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Transformer Based Model for Political Spanish Text
No full textConflict research is a subfield of political science which covers protests, riots, repression,
genocide, criminal violence etc. Conflict researchers are interested in tracking and analyzing
conflict events. Due to the large number of conflicts happening across the globe, manually
tracking and annotating conflicts can be a laborious task and so researchers use language models
to automate the process. While transformer-based language models have already been trained on
English text, there has been no work done on training models on Spanish text to the best of our
knowledge. Spanish is one of the most widely spoken languages in the world and it’s the
medium used to express many conflicts happening in Latin America and so a model trained
exclusively on Spanish text would hypothetically outperform models based on other languages.
With this objective in mind first a domain-specific text corpus is mined from various Spanish
websites and then a BERT based model is trained from scratch on the corpus. The model is then
evaluated on downstream tasks on some available datasets to assess the model’s practical
application in conflict research. Finally, we evaluate several versions of BERT to compare the
performance of our model
Spherical Time
No full textThe focus of this thesis is the artful expression of time as a non-linear construct. I used a
holography technique to create a space to show 3D vision as a new advanced technology that
fosters the exploratory processes of the mind. I considered changes based on human perception
of keeping time by having participants touch the screen for a long time, or just pressing and
releasing a button quickly for a short time. In this installation, there is free space for the audience
to select a time with varying speeds or to slow down. Multiple visions of time, for me, are like
giving participants variable chances to find the best way of living, like a journey between the
past, present, and future
CAD Tools for PCB Reverse Engineering and IC Interconnect
No full textThis thesis will introduce two different CAD tools, MTBOM, and SMOR, for two specific
applications.
We developed our original tool, MTBOM, Metal Trace to Bill Of Materials automation for
Printed Circuit Board Reverse Engineering (PCB-RE). Here, we assumed that the PCBs are
devoid of any components or silkscreens, with only the wiring traces accessible on the various
layers. This models the scenario where the PCBs are damaged and/or discarded. PCB-RE
is highly useful for design verification and fault isolation of essential legacy systems, where
it often happens that some parts in a legacy system are required to be replaced while there
are no records in system documentation; MTBOM can offer a solution to such a situation
identifying such parts by simply metal analysis. We demonstrate that our PCB-RE tool
extracts the correct Bill of Materials (BoM) for ten different PCBs by analyzing primarily
the metal layers. The proposed PCB-RE tool MTBOM detected every integrated circuit
(IC) on the PCBs with no false positives or negatives. This scheme also identifies passive
components, such as resistors, capacitors, and inductors.
In SMOR, we have proposed a Simple Model Order Reduction approach for parasitic extrac-
tions of metal interconnects. Parasitic EXtractions (PEX) of the metal interconnects are
complex, consisting of millions or more passive elements. Consequently, the space requirements for PEX are enormous, and the simulation times are unacceptably long. The model
order reduction method called PACT in Synopsys’ HSPICE simulator significantly reduces
the simulation times. However, in SMOR, we have developed a simple technique to minimize
each non-branching metal segment extraction to a single RC pi-element. And then, we can
reduce the aggregate RC branches based on fundamental network analysis theorems. The
effective delay to any number of projected nodes is modeled with the minimum number of
RC components. When we applied SMOR on the C880 (an 8-bit ALU) ISCAS benchmark
circuit for GF 12nm FinFET technology, it resulted in over a 10X reduction in R, and about
3X reduction in C size, while maintaining 100% delay accuracy and featuring approximately
3X speed up while applying on HSPICE and can make 73% speed up in simulation time
while integrated with PACT compared to using PACT only.
