Nanoindentation study of buckling and friction of silicon nanolines

textSilicon-based nanostructures are essential building blocks for nanoelectronic devices and nano-electromechanical systems (NEMS). As the silicon device size continues to scale down, the surface to volume ratio becomes larger, rendering the properties of surfaces and interfaces more important for improving the properties of the nano-devices and systems. One of those properties is the friction, which is important in controlling the functionality and reliability of the nano-device and systems. The goal of this dissertation is to investigate the deformation and friction behaviors of single crystalline silicon nanolines (SiNLs) using nanoindentation techniques. Following an introduction and a summary of the theoretical background of contact friction in Chapters 1 and 2, the results of this thesis are presented in three chapters. In Chapter 3, the fabrication of the silicon nanolines is described. The fabrication method yielded high-quality single-crystals with line width ranging from 30nm to 90nm and height to width aspect ratio ranging from 10 to 25. These SiNL structures have properties and dimensions well suited for the study of the mechanical and friction behaviors at the nanoscale. In Chapter 4, we describe the study of the mechanical properties of SiNLs using the nanoindentation method. The loading-displacement curves show that the critical load to induce the buckling of the SiNLs can be correlated to the contact friction and geometry of SiNLs. A map was built as a guideline to describe the selection of buckling modes. The map was divided into three regions where different regions correlate to different buckling modes including Mode I, Mode II and slidingbending of SiNLs. In Chapter 5, we describe the study of the contact friction of the SiNL structures. The friction coefficient at the contact was extracted from the loaddisplacement curves. Subsequently, the frictional shear stress was evaluated. In addition, the effect of the interface between the indenter and SiNLs was investigated using SiNLs with surfaces coated by a thin silicon dioxide or chromium film. The material of the interface was found to influence significantly the contact friction and its behavior. Cyclic loading-unloading experiments showed the friction coefficient dramatically changed after only a few loading cycles, indicating the contact history is important in controlling the friction behaviors of SiNLs at nanoscales. This thesis is concluded with a summary of the results and proposed future studies.Physic

Robust Unsupervised Cross-Lingual Word Embedding using Domain Flow Interpolation

This paper investigates an unsupervised approach towards deriving a universal, cross-lingual word embedding space, where words with similar semantics from different languages are close to one another. Previous adversarial approaches have shown promising results in inducing cross-lingual word embedding without parallel data. However, the training stage shows instability for distant language pairs. Instead of mapping the source language space directly to the target language space, we propose to make use of a sequence of intermediate spaces for smooth bridging. Each intermediate space may be conceived as a pseudo-language space and is introduced via simple linear interpolation. This approach is modeled after domain flow in computer vision, but with a modified objective function. Experiments on intrinsic Bilingual Dictionary Induction tasks show that the proposed approach can improve the robustness of adversarial models with comparable and even better precision. Further experiments on the downstream task of Cross-Lingual Natural Language Inference show that the proposed model achieves significant performance improvement for distant language pairs in downstream tasks compared to state-of-the-art adversarial and non-adversarial models

Event-triggered optimal control of completely unknown nonlinear systems via identifier-critic learning

summary:This paper proposes an online identifier-critic learning framework for event-triggered optimal control of completely unknown nonlinear systems. Unlike classical adaptive dynamic programming (ADP) methods with actor-critic neural networks (NNs), a filter-regression-based approach is developed to reconstruct the unknown system dynamics, and thus avoid the dependence on an accurate system model in the control design loop. Meanwhile, NN adaptive laws are designed for the parameter estimation by using only the measured system state and input data, and facilitate the identifier-critic NN design. The convergence of the adaptive laws is analyzed. Furthermore, in order to reduce state sampling frequency, two kinds of aperiodic sampling schemes, namely static and dynamic event triggers, are embedded into the proposed optimal control design. Finally, simulation results are presented to demonstrate the effectiveness of the proposed event-triggered optimal control strategy

Improved Differential Cryptanalysis on SPECK Using Plaintext Structures

Plaintext structures are a commonly-used technique for improving differential cryptanalysis. Generally, there are two types of plaintext structures: multiple-differential structures and truncated-differential structures. Both types have been widely used in cryptanalysis of S-box-based ciphers while for SPECK, an Addition-Rotation-XOR (ARX) cipher, the truncated-differential structure has not been used so far. In this paper, we investigate the properties of modular addition and propose a method to construct truncated-differential structures for SPECK. Moreover, we show that a combination of both types of structures is also possible for SPECK. For recovering the key of SPECK, we propose dedicated algorithms and apply them to various differential distinguishers, which helps to obtain a series of improved attacks on all variants of SPECK. Notably, on SPECK128, the time complexity of the attack can be reduced by a factor up to 2^15. The results show that the combination of both structures helps to improve the data and time complexity at the same time, as in the cryptanalysis of S-box-based ciphers

