Macquarie University
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Circuit-based monitoring of high-performance semiconductor manufacturing processes

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posted on 2022-03-28, 12:32 authored by Evgeny Kuxa
The conventional process of semiconductor manufacturing is done by testing the electrical properties of the structures and devices which comprise the process control monitor, or PCM. Being useful at spotting process fluctuations over long periods of time, the PCM poorly predicts the nonlinear behaviour of the real circuits. This means that good PCM measurement results do not guarantee the expected performance of the functional circuits. An augmented PCM is proposed which uses a simple circuit to relate process variation to nonlinear circuit performance. The suggested circuit control monitor, or CCM, is a nonlinear circuit whose signal can be related to the state of the manufacturing process. It is expected that the correlation between the CCMs' and functional nonlinear circuits' performance would be stronger. A chaotic Chua's oscillator-based CCM is designed. It is implemented using the GaAs pHEMT manufacturing process which required developing a new version of the circuit's nonlinear element. The circuit equations suggested that the individual oscillator signals contain the features in the form of equilibrium levels which can indicate the state of the process. A computer algorithm is implemented as an analysis tool to retrieve the chaotic features of the measured circuit data. It is found that equilibrium levels uctuate across the wafer and are closely correlated with both, the PCM parameters and the nonlinear parameters of the functional circuits. Overall, the results are regarded as satisfactory and the viability of the CCM approach is demonstrated.


Table of Contents

1. Introduction -- 2. Overview -- 3.Chua's circuit analysis -- 4. Chua's circuit prototyping -- 5. Integrated design of the CCM -- 6. CCM testing -- 7. CCM correlation with PCM -- 8. CCM and nonlinear circuits -- 9. Conclusions.


Bibliography: pages 185-196 Empirical thesis.

Awarding Institution

Macquarie University

Degree Type

Thesis PhD


PhD, Macquarie University, Faculty of Science and Engineering, Department of Engineering

Department, Centre or School

Department of Engineering

Year of Award


Principal Supervisor

Michael Heimlich

Additional Supervisor 1

Anthony Parker


Copyright Evgeny Kuxa 2015. Copyright disclaimer:




1 online resource (xxiv, 196) illustrations (some colour)

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