927 research outputs found
Virtual metrology for plasma etch processes.
Plasma processes can present dicult control challenges due to time-varying dynamics
and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the
use of mathematical models with accessible measurements from an operating process to
estimate variables of interest. This thesis addresses the challenge of virtual metrology
for plasma processes, with a particular focus on semiconductor plasma etch.
Introductory material covering the essentials of plasma physics, plasma etching, plasma
measurement techniques, and black-box modelling techniques is rst presented for readers
not familiar with these subjects. A comprehensive literature review is then completed
to detail the state of the art in modelling and VM research for plasma etch processes.
To demonstrate the versatility of VM, a temperature monitoring system utilising a
state-space model and Luenberger observer is designed for the variable specic impulse
magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The
temperature monitoring system uses optical emission spectroscopy (OES) measurements
from the VASIMR engine plasma to correct temperature estimates in the presence of
modelling error and inaccurate initial conditions. Temperature estimates within 2% of
the real values are achieved using this scheme.
An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate
plasma etch rate for an industrial plasma etch process is presented. The VM
models estimate etch rate using measurements from the processing tool and a plasma
impedance monitor (PIM). A selection of modelling techniques are considered for VM
modelling, and Gaussian process regression (GPR) is applied for the rst time for VM
of plasma etch rate. Models with global and local scope are compared, and modelling
schemes that attempt to cater for the etch process dynamics are proposed. GPR-based
windowed models produce the most accurate estimates, achieving mean absolute percentage
errors (MAPEs) of approximately 1:15%. The consistency of the results presented
suggests that this level of accuracy represents the best accuracy achievable for
the plasma etch system at the current frequency of metrology.
Finally, a real-time VM and model predictive control (MPC) scheme for control of
plasma electron density in an industrial etch chamber is designed and tested. The VM
scheme uses PIM measurements to estimate electron density in real time. A predictive
functional control (PFC) scheme is implemented to cater for a time delay in the VM
system. The controller achieves time constants of less than one second, no overshoot,
and excellent disturbance rejection properties. The PFC scheme is further expanded by
adapting the internal model in the controller in real time in response to changes in the
process operating point
Virtual metrology for plasma etch processes.
Plasma processes can present dicult control challenges due to time-varying dynamics
and a lack of relevant and/or regular measurements. Virtual metrology (VM) is the
use of mathematical models with accessible measurements from an operating process to
estimate variables of interest. This thesis addresses the challenge of virtual metrology
for plasma processes, with a particular focus on semiconductor plasma etch.
Introductory material covering the essentials of plasma physics, plasma etching, plasma
measurement techniques, and black-box modelling techniques is rst presented for readers
not familiar with these subjects. A comprehensive literature review is then completed
to detail the state of the art in modelling and VM research for plasma etch processes.
To demonstrate the versatility of VM, a temperature monitoring system utilising a
state-space model and Luenberger observer is designed for the variable specic impulse
magnetoplasma rocket (VASIMR) engine, a plasma-based space propulsion system. The
temperature monitoring system uses optical emission spectroscopy (OES) measurements
from the VASIMR engine plasma to correct temperature estimates in the presence of
modelling error and inaccurate initial conditions. Temperature estimates within 2% of
the real values are achieved using this scheme.
An extensive examination of the implementation of a wafer-to-wafer VM scheme to estimate
plasma etch rate for an industrial plasma etch process is presented. The VM
models estimate etch rate using measurements from the processing tool and a plasma
impedance monitor (PIM). A selection of modelling techniques are considered for VM
modelling, and Gaussian process regression (GPR) is applied for the rst time for VM
of plasma etch rate. Models with global and local scope are compared, and modelling
schemes that attempt to cater for the etch process dynamics are proposed. GPR-based
windowed models produce the most accurate estimates, achieving mean absolute percentage
errors (MAPEs) of approximately 1:15%. The consistency of the results presented
suggests that this level of accuracy represents the best accuracy achievable for
the plasma etch system at the current frequency of metrology.
