Large scale fabrication of nitrogen vacancy-embedded diamond nanostructures for single-photon source applications

Some color centers in diamond can serve as quantum bits which can be manipulated with microwave pulses and read out with laser, even at room temperature. However, the photon collection efficiency of bulk diamond is greatly reduced by refraction at the diamond/air interface. To address this issue, we fabricated arrays of diamond nanostructures, differing in both diameter and top end shape, with HSQ and Cr as the etching mask materials, aiming toward large scale fabrication of single-photon sources with enhanced collection efficiency made of nitrogen vacancy (NV) embedded diamond. With a mixture of O2 and CHF3 gas plasma, diamond pillars with diameters down to 45 nm were obtained. The top end shape evolution has been represented with a simple model. The tests of size dependent single-photon properties confirmed an improved single-photon collection efficiency enhancement, larger than tenfold, and a mild decrease of decoherence time with decreasing pillar diameter was observed as expected. These results provide useful information for future applications of nanostructured diamond as a single-photon source

A training effect on electrical properties in nanoscale BiFeO3

We report our observation of the training effect on dc electrical properties in a nanochain of BiFeO3 as a result of large scale migration of defects under the combined influence of electric field and Joule heating. We show that an optimum number of cycles of electric field within the range zero to similar to 1.0 MV cm(-1) across a temperature range 80-300 K helps in reaching the stable state via a glass-transition-like process in the defect structure. Further treatment does not give rise to any substantial modification. We conclude that such a training effect is ubiquitous in pristine nanowires or chains of oxides and needs to be addressed for applications in nanoelectronic devices

A Malicious Mining Code Detection Method Based on Multi-Features Fusion

With the continuous increase in the economic value of new digital currencies represented by Bitcoin, more and more cybercriminals use malicious code to occupy victims system resources and network resources for mining without the victims permission, thereby obtaining cryptocurrency. This type of malicious code named malicious mining code has brought considerable influence and harm to society, enterprises and users. The mining code always conceals the fact that it consumes computer resources in a way that is difficult for ordinary people to discover. This paper proposes a malicious mining code detection method based on feature fusion and machine learning. First, we analyze from static analysis methods and statistical analysis methods to extract multi-dimensional features. Then for multi-dimensional text features, feature vectors are extracted through the n-gram model and TF-IDF, and best feature vectors are selected through the classifier and we fuse these best feature vectors with other statistic features to train our detection model. Finally, automatic detection is performed based on the machine learning framework. The experimental results show that the recognition accuracy of our method can reach 98.0%, its f1 score reach 0.969, and the ROCs AUC reach 0.973

Primary Nucleation-Dominated Chemical Vapor Deposition Growth for Uniform Graphene Monolayers on Dielectric Substrate

Direct chemical vapor deposition growth of high quality graphene on dielectric substrates holds great promise for practical applications in electronics and optoelectronics. However, graphene growth on dielectrics always suffers from the issues of inhomogeneity and/or poor quality. Here, we first reveal that a novel precursor-modification strategy can successfully suppress the secondary nucleation of graphene to evolve ultrauniform graphene monolayer film on dielectric substrates. A mechanistic study indicates that the hydroxylation of silica substrate weakens the binding between graphene edges and substrate, thus realizing the primary nucleation-dominated growth. Field-effect transistors based on the graphene films show exceptional electrical performance with the charge carrier mobility up to 3800 cm(2) V-1 s(-1) in air, which is much higher than those reported results of graphene films grown on dielectrics

Numerical Simulation of Coalescence-Induced Jumping of Multidroplets on Superhydrophobic Surfaces: Initial Droplet Arrangement Effect

The coalescence-induced droplet jumping on superhydrophobic surfaces (SHSs) has attracted considerable attention over the past several years. Most of the studies on droplet jumping mainly focus on two-droplet coalescence events whereas the coalescence of three or more droplets is actually more frequent and still remains poorly understood. In this work, a 3D lattice Boltzmann simulation is carried out to investigate the effect of initial droplet arrangements on the coalescence-induced jumping of three equally sized droplets. Depending on the initial position of droplets on the surface, the droplet coalescence behaviors can be generally classified into two types: one is that all droplets coalesce together instantaneously (concentrated configuration), and the other is that the initial coalesced droplet sweeps up the third droplet in its moving path (spaced configuration). The critical Ohnesorge number, <i>Oh</i>, for the transition of inertial-capillary-dominated coalescence to inertially limited-viscous coalescence is found to be 0.10 for droplet coalescence on SHSs with a contact angle of 160°. The jumping droplet velocity for concentrated multidroplet coalescence at <i>Oh</i> ⩽ 0.10 still follows the inertial-capillary scaling with an increased prefactor, which indicates a viable jumping droplet velocity enhancement scheme. However, the droplet jumping velocity is drastically reduced for the spaced configuration compared to that for the aforementioned concentrated configuration. Because <i>Oh</i> exceeds 0.10, the effects of initial droplet arrangements on multidroplet jumping become weaker as viscosity plays a key role in the merging process. This work will provide effective guidelines for the design of functional SHSs with enhanced droplet jumping for a wide range of industrial applications