bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient mid-infrared wavelength converter based on plasmon-enhanced nonlinear response in graphene nanoribbons
Authors: Chi Jiao , Liu Hongjun , Wang Zhaolu , Huang Nan 
Published: December 2021

Abstract
Graphene plasmons with enhanced localized electric field have been used for boosting the light–matter interaction in linear optical nano-devices. Meanwhile, graphene is an excellent nonlinear material for several third-order nonlinear processes. We present a theoretical investigation of the mechanism of plasmon-enhanced third-order nonlinearity susceptibility of graphene nanoribbons. It is demonstrated that the third-order nonlinearity susceptibility of graphene nanoribbons with excited graphene surface plasmon polaritons can be an order of magnitude larger than the intrinsic susceptibility of a continuous graphene sheet. Combining these properties with the relaxed phase matching condition due to the ultrathin graphene, we propose a novel plasmon-enhanced mid-infrared (MIR) wavelength converter with arrays of graphene nanoribbons. The wavelength of signal light is in the MIR range, which can excite the tunable surface plasmons polaritons in arrays of graphene nanoribbons. The efficiency of the converter from MIR to near-infrared wavelength can be remarkably improved by 60 times compared with a graphene sheet without graphene plasmons. This work provides a novel idea for the efficient application of graphene in nonlinear optical nano-devices. The proposed MIR wavelength converter is compact, tunable and has promising potential in graphene-based MIR detectors with high detection efficiency.
Plasma-catalytic NO
x
production in a three-level coupled rotating electrodes air plasma combined with nano-sized TiO2
Authors: Lei Xinyu , Cheng He , Nie LanLan , Xian YuBin , Lu Xinpei 
Published: December 2021

Abstract
A novel three-level coupled rotating electrodes air plasma with nano-sized TiO2 photocatalysts is developed for plasma-catalytic NO
x
production. The effects of plasma catalysis on NO
x
production with different air flow rates, different N2 fractions and different humidity levels are evaluated. Final results show the exceptional synergistic effect between TiO2 and three-level coupled rotating electrodes air plasma significantly increases the NO
x
concentration by 68.32% (from 4952 to 8335 ppm) and reduces the energy cost by 40.55% (from 2.91 to 1.73 MJ mol−1) at an air flow rate of 12 l min−1 and relative humidity level of 12%, which beats the ideal thermodynamic energy limit ∼2.5 MJ mol−1 for the thermal gas-phase process. A possible mechanism for enhanced NO
x
production with TiO2 is discussed: Highly energetic electrons in plasma contribute to the formations of the electron–hole pairs and oxygen vacancy (Vo) on the TiO2 catalyst surface, which may facilitate the dissociative adsorption of O2 molecules to form superoxide radical groups (like O2
−), and H2O molecules to form surface hydroxyl groups (like OH·), and thus, improving energy efficiency.
Study on Li ion diffusion in LixV2O5 using first principle calculations and kinetic Monte Carlo simulations
Authors: Dietrich Fabian , Cisternas Eduardo , Marcelo Pasinetti Pedro , dos Santos Gonzalo 
Published: December 2021

Abstract
We study the Li diffusion in Li
x
V2O5 (

0
<
x
⩽
1

)—a potential cathode material for Lithium ion batteries. Different diffusion pathways in this material with dependence on the Li ion concentration are investigated by applying first-principles calculations. The results are used to obtain the corresponding diffusion coefficients by employing two complementary methodologies: Kinetic Monte Carlo (KMC) simulations and a statistical thermodynamics approach. The KMC simulations for two different crystal planes give new evidence that the diffusion occurs mainly along the [010] direction, while the corresponding diffusion coefficients show a temperature dependence obeying Arrhenius’ Law. The necessity of the consideration of concentration-dependent barrier heights in the KMC simulations are demonstrated by looking at the significant changes of the concentration-dependence of the diffusion coefficients. The simulated diffusion coefficients of the combined approach show a good quantitative agreement with experimental data reported previously.
Rare-earth tuned magnetism and magnetocaloric effects in double perovskites R
2NiMnO6
Authors: Ali Anzar , Pasrija Kanika , Sharma Gyaneshwar , Kumar Sanjeev , Singh Yogesh 
Published: December 2021

Abstract
We present a comprehensive experimental study of magnetization (2 < T < 300 K, 1 < H < 8 T) and magnetocaloric effect in double perovskite materials R
2NiMnO6 with R = Pr, Nd, Sm, Gd, Tb, and Dy. While a paramagnetic to ferromagnetic transition, with TC in the range

∼
100
−
200

K, is a common feature that can be attributed to the ordering of Mn4+ and Ni2+ magnetic moments, qualitatively distinct behavior depending on the choice of R is observed at low temperatures. These low-temperature anomalies in magnetization are also manifest in the change in magnetic entropy, −ΔS

M
, whose sign depends on the choice of R. In order to understand these results, we present theoretical analysis based on mean-field approximation and Monte Carlo simulations on a minimal spin model. The model correctly captures the key features of the experimental observations.
Post-nucleation evolution of the liquid–solid interface in nanowire growth
Authors: Maliakkal Carina B , Jacobsson Daniel , Tornberg Marcus , Dick Kimberly A 
Published: December 2021

