Abstract:
One or more first parameters associated with an electronic device manufacturing process are monitored. An artificial neural network associated with the one or more first parameters is determined. One or more second parameters are determined using the artificial neural network. The one or more first parameters are adjusted using the one or more second parameters.
Abstract:
Methods for reducing line width roughness and/or critical dimension nonuniformity in a photoresist pattern are provided herein. In some embodiments, a method of reducing line width roughness along a sidewall of a patterned photoresist layer disposed atop a substrate includes: (a) depositing a first layer atop the sidewall of the patterned photoresist layer; (b) etching the first layer and the sidewall after depositing the first layer to reduce the line width roughness of the patterned photoresist layer. In some embodiments, (a)-(b) may be repeated until the line width roughness is substantially smooth.
Abstract:
Methods for reducing the line width roughness on a photoresist pattern are provided herein. In some embodiments, a method of processing a patterned photoresist layer disposed atop a substrate includes flowing a process gas into a processing volume of a process chamber having the substrate disposed therein; forming a plasma within the process chamber from the process gas, wherein the plasma has a ion energy of about 1 eV to about 10 eV; and etching the patterned photoresist layer with species from the plasma to at least one of smooth a line width roughness of a sidewall of the patterned photoresist layer or remove debris.