Matching Items (147)
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Description
Alloying in semiconductors has enabled many civilian technologies in optoelectronic, photonic fields and more. While the phenomenon of alloying is well established in traditional bulk semiconductors, owing to vastly available ternary phase diagrams, the ability to alloy in 2D systems are less clear. Recently anisotropic materials such as ReS2 and

Alloying in semiconductors has enabled many civilian technologies in optoelectronic, photonic fields and more. While the phenomenon of alloying is well established in traditional bulk semiconductors, owing to vastly available ternary phase diagrams, the ability to alloy in 2D systems are less clear. Recently anisotropic materials such as ReS2 and TiS3 have been extensively studied due to their direct-gap semiconductor and high mobility behaviors. This work is a report on alloys of ReS2 & ReSe2 and TiS3 &TiSe3.

Alloying selenium into ReS2 in the creation of ReS2xSe2-x, tunes the band gap and changes its vibrational spectrum. Depositing this alloy using bottom up approach has resulted in the loss of crystallinity. This loss of crystallinity was evidenced by grain boundaries and point defect shown by TEM images.

Also, in the creation of TiS3xSe3-x, by alloying Se into TiS3, a fixed ratio of 8% selenium deposit into TiS3 host matrix is observed. This is despite the vastly differing precursor amounts and growth temperatures, as evinced by detailed TEM, EDAX, TEM diffraction, and Raman spectroscopy measurements. This unusual behavior contrasts with other well-known layered material systems such as MoSSe, WMoS2 where continuous alloying can be attained. Cluster expansion theory calculations suggest that only limited composition (x) can be achieved. Considering the fact that TiSe3 vdW crystals have not been synthesized in the past, these alloying rejections can be attributed to energetic instability in the ternary phase diagrams estimated by calculations performed. Overall findings highlight potential means and challenges in achieving stable alloying in promising direct gap and high carrier mobility TiS3 materials.
ContributorsAgarwal, Ashutosh (Author) / Tongay, Sefaattin (Thesis advisor) / Green, Matthew (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
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Description
In a 2004 paper, John Nagy raised the possibility of the existence of a hypertumor \emph{i.e.}, a focus of aggressively reproducing parenchyma cells that invade part or all of a tumor. His model used a system of nonlinear ordinary differential equations to find a suitable set of conditions for which

In a 2004 paper, John Nagy raised the possibility of the existence of a hypertumor \emph{i.e.}, a focus of aggressively reproducing parenchyma cells that invade part or all of a tumor. His model used a system of nonlinear ordinary differential equations to find a suitable set of conditions for which these hypertumors exist. Here that model is expanded by transforming it into a system of nonlinear partial differential equations with diffusion, advection, and a free boundary condition to represent a radially symmetric tumor growth. Two strains of parenchymal cells are incorporated; one forming almost the entirety of the tumor while the much more aggressive strain

appears in a smaller region inside of the tumor. Simulations show that if the aggressive strain focuses its efforts on proliferating and does not contribute to angiogenesis signaling when in a hypoxic state, a hypertumor will form. More importantly, this resultant aggressive tumor is paradoxically prone to extinction and hypothesize is the cause of necrosis in many vascularized tumors.
ContributorsAlvarez, Roberto L (Author) / Milner, Fabio A (Thesis advisor) / Nagy, John D. (Committee member) / Kuang, Yang (Committee member) / Thieme, Horst (Committee member) / Mahalov, Alex (Committee member) / Smith, Hal (Committee member) / Arizona State University (Publisher)
Created2014
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Description

Predicting the timing of a castrate resistant prostate cancer is critical to lowering medical costs and improving the quality of life of advanced prostate cancer patients. We formulate, compare and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). We accomplish these tasks by employing

Predicting the timing of a castrate resistant prostate cancer is critical to lowering medical costs and improving the quality of life of advanced prostate cancer patients. We formulate, compare and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). We accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). While these models are simplifications of a previously published model, they fit data with similar accuracy and improve forecasting results. Both models describe the progression of androgen resistance. Although Model 1 is simpler than the more realistic Model 2, it can fit clinical data to a greater precision. However, we found that Model 2 can forecast future PSA levels more accurately. These findings suggest that including more realistic mechanisms of androgen dynamics in a two population model may help androgen resistance timing prediction.

ContributorsBaez, Javier (Author) / Kuang, Yang (Author) / College of Liberal Arts and Sciences (Contributor)
Created2016-11-16
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Description

Background:
Data assimilation refers to methods for updating the state vector (initial condition) of a complex spatiotemporal model (such as a numerical weather model) by combining new observations with one or more prior forecasts. We consider the potential feasibility of this approach for making short-term (60-day) forecasts of the growth and

Background:
Data assimilation refers to methods for updating the state vector (initial condition) of a complex spatiotemporal model (such as a numerical weather model) by combining new observations with one or more prior forecasts. We consider the potential feasibility of this approach for making short-term (60-day) forecasts of the growth and spread of a malignant brain cancer (glioblastoma multiforme) in individual patient cases, where the observations are synthetic magnetic resonance images of a hypothetical tumor.

Results:
We apply a modern state estimation algorithm (the Local Ensemble Transform Kalman Filter), previously developed for numerical weather prediction, to two different mathematical models of glioblastoma, taking into account likely errors in model parameters and measurement uncertainties in magnetic resonance imaging. The filter can accurately shadow the growth of a representative synthetic tumor for 360 days (six 60-day forecast/update cycles) in the presence of a moderate degree of systematic model error and measurement noise.

