Electrical and optical characterization of conducting polymers by THz time-domain spectroscopy

The absorption and index of refraction of polypyrrole (PPy) and poly-3-methylthiophene (PMeT), from low frequencies up to 4 THz, have been measured by tera-Herz (THz) time-domain spectroscopy. The complex conductance was obtained over this range of frequency. Highly conducting metallic samples follow the Drude model, whereas less conducting ones fit the localization-modified Drude model. The carrier scattering time and mobility in conducting polymers can be directly determined from these measurements.

Direct observation of low frequency confined acoustic phonons in silver nanoparticles: Terahertz time domain spectroscopy

Terahertz time domain spectroscopy has been used to study low frequency confined acoustic phonons of silver nanoparticles embedded in poly (vinyl alcohol) matrix in the spectral range of 0.1-2.5 THz. The real and imaginary parts of the dielectric function show two bands at 0.60 and 2.12 THz attributed to the spheroidal and toroidal modes of silver nanoparticles, thus demonstrating the usefulness of terahertz time domain spectroscopy as a complementary technique to Raman spectroscopy in characterizing the nanoparticles. (C) 2010 American Institute of Physics. [doi:10.1063/1.3456372]

Terahertz Time Domain Spectroscopy to Detect Low-Frequency Vibrations of Double-Walled Carbon Nanotubes

We have measured the frequency-dependent real index of refraction and extinction coefficient (and hence the complex dielectric function) of a free-standing double-walled carbon nanotube film of thickness 200 nm by using terahertz time domain spectroscopy in the frequency range 0.1 to 2.5 THz. The real index of refraction and extinction coefficient have very high values of approximately 52 and 35, respectively, at 0.1 THz, which decrease at higher frequencies. Two low-frequency phonon modes of the carbon nanotubes at 0.45 and 0.75 THz were clearly observed for the first time in the real and imaginary parts of the complex dielectric function along with a broad resonance centred at around 1.45 THz, the latter being similar to that in single-walled carbon nanotubes assigned to electronic excitations. Our experiments bring out a possible application of double-walled carbon nanotube films as a neutral density filter in the THz range.

Terahertz time domain spectroscopy of amino acids and sugars

A time-domain spectrometer for use in the terahertz (THz) spectral range was designed and constructed. Due to there being few existing methods of generating and detecting THz radiation, the spectrometer is expected to have vast applications to solid, liquid, and gas phase samples. In particular, knowledge of complex organic chemistry and chemical abundances in the interstellar medium (ISM) can be obtained when compared to astronomical data. The THz spectral region is of particular interest due to reduced line density when compared to the millimeter wave spectrum, the existence of high resolution observatories, and potentially strong transitions resulting from the lowest-lying vibrational modes of large molecules.

The heart of the THz time-domain spectrometer (THz-TDS) is the ultrafast laser. Due to the femtosecond duration of ultrafast laser pulses and an energy-time uncertainty relationship, the pulses typically have a several-THz bandwidth. By various means of optical rectification, the optical pulse carrier envelope shape, i.e. intensity-time profile, can be transferred to the phase of the resulting THz pulse. As a consequence, optical pump-THz probe spectroscopy is readily achieved, as was demonstrated in studies of dye-sensitized TiO₂, as discussed in chapter 4. Detection of the terahertz radiation is commonly based on electro-optic sampling and provides full phase information. This allows for accurate determination of both the real and imaginary index of refraction, the so-called optical constants, without additional analysis. A suite of amino acids and sugars, all of which have been found in meteorites, were studied in crystalline form embedded in a polyethylene matrix. As the temperature was varied between 10 and 310 K, various strong vibrational modes were found to shift in spectral intensity and frequency. Such modes can be attributed to intramolecular, intermolecular, or phonon modes, or to some combination of the three.

An efficient frequency-domain algorithm for wave scattering problems with application to jet noise

This paper presents a pseudo-time-step method to calculate a (vector) Green function for the adjoint linearised Euler equations as a scattering problem in the frequency domain, for use as a jet-noise propagation prediction tool. A method of selecting the acoustics-related solution in a truncated spatial domain while suppressing any possible shear-layer-type instability is presented. Numerical tests for 3-D axisymmetrical parallel mean flows against semi-analytical reference solutions indicate that the new iterative algorithm is capable of producing accurate solutions with modest computational requirements.

