A single intrinsic Josephson junction with double-sided fabrication technique

We make stacks of intrinsic Josephson junctions (IJJs) imbedded in the bulk of very thin ($d\leq 100$~nm) $\mathrm{Bi_2Sr_2CaCu_2O_{8+x}}$ single crystals. By precisely controlling the etching depth during the double-sided fabrication process, the stacks can be reproducibly tailor-made to be of any microscopic height ($0-9 \mathrm{nm} <d$), i.e. enclosing a specified number of IJJ (0-6), including the important case of a single junction. We discuss reproducible gap-like features in the current-voltage characteristics of the samples at high bias.Comment: 3 pages, 4 figures, to be published in APL May. 2

Superconducting properties of ultrathin Bi2Sr2CaCu2O8+x single crystals

We use Ar-ion milling to thin Bi2212 single crystals down to a few nanometers or one-to-two (CuO2)2 layers. With decreasing the thickness, superconducting transition temperature gradually decreases to zero and the in-plane resistivity increases to large values indicating the existence of a superconductor-insulator transition in ultrathin Bi2212 single crystals.Comment: 17 pages, 6 figures, to appear in J. Appl. Phys. 98(3) 200

Multifunctional luminescent nanomaterials from NaLa(MoO 4) 2:Eu 3+ /Tb 3+ with tunable decay lifetimes, emission colors, and enhanced cell viability

A facile, but effective, method has been developed for large-scale preparation of NaLa(MoO 4) 2 nanorods and microflowers co-doped with Eu 3+ and Tb 3+ ions (abbreviated as: NLM:Ln 3+). The as-synthesized nanomaterials possess a pure tetragonal phase with variable morphologies from shuttle-like nanorods to microflowers by controlling the reaction temperature and the amount of ethylene glycol used. Consequently, the resulting nanomaterials exhibit superb luminescent emissions over the visible region from red through yellow to green by simply changing the relative doping ratios of Eu 3+ to Tb 3+ ions. Biocompatibility study indicates that the addition of NLM:Ln 3+ nanomaterials can stimulate the growth of normal human retinal pigment epithelium (ARPE-19) cells. Therefore, the newly-developed NaLa(MoO 4) 2 nanomaterials hold potentials for a wide range of multifunctional applications, including bioimaging, security protection, optical display, optoelectronics for information storage, and cell stimulation

Electronic structure of C60 and C70 molecules: Generating function approach

We study the electronic structure of C60 and C70 molecules within the tight-binding approximation. Our approach is based on recursive evaluations of the generating function, which provide the density of states of the system. Our results for C60 are consistent with previous calculations using very different methods, and we have also obtained results for the much-less-studied C70 case.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31459/1/0000381.pd

Imperceptible Physical Attack against Face Recognition Systems via LED Illumination Modulation

Although face recognition starts to play an important role in our daily life, we need to pay attention that data-driven face recognition vision systems are vulnerable to adversarial attacks. However, the current two categories of adversarial attacks, namely digital attacks and physical attacks both have drawbacks, with the former ones impractical and the latter one conspicuous, high-computational and inexecutable. To address the issues, we propose a practical, executable, inconspicuous and low computational adversarial attack based on LED illumination modulation. To fool the systems, the proposed attack generates imperceptible luminance changes to human eyes through fast intensity modulation of scene LED illumination and uses the rolling shutter effect of CMOS image sensors in face recognition systems to implant luminance information perturbation to the captured face images. In summary,we present a denial-of-service (DoS) attack for face detection and a dodging attack for face verification. We also evaluate their effectiveness against well-known face detection models, Dlib, MTCNN and RetinaFace , and face verification models, Dlib, FaceNet,and ArcFace.The extensive experiments show that the success rates of DoS attacks against face detection models reach 97.67%, 100%, and 100%, respectively, and the success rates of dodging attacks against all face verification models reach 100%