This dissertation presents MTBOM in its first three chapters, and we dedicate the last
chapter to delivering SMOR
Speech and Acoustic Sound Analysis for Cochlear Implants/hearing Aids System: Advancements With Machine Learning Environmental Sound Perception and Safety Assessment
No full textCochlear Implant (CI) and Hearing Aid (HA) Research Platforms (RP) are commonly used by
the research community to propose new algorithms, conduct scientific field-tests, and explore
hearing/perception-based rehabilitation protocols. RPs are generally assumed to be safe for any
customization or any new algorithm development, and many researchers typically perform
baseline tests to verify the functionality and address any safety concerns. In this thesis, a two
related research goals are addressed: (i) CI research platform Burn-In safety protocol, and (ii)
environmental acoustic sound classification/assessment for smart space CI systems. In the first
task, a two-phase analysis and safety evaluation protocol that can be systematically applied to
assess any RP in two phases is proposed, namely, (i) acoustic phase and (ii) electric stimulation
parameter phase. In the acoustic phase, the output electric/acoustic stimulation of RP for diverse
acoustic conditions are assessed for safety compliance and performance evaluation. In the
stimulation parameter phase, the reliability of a RP to accurately generate electrical stimuli that
are compliant with the established limits for safety are explored. The proposed “Burn-In”
evaluation protocol can be applied to any RP, and in this work, the Costakis Cochlear Implant
Mobile (CCi-MOBILE) RP is used for assessment. Additionally, guidelines for addressing
experimental variability such as custom algorithms, stimulation techniques, and best practices for
subsampling of the acoustic and parameter test spaces are addressed. Next, the second thesis
goal/task, acoustic sound space analysis and knowledge characterization is addressed. In general,
non-linguistic sound (NLS) perception plays an important role in engaging listener response to
various safety scenarios and enabling user autonomy, environmental awareness. However, most
CI research efforts are speech driven and improved perception of environmental sounds are
largely assumed, with some suggesting no benefit in NLS perception following implantation. In
this work, Convolutional Neural Network (CNN) based NLS classification models are used to
compare CI-simulated and NH classification performance with NH and CI human listener
performance. Furthermore, a novel NLS enhancement algorithm is proposed to improve NLS
perception among CI listeners. The NLS enhancement algorithm focuses on estimating filter
gains that optimally preserve the perceptually important spectro-temporal characteristics in CI
processing. The proposed NLS enhancement algorithm is evaluated for improvement in
identification using the NLS classification models. A competing NLS source model is also
developed using a mixture of two sound sources (i) ‘target’ (safety/threat interest) and (ii)
‘interference’. An end-to-end (E2E) deep source separation algorithm and proposed NLS
enhancement approaches are applied to assess improvement in ‘target' perception. NLS
perceptual characteristics are comparatively evaluated in baseline-mixed, source separated, and
source separated + NLS enhanced modes among CI and NH listeners. Listener responses based
on interference, audio quality, and distortion measures are recorded using a subjective scale and
forced choice pairwise preference based on a comparative assessment of source separation and
source separation + NLS enhancement techniques. Taken collectively, the contributions from CI
research platform , Burn-In safety assessment protocol, the first of its kind in the field, along
with the non-linguistic sound source analysis, enhancement and classification based on machine
learning/CNN model have contributed towards the advancements for next generation CI systems
The Effects of Gasoline Taxes and Efforts to Curb Carbon Dioxide Emissions
No full textThere are three chapters in my dissertation. In two of the three chapters, I use panel analysis and
an event study to examine the short-run and long-run impacts of state gasoline taxes, respectively.
In another chapter I track the -convergence of global carbon dioxide emissions, in order to tease
out the effects of the Kyoto Protocol on multilateral environmental cooperation.
