Hl. Maynard et al., PLASMA-ETCHING ENDPOINTING BY MONITORING RADIOFREQUENCY POWER-SYSTEMSWITH AN ARTIFICIAL NEURAL-NETWORK, Journal of the Electrochemical Society, 143(6), 1996, pp. 2029-2035
We demonstrate that the endpoint of an etching process can be determin
ed by monitoring only values in the plasma tool's radio-frequency (RF)
power system, the reflected power from the plasma source and wafer pl
aten power supplies, capacitor values in the RF matchboxes, and the de
bias. This is a systems approach that views the wafer as part of the
electrical circuit. As the films on the wafer etch away, the effective
impedance of both the wafer and the plasma changes. The state of the
RF system is fed into the endpointing system, and the impedance change
marks the endpoint. The artificial neural network was trained using e
ndpoints called by an operator monitoring the etching with an in situ
ellipsometer. The neural network was trained and tested on 51 wafers,
and proved to be as accurate as the operator in calling endpoint. The
particular example discussed in this paper finds the TiN endpoint duri
ng the etching of 0.25 mu m TiN-polysilicon gate stacks in a Lucas Lab
s helicon high-density plasma etcher. Problems encountered while devel
oping the network are discussed, as are some of the limitations of neu
ral networks.