Abstract: Embodiments disclosed herein include a method of monitoring a photoresist deposition process. In an embodiment, the method comprises depositing a photoresist layer to a first thickness over a substrate, measuring a property of the photoresist layer with a first electromagnetic (EM) radiation source, depositing the photoresist layer to a second thickness over the substrate, and measuring the property of the photoresist layer with the first EM radiation source.

Abstract: Embodiments disclosed herein include a method of optimizing a post deposition bake of a photoresist layer. In an embodiment, the method comprises depositing the photoresist layer on a substrate, baking the photoresist layer, and measuring properties of the photoresist layer with an optical tool.

Abstract: Embodiments of the present disclosure generally relate to methods for providing real-time characterization of photoresist properties. In some embodiments, a method of preparing a patterned photoresist on a substrate includes forming an unpatterned photoresist on the substrate, exposing the unpatterned photoresist to a first dose of EM radiation at a first location on the unpatterned photoresist with a first light source, and measuring an optical property of the unpatterned photoresist and exposing the unpatterned photoresist to a second dose of EM radiation at the first location on the unpatterned photoresist to create a patterned or partially patterned photoresist. The second dose of EM radiation has a greater wavelength, a greater number of pulses, or a longer exposure period than the first dose of EM radiation with a second light source. Also, at least one of the first light source and the second light source is an on-board metrology device.

Abstract: One embodiment disclosed relates to a method for accurate electron beam metrology. A substrate with a target feature is loaded into a scanning electron microscope. An electron beam is scanned over the target feature, and scattered electrons are detected therefrom. A characteristic of the target feature is measured by finding optimal values for parameters of a mathematical model which accounts for substrate charging effects. Principal component analysis may be used to advantageously result in reduced requirements for processing time and/or computational speed.