The first chapter examines short-run pass-through rates of state excise gasoline taxes using
monthly data for US states from 1987-2011. We consider several factors that may affect pass-
through, including neighbor states, commuting patterns like miles travelled per person per day,
the percentage of people who commute by public transportation or work from home. We also
examine the asymmetric effects of tax increases versus tax decreases on pass-through. We find
state gasoline excise taxes are fully shifted to consumers, while wholesale prices are partially
shifted to retail prices, indicating that suppliers digest the increased input cost, but not the
increased tax burden. We also find a tax increase and a tax decrease have asymmetric effects on
pass-through when gasoline production is near capacity. More specifically, when supply is
highly constrained, the pass-through of a tax cut is only one third, while that of a tax increase is
one. In other words, when capacity constraints are binding, most of the benefits from a tax
decrease accrue to suppliers, while nearly all tax burdens from a tax increase accrue to
consumers. Furthermore, the pass-through rates decrease for the states with more neighbors,
implying that residents may avoid taxes by purchasing gasoline from neighboring states. Finally,
we find a state-level price elasticity of gasoline demand of .
The second chapter uses a weak -convergence method to examine the convergence of carbon
dioxide emissions per capita for a global sample of 152 countries for the time period 1960–2014.
We find evidence of convergence for both an OECD sample and a global sample. The global
convergence in emissions is mainly attributable to the strong convergence pattern for non-OECD
countries after 1997. This provides evidence that the Kyoto Protocol contributed to the
convergence in global CO2 emissions.
The third chapter uses state-level monthly dataset and a long-run event study to examine the
effects of state tax increases on future gasoline retail prices. Each tax increase is used as a data
point to develop a SUR model (Seemingly Unrelated Regressions) with wholesale prices
working as the control to investigate the changes in retail prices for the next ten months after
events. I find that the events cause a temporary decline in future retail prices for the next four
months, and higher tax increases cause bigger decline. In other words, the abnormal returns
resulting from the events take about five month to recover
Design of Large Wind Turbine Rotors Through Passive and Active Load Mitigation Strategies
No full textWind energy over the years has positioned itself to become a primary source of renewable
energy and this is attributed to the reduction in the Levelized Cost of Energy (LCOE).
Historically, this is accomplished by an increase in tower heights which allow access to higher
wind speeds, and also by increasing rotor diameters which allow for more power capture.
However, there are significant challenges that come with these large turbines like aeroelastic
instabilities of the blades due to their long and slender nature, and the need for more robust
turbine components that can withstand the larger loads associated with large turbines. This
has motivated the development of design strategies that incorporate different methods of load
alleviation to achieve optimized wind turbine designs that can result in lower LCOE. This
dissertation presents various methods of designing wind turbine rotors that take advantage
of passive and active load reduction strategies.
First, classical flutter is addressed for the design of large blades. Flutter is an aeroelastic
instability that contributes to fatigue damage, or in the worst case can least to sudden catastrophic turbine failure. A comprehensive evaluation of flutter behavior including classical
flutter, edgewise vibration, and flutter mode characteristics for two- and three-bladed wind
turbine blade designs is carried out. Further, a study is performed to evaluate mitigation
of flutter in the design process via structural redesign by evaluating the effect of leadingvi
edge and trailing edge reinforcement on flutter speed and hence demonstrates the ability to
increase the flutter speed and satisfy structural design requirements (such as fatigue) while
maintaining or even reducing blade mass. This flutter structural mitigation study is conducted for two wind turbine designs, one a two-bladed rotor and the other a three-bladed
rotor.
Second, a new rotor design methodology is developed to integrate active load control in the
form of controllable gurney flaps. A comprehensive sequential iterative design procedure
is developed that integrates aerodynamics, structural, and baseline turbine control system
design with advanced active load control into a design process. This procedure also takes into
account the contribution of loads on all major components of the turbine. To realize the best
LCOE reduction solution, new methods to evaluate blade structural properties are developed
wherein, the reductions in damage equivalent loads (i.e.; fatigue loads) due to a generic active
load control system are mapped to structural design improvements in terms of blade mass
reduction, cost reduction in other major turbine components, and LCOE reductions that
result from integration and redesign of the turbine with the active load control system.
