Energy level alignment at the porphyrin/cobaltocene interface: From transfer doping to cobalt intercalation

N-type doping of the organic semiconductor zinc tetraphenylporphyrin (ZnTPP) by overlayers of the reducing molecule decamethylcobaltocene (${\mathit{CoCp}}_2^1$) is demonstrated using photoelectron spectroscopy. A transfer doping model involving integer charge transfer between molecules reproduces quantitatively all measured level shifts as a function of ${\mathit{CoCp}}_2^1$ coverage using the ionisation potential of ${\mathit{CoCp}}_2^1$ and the electron affinity of ZnTPP as sole input parameters. The model yields the experimentally observed limitation of doping to the first monolayer of cobaltocene while further layers remain neutral without the need to resort to special bonding arrangements for the first monolayer. Temperature-dependent studies reveal that doping is still present at room temperature, despite the high vapour pressure of ${\mathit{CoCp}}_2^1$. Higher annealing temperatures initiate ${\mathit{CoCp}}_2^1$ molecular dissociation and diffusion of Co atoms into the ZnTPP film. Hence, the nature of doping changes from surface molecular transfer doping to bulk metallic doping as a function of temperature.     

Low complexity PAPR reduction techniques for clipping and quantization noise mitigation in direct-detection O-OFDM systems

We present different distortionless peak-to-average power ratio (PAPR) reduction techniques that can be easily applied, without any symmetry restriction, in direct-detection (DD) optical orthogonal frequency division multiplexing (O-OFDM) systems based on the fast Hartley transform (FHT). The performance of DD O-OFDM systems is limited by the constraints on system components such as digital-to-analog converter (DAC), analog-to-digital converter (ADC), the Mach–Zehnder modulator (MZM) and electrical amplifiers. In this paper, in order to relax the constraints on these components, we propose to symmetrically clip the transmitted signal and apply low complexity (LC) distortionless PAPR reduction schemes able to mitigate, at the same time, PAPR, quantization and clipping noise. We demonstrate that, applying LC-selective mapping (SLM) without any additional transform block, the PAPR reduction is $1.5\text{dB}$ with only one additional FHT block using LC-partial transmit sequence (PTS) with random partitions; up to $3.1\text{dB}$ reduction is obtained. Moreover, the sensitivity performance and the power efficiency are enhanced. In fact, applying LC PAPR reduction techniques with one additional transform block and a 6 bit DAC resolution, the required receiver power for 8 dB clipping level and for a ${10}^{-3}\text{BER}$ is reduced by $5.1\text{dB}$.     

VideoSet: A large-scale compressed video quality dataset based on JND measurement

A new methodology to measure coded image/video quality using the just-noticeable-difference (JND) idea was proposed in Lin et al. (2015). Several small JND-based image/video quality datasets were released by the Media Communications Lab at the University of Southern California in Jin et al. (2016) and Wang et al. (2016) [3]. In this work, we present an effort to build a large-scale JND-based coded video quality dataset. The dataset consists of 220 5-s sequences in four resolutions (i.e., $1920\times 1080\text{,}1280\times 720\text{,}960\times 540$ and $640\times 360$). For each of the 880 video clips, we encode it using the H.264/AVC codec with $\mathit{QP}=1\text{,}\dots \text{,}51$ and measure the first three JND points with 30 + subjects. The dataset is called the “VideoSet”, which is an acronym for “Video Subject Evaluation Test (SET)”. This work describes the subjective test procedure, detection and removal of outlying measured data, and the properties of collected JND data. Finally, the significance and implications of the VideoSet to future video coding research and standardization efforts are pointed out. All source/coded video clips as well as measured JND data included in the VideoSet are available to the public in the IEEE DataPort (Wang et al., 2016 [4]).