In any plasma etch process, there are slight variations in the output of generators, mass
flows, and pressure control systems that may sometimes contribute to run-to-run
differences in the final product. Even excluding material differences, endpoint times can
vary somewhat, requiring an accurate endpoint system to stop processing at the
appropriate time. The most widely accepted systems for plasma endpoint detection are
based on optical emission spectroscopy (OES). OES-based endpoint systems analyze the
visible and near-visible electromagnetic radiation emitted by the plasma in order to detect
subtle changes that occur when a film has been completely etched. A signal can be
constructed from this data and used to stop or otherwise modify the process.
Other methods exist for detecting endpoint. Laser reflectance is well known to
photomask etch engineers, but there are also lesser known methods that depend on
detecting changes in pressure, DC bias, or match network positions.
Each system has its own unique set of strengths and weaknesses. While all of these
systems are quite capable of detecting endpoint under normal circumstances, the
requirements of low load photomask etching are extremely demanding. Therefore, a
need exists to enhance endpoint detection on low load photomasks. Our proposed
method is a multi-sensor system that includes measurements of several process
parameters in addition to emission spectra to generate an endpoint signal that is more
robust than an endpoint signal produced by a single sensor.