Third, using the design methodologies established, newer rotor designs with a larger rotor
radius are explored to examine the impacts of the active load control system. These rotors
take advantage of the fatigue load reductions due to the controllable gurney flaps integrated
into the design. The effect of the controllable gurney flaps is evaluated for various blade and
non-blade component loads on the turbine. This methodology results in larger rotors that
have increased energy capture and reduced LCOE’s. For this study, two different turbine
operating strategies are followed, one limits the turbine power to that of the baseline while
the other allows the turbine to extract more power at higher wind speeds.
Finally, a method is introduced to support the realization of new passive and active load
mitigation strategies by improving prototype wind turbine development. A novel method
of developing a multi-fidelity digital twin structural model of a wind turbine blade is presented. The digital twin model development methodology, presented herein, involves a novel
calibration process to integrate a wide range of information including design specifications,
manufacturing information, and structural testing data (modal and static) to produce a
multi-fidelity digital twin structural model: a detailed high-fidelity model (i.e., 3D FEA)
and consistent beam-type models for aeroelastic simulation. Digital twin models are useful to cost-effectively evaluate the performance of new technologies in the field like novel
downwind rotors and controllable gurney flaps. Finally, the new methodology is demonstrated for an as-built two-bladed downwind prototype rotor resulting in a multi-fidelity
digital twin model which has a 1% match in mass properties, 3.2% in blade frequencies,
and 6% in deflection to the as-built blade. The rotor examined is the SUMR – Demonstrator (SUMR-D), which was installed on the Controls Advanced Research Testbed (CART-2)
wind turbine at the National Wind Technology Center. The digital twin model developed
here was utilized to design controllers to safely operate SUMR-D in field tests, which are
providing additional data for further evaluation and development of the multi-fidelity digital
twin structural model
Characterization and Modeling of Mechanical Behavior of Sandwich Composites and 3D-printed Polymers at Meso and Nano Scales
No full textThis dissertation covers the topics of mechanical characterizations of sandwich composites and
3D printed polymers which can potentially be used in the wind turbine blades. Chapter 1 is
studying the localized viscoelastic properties at the skin-core interphase of a sandwich composite
using a viscoelastic nanoindentation technique. The skin-core interphase stiffness is one of the
most important design factors in the sandwich composite. However, the stiffness distribution on
the interphase remains unclear. Chapter 2 is studying the effects of resin uptake on the mechanical
properties of sandwich composites under bending conditions. Improper resin uptake could lead to
the resin starvation issue in the matrix or interphase and decrease the stiffness of the skin. So,
defining an adequate range of the sandwich composite is essential in the design and optimization
of the sandwich composite. And the effect of resin uptake on the sandwich composite has rarely
been studied. Chapter 3 is studying the bonding quality of the displacement-controlled resistance
welded; adhesive-bonded slender 3D-printed PLA beams through three-point bending
experiments. The 3D printed polymer beams (e.g.; PLA, ABS, etc.) can act as the core material of
the sandwich composite. However, due to the limitation of the building volume of the conventional
3D printer, a good bonding technique is needed to extend the volume of the structure with
satisfactory structural integrity. How sufficient the 3D printed polymer is bonded together needs
further investigation. Chapter 4 is studying the in-plane and out-of-plane shear strength and
stiffness of the PVC foam core, balsa core, and 3D printed core sandwich composites by three-
point bending and four-point bending tests. The core material of the sandwich composites plays a
critical role in the structural integrity of the wind turbine blade. The 3D print process possesses a
lot of advantages compared with the traditional manufacturing routine. However, whether the 3D-
printed engineering core has the potential to replace the conventional core materials needs further
attention. Chapter 5 is studying the annealing effect on the flexural strength and modulus, and the
bonding quality of adhesive bonded, and thermoformed 3D-printed PLA beams and 3-inch chords
by three-point bending experiments. The Fused Deposition Modeling (FDM) possess is one of the
suitable manufacturing processes for the small-scale and thermoplastic wind turbine blades.
However, what types of 3D printing parameters are suitable for thermoplastic wind turbine blade
fabrication is still not clear. Also, the engineering structure fabricated by the FDM process usually
needs to strengthen the deposited layer adhesion to increase its durability. Whether the annealing
treatment is beneficial to the durability still needs further investigation.