On the localization of water-soluble porphyrins in micellar systems evaluated by static and time-resolved frequency-domain fluorescence techniques

Fluorescence quenching of meso-tetrakis-4-sulfonatophenyl (TPPS4) and meso-tetrakis-4-N-methylpyridil (TMPyP) porphyrins is studied in aqueous solution and upon addition of micelles of sodium dodecylsulfate (SDS), cetyltrimethylammonium chloride (CTAC), N-hexadecyl-N,N-dimethyl-3-ammonio-1-propanesulfonate (HPS) and t-octylphenoxypolyethoxyethanol (Triton X-100). Potassium iodide (KI) was used as quencher. Steady-state Stern-Volmer plots were best fitted by a quadratic equation, including dynamic (K-D) and static (K-s) quenching. Ks was significantly smaller than K-D. Frequency-domain fluorescence lifetimes allowed estimating bimolecular quenching constants, k(q). At 25 degrees C, in aqueous solution, TMPyP shows k(q), values a factor of 2-3 higher than the diffusional limit. TPPS4 shows collisional quenching with pH dependent k(q) values. For TMPyP quenching results are consistent with reported binding constants: a significant reduction of quenching takes place for SDS, a moderate reduction is observed for H PS and almost no change is seen for Triton X-100. Similar data were obtained at 50 C. For CTAC-TPPS4 system an enhancement of quenching was observed as compared to pure buffer. This is probably associated to accumulation of iodide at the cationic micellar interface. The attraction between CTAC headgroups and 1(-), and repulsion between SDS and 1(-), enhances and reduces the fluorescence quenching, respectively, of porphyrins located at the micellar interface. The small quenching of TPPS4 in Triton X-100 is consistent with strong binding as reported in the literature. (C) 2008 Elsevier B.V. All rights reserved.

Probing the aging effect in metallic polypyrrole by terahertz time-domain spectroscopy

Terahertz time-domain spectroscopy has been carried out on a metallic film of polypyrrole (PPy doped by PF6). The sample was exposed to air to investigate how the conductivity of the film varies as a function of time. The absorption and dispersion of the film decrease during initial days, and then tend to saturate. The conductivity of unaged sample follows the Drude model, and upon aging the data fit to the localization-modified Drude model. The fitting parameters show that the number of charge carriers decreases during the aging process. The initial rapid decrease in conductivity suggests that some of the delocalized carriers are localized due to aging. (C) 2007 American Institute of Physics.

Wave propagation and the frequency domain Green's functions in viscoelastic Biot/squirt (BISQ) media

In this paper, we examine the characteristics of elastic wave propagation in viscoelastic porous media, which contain simultaneously both the Biot-flow and the squirt-flow mechanisms (BISQ). The frequency-domain Green's functions for viscoelastic BISQ media are then derived based on the classic potential function methods. Our numerical results show that S-waves are only affected by viscoelasticity, but not by squirt-flows. However, the phase velocity and attenuation of fast P-waves are seriously influenced by both viscoelasticity and squirt-flows; and there exist two peaks in the attenuation-frequency variations of fast P-waves. In the low-frequency range, the squirt-flow characteristic length, not viscoelasticity, affects the phase velocity of slow P-waves, whereas it is opposite in the high-frequency range. As to the contribution of potential functions of two types of compressional waves to the Green's function, the squirt-flow length has a small effect, and the effects of viscoelastic parameter are mainly in the higher frequency range. Crown Copyright (C) 2006 Published by Elsevier Ltd. All rights reserved.

Upper hybrid resonance absorption and scattering from a plasma column

The electromagnetic scattering and absorption properties of small (kr~1/2) inhomogeneous magnetoplasma columns are calculated via the full set of Maxwell's equations with tensor dielectric constitutive relation. The cold plasma model with collisional damping is used to describe the column. The equations are solved numerically, subject to boundary conditions appropriate to an infinite parallel strip line and to an incident plane wave. The results are similar for several density profiles and exhibit semiquantitative agreement with measurements in waveguide. The absorption is spatially limited, especially for small collision frequency, to a narrow hybrid resonant layer and is essentially zero when there is no hybrid layer in the column. The reflection is also enhanced when the hybrid layer is present, but the value of the reflection coefficient is strongly modified by the presence of the glass tube. The nature of the solutions and an extensive discussion of the conditions under which the cold collisional model should yield valid results is presented.