Abstract
We study using in situ transmission electron microscopy the birth of GaAs nanowires from liquid Au–Ga catalysts on amorphous substrates. Lattice-resolved observations of the starting stages of growth are reported here for the first time. It reveals how the initial nanostructure evolves into a nanowire growing in a zincblende 〈111〉 or the equivalent wurtzite〈0001〉 direction. This growth direction(s) is what is typically observed in most III–V and II–VI nanowires. However, the reason for this preferential nanowire growth along this direction is still a dilemma. Based on the videos recorded shortly after the nucleation of nanowires, we argue that the lower catalyst droplet-nanowire interface energy of the {111} facet when zincblende (or the equivalent {0001} facet in wurtzite) is the reason for this direction selectivity in nanowires.
Plume neutralization of an ionic liquid electrospray thruster: better insights from particle-in-cell modelling
Authors: Zhang Baiyi , Cai Guobiao , He Bijiao , Zhang Kai , Zheng Hongru , Wang Weizong 
Published: December 2021

Abstract
Ionic liquid electrospray thrusters with high specific impulse, high thrust accuracy and low thrust noise are very promising for space gravitational wave detection missions. The plume, which may lead to surface charging of solar panels and sensitive spacecraft components is a great concern for the applications of electrospray thruster. Therefore, this paper investigates the plume neutralization process of the ionic liquid electrospray thruster through fully kinetic particle-in-cell simulations. The unipolarity operation mode is firstly simulated and compared with the experimental measurements. The bipolar operation mode is analyzed by considering the premixing and the separation of positive and negative ion beams. At the same time, the effect of beam spacing on the plume characteristics is investigated. The results show that the plume neutralization of the ionic liquid electrospray thruster is achieved by the spatial and temporal oscillations of the ion beams. In the horizontal direction, the spatial oscillations are caused by the different mass and hence velocities of positive and negative ions. In the vertical direction, the spatial oscillations are mainly because of the non-zero beam spacing. The temporal oscillations may be related to the tradition plasma oscillation. As the beam spacing increases, the oscillation amplitude of the horizontal electric potential curve changes scarcely; however, in the vertical direction, the oscillation amplitude of the curve increases. The ion temperature goes up with the beam spacing and the deviation of the temperature of beam ions does not exceed 15 eV in the horizontal direction but exceeds 100 eV in the vertical direction. Moreover, the plume divergence half angle and the beam spacing are positively correlated, suggesting that the ionic electrospray thrusters with positive and negative polarity need to be placed as close as possible in the spacecraft.
Nanoscale wafer patterning using SPM induced local anodic oxidation in InP substrates
Authors: Ovenden Charlotte , Farrer Ian , Skolnick Maurice S , Heffernan Jon 
Published: December 2021

Abstract
Atomic force microscopy (AFM) assisted local anodic oxidation (LAO) offers advantages over other semiconductor fabrication techniques as it is a low contamination method. We demonstrate the fabrication of deep and highly reproducible nanohole arrays on InP using LAO. Nanohole and nano-oxide mound radius and depth are controlled independently by altering AFM tip bias and humidity, with a maximum nanohole depth of 15.6 ± 1.2 nm being achieved. Additionally, the effect of tip write speed on oxide line formation is compared for n-type, p-type and semi-insulating substrates, which shows that n-type InP oxidizes at a slower rate that semi-insulated or p-type InP. Finally, we calculate the activation energy for LAO of semi-insulating InP to be 0.4 eV, suggesting the oxidation mechanism is similar to that which occurs during plasma oxidation.
Dual-mode dendritic devices enhanced neural network based on electrolyte gated transistors
Authors: Jing Zhaokun , Yang Yuchao , Huang Ru 
Published: December 2021

Abstract
As a fundamental component of biological neurons, dendrites have been proven to have crucial effects in neuronal activities. Single neurons with dendrite structures show high signal processing capability that is analogous to a multilayer perceptron (MLP), whereas oversimplified point neuron models are still prevalent in artificial intelligence algorithms and neuromorphic systems and fundamentally limit their efficiency and functionality of the systems constructed. In this study, we propose a dual-mode dendritic device based on electrolyte gated transistor, which can be operated to generate both supralinear and sublinear current–voltage responses when receiving input voltage pulses. We propose and demonstrate that the dual-mode dendritic devices can be used as a dendritic processing block between weight matrices and output neurons so as to dramatically enhance the expression ability of the neural networks. A dual-mode dendrites-enhanced neural network is therefore constructed with only two trainable parameters in the second layer, thus achieving 1000× reduction in the amount of second layer parameter compared to MLP. After training by back propagation, the network reaches 90.1% accuracy in MNIST handwritten digits classification, showing advantage of the present dual-mode dendritic devices in building highly efficient neuromorphic computing.
Parametric study of high-energy ring-shaped electron beams from a laser wakefield accelerator
Authors: Maitrallain A , Brunetti E , Streeter M J V , Kettle B , Spesyvtsev R , Vieux G , Shahzad M , Ersfeld B , Yoffe S R , Kornaszewski A , Finlay O , Ma Y , Albert F , Bourgeois N , Dann S J D , Lemos N , Cipiccia S , Cole J M , González I G , Willingale L , Higginbotham A , Hussein A E , Šmid M , Falk K , Krushelnick K , Lopes N C , Gerstmayr E , Lumsdon C , Lundh O , Mangles S P D , Najmudin Z , Rajeev P P , Symes D R , Thomas A G R , Jaroszynski D A 
Published: December 2021

Abstract
Laser wakefield accelerators commonly produce on-axis, low-divergence, high-energy electron beams. However, a high charge, annular shaped beam can be trapped outside the bubble and accelerated to high energies. Here we present a parametric study on the production of low-energy-spread, ultra-relativistic electron ring beams in a two-stage gas cell. Ring-shaped