Debonding at the core–skin interphase region is one of the primary failure modes in sandwich
composites under shear loads. As a result, the ability to characterize the mechanical properties at
the interphase region between the composite skin and core is critical for design analysis. This work
intends to use nanoindentation to characterize the viscoelastic properties at the interphase region,
which can potentially have mechanical properties changing from the composite skin to the core.
A sandwich composite using a polyvinyl chloride foam core covered with glass fiber/resin
composite skins was prepared by vacuum-assisted resin transfer molding. Nanoindentation at an
array of sites was made by a Berkovich nanoindenter tip. The recorded nanoindentation load and
depth as a function of time were analyzed using viscoelastic analysis. Results are reported for the
shear creep compliance and Young’s relaxation modulus at various locations of the interphase
region. The change of viscoelastic properties from higher values close to the fiber composite skin
region to the smaller values similar to the foam core was captured. The Young’s modulus at a
given strain rate, which is also equal to the time-averaged Young’s modulus across the interphase
region was obtained. The interphase Young’s modulus at a loading rate of 1 mN/s was determined
to change from 1.4 GPa close to composite skin to 0.8 GPa close to the core. This work
demonstrated the feasibility and effectiveness of nanoindentation-based interphase
characterizations to be used as an input for the interphase stress distribution calculations, which
can eventually enrich the design process of such sandwich composites.
Resin uptake plays a critical role in the stiffness-to-weight ratio of wind turbine blades in which
sandwich composites are used extensively. This work examines the flexural properties of
nominally half-inch thick sandwich composites made with polyvinyl chloride (PVC) foam cores
(H60 and H80; PSC and GPC) at several resin uptakes. We found that the specific flexural strength
and modulus for the H80 GPC sandwich composites increase from 82.04 to 90.70 ( ∙ ) ⁄
and 6.03 to 7.13 ( ∙ ) ⁄ , respectively, with 11.0 % resin uptake reduction, which stands
out among the four core sandwich composites. Considering reaching a high stiffness-to-weight
ratio while preventing resin starvation, 32 to 38 % and 40 to 45 % resin uptakes are adequate
ranges for the H80 PSC and GPC sandwich composites, respectively. The H60 GPC sandwich
composites have lower debonding toughness than H60 PSC due to stress concentration in the
smooth side skin-core interphase region. The failure mode of the sandwich composites depends on
the core stiffness and surface texture. The H60 GPC sandwich composites exhibit core shearing
and bottom skin-core debonding failure, while the H80 GPC and PSC sandwich composites show
top skin cracking and core crushing failure. The findings indicate that an appropriate range of resin
uptake exists for each type of core sandwich composite, and that within the range, a low-resin
uptake leads to lighter blades and thus lower cyclic gravitational loads, beneficial for long blades.
