Design, Fabrication, and Characterization of Carbon Nanotube Field Emission Devices for Advanced Applications

<p>Carbon nanotubes (CNTs) have recently emerged as promising candidates for electron field emission (FE) cathodes in integrated FE devices. These nanostructured carbon materials possess exceptional properties and their synthesis can be thoroughly controlled. Their integration into advanced electronic devices, including not only FE cathodes, but sensors, energy storage devices, and circuit components, has seen rapid growth in recent years. The results of the studies presented here demonstrate that the CNT field emitter is an excellent candidate for next generation vacuum microelectronics and related electron emission devices in several advanced applications.</p><p> The work presented in this study addresses determining factors that currently confine the performance and application of CNT-FE devices. Characterization studies and improvements to the FE properties of CNTs, along with Micro-Electro-Mechanical Systems (MEMS) design and fabrication, were utilized in achieving these goals. Important performance limiting parameters, including emitter lifetime and failure from poor substrate adhesion, are examined. The compatibility and integration of CNT emitters with the governing MEMS substrate (i.e., polycrystalline silicon), and its impact on these performance limiting parameters, are reported. CNT growth mechanisms and kinetics were investigated and compared to silicon (100) to improve the design of CNT emitter integrated MEMS based electronic devices, specifically in vacuum microelectronic device (VMD) applications.</p><p> Improved growth allowed for design and development of novel cold-cathode FE devices utilizing CNT field emitters. A chemical ionization (CI) source based on a CNT-FE electron source was developed and evaluated in a commercial desktop mass spectrometer for explosives trace detection. This work demonstrated the first reported use of a CNT-based ion source capable of collecting CI mass spectra. The CNT-FE source demonstrated low power requirements, pulsing capabilities, and average lifetimes of over 320 hours when operated in constant emission mode under elevated pressures, without sacrificing performance. Additionally, a novel packaged ion source for miniature mass spectrometer applications using CNT emitters, a MEMS based Nier-type geometry, and a Low Temperature Cofired Ceramic (LTCC) 3D scaffold with integrated ion optics were developed and characterized. While previous research has shown other devices capable of collecting ion currents on chip, this LTCC packaged MEMS micro-ion source demonstrated improvements in energy and angular dispersion as well as the ability to direct the ions out of the packaged source and towards a mass analyzer. Simulations and experimental design, fabrication, and characterization were used to make these improvements.</p><p> Finally, novel CNT-FE devices were developed to investigate their potential to perform as active circuit elements in VMD circuits. Difficulty integrating devices at micron-scales has hindered the use of vacuum electronic devices in integrated circuits, despite the unique advantages they offer in select applications. Using a combination of particle trajectory simulation and experimental characterization, device performance in an integrated platform was investigated. Solutions to the difficulties in operating multiple devices in close proximity and enhancing electron transmission (i.e., reducing grid loss) are explored in detail. A systematic and iterative process was used to develop isolation structures that reduced crosstalk between neighboring devices from 15% on average, to nearly zero. Innovative geometries and a new operational mode reduced grid loss by nearly threefold, thereby improving transmission of the emitted cathode current to the anode from 25% in initial designs to 70% on average. These performance enhancements are important enablers for larger scale integration and for the realization of complex vacuum microelectronic circuits.</p>

Carbon mitigation costs for the commercial building sector: Discrete-continuous choice analysis of multifuel energy demand

We estimate a carbon mitigation cost curve for the U.S. commercial sector based on econometric estimation of the responsiveness of fuel demand and equipment choices to energy price changes. The model econometrically estimates fuel demand conditional on fuel choice, which is characterized by a multinomial logit model. Separate estimation of end uses (e.g., heating, cooking) using the U.S. Commercial Buildings Energy Consumption Survey allows for exceptionally detailed estimation of price responsiveness disaggregated by end use and fuel type. We then construct aggregate long-run elasticities, by fuel type, through a series of simulations; own-price elasticities range from -0.9 for district heat services to -2.9 for fuel oil. The simulations form the basis of a marginal cost curve for carbon mitigation, which suggests that a price of $20 per ton of carbon would result in an 8% reduction in commercial carbon emissions, and a price of $100 per ton would result in a 28% reduction. © 2008 Elsevier B.V. All rights reserved.

Essays in Macro Finance

<p>I study the link between capital markets and sources of macroeconomic risk. In chapter 1 I show that expected inflation risk is priced in the cross section of stock returns even after controlling for cash flow growth and volatility risks. Motivated by this evidence I study a long run risk model with a built-in inflation non-neutrality channel that allows me to decompose the real stochastic discount factor into news about current and expected cash flow growth, news about expected inflation and news about volatility. The model can successfully price a broad menu of assets and provides a setting for analyzing cross sectional variation in expected inflation risk premium. For industries like retail and durable goods inflation risk can account for nearly a third of the overall risk premium while the energy industry and a broad commodity index act like inflation hedges. Nominal bonds are exposed to expected inflation risk and have inflation premiums that increase with bond maturity. The price of expected inflation risk was very high during the 70's and 80's, but has come down a lot since being very close to zero over the past decade. On average, the expected inflation price of risk is negative, consistent with the view that periods of high inflation represent a "bad" state of the world and are associated with low economic growth and poor stock market performance. In chapter 2 I look at the way capital markets react to predetermined macroeconomic announcements. I document significantly higher excess returns on the US stock market on macro release dates as compared to days when no macroeconomic news hit the market. Almost the entire equity premium since 1997 is being realized on days when macroeconomic news are released. At high frequency, there is a pattern of returns increasing in the hours prior to the pre-determined announcement time, peaking around the time of the announcement and dropping thereafter.</p>

Path Optimization in Free Energy Calculations

<p>Free energy calculations are a computational method for determining thermodynamic quantities, such as free energies of binding, via simulation. </p><p>Currently, due to computational and algorithmic limitations, free energy calculations are limited in scope.</p><p>In this work, we propose two methods for improving the efficiency of free energy calculations.</p><p>First, we expand the state space of alchemical intermediates, and show that this expansion enables us to calculate free energies along lower variance paths.</p><p>We use Q-learning, a reinforcement learning technique, to discover and optimize paths at low computational cost.</p><p>Second, we reduce the cost of sampling along a given path by using sequential Monte Carlo samplers.</p><p>We develop a new free energy estimator, pCrooks (pairwise Crooks), a variant on the Crooks fluctuation theorem (CFT), which enables decomposition of the variance of the free energy estimate for discrete paths, while retaining beneficial characteristics of CFT.</p><p>Combining these two advancements, we show that for some test models, optimal expanded-space paths have a nearly 80% reduction in variance relative to the standard path.</p><p>Additionally, our free energy estimator converges at a more consistent rate and on average 1.8 times faster when we enable path searching, even when the cost of path discovery and refinement is considered.</p>