Nanomechanical characterization of quantum interference in a topological insulator nanowire

The discovery of two-dimensional gapless Dirac fermions in graphene and topological insulators (TI) has sparked extensive ongoing research toward applications of their unique electronic properties. The gapless surface states in three-dimensional insulators indicate a distinct topological phase of matter with a non-trivial Z2 invariant that can be verified by angle-resolved photoemission spectroscopy or magnetoresistance quantum oscillation. In TI nanowires, the gapless surface states exhibit Aharonov-Bohm (AB) oscillations in conductance, with this quantum interference effect accompanying a change in the number of transverse one-dimensional modes in transport. Thus, while the density of states (DOS) of such nanowires is expected to show such AB oscillation, this effect has yet to be observed. Here, we adopt nanomechanical measurements that reveal AB oscillations in the DOS of a topological insulator. The TI nanowire under study is an electromechanical resonator embedded in an electrical circuit, and quantum capacitance effects from DOS oscillation modulate the circuit capacitance thereby altering the spring constant to generate mechanical resonant frequency shifts. Detection of the quantum capacitance effects from surface-state DOS is facilitated by the small effective capacitances and high quality factors of nanomechanical resonators, and as such the present technique could be extended to study diverse quantum materials at nanoscale.Comment: 15+16 pages, 4+11 figure

An Empirical Investigation of Smart Product Adoption

The advance of information technologies and the Internet have been enabling the transformation of physical products into smart products by embedding information technologies into the products and thereby making them intelligent. The movement to the ‘Internet of Things’ is accelerating connection of the products to the net. While those changes could enhance value propositions of products, they might also cause consumer privacy concerns, which might hinder smart product adoption, because the smartness of the product mainly takes advantage of personal information about the users. This study aims to investigate consumers’ intention to adopt smart products. Building on previous studies on smart products and privacy literature, we propose a research model that explains factors influencing consumers’ intention to adopt smart products. The proposed research model is empirically tested using data from an online survey of consumers. The overall results validate the proposed research model of smart product adoption. Specifically, perceived personalization is found to positively affect consumers’ intention to adopt smart products, whereas information privacy risk decreases the intention. We also find that the attributes of personal information are critical antecedents of consumers’ risk-benefit assessment. The sensitivity of information increases information privacy risk while the congruency of information enhances perceived personalization. Based on the results, theoretical and managerial implications are discussed

Strain Rate Effect on High Performance Fiber Reinforced Cementitious Composites Using Slip Hardening High Strength Steel Fibers.

The objective of this research is to develop an understanding of the high strain rate response of High Performance Fiber Reinforced Cementitious Composites (HPFRCC). The research is divided into four parts. In the first, HPFRCC with high tensile strength (>10MPa) and ductility (>0.5%) is developed by using slip hardening fibers within a high strength mortar. Two types of fibers, twisted and hooked, are used in volume fractions ranging from 1 to 2%. The large slip capacity of twisted fibers during pullout generates large pullout energy (large equivalent bond strength), and thus leads to high strain capacity composites with multiple micro-cracks. In the second part, experiments are performed to investigate the effect of strain rate on fiber pullout and composite response. The rate sensitivity of HPFRCC in tension depends on fiber type, volume fraction and matrix strength (or composition). As the strain rate increases, HPFRCC with twisted fibers exhibits a pronounced, beneficial strain rate effect, i.e. a higher tensile strength is achieved with no reduction in strain capacity. In contrast, HPFRCC with hooked fiber show no clear strain rate effect. In the third part of this work, a new impact test system that employs suddenly released elastic strain energy is developed to enable impact testing for cementitious composites with large-sized specimen. A prototype system that was simulated and built is only 1.5m in height and can generate a high rate impact pulse. Compared to current impact test system, the new setup is inexpensive, small, portable, safe and easy to operate. Finally, the source of strength enhancement for cement-based materials under high rate compressive loadings was investigated through computational simulation models. The observed strain rate effect or mortar under compression is primarily, but not totally, due to lateral inertial effects under high rate loading and the pressure dependent nature of cementitious materials. The test and simulation results show that it is possible to develop a high performance cementitious composite with 1% to 2% volume fraction of fibers that has high energy absorption capacity and that can therefore be used to mitigate the effect of extreme loading such as earthquakes, impact, and blast.Ph.D.Civil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/62226/1/kdjoo_1.pd

Heart rate variability as a preictal marker for determining the laterality of seizure onset zone in frontal lobe epilepsy

Determining the laterality of the seizure onset zone is challenging in frontal lobe epilepsy (FLE) due to the rapid propagation of epileptic discharges to the contralateral hemisphere. There is hemispheric lateralization of autonomic control, and heart rate is modulated by interactions between the sympathetic and parasympathetic nervous systems. Based on this notion, the laterality of seizure foci in FLE might be determined using heart rate variability (HRV) parameters. We explored preictal markers for differentiating the laterality of seizure foci in FLE using HRV parameters. Twelve patients with FLE (6 right FLE and 6 left FLE) were included in the analyzes. A total of 551 (460 left FLE and 91 right FLE) 1-min epoch electrocardiography data were used for HRV analysis. We found that most HRV parameters differed between the left and right FLE groups. Among the machine learning algorithms applied in this study, the light gradient boosting machine was the most accurate, with an AUC value of 0.983 and a classification accuracy of 0.961. Our findings suggest that HRV parameter-based laterality determination models can be convenient and effective tools in clinical settings. Considering that heart rate can be easily measured in real time with a wearable device, our proposed method can be applied to a closed-loop device as a real-time monitoring tool for determining the side of stimulation