Fused deposition modeling (FDM) is often used in additive manufacturing of materials such as
thermoplastics and metals. Due to the size limitation in the building volume of an FDM system,
fusion joining two or more FDM printed parts allows upscaling to manufacture larger structures
by the assembly of printed subcomponent parts. In this work, a displacement-controlled joining
process was used, rather than a force-controlled process previously reported. The bonding quality
of the resistance welded, adhesive bonded slender polylactic acid (PLA) beams was investigated
using three-point bending experiments. The slender beams were fabricated by FDM with a 0.3 mm
layer thickness. Several infill patterns were explored, and it was determined that the 3D-triangular
infill pattern gives the highest flexural properties. Three types of metal mesh, namely 30% (open
area fraction)/ 0.11 mm (open size) Ni-Cu, 34%/0.07 mm Ni-Cu, and 36%/0.25 mm Co-Ni, were
used as the heating elements. The micrographs of the PLA slender beams resistance welded by the
three types of metal meshes show that there are no voids formed in the interphase region. Process
parameters were varied, including the power output, mesh opening size, wire diameter, wire
resistivity, initial joining pressure, displacement rate, and total displacement traveled. The
mechanical properties of the resistance welded beams are compared with those of the
corresponding beams printed continuously on FDM. Optimum process parameters were
determined for the configuration investigated. In general, a smaller opening size, smaller wire
diameter, and higher wire electrical resistivity are preferred in the resistance welding under a low
current to reach a higher bonding quality. A higher wire diameter with a larger opening size yields
a higher flexural modulus. The flexural strength does not depend on the types of materials used
for the Joule heating meshes; in addition, it does not depend on the mesh opening area fraction and
wire diameter. The beam samples joined by Ni/Cu mesh (34%/0.07 mm Ni-Cu metal mesh)
possesses 96%, 94%, and 88% of the flexural strength, modulus, and maximum allowable strain,
respectively, of the one continuous FDM printed sample; this sample gives the flexural properties
closest to the continuously printed sample. The adhesive, cohesive, substrate and opening crack
failure modes were captured for the resistance welded, adhesive bonded, and continuously printed
slender beams. The substrate failure mode is the most desired failure mode which correlated to the
highest bonding strength. Surface strain concentration was found in the bonding region. The
normal strain dominates when the flexural load is applied to the continuously printed sample.
Whether the 3D printed artifacts with the Fused Deposition Modeling (FDM) process remains
further investigation in structural engineering applications, especially in wind turbine industries.
In this work, the effect of resin uptake on shear strength and stiffness of compression-molded H60
PVC foam core, end-grain balsa core, and PLA lattice core sandwich composites were
systematically studied through three-point and four-point bending tests. The surface strain and
failure modes were investigated by DIC and fractured images. The skin/core bonding quality is
shown to affect the in-plane and out-of-plane shear strength and stiffness of the 3D printed lattice
core sandwich composites. The PLA filament is chosen for the 3D printed core material with
sufficient strength to weight ratio and cost-effectiveness. The out-of-plane and in-plane shear
strength and stiffness of two types of core sandwich composites were investigated by three-point
bending and four-point bending tests. In the 3D printed core sandwich composites, based on the
information on specific out-of-plane shear strength and stiffness, the optimized resin uptake regime
of PLA core sandwich composites is from 20.43% to 22.86%. In the PLA core sandwich
composites, the specific out-of-plane shear strength and stiffness increase from 19.22% to 20.43%
of resin uptake, and then decrease from 22.86% to 25.79%. Both low and high amounts of resin in
the interphase region of the 3D printed core sandwich composites lead to low bonding strength.
The in-plane shear strength and stiffness of three types of core sandwich composites were
computed based on the out-of-plane shear strength and stiffness. The specific in-plane shear
stiffness of 3D printed and raw balsa core sandwich composites are similar. The UV light curing
epoxy-based agent coated balsa core sandwich composites possess 8.19% and 15.16% higher
specific in-plane shear stiffness than 3D printed core sandwich composites within all resin uptake
regimes. The UV light curing epoxy-based agent coated balsa core sandwich composites possess
9.81% and 17.44% higher specific in-plane shear stiffness than 3D printed core sandwich
composites within an optimized resin uptake regime. The 3D printed core stands out among
conventional PVC core materials and is similar to conventional balsa core materials in shear and
specific shear strength and stiffness. As a result, this work presents some new and important
findings that support the greater use of additive manufacturing of core materials in applications
such as wind turbine blades. A few subjects still need to be studied in the future regarding the PLA
lattice core sandwich composites, including the performance under high cycle fatigue, debonding
toughness in the interphase region, and strategies for the interphase stiffness enhancement.