Comparison of Apparent Diffusion Coefficient and T2 Relaxation Time Variation Patterns in Assessment of Age and Disc Level Related Intervertebral Disc Changes

Purpose To compare the variation patterns of ADC and T2 values in different age and intervertebral disc (IVD) levels, thus to identify their sensitivities in assessing age and disc level related IVDs changes. Materials and Methods The T2 and ADC values were recorded from 345 IVDs of 69 volunteers. Kendall's correlation analysis was used to identify the relationship between age and T2/ADC mean values respectively. The one-way analysis of variance (ANOVA) with post hoc analysis was then applied to test the differences of T2 and ADC values among different IVD levels and age groups, followed by linear regression analysis between age (45 years) and T2/ADC mean values. This study was approved by the Ethics Committee of the Chinese Academy of Medical Sciences and the Peking Union Medical College Hospital. Results: Significant negative correlation was observed between age and T2/ADC mean values. The T2 and ADC values showed significant differences among IVD levels and among age groups except for T2 values in age group 1 (25–34 years) and group 2 (35–44 years), and for ADC values at L1–2 level. Both T2 and ADC values showed significant differences between young (age45 years) at each IVD level. A linear relationship was observed between age and T2/ADC mean values in the elderly group as well as in the young group for the ADC mean values, while no such tendency was identified in the young group for the T2 mean values. Conclusions: ADC values may be a more sensitive parameter than T2 in assessing age and disc level related intervertebral disc changes

Adherence to diabetes risk reduction diet and the risk of head and neck cancer: a prospective study of 101,755 American adults

BackgroundAdherence to the diabetes risk reduction diet (DRRD) may potentially reduce the risk of developing head and neck cancer (HNC) as the diet includes fruits and limits red and processed meats, known risk factors for HNC. However, there is currently no epidemiological research to investigate this potential association.MethodsThe present study utilized data on demographics, lifestyles, medications, and diets of participants from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to explore the potential association between adherence to DRRD and the risk of HNC. We used a DRRD score to evaluate adherence to the dietary pattern and employed Cox regression analysis to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for HNC risk. Several subgroup analyses were carried out to identify potential effect modifiers, and multiple sensitivity analyses were performed to evaluate the stability of the correlation. The nine components of the DRRD was assessed separately for its association with the risk of HNC.ResultsDuring a mean follow up of 8.84 years, 279 cases of HNC were observed. DDRD score was found to be inversely associated with the risk of HNC (HR Q4 vs. Q1: 0.582; 95% CI: 0.396, 0.856; p = 0.005 for trend) in a linear dose–response manner (p = 0.211 for non-linearity). Subgroup analysis indicated this inverse correlation was more pronounced among participants who had never smoked (HRQ4 vs. Q1: 0.193; 95% CI: 0.073, 0.511; p < 0.001 for trend) compared to current or former smokers (p = 0.044 for interaction). The primary association of DDRD and HNC risk remained robust after several sensitivity analyses. Regarding the individual components of DRRD, an inverse association was also observed between the risk of HNC and increased intake of cereal fiber and whole fruit (all p < 0.05 for trend).ConclusionOur findings provide evidence that following the DRRD pattern may reduce the risk of NHC, especially for non-smokers

Wolfgang FreyNanoindentation Study of Buckling and Friction of Silicon Nanolines By

To my wife, Xiaoning Liu and my son, Daniel LuoAcknowledgements I would like to express my gratitude to all those who gave me the possibility to complete this thesis. During the last several years, I had enormous help and support from many friends and teachers. Without them, I would not finish my degree at the University of Texas at Austin. First, I am deeply indebted to my advisor, Prof. Paul S. Ho. Without Dr. Ho’s continuous support and advice, both professionally and personally, thought out my doctoral work, I was unable to make progress toward the finishing of my degree. I would like to extend my sincere appreciation to all my graduate committee members, Prof. Chih-Kang Shih, Prof. Ernst-Ludwig Florin, Prof. Zhen Yao, and Prof. Wolfgang Frey for serving the committee and their support and encouragement. I specially thank Dr. Jang-Hi Im for his continuous support and advice throughout my doctoral work; thank Dr. Ryan Scott Smith and Dr. Bin Li for numerous suggestions and invaluable help on my thesis. I also want to take this opportunity to thank my colleagues and friends in the Laboratory for Interconnect and Packaging for their advice and discussions about m