Advanced Monte Carlo Simulation and Machine Learning for Frequency Domain Optical Coherence Tomography

Optical Coherence Tomography(OCT) is a popular, rapidly growing imaging technique with an increasing number of bio-medical applications due to its noninvasive nature. However, there are three major challenges in understanding and improving an OCT system: (1) Obtaining an OCT image is not easy. It either takes a real medical experiment or requires days of computer simulation. Without much data, it is difficult to study the physical processes underlying OCT imaging of different objects simply because there aren't many imaged objects. (2) Interpretation of an OCT image is also hard. This challenge is more profound than it appears. For instance, it would require a trained expert to tell from an OCT image of human skin whether there is a lesion or not. This is expensive in its own right, but even the expert cannot be sure about the exact size of the lesion or the width of the various skin layers. The take-away message is that analyzing an OCT image even from a high level would usually require a trained expert, and pixel-level interpretation is simply unrealistic. The reason is simple: we have OCT images but not their underlying ground-truth structure, so there is nothing to learn from. (3) The imaging depth of OCT is very limited (millimeter or sub-millimeter on human tissues). While OCT utilizes infrared light for illumination to stay noninvasive, the downside of this is that photons at such long wavelengths can only penetrate a limited depth into the tissue before getting back-scattered. To image a particular region of a tissue, photons first need to reach that region. As a result, OCT signals from deeper regions of the tissue are both weak (since few photons reached there) and distorted (due to multiple scatterings of the contributing photons). This fact alone makes OCT images very hard to interpret.

This thesis addresses the above challenges by successfully developing an advanced Monte Carlo simulation platform which is 10000 times faster than the state-of-the-art simulator in the literature, bringing down the simulation time from 360 hours to a single minute. This powerful simulation tool not only enables us to efficiently generate as many OCT images of objects with arbitrary structure and shape as we want on a common desktop computer, but it also provides us the underlying ground-truth of the simulated images at the same time because we dictate them at the beginning of the simulation. This is one of the key contributions of this thesis. What allows us to build such a powerful simulation tool includes a thorough understanding of the signal formation process, clever implementation of the importance sampling/photon splitting procedure, efficient use of a voxel-based mesh system in determining photon-mesh interception, and a parallel computation of different A-scans that consist a full OCT image, among other programming and mathematical tricks, which will be explained in detail later in the thesis.

Next we aim at the inverse problem: given an OCT image, predict/reconstruct its ground-truth structure on a pixel level. By solving this problem we would be able to interpret an OCT image completely and precisely without the help from a trained expert. It turns out that we can do much better. For simple structures we are able to reconstruct the ground-truth of an OCT image more than 98% correctly, and for more complicated structures (e.g., a multi-layered brain structure) we are looking at 93%. We achieved this through extensive uses of Machine Learning. The success of the Monte Carlo simulation already puts us in a great position by providing us with a great deal of data (effectively unlimited), in the form of (image, truth) pairs. Through a transformation of the high-dimensional response variable, we convert the learning task into a multi-output multi-class classification problem and a multi-output regression problem. We then build a hierarchy architecture of machine learning models (committee of experts) and train different parts of the architecture with specifically designed data sets. In prediction, an unseen OCT image first goes through a classification model to determine its structure (e.g., the number and the types of layers present in the image); then the image is handed to a regression model that is trained specifically for that particular structure to predict the length of the different layers and by doing so reconstruct the ground-truth of the image. We also demonstrate that ideas from Deep Learning can be useful to further improve the performance.

It is worth pointing out that solving the inverse problem automatically improves the imaging depth, since previously the lower half of an OCT image (i.e., greater depth) can be hardly seen but now becomes fully resolved. Interestingly, although OCT signals consisting the lower half of the image are weak, messy, and uninterpretable to human eyes, they still carry enough information which when fed into a well-trained machine learning model spits out precisely the true structure of the object being imaged. This is just another case where Artificial Intelligence (AI) outperforms human. To the best knowledge of the author, this thesis is not only a success but also the first attempt to reconstruct an OCT image at a pixel level. To even give a try on this kind of task, it would require fully annotated OCT images and a lot of them (hundreds or even thousands). This is clearly impossible without a powerful simulation tool like the one developed in this thesis.