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New York City Research Initiative

Research Projects at Southern Connecticut State University

Go to projects in: 2009 | 2008 | 2006 | 2005

Southern Connecticut State University — 2009

Evaluation of Surface Texture Parameters' Ability to Determine Roughness Atomic Force Microscopy Images
Team Members

Principle Investigator (PI):
Dr. John Daponte

Team Members:
Bethany Niedzielski, Carlos Solano,
Deborah Day, Ellen Scanley,
Dr. Christine Broadbridge

Taylor Malone, High School Student

Final Research Presentation
Summary

Abstract: As electrical components become smaller and more condensed, nanotechnology is needed to create new and better materials for these components. The materials used in this research were Indium, Gallium, Arsenide, and Aluminum Oxide made by Molecualr Beam Epitaxy and Jet Vapor Deposition respectively. Several samples of each material were imaged using an Atomic Force Microscope (AFM) which shows the topography of a sample. The surface texture of these samples was the primary focus of this research because, generally, a smoother sample will have more desirable electrical properties than a rough sample. Using various parameters from the AFM and an image processing software ImageJ, our goal was to determine which parameters best protray the roughness of a sample. We found that standard deviation, inverse difference moment, and entropy portray roughness the best. These results will aid future experiments that more directly involve the electrical properties of similar materials.

A Qualitative and Quantitative Analysis of Bone Porosities Through the Tabletop Scanning Electron Microscope
Team Members

Principle Investigator (PI):
Dr. John Daponte

Team Members:
Dr. Christine Broadbridge, Dr. Stefan Judex,
Dalisha Daniel, Lisa Alter

Divya Krishnamoorthy, Undergraduate Student

Final Research Presentation
Summary

Abstract: The objective of this experiment was to access the effectiveness of using a new generation instrument, the TM-1000 tabletop scanning electron microscope to analyze cortical bone porosity in BALB mice tibiae. Scientists have been intrigued by the porosity growth of the skeleton and especially the development of diseases such as Osteoporosis and bone morphology changes during spaceflight. The tabletop SEM is proven to be very efficient, as it requires minimal sample preparation, acquires resolutions of up to 30 nm and shows high contrasts. Porosities were measured on the periosteal and intracortical surfaces of the bone. Intracortical porosity was analyzed on transverse sections of the tibiae that were prepared two different ways, by cutting with a diamond wheel saw and by razor fracturing. Image processing techniques for background smoothing, thresholding algorithms, and noise filters were studied. A rolling ball background correction accompanied by the Shanbhag threshold and Despeckle filter proved to be most efficient on the SEM grayscale images. The techniques established here will be used to analyze periosteal and intracortical porosities on disused mouse bones.

Southern Connecticut State University — 2008

Analyzing the Surface Roughness of Gate Dielectrics
Team Members

Principle Investigator (PI):
Dr. John DaPonte

Co-Principle Investigator (Co-PI):
Dr. Christine Broadbridge

Researchers:

Leah Mirabelle, Graduate Student
Patrick Benjamin,Undergraduate Student
Bethany Niedzielski, High School

Final Research Presentation
Summary

Nanotechnology is a multidisciplinary field that deals with particles on the atomic scale, generally between 1 and 100 nanometers in size. This field is extremely promising due to the difference in material properties between a nanomaterial, and that same material in bulk form.

This study focused on determining the surface roughness of three samples of Al2O3, which were made in different processing conditions, by comparing their texture statistics to that of a control (cleaned silicon). The samples were prepared by Jet Vapor Deposition with the flow rate and carrier gas as variables and imaged using the atomic force microscope (AFM) in tapping mode. The AFM images were processed in ImageJ and utilized the plug-in "Batch Texture" which returned 16 texture parameters. These parameters, as well as two obtained directly from the AFM, were graphed against those for the control substance to determine which parameters best classify surface roughness.

