Studies of polymer thin films using atomic force microscopy

This thesis focuses on how the properties of polymer thin films depend on the film thickness and molecular weight (Mw). Previous studies of polystyrene (PS) films coated on silica with Mw of 2.4 and 212 kg/mol found that the viscosity of the films decreases with decreasing film thickness. A two-layer model assuming a 3 nm thick mobile layer situated at the top surface of the film and hydrodynamically coupled to a bulklike inner layer is able to describe the viscosity of the films. To better understand the dynamics exhibited by the surface mobile layer, this work extends the measurement to various other Mw up to 2316 kg/mol. The result shows that the viscosity of the films also decreases with decreasing film thickness and can be described by the same two-layer model. But there are exceptional findings as well. Specifically, the viscosity of the high-Mw films (> 60 kg/mol) exhibit a Mw^0 dependence, distinctly different from the Mw^3.4 dependence exhibited by the viscosity of the bulk polymer. Moreover, the surface chains in the high-Mw films, as inferred from the two-layer model, are in an unphysically stretched state. These observations led to the conjecture that the viscosity reduction in the high-Mw films is due to a different mechanism from that in the lower Mw films which is directly tied to the surface mobile layer as in the two-layer model. To scrutinize this conjecture, viscosity measurement is extended to PS films doped with Dioctyl phthalate (DOP). A previous experiment showed that the influence of the surface on the overall dynamics in this system is likely to be much smaller than in the undoped films. The measurement results are examined to determine, among other things, whether the viscosity reduction relative to that in the undoped films is weaker in the low-Mw than in the high-Mw regime

Pyramiding stacking of multigenes (PSM): a simple, flexible and efficient multigene stacking system based on Gibson assembly and gateway cloning

Genetic engineering of complex metabolic pathways and multiple traits often requires the introduction of multiple genes. The construction of plasmids carrying multiple DNA fragments plays a vital role in these processes. In this study, the Gibson assembly and Gateway cloning combined Pyramiding Stacking of Multigenes (PSM) system was developed to assemble multiple transgenes into a single T-DNA. Combining the advantages of Gibson assembly and Gateway cloning, the PSM system uses an inverted pyramid stacking route and allows fast, flexible and efficient stacking of multiple genes into a binary vector. The PSM system contains two modular designed entry vectors (each containing two different attL sites and two selectable markers) and one Gateway-compatible destination vector (containing four attR sites and two negative selection markers). The target genes are primarily assembled into the entry vectors via two parallel rounds of Gibson assembly reactions. Then, the cargos in the entry constructs are integrated into the destination vector via a single tube Gateway LR reaction. To demonstrate PSM’s capabilities, four and nine gene expression cassettes were respectively assembled into the destination vector to generate two binary expression vectors. The transgenic analysis of these constructs in Arabidopsis demonstrated the reliability of the constructs generated by PSM. Due to its flexibility, simplicity and versatility, PSM has great potential for genetic engineering, synthetic biology and the improvement of multiple traits

Deep learning for seismic phase detection and picking in the aftershock zone of 2008 M_W 7.9 Wenchuan Earthquake

The increasing volume of seismic data from long-term continuous monitoring motivates the development of algorithms based on convolutional neural network (CNN) for faster and more reliable phase detection and picking. However, many less studied regions lack a significant amount of labeled events needed for traditional CNN approaches. In this paper, we present a CNN-based Phase-Identification Classifier (CPIC) designed for phase detection and picking on small to medium sized training datasets. When trained on 30,146 labeled phases and applied to one-month of continuous recordings during the aftershock sequences of the 2008 M_W 7.9 Wenchuan Earthquake in Sichuan, China, CPIC detects 97.5% of the manually picked phases in the standard catalog and predicts their arrival times with a five-times improvement over the ObsPy AR picker. In addition, unlike other CNN-based approaches that require millions of training samples, when the off-line training set size of CPIC is reduced to only a few thousand training samples the accuracy stays above 95%. The deployment of CPIC takes less than 12 h to pick arrivals in 31-day recordings on 14 stations. In addition to the catalog phases manually picked by analysts, CPIC finds more phases for existing events and new events missed in the catalog. Among those additional detections, some are confirmed by a matched filter method while others require further investigation. Finally, when tested on a small dataset from a different region (Oklahoma, US), CPIC achieves 97% accuracy after fine tuning only the fully connected layer of the model. This result suggests that the CPIC developed in this study can be used to identify and pick P/S arrivals in other regions with no or minimum labeled phases