Finally, a real-time VM and model predictive control (MPC) scheme for control of
plasma electron density in an industrial etch chamber is designed and tested. The VM
scheme uses PIM measurements to estimate electron density in real time. A predictive
functional control (PFC) scheme is implemented to cater for a time delay in the VM
system. The controller achieves time constants of less than one second, no overshoot,
and excellent disturbance rejection properties. The PFC scheme is further expanded by
adapting the internal model in the controller in real time in response to changes in the
process operating point
Queering the classroom: a study of performativity and musical engagement in high school
Creating inclusive environments that are safe and respectful of all students in the spectrum is paramount to students’ success and well-being in music (Carter, 2011). When students feel safe and supported, they may express themselves more freely and participate in music more fully (Hill, 2019). Yet, freedom to express oneself is inhibited by heteronormative beliefs and practices that perpetuate gender stereotypes, suppress queer thinking, and form the origins of homophobia and transphobia (Butler, 2004; Sedgwick, 1990/2008; Warner, 1993). This study featured a narrative inquiry design which utilized the lens of queer theory and Butler’s (1990/1999) concept of gender performativity to examine high school musical engagement through the recollections and perceptions of three trans young adults. The purpose of this study was to explore ways that gender and music intersect in high school, as well as illuminate behaviors that constrained or enabled the participants’ abilities to participate fully in school music. Data was gathered through interviews with the participants during which they recounted past musical experiences in school, family, and community contexts. Findings from a comparative analysis revealed eight areas that were crucial to the participants’ affirmation of identity and musical engagement: supportive people, singing alone and with others, negotiating traditions, meaningful performing experiences, safe spaces and safe people, role of media, personal agency, and role of the music teacher. This study contributes to a growing body of music education research rooted in queer theory that dismantles the binary gender categories of “male” and “female” and, instead, considers the entire spectrum of gender. Results of this study may help educators remove barriers between gender identity and musical engagement by informing practice that opens channels for learning and builds stronger connections to music
Gaussian Process Regression for Virtual Metrology of Plasma Etch
Plasma etch is a complex semiconductor manufacturing process in which
material is removed from the surface of a silicon wafer using a gas in plasma form.
As the process etch rate cannot be measured easily during or after processing, virtual
metrology is employed to predict the etch rate instantly using ancillary process variables.
Virtual metrology is the prediction of metrology variables using other easily accessible
variables and mathematical models. This paper investigates the use of Gaussian process
regression as a virtual metrology modelling technique for plasma etch data
Real-time virtual metrology and control for plasma etch
Plasma etch is a semiconductor manufacturing process during which material is removed from the surface
of semiconducting wafers, typically made of silicon, using gases in plasma form. A host of chemical
and electrical complexities make the etch process notoriously difficult to model and troublesome to
control. This work demonstrates the use of a real-time model predictive control scheme to control plasma
electron density and plasma etch rate in the presence of disturbances to the ground path of the chamber.