The best parameters were found to be RMS roughness and mean roughness, both of which were obtained from the AFM. According to these parameters, sample 2, which was prepared at a flow rate of 300 sccm with carrier gases of Argon and Nitrogen, was the smoothest of the three samples.

Southern Connecticut State University — 2006

Particle Analysis of Transmission Electron Microscopy Images
Team Members

Principle Investigator (PI):
Dr. John DaPonte

Researchers:
Thomas Sadowski, Graduate Student

Monica Sawicki

Lisa Marinella

Paidemwoyo Munhutu

Divya Krishna, SHARP Apprentice

Final Research Presentation
Summary

Platinum nanoparticle images were analyzed through an imaging software called ImageJ to find particle size and size distribution.

Several pre-processing techniques were experimented with including:
-Rolling Ball Algorithm
-Pseudo Flat Field Correction

Reasons for pre-processing include elimination of:
-The Haloing effect
-Excess amount of noise
-Image contamination

Several thresholding algorithms were experimented with including:
-Entropy Thresholding
-Kittler Thresholding
-Calvart-Riddler Thresholding

Difficulties arising with the use of thresholding algorithms include:
-Erosion of nanoparticles in binary image
-Expansion of nanoparticles in binary image
-Incorrect representation of original particle image

Southern Connecticut State University — 2005

Image Segmentation Techniques
Team Members

Principle Investigator (PI):
Dr. John DaPonte

Researchers:
Michael Clark, Graduate Student

Thomas Sadowski, Graduate Student
Paul Thomas, Undergraduate Student

Elizabeth Wood, Undergraduate Student
Paul Nelson, SHARP Apprentice

Final Research Presentation
Summary

1. Last year, the Dr. John DaPonte and his students completed a preliminary study on the application of image segmentation techniques to bone density images in collaboration with Dr. Stefan Judex at SUNY Stony Brook. In the next phase, again in collaboration with Dr. Judex, the primary objective is to investigate quantitative ways to confirm our qualitative results, using bone density 3D calculation software that outputs numerous bone density parameters to quantitatively evaluate bone loss in subjects exposed to prolonged weightlessness.

2. Tri-State Stem STEP Alliance Proposal to NSF, Quantitative Analysis of Bone Density Images to both the Connecticut Space Grant Consortium and Connecticut University Faculty Research Grant Program. Also, "The Investigation of Deconvolution Algorithms for the Enhancement of Mirco CT Scan Images" to NASA Human Health and Performance under Research Opportunities for Ground-Based Studies for Human Health in Space.

3. The follow up to last summers research at SCSU has been two independent studies by Tom Sadowski and Mike Clark. Tom Sadowski is also doing a honors thesis this semester.

4. Two conference papers have resulted from last year's research. One was presented on March 29, 2005 to the SPIE Conference on Visual Information Processing and the Second paper will be presented to the ASEE New England Regional Conference on April 9 of this year. Mike Clark is also submitting a short paper to the North Eastern Bioengineering Conference at Stevens Institute of Technology but we have not heard about this paper yet.>P>5. SCSU's NYCRI team will assist NASA GISS teams with computer imaging.

Image Segmentation of Bone Density Images
Team Members

Principle Investigator (PI):
Dr. John DaPonte

Researchers:
Magan Damon, Graduate Student
Michael Clark, Undergraduate Student
Tom Sadowski, Undergraduate Student
Charles Tirrell, Undergraduate Student
Rebecca Kamins, SHARP Apprentice

Final Research Presentation
Summary

This study will investigate the potential of several segmentation algorithms to distinguish between bone and soft tissue on micro CAT scan images. Images will be transferred from the State University of New York (SUNY) at Stony Brook to Southern for analysis by the proposed PI and three undergraduate students. This will be a retrospective study with the intent of using the results to formulate guidelines that will make future data collection more efficient. The resulting recommendations will provide SUNY researchers with a better method of tracking bone loss in Astronauts subjected to prolonged weightlessness and people who suffer from Osteoporosis.

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