The Causal Learning of Retail Delinquency

This paper focuses on the expected difference in borrower's repayment when there is a change in the lender's credit decisions. Classical estimators overlook the confounding effects and hence the estimation error can be magnificent. As such, we propose another approach to construct the estimators such that the error can be greatly reduced. The proposed estimators are shown to be unbiased, consistent, and robust through a combination of theoretical analysis and numerical testing. Moreover, we compare the power of estimating the causal quantities between the classical estimators and the proposed estimators. The comparison is tested across a wide range of models, including linear regression models, tree-based models, and neural network-based models, under different simulated datasets that exhibit different levels of causality, different degrees of nonlinearity, and different distributional properties. Most importantly, we apply our approaches to a large observational dataset provided by a global technology firm that operates in both the e-commerce and the lending business. We find that the relative reduction of estimation error is strikingly substantial if the causal effects are accounted for correctly.Comment: This paper was accepted and will be published in the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21

Nanoscale Cathodoluminescence Spectroscopy Probing the Nitride Quantum Wells in an Electron Microcope

To gain a deeper understanding of the luminescence of multiquantum wells and the factors affecting it on a microscopic level, cathodoluminescence combined with scanning transmission electron microscopy and spectroscopy was used to reveal the luminescence of In0.15Ga0.85N five-period multiquantum wells. The composition-wave-energy relationship was established in combination with energy-dispersive X-ray spectroscopy , and the bandgaps of In0.15Ga0.85N and GaN in multiple quantum wells were extracted by electron energy loss spectroscopy to understand the features of cathodoluminescence luminescence spectra. The luminescence differences between different periods of multiquantum wells and the effects on the luminescence of multiple quantum wells owing to defects such as composition fluctuation and dislocations were revealed. Our study establishing the direct correspondence between the atomic structure of InxGa1-xN multiquantum wells and photoelectric properties, provides useful information for nitride applications.Comment: 13 pages,4 figure

Abundant aftershock sequence of the 2015 M_w7.5 Hindu Kush intermediate-depth earthquake

The 2015 M_w7.5 Hindu Kush earthquake occurred at a depth of 213 km beneath the Hindu Kush region of Afghanistan. While many early aftershocks were missing from the global earthquake catalogues, this sequence was recorded continuously by eight broad-band stations within 500 km. Here we use a waveform matching technique to systematically detect earthquakes around the main shock. More than 3000 events are detected within 35 d after the main shock, as compared with 42 listed in the Advanced National Seismic System catalogue (or 196 in the International Seismological Centre catalogue). The aftershock sequence generally follows the Omori's law with a decay constant p = 0.92. We also apply the recently developed double-pair double-difference technique to relocate all detected aftershocks. Most of them are located to the west of the hypocentre of the main shock, consistent with the westward propagation of the main-shock rupture. The aftershocks outline a nearly vertical southward dipping plane, which matches well with one of the nodal planes of the main shock. We conclude that the aftershock sequence of this intermediate-depth earthquake shares many similarities with those for shallow earthquakes and infer that there are some common mechanisms responsible for shallow and intermediate-depth earthquakes

SAPPHIRE: Search for exotic parity-violation interactions with quantum spin amplifiers

Quantum sensing provides sensitive tabletop tools to search for exotic spin-dependent interactions beyond the Standard Model, which has attracted great attention in theories and experiments. Here we develop a technique based on quantum Spin Amplifier for Particle PHysIcs REsearch (SAPPHIRE) to resonantly search for exotic interactions, specifically parity-odd spin-spin interactions. The present technique effectively amplifies the pseudomagnetic field generated by exotic interactions by a factor of about 200 while being insensitive to spurious external magnetic fields. Our studies, using such a quantum amplification technique, open the doors to exploring the parity-violation interactions mediated by Z' bosons in the challenging parameter space (force range between 3 mm and 0.1 km) and set the most stringent constraints on Z'-mediated electron-neutron couplings, significantly improving previous limits by up to five orders of magnitude. Moreover, our bounds on Z'-mediated couplings between nucleons reaches into a hitherto unexplored parameter space (force range below 1 m), complementing the existing astrophysical and laboratory studies.Comment: 8 pages, 5 figure

(E)-1-(3,5-Difluoro­phen­yl)-3-(2,4-dimeth­oxy­phen­yl)prop-2-en-1-one

The title compound, C17H14F2O3, is approximately planar, the dihedral angle between the rings being 5.46 (2)°. The H atoms of the central propenone group are trans. The crystal structure is stabilized by inter­molecular C—H⋯F hydrogen bonds