Small-scaled additively manufactured wind turbines give a solution for power generation in rural
areas and large-scale wind turbines performance prediction by on-site construction, hence reducing
the construction error and impact on the climate change. This work mainly investigates the effects
of annealing on the structural performance of 3D printed short beams and 3-inch chords (smooth,
adhesive bonded, thermoformed) by three-point bending experiments. The effect of vertical shells,
horizontal shells, bed temperature, nozzle temperature, and printing resolution was systematically
studied through three-point bending experiments. The 3D printed beams with 2 vertical shells and
4 horizontal shells possess the highest specific flexural modulus (4.81 × 10 3
± 37.24
( 3⁄ )⁄ ). The 3D printed beams with 3 vertical shells and 3 horizontal shells possess the
highest specific flexural strength (105.17 ± 1.17 ( 3⁄ )⁄ ). The 60 °C bed temperature and
215 °C nozzle temperature achieve the best-deposited layers adhesion quality. The 0.6 mm nozzle
diameter is an adequate resolution to 3D print a small-scale wind turbine blade with satisfactory
efficiency and complexity. The effect of the annealing time on the 3D printed short beams and 3-
inch chord were studied by three-point bending experiments. The 70 °C with 0.5 hours is an
adequate annealing plan for a constant temperature annealing treatment due to a relatively small
shrinkage under a unit heating time by a higher temperature for the smooth and adhesive bonded
type 3D printed structure. For the thermoformed 3D printed structure, no annealing treatment is
needed for maximizing the strength to weight ratio, annealing treatment is suggested for
maximizing the modulus to weight ratio. The thermal buckling and edge wrapping were captured
under the 70 °C/0.5 hour annealing treatment for 2 vertical shells and 4 horizontal shells 3D printed
beams. So, a sufficient thickness of the vertical side should be achieved to encounter the thermal
buckling and edge wrapping. Annealing treatment is not suitable for the 3-inch chord due to low
flexural strength, flexural stiffness improvement, and a high level of volumetric shrinkage on the
lengthwise
Living Cels: Tracing the Narrative of the Animation Art Object From Production to Collection
No full textAnalyzing the developmental and production art that survives from Walt Disney Studios’ 1959
animated feature Sleeping Beauty, as well as subsequent limited-edition collector’s cels and other
made-for-display objects, this thesis seeks to apply narrative theory to the realm of animation art
and its practices of collection. Animation as an art form evolved quickly throughout the course of
the 20th century, with the creation of thousands of physical objects such as conceptual paintings,
animation drawings, and painted cels necessitated by the production process for every cel-
animated feature until the late 1990s. Practices of collecting “animation art” gives way to unique
methods of display, conservation, and restoration – creating new art out of the by-products of
existing work by changing and recontextualizing immaterial animation through their static,
physical objects. The visual style of Disney’s Sleeping Beauty (1959) takes influences from
narrative medieval artwork and combines it with modern illustrative styles while employing
some of Disney’s most iconic artists, giving way to distinct and historically significant animation
art pieces that survive today. These vestigial artifacts are sought after due to their scarcity now
that the industry has turned primarily digital; however, animation art is much more than artifact.
Its allure stems from a combination of different narratives – the macro-narratives of the films
they represent, the micro-narratives that the objects visually depict, and the historical narratives
of the production process they took part of, implicit in their material qualities and marks of
authenticity. By considering how narrative is carried and transformed in Sleeping Beauty, the
works that inspired it, and the animation art that remains after its production wrapped, this thesis
exemplifies how story makes otherwise disposable objects appealing as art and suggests a
layered narrative imbued in animation art that simultaneously acknowledges its content,
materiality, and provenance to interpret the artform through the lens of narratology
Design and Synthesis of Polymer Nanocomposites for Additive Manufacturing
No full textAdditive manufacturing or 3D printing is a process where the materials are deposited in a layer-
by-layer fashion according to a pre-designed computer aided file to fabricate required geometries.
