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- Title
- EFFECTS OF DEPOSITION TEMPERATURE AND POST DEPOSITION ANNEALING ON THE ELECTRICAL PROPERTIES OF BARIUM STRONTIUM TITANATE THIN FILM FOR EMBEDDED CAPACITOR APPLICATIONS.
- Creator
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Peelamedu Ranganathan, Raviprakash, Kalpathy. B, Sundaram, University of Central Florida
- Abstract / Description
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A higher degree of system level integration can be achieved by integrating the passive components into semiconductor devices, which seem to be an enabling technology for portable communication and modern electronic devices. Greater functionality, higher performance and increase in reliability can be achieved by miniaturizing and reducing the number of components in integrated circuits. The functional potential of small electronic devices can be enormously increased by implementing the...
Show moreA higher degree of system level integration can be achieved by integrating the passive components into semiconductor devices, which seem to be an enabling technology for portable communication and modern electronic devices. Greater functionality, higher performance and increase in reliability can be achieved by miniaturizing and reducing the number of components in integrated circuits. The functional potential of small electronic devices can be enormously increased by implementing the embedded capacitors, resistors and inductors. This would free up surface real estate allowing either a smaller footprint or more silicon devices to be placed on the same sized substrate. This thesis focuses on the effect of deposition temperature and post deposition annealing (PDA) in different gas ambient on the electrical properties of sputter deposited ferroelectric Barium Strontium Titanate (Ba0.5St0.5) TiO3 thin film capacitors. Approximately 2000Å of Barium Strontium Titanate (BST) thin film was deposited at different substrate temperatures (400,450,500 and 550◦C) on cleaned silicon substrates. These BST films were then annealed separately in 100% N2, 100% O2 and 10% O2 + 90% N2 at 575◦C in sputtering machine (PVD anneal) and a three zone annealing Lindberg furnace. The objective of this thesis was to compare the effect of PDA on the electrical properties of BST films deposited at different substrate temperatures between PVD annealing and furnace annealing. For this work, tantalum thin film was used as top and bottom electrode to fabricate the capacitors. BST thin film capacitors were fabricated and characterized for leakage current and dielectric breakdown. Roughness study on pre and post annealed BST films were done using optical profilometer. The capacitors were tested using HP impedance analyzer in the frequency range from 10Hz through 1 MHz. From the experiments, 100% O2 annealed furnace annealed BST thin film seem to have better dielectric constant, higher breakdown voltage and nominal capacitance density.
Show less - Date Issued
- 2004
- Identifier
- CFE0000314, ucf:46310
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000314
- Title
- INVESTIGATIONS ON RF SPUTTER DEPOSITED SICN THIN FILMS FOR MEMS APPLICATIONS.
- Creator
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Todi, Ravi, Coffey, Kevin, University of Central Florida
- Abstract / Description
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With the rapid increase in miniaturization of mechanical components, the need for a hard, protective coatings is of great importance. In this study we investigate some of the mechanical, chemical and physical properties of the SiCN thin films. Thin films of amorphous silicon carbide nitride (a-SiCxNy) were deposited in a RF magnetron sputtering system using a powder pressed SiC target. Films with various compositions were deposited on to silicon substrate by changing the N2/Ar gas ratios...
Show moreWith the rapid increase in miniaturization of mechanical components, the need for a hard, protective coatings is of great importance. In this study we investigate some of the mechanical, chemical and physical properties of the SiCN thin films. Thin films of amorphous silicon carbide nitride (a-SiCxNy) were deposited in a RF magnetron sputtering system using a powder pressed SiC target. Films with various compositions were deposited on to silicon substrate by changing the N2/Ar gas ratios during sputtering. Nano-indentation studies were performed to investigate the mechanical properties such as hardness and reduced modulus of the SiCN films. Surface morphology of the films was characterized by using atomic force microscopy (AFM). X-ray photoelectron spectroscopy (XPS) data indicated that the chemical status is highly sensitive to the nitrogen ratios during sputtering. Further, the films were annealed in dry oxygen ambient in the temperature range of 400 – 900°C and characterized using XPS to investigate the chemical composition and oxidation kinetics at each annealing temperature. The surface roughness of these films was studied as a function of annealing temperature and film composition with the help of a "Veeco" optical profilometer. Nano-indentation studies indicated that the hardness and the reduced modulus of the film are sensitive to the N2/Ar ratio of gas flow during sputtering. AFM studies revealed that the films become smoother as the N2/Ar ratio is increased. XPS data indicated the existence of C-N phases in the as-deposited films. The study of oxidation kinetics of RF sputter deposited SiCN thin films, using XPS, suggest that N2 co-sputtering helps to suppress the formation of a surface oxide, by allowing un-bonded Si to bond with N and C inside the vacuum chamber as opposed to bonding with O in atmosphere.
Show less - Date Issued
- 2005
- Identifier
- CFE0000839, ucf:46669
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000839
- Title
- CHARACTERIZATION OF AN ADVANCED NEURON MODEL.