Conclusions:
The mathematical methodology described here may prove useful for other modeling efforts in biology and oncology. An accurate forecast system for glioblastoma may prove useful in clinical settings for treatment planning and patient counseling.

ContributorsKostelich, Eric (Author) / Kuang, Yang (Author) / McDaniel, Joshua (Author) / Moore, Nina Z. (Author) / Martirosyan, Nikolay L. (Author) / Preul, Mark C. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2011-12-21
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Description
Hyperspectral imaging is a novel technology which allows for the collection of reflectance spectra of a sample in-situ and at a distance. A rapidly developing technology, hyperspectral imaging has been of particular interest in the field of art characterization, authentication, and conservation as it avoids the pitfalls of traditional characterization

Hyperspectral imaging is a novel technology which allows for the collection of reflectance spectra of a sample in-situ and at a distance. A rapidly developing technology, hyperspectral imaging has been of particular interest in the field of art characterization, authentication, and conservation as it avoids the pitfalls of traditional characterization techniques and allows for the rapid and wide collection of data never before possible. It is hypothesized that by combining the power of hyperspectral imaging with machine learning, a new framework for the in-situ and automated characterization and authentication of artworks can be developed. This project, using the CMYK set of inks, began the preliminary development of such a framework. It was found that hyperspectral imaging and machine learning as a combination show significant potential as an avenue for art authentication, though further progress and research is needed to match the reliability of status quo techniques.
ContributorsChowdhury, Tanzil Aziz (Author) / Newman, Nathan (Thesis director) / Tongay, Sefaattin (Committee member) / School of Politics and Global Studies (Contributor) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
Glioblastoma multiforme (GBMs) is the most prevalent brain tumor type and causes approximately 40% of all non-metastic primary tumors in adult patients [1]. GBMs are malignant, grade-4 brain tumors, the most aggressive classication as established by the World Health Organization and are marked by their low survival rate; the median

Glioblastoma multiforme (GBMs) is the most prevalent brain tumor type and causes approximately 40% of all non-metastic primary tumors in adult patients [1]. GBMs are malignant, grade-4 brain tumors, the most aggressive classication as established by the World Health Organization and are marked by their low survival rate; the median survival time is only twelve months from initial diagnosis: Patients who live more than three years are considered long-term survivors [2]. GBMs are highly invasive and their diffusive growth pattern makes it impossible to remove the tumors by surgery alone [3]. The purpose of this paper is to use individual patient data to parameterize a model of GBMs that allows for data on tumor growth and development to be captured on a clinically relevant time scale. Such an endeavor is the rst step to a clinically applicable predictions of GBMs. Previous research has yielded models that adequately represent the development of GBMs, but they have not attempted to follow specic patient cases through the entire tumor process. Using the model utilized by Kostelich et al. [4], I will attempt to redress this deciency. In doing so, I will improve upon a family of models that can be used to approximate the time of development and/or structure evolution in GBMs. The eventual goal is to incorporate Magnetic Resonance Imaging (MRI) data into a parameterized model of GBMs in such a way that it can be used clinically to predict tumor growth and behavior. Furthermore, I hope to come to a denitive conclusion as to the accuracy of the Koteslich et al. model throughout the development of GBMs tumors.
ContributorsManning, Miles (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Preul, Mark (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2012-12
Description
Transition metal dichalcogenides (TMDs) are a family of layered crystals with the chemical formula MX2 (M = W, Nb, Mo, Ta and X = S, Se, Te). These TMDs exhibit many fascinating optical and electronic properties making them strong candidates for high-end electronics, optoelectronic application, and spintronics. The layered structure

Transition metal dichalcogenides (TMDs) are a family of layered crystals with the chemical formula MX2 (M = W, Nb, Mo, Ta and X = S, Se, Te). These TMDs exhibit many fascinating optical and electronic properties making them strong candidates for high-end electronics, optoelectronic application, and spintronics. The layered structure of TMDs allows the crystal to be mechanically exfoliated to a monolayer limit, where bulk-scale properties no longer apply and quantum effects arise, including an indirect-to-direct bandgap transition. Controllably tuning the electronic properties of TMDs like WSe2 is therefore a highly attractive prospect achieved by substitutionally doping the metal atoms to enable n- and p-type doping at various concentrations, which can ultimately lead to more effective electronic devices due to increased charge carriers, faster transmission times and possibly new electronic and optical properties to be probed. WSe2 is expected to exhibit the largest spin splitting size and spin-orbit coupling, which leads to exciting potential applications in spintronics over its similar TMD counterparts, which can be controlled through electrical doping. Unfortunately, the well-established doping technique of ion implantation is unable to preserve the crystal quality leading to a major roadblock for the electronics applications of tungsten diselenide. Synthesizing WSe2 via chemical vapor transport (CVT) and flux method have been previously established, but controllable p-type (niobium) doping WSe2 in low concentrations ranges (<1 at %) by CVT methods requires further experimentation and study. This work studies the chemical vapor transport synthesis of doped-TMD W1-xNbxSe2 through characterization techniques of X-ray Diffraction, Scanning Electron Microscopy, Energy Dispersive X-ray Spectroscopy, and X-ray Photoelectron Spectroscopy techniques. In this work, it is observed that excess selenium transport does not enhance the controllability of niobium doping in WSe2, and that tellurium tetrachloride (TeCl4) transport has several barriers in successfully incorporating niobium into WSe2.
ContributorsRuddick, Hayley (Author) / Tongay, Sefaattin (Thesis director) / Jiao, Yang (Committee member) / Barrett, The Honors College (Contributor) / Materials Science and Engineering Program (Contributor)
Created2024-05