Virtual metrology (VM) models, using plasma impedance measurements, are used to estimate the plasma
electron density and plasma etch rate in real time for control, eliminating the requirement for invasive
measurements. The virtual metrology and control schemes exhibit fast set-point tracking and disturbance
rejection capabilities. Etch rate can be controlled to within 1% of the desired value. Such control represents
a significant improvement over open-loop operation of etch tools, where variances in etch rate of up to
5% can be observed during production processes due to disturbances in tool state and material properties
Global and Local Virtual Metrology Models for a Plasma Etch Process
Virtual metrology (VM) is the estimation of metrology
variables that may be expensive or difficult to measure using
readily available process information. This paper investigates the
application of global and local VM schemes to a data set recorded
from an industrial plasma etch chamber. Windowed VM models
are shown to be the most accurate local VM scheme, capable
of producing useful estimates of plasma etch rates over multiple
chamber maintenance events and many thousands of wafers. Partial
least-squares regression, artificial neural networks, and Gaussian
process regression are investigated as candidate modeling
techniques, with windowed Gaussian process regression models
providing the most accurate results for the data set investigated
Electrochemiluminescence (ECL) sensing properties of water soluble core-shell CdSe/ZnS quantum dots/Nafion composite films
Water soluble positively charged 2-(dimethylamino) ethanethiol (DAET)-protected core-shell CdSe/ZnS quantum dots (QDs) were synthesized and incorporated within negatively charged Nafion polymer films. The water soluble QDs were characterized using UV-visible and fluorescence spectroscopies. Nafion/QDs composite films were deposited on glassy carbon electrodes and characterized using cyclic voltammetry. The electrochemiluminescence (ECL) using hydrogen peroxide as co-reactant was enhanced for Nafion/QDs composite films compared to films of the bare QDs. Significantly, no ECL was observed for Nafion/QDs composite films when peroxydisulfate was used as the co-reactant, suggesting that the permselective properties of the Nafion effectively exclude the co-reactant. The ECL quenching by glutathione depends linearly on its concentration when hydrogen peroxide is used as the co-reactant, opening up the possibility to use Nafion/QDs composite films for various electroanalytical applications
State Estimation for the VASIMR Plasma Engine
This paper presents work on the application of virtual metrology techniques to the VAriable Specific Impulse Magnetoplasma Rocket (VASMIR) engine. The work concentrates on the estimation of internal temperatures of the rocket using state space models and Optical Emission Spectroscopy (OES). These estimations are useful as direct thermal measurements will not be available in the final system design
Temperature Estimation for a Plasma-Propelled Rocket Engine
The VASIMR propulsion system is an ion propulsion system for spacecraft that uses magnetic fields to accelerate plasma to produce thrust. Undesired heat produced in the helicon section of VASIMR must be monitored and removed safely to avoid damage to system components, especially when higher power operating regimes are explored. This article demonstrates a strategy for distributed temperature estimation, based on OES measurement, and a model where the states represent the distributed temperature profile. OES provides a noninvasive measurement technique, which can be used as an output "correction" term for a state-estimation scheme. In this application, it is shown that the 2048 OES channels recorded can be accurately represented by only three principal components for temperature estimation. Use of the principal components as corrector terms in the state-space model dramatically improve model accuracy and the capability of the model to recover from unknown initial conditions and multiple system input changes
Nano-Imprinted Thin Films of Reactive, Azlactone-Containing Polymers: Combining Methods for the Topographic Patterning of Cell Substrates with Opportunities for Facile Post-Fabrication Chemical Functionalization
Laser scanning confocal microscopy (LSCM) and atomic force microscopy (AFM) were used to characterize changes in nanoscale structure that occur when ultrathin polyelectrolyte multilayers (PEMs) are incubated in aqueous media. The PEMs investigated here were fabricated by the deposition of alternating layers of plasmid DNA and a hydrolytically degradable polyamine onto a precursor film composed of alternating layers of linear poly(ethylene imine) (LPEI) and sodium poly(styrene sulfonate) (SPS). Past studies of these materials in the context of gene delivery revealed transformations from a morphology that is smooth and uniform to one characterized by the formation of nanometer-scale particulate structures. We demonstrate that in-plane registration of LSCM and AFM images acquired from the same locations of films fabricated using fluorescently labeled polyelectrolytes allows the spatial distribution of individual polyelectrolyte species to be determined relative to the locations of topographic features that form during this transformation. Our results suggest that this physical transformation leads to a morphology consisting of a relatively less disturbed portion of film composed of polyamine and DNA juxtaposed over an array of particulate structures composed predominantly of LPEI and SPS. Characterization by scanning electron microscopy and energy-dispersive X-ray microanalysis provides additional support for this interpretation. The combination of these different microscopy techniques provides insight into the structures and dynamics of these multicomponent thin films that cannot be achieved using any one method alone, and could prove useful for the further development of these assemblies as platforms for the surface-mediated delivery of DNA
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