311 research outputs found
Fermions, Gauge Theories, and the Sinc Function Representation for Feynman Diagrams
We extend our new approach for numeric evaluation of Feynman diagrams to
integrals that include fermionic and vector propagators. In this initial
discussion we begin by deriving the Sinc function representation for the
propagators of spin-1/2 and spin-1 fields and exploring their properties. We
show that the attributes of the spin-0 propagator which allowed us to derive
the Sinc function representation for scalar field Feynman integrals are shared
by fields with non-zero spin. We then investigate the application of the Sinc
function representation to simple QED diagrams, including first order
corrections to the propagators and the vertex.Comment: 10 pages, Latex, 9 figure
Phase Separation and Magnetic Order in K-doped Iron Selenide Superconductor
Alkali-doped iron selenide is the latest member of high Tc superconductor
family, and its peculiar characters have immediately attracted extensive
attention. We prepared high-quality potassium-doped iron selenide (KxFe2-ySe2)
thin films by molecular beam epitaxy and unambiguously demonstrated the
existence of phase separation, which is currently under debate, in this
material using scanning tunneling microscopy and spectroscopy. The
stoichiometric superconducting phase KFe2Se2 contains no iron vacancies, while
the insulating phase has a \surd5\times\surd5 vacancy order. The iron vacancies
are shown always destructive to superconductivity in KFe2Se2. Our study on the
subgap bound states induced by the iron vacancies further reveals a
magnetically-related bipartite order in the superconducting phase. These
findings not only solve the existing controversies in the atomic and electronic
structures in KxFe2-ySe2, but also provide valuable information on
understanding the superconductivity and its interplay with magnetism in
iron-based superconductors
Time-Constrained Ensemble Sensing With Heterogeneous IoT Devices in Intelligent Transportation Systems
Recently we have witnessed the rise of Artificial Intelligence of Things (AIoT) and the shift of sensing paradigm from cloud-centric to the edge-centric, which effectively improves the sensing capability of intelligence transportation systems. To improve the real-time sensing performance, in this work we propose an ensemble sensing based scheme to solve the time-constraint synchronized inference problem and achieve robust inference with heterogeneous IoT devices in intelligence transportation systems. We design and implement Ensen, which incorporates various novel techniques such as customized DNN model design, KD-based model training, and dynamic deep ensemble management, etc., to achieve improved accuracy and maximize the computational resource usage of the whole sensing group. Extensive evaluations on different types of common IoT devices have shown that Ensen achieves a robust performance and can be easily extended to different types of convolutional neural networks
Stretchable Self-Healable Semiconducting Polymer Film for Active-Matrix Strain-Sensing Array
Skin-like sensory devidces shoud be stretchable and self-healable to meet the demands for future electronic skin applications. Despite recent notable advances in skin-inspired electronic materials, it remains challenging to confer these desired functionalities to an active semiconductor. Here, we report a strain-sensitive, stretchable, and autonomously self-healable semiconducting film achieved through blending of a polymer semiconductor and a self-healable elastomer, both of which are dynamically cross-linked by metal coordination. We observed that by controlling the percolation threshold of the polymer semiconductor, the blend film became strain sensitive, with a gauge factor of 5.75 x 105 at 100% strain in a stretchable transistor. The blend film is also highly stretchable (fracture strain, \u3e1300%) and autonomously self-healable at room temperature. We proceed to demonstrate a fully integrated 5 x 5 stretchable active-matrix transistor sensor array capable of detecting strain distribution through surface deformation
Flexoelectric control of a ferromagnetic metal
Electric fields have played a key role in discovering and controlling exotic
electronic states of condensed matter. However, electric fields usually do not
work in metals as free carriers tend to screen electrostatic fields. While a
pseudo-electric field generated by inhomogeneous lattice strain, namely a
flexoelectric field, can in principle work in all classes of materials, it
remains experimentally unexplored in metals. Here, using heteroepitaxy and
atomic-scale imaging, we show that flexoelectric fields can polarize a metallic
oxide SrRuO3 with unexpectedly large Ru off-center displacements. We also
observe that the flexoelectrically induced polar state of SrRuO3 leads to
sizable lattice expansion, similar to the electrostrictive expansion caused by
ionic displacements in dielectrics under an external electric field. We further
suggest that flexoelectrically driven Ru off-centering promotes strong coupling
between lattice and electronic degrees of freedom, possibly enhancing the
ferromagnetism of SrRuO3. Beyond conventional electric fields, flexoelectric
fields may universally engender novel electronic states and their control via
pure atomic displacements in a nondestructive and fast manner.Comment: 33 pages, 13 figure
Searching for Better Plasmonic Materials
Plasmonics is a research area merging the fields of optics and
nanoelectronics by confining light with relatively large free-space wavelength
to the nanometer scale - thereby enabling a family of novel devices. Current
plasmonic devices at telecommunication and optical frequencies face significant
challenges due to losses encountered in the constituent plasmonic materials.
These large losses seriously limit the practicality of these metals for many
novel applications. This paper provides an overview of alternative plasmonic
materials along with motivation for each material choice and important aspects
of fabrication. A comparative study of various materials including metals,
metal alloys and heavily doped semiconductors is presented. The performance of
each material is evaluated based on quality factors defined for each class of
plasmonic devices. Most importantly, this paper outlines an approach for
realizing optimal plasmonic material properties for specific frequencies and
applications, thereby providing a reference for those searching for better
plasmonic materials.Comment: 27 pages, 6 figures, 2 table
Improvement in NO2 Sensing Properties of Semiconductor-Type Gas Sensors by Loading of Au Into Porous In2O3 Powders
Porous (pr-) In2O3 powders loaded with and without noble metals (Au, Pd, or Pt) were prepared by ultrasonic spray pyrolysis employing the PMMA microspheres as a template (typical particle size (ps): 28 or 70 nm with a diameter), and their NO2 sensing properties were examined. The Au loading on the pr-In2O3 was effective to increase the NO2 response at lower operating temperature (?200°C), while the metal loading of Pd or Pt were hardly effective. In addition, a decrease in the PMMA microspheres (from 70 to 28 nm in ps) largely increased the NO2 response,and an optimized amount of Au loaded on the pr-In2O3 sensor was 1.0 wt%. The decrease in the thickness of the sensing layer improved the NO2 response and response speed. It was suggested that the Au loading enhanced the amount of the negatively adsorbed NO2 on the bottom part of the sensing layer, leading to the increase in the NO2 response. Furthermore, the introduction of additional macropores (ps: 150 nm) to the 1.0 wt% Au loaded pr-In2O3 sensor increased the response to a low concentration of NO2 (0.025 ppm) at 30°C. Therefore, it was found that easy gas diffusion from the surface to the bottom part of the sensing layer increased the effective concentration of NO2, and thus the NO2 response was increased
Pairing symmetry and properties of iron-based high temperature superconductors
Pairing symmetry is important to indentify the pairing mechanism. The
analysis becomes particularly timely and important for the newly discovered
iron-based multi-orbital superconductors. From group theory point of view we
classified all pairing matrices (in the orbital space) that carry irreducible
representations of the system. The quasiparticle gap falls into three
categories: full, nodal and gapless. The nodal-gap states show conventional
Volovik effect even for on-site pairing. The gapless states are odd in orbital
space, have a negative superfluid density and are therefore unstable. In
connection to experiments we proposed possible pairing states and implications
for the pairing mechanism.Comment: 4 pages, 1 table, 2 figures, polished versio
- …