Characterizing The Energetic Landscape In Solution Processable Solar Cells Via Frequency-Dependent Impedance Measurements

This thesis presents measurements and analyses aimed at describing charge transport dynamics in quantum dot (QD) photovoltaics (PVs). Due to their solution processability and unique size-dependent optoelectronic properties, ensembles of electronically coupled QDs (QD solids) provide an exciting platform for next generation PV devices. However, the structural disorder associated with the formation of conductive QD solids gives rise to a complicated density of states (DOS) emerging from the distribution of mesoscale charge dynamics occurring in these materials. I present phenomological models to describe the DOS in the disordered energetic and spatial landscape of QD solids that relies on a suite of frequency-domain measurements known as impedance spectroscopy (IS). Though specific applications of IS such as thermal admittance spectroscopy (TAS) have been applied to the capacitance characteristics of QD solids, a fuller picture of the DOS in these materials is afforded by analysis of the time-scales evident in the full impedance characteristics of QD devices. I heuristically propose extensions of charge transport models developed for capacitance-voltage (CV) measurements of bulk semiconductors to describe the frequency-dependent capacitance and conductance response of a variety of QD solar cell device architectures. In Chapter 3, I show how TAS and drive level capacitance profiling (DLCP) characterization of a QD Schottky junction is linked to charge hopping processes observed in AC conductance data. This allows me to map the time scales detected in these data to the DOS in the QD solid. I then suggest how the observed DOS translates onto macroscale device properties like the diode current. In Chapter 4, I apply these techniques to a QD heterojunction device. I use forward biased IS characterization to suggest the presence of a defect state at the junction interface, and calculate the associated distribution of carrier lifetimes. In Chapter 5, I attempt to extend this model to a QD p-i-n heterojunction solar cell, and obtain a response consistent with interfacial trapping and carrier transport. Though unambiguous identification of the origin of these responses proves beyond the scope of this thesis, I use illuminated TAS and DLCP measurements to show the presence of an interfacial trap for photogenerated electrons

Diagnostic Decays of the X(3872)

The unusual properties of the X(3872) have led to speculation that it is a weakly bound state of mesons, chiefly $D^0\bar D^{0*}$. Tests of this hypothesis are investigated and it is proposed that measuring the $3\pi J/\psi$, $\gamma J/\psi$, $\gamma \psi'$, $\bar K K^*$, and $\pi\rho$ decay modes of the $X$ will serve as a definitive diagnostic of the molecule hypothesis.Comment: 6 pages revtex4, 3 eps figure

Using ALD To Bond CNTs to Substrates and Matrices

Atomic-layer deposition (ALD) has been shown to be effective as a means of coating carbon nanotubes (CNTs) with layers of Al2O3 that form strong bonds between the CNTs and the substrates on which the CNTs are grown. ALD is a previously developed vaporphase thin-film-growth technique. ALD differs from conventional chemical vapor deposition, in which material is deposited continually by thermal decomposition of a precursor gas. In ALD, material is deposited one layer of atoms at a time because the deposition process is self-limiting and driven by chemical reactions between the precursor gas and the surface of the substrate or the previously deposited layer

Arterial spin labeled MRI detects clinically relevant increases in myocardial blood flow with vasodilatation

ObjectivesThis study sought to determine whether arterial spin labeled (ASL) cardiac magnetic resonance (CMR) is capable of detecting clinically relevant increases in regional myocardial blood flow (MBF) with vasodilator stress testing in human myocardium.BackgroundMeasurements of regional myocardial perfusion at rest and during vasodilatation are used to determine perfusion reserve, which indicates the presence and distribution of myocardial ischemia. ASL CMR is a perfusion imaging technique that does not require any contrast agents, and is therefore safe for use in patients with end-stage renal disease, and capable of repeated or continuous measurement.MethodsMyocardial ASL scans at rest and during adenosine infusion were incorporated into a routine CMR adenosine induced vasodilator stress protocol and was performed in 29 patients. Patients who were suspected of having ischemic heart disease based on first-pass imaging also underwent x-ray angiography. Myocardial ASL was performed using double-gated flow-sensitive alternating inversion recovery tagging and balanced steady-state free precession imaging at 3-T.ResultsSixteen patients were found to be normal and 13 patients were found to have visible perfusion defect based on first-pass CMR using intravenous gadolinium chelate. In the normal subjects, there was a statistically significant difference between MBF measured by ASL during adenosine infusion (3.67 ± 1.36 ml/g/min), compared to at rest (0.97 ± 0.64 ml/g/min), with p < 0.0001. There was also a statistically significant difference in perfusion reserve (MBFstress/MBFrest) between normal myocardial segments (3.18 ± 1.54) and the most ischemic segments in the patients with coronary artery disease identified by x-ray angiography (1.44 ± 0.97), with p = 0.0011.ConclusionsThis study indicates that myocardial ASL is capable of detecting clinically relevant increases in MBF with vasodilatation and has the potential to identify myocardial ischemia

How research data deliver non-academic impacts : A secondary analysis of UK Research Excellence Framework impact case studies

This study investigates how research data contributes to non-academic impacts using a secondary analysis of high-scoring impact case studies from the UK’s Research Excellence Framework (REF). A content analysis was conducted to identify patterns, linking research data and impact. The most prevalent type of research data-driven impact related to “practice” (45%), which included changing how professionals operate, changing organizational culture and improving workplace productivity or outcomes. The second most common category was “government impacts”, including reducing government service costs and enhancing government effectiveness or efficiency. Impacts from research data were developed most frequently through “improved institutional processes or methods” (40%) and developing impact via pre-analyzed or curated information in reports (32%), followed by “analytic software or methods” (26%). The analysis found that research data on their own rarely generate impacts. Instead they require analysis, curation, product development or other forms of significant intervention to leverage broader non-academic impacts