fluid from the wafer surface, the first system configured to detect a gas/liquid transition of the fluid and determine a volume of liquid sample dispensed; a second system configured for positioning adjacent a second line downstream from the scanning nozzle, the second system configured to detect a gas/liquid transition of fluid flowing through the second line and determine a volume of liquid sample recovered from the wafer surface; and a controller configured to generate an alert if the volume of liquid sample recovered is not within a threshold amount compared to the volume of liquid sample dispensed.

A method includes patterning a hard mask over a target layer, capturing a low resolution image of the hard mask, and enhancing the low resolution image of the hard mask with a first machine learning model to produce an enhanced image of the hard mask. The method further includes analyzing the enhanced image of the hard mask with a second machine learning model to determine whether the target layer has defects.

A thickness estimating apparatus includes a transfer robot, a light source, a camera, a memory and a controller. The memory stores a thickness predicting model generated based on a data set including a thickness of at least one of a test wafer corresponding to the wafer or a test element layer formed on the test wafer, and the thickness predicting model being trained to minimize a loss function of the data set. The controller applies pixel data, which is acquired from at least one pixel selected from a plurality of pixels included in a captured image, to the thickness predicting model, to predict a thickness of at least one of the wafer or an element layer formed on the wafer in a position corresponding to a position of the selected pixel.

One example of an inspection system includes a laser, a magnification changer, and a first camera. The laser projects a line onto a wafer to be inspected. The magnification changer includes a plurality of selectable lenses of different magnification. The first camera images the line projected onto the wafer and outputs three-dimensional line data indicating the height of features of the wafer. Each lens of the magnification changer provides the same nominal focal plane position of the first camera with respect to the wafer.

Methods and systems for controlling pressure in a cavity of a light source are provided. One system includes a barometric pressure sensor configured for measuring pressure in a cavity of a light source. The system also includes one or more gas flow elements configured for controlling an amount of one or more gases in the cavity. In addition, the system includes a control subsystem configured for comparing the measured pressure to a predetermined range of values for the pressure and, when the measured pressure is outside of the predetermined range, altering a parameter of at least one of the one or more gas flow elements based on results of the comparing.

In a side view, when an angle θ1 formed between the light axis of light incident on a surface of a silicon wafer and the surface (or an imaginary plane corresponding to the surface) is 67° to 78° and an angle formed between the surface of the silicon wafer (or an imaginary plane corresponding to the surface) and the detection optical axis of a photodetector is θ2, θ1−θ2 is −6° to −1° or 1° to 6°.

An inspecting apparatus includes a table for supporting a workpiece thereon, a light applying unit for applying light to the workpiece supported on the table, and a light detector for detecting light reflected from the workpiece. The light detector includes a camera and a diffusion plate disposed between the table and the camera.

In a processing apparatus, a vibration detecting unit includes a light source, an interference unit configured to apply light emitted from the light source to a measurement target member and generate an interference pattern image. A control unit includes a storage section configured to store a first interference pattern image captured at a predetermined timing by the imaging unit and a second interference pattern image captured at a timing different from the timing of the first interference pattern image by the imaging unit, a comparing section configured to compare the first interference pattern image and the second interference pattern image stored in the storage section with each other, and a vibration detecting section configured to detect vibration on the basis of the first interference pattern image and the second interference pattern image compared with each other by the comparing section.

Measurement cavities described herein include a cylindrical chamber having a first open end and a second open end; a first cap covering the first open end of the cylindrical chamber and a second cap covering the second open end of the cylindrical chamber, wherein the first and second caps hermetically seal the cylindrical chamber and wherein the first cap is rigidly coupled to the second cap; and a wafer holder positioned within and coupled to the cylindrical chamber. The measurement cavity has a mass m, a stiffness k, and a damping constant c configured such that the transmissibility $.Math.\frac{x}{F}.Math.$
of an input force at 60 Hz in the measurement cavity is reduced by a factor of at least 10 and the measurement cavity has a natural frequency of greater than 300 Hz.

A reticle inspection system may include two or more inspection tools to generate two or more sets of inspection images for characterizing a reticle, where the two or more inspection tools include at least one reticle inspection tool providing inspection images of the reticle. The reticle inspection system may further include a controller to correlate data from the two or more sets of inspection images to positions on the reticle, detect one or more defects of interest on the reticle with the correlated data as inputs to a multi-input defect detection model, and output defect data associated with the defects of interest.