- Creator
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Echanique, Christopher, Behal, Aman, University of Central Florida
- Abstract / Description
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This thesis focuses on an adaptive quadratic spiking model of a motoneuron that is both versatile in its ability to represent a range of experimentally observed neuronal firing patterns as well as computationally efficient for large network simulation. The objective of research is to fit membrane voltage data to the model using a parameter estimation approach involving simulated annealing. By manipulating the system dynamics of the model, a realizable model with linear parameterization (LP)...
Show moreThis thesis focuses on an adaptive quadratic spiking model of a motoneuron that is both versatile in its ability to represent a range of experimentally observed neuronal firing patterns as well as computationally efficient for large network simulation. The objective of research is to fit membrane voltage data to the model using a parameter estimation approach involving simulated annealing. By manipulating the system dynamics of the model, a realizable model with linear parameterization (LP) can be obtained to simplify the estimation process. With a persistently excited current input applied to the model, simulated annealing is used to efficiently determine the best model parameters that minimize the square error function between the membrane voltage reference data and data generated by the LP model. Results obtained through simulation of this approach show feasibility to predict a range of different neuron firing patterns.
Show less - Date Issued
- 2012
- Identifier
- CFH0004259, ucf:44958
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004259
- Title
- DATA-TRUE CHARACTERIZATION OF NEURONAL MODELS.
- Creator
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Suarez, Jose, Behal, Aman, University of Central Florida
- Abstract / Description
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In this thesis, a weighted least squares approach is initially presented to estimate the parameters of an adaptive quadratic neuronal model. By casting the discontinuities in the state variables at the spiking instants as an impulse train driving the system dynamics, the neuronal output is represented as a linearly parameterized model that depends on ltered versions of the input current and the output voltage at the cell membrane. A prediction errorbased weighted least squares method is...
Show moreIn this thesis, a weighted least squares approach is initially presented to estimate the parameters of an adaptive quadratic neuronal model. By casting the discontinuities in the state variables at the spiking instants as an impulse train driving the system dynamics, the neuronal output is represented as a linearly parameterized model that depends on ltered versions of the input current and the output voltage at the cell membrane. A prediction errorbased weighted least squares method is formulated for the model. This method allows for rapid estimation of model parameters under a persistently exciting input current injection. Simulation results show the feasibility of this approach to predict multiple neuronal ring patterns. Results of the method using data from a detailed ion-channel based model showed issues that served as the basis for the more robust resonate-and- re model presented. A second method is proposed to overcome some of the issues found in the adaptive quadratic model presented. The original quadratic model is replaced by a linear resonateand- re model -with stochastic threshold- that is both computational efficient and suitable for larger network simulations. The parameter estimation method presented here consists of different stages where the set of parameters is divided in to two. The rst set of parameters is assumed to represent the subthreshold dynamics of the model, and it is estimated using a nonlinear least squares algorithm, while the second set is associated with the threshold and reset parameters as its estimated using maximum likelihood formulations. The validity of the estimation method is then tested using detailed Hodgkin-Huxley model data as well as experimental voltage recordings from rat motoneurons.
Show less - Date Issued
- 2011
- Identifier
- CFE0003917, ucf:48724
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003917
- Title
- Solving Constraint Satisfaction Problems with Matrix Product States.
- Creator
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Pelton, Sabine, Mucciolo, Eduardo, Ishigami, Masa, Leuenberger, Michael, University of Central Florida
- Abstract / Description
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In the past decade, Matrix Product State (MPS) algorithms have emerged as an efficient method of modeling some many-body quantum spin systems. Since spin system Hamiltonians can be considered constraint satisfaction problems (CSPs), it follows that MPS should provide a versatile framework for studying a variety of general CSPs. In this thesis, we apply MPS to two types of CSP. First, use MPS to simulate adiabatic quantum computation (AQC), where the target Hamiltonians are instances of a...
Show moreIn the past decade, Matrix Product State (MPS) algorithms have emerged as an efficient method of modeling some many-body quantum spin systems. Since spin system Hamiltonians can be considered constraint satisfaction problems (CSPs), it follows that MPS should provide a versatile framework for studying a variety of general CSPs. In this thesis, we apply MPS to two types of CSP. First, use MPS to simulate adiabatic quantum computation (AQC), where the target Hamiltonians are instances of a fully connected, random Ising spin glass. Results of the simulations help shed light on why AQC fails for some optimization problems. We then present the novel application of a modified MPS algorithm to classical Boolean satisfiability problems, specifically k-SAT and max k-SAT. By construction, the algorithm also counts solutions to a given Boolean formula (\#-SAT). For easy satisfiable instances, the method is more expensive than other existing algorithms; however, for hard and unsatisfiable instances, the method succeeds in finding satisfying assignments where other algorithms fail to converge.
Show less - Date Issued
- 2017
- Identifier
- CFE0006902, ucf:51713
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006902