There are a wide range of materials from thermoplastics, polymeric resins, metals, alloys,
nanocomposites, to hydrogels that have been used in 3D printing, as well as several different types
of processes are available for 3D printing. Fused filament fabrication, ink jet printing,
stereolithography (SLA) and digital light projection (DLP) can be recognized as the most popular
and affordable techniques. This manufacturing technique is very promising as a user friendly,
customizable setup without the need to manufacture through expensive molding processes or
producing waste from subtractive manufacturing methods such as milling. Even though it
possesses all the advantages, poor interlayer adhesion, limited mechanical properties, low
resolution and rough surface finish is limiting its applications at large scale. Vat
photopolymerization 3D printing techniques provide better resolution as high as 10 μm for the
printed parts from SLA and DLP compared to other 3D printing techniques. Here, a photo resin
that contains photocurable monomers and oligomers, crosslinkers are polymerized in a print vat
using UV irradiation in the presence of a photoinitiator. The photo printed structures show fine
resolution and smooth surface finish, yet the mechanical properties of the printed parts are
inadequate for end use applications. To address this limitation different approaches were taken and
studied, thus the overall goal of this research was to enhance properties of 3D printed objects and
to develop methodologies to improve photo printing processes that would ultimately improve
intrinsic properties of the photo printed materials.
Chapter 1 of the dissertation provides a literature review about 3D printing techniques, materials,
and the limitations of additive manufacturing. This chapter further discusses the approaches taken
to overcome the limitations by introducing ways to improve the mechanical properties.
Chapter 2 describes our work in enhancing mechanical properties through a nanofiller derived
from Kevlar and how we successfully 3D printed photoresin formulations using stereolithography
without compromising printability. We discuss a methodology that can be used to incorporate
unprocessable fibrous fillers in a resin formulation.
Chapter 3 provides insights about how supramolecular interactions provide 3D printable materials
with noncovalent cross-linking and stimuli-responsive properties to improve their processability
and functionality. We evaluated urea formulations with aliphatic and aromatic sidechains and
showed physical evidence for the presence of hydrogen bonding using variable temperature
Fourier transform infrared (VT-ATR-FTIR) spectroscopy and van’t Hoff analysis. The self-
healing efficiency of these formulations was characterized by measuring the recovery of their
tensile mechanical properties.
Chapter 4 describes our approach to process Metal Organic-Frameworks in vat
photopolymerization. A new method is introduced to construct complex structures with fine
features by integrating high loading weight percentages of MOF crystals to a photocurable acrylate
formulation. Through free radical polymerization in a DLP setup, MOF loaded nanocomposites
were 3D printed, and its catalytic performances were studied
Charge Transport and Device Physics in Fullerene-based Organic Photovoltaics
No full textOrganic photovoltaics (OPV) has been one of the consistently researched photovoltaic (PV)
technology for the past three decades. Efficient charge generation, charge transport, and
collection process account for higher performance in OPV devices. Several donor and nonfullerene (NFA) acceptors are developed to enhance charge generation. However, charge
transport and collection still need critical understanding to further boost the device performance.
In this dissertation, we focus on characterizing the defect states for efficient charge collection
and charge transport mechanism in fullerene-based OPV devices. Surface photovoltage
spectroscopy (SPS) was applied to probe the defect states without fabricating the complete
devices. The physical location and the energetics of defect states are determined by comparing
two types of SPS and top layer deposition. Understanding the charge transport mechanism is
highly important in fullerene-based OPVs, where donor concentration is too low to form a
percolation path to the anode. The effect of device architecture was studied to gain insights into
the charge transport in fullerene-based OPV devices. From experimental results combined with
drift-diffusion simulations, we found the imbalance in carrier mobility between electrons and
holes results in inferior performance in inverted devices. Thienothiophene (TT)-based small
molecule donors was designed and synthesized to study the photocurrent generation in fullerenebased OPVs. The donor and acceptor must form type-II energy level alignment at its interface for
efficient exciton dissociation. We showed that the hole back transfers from donor to acceptor and
transports to the anode via fullerene matrix. The photocurrent generation results from the hole
back transfer mechanism in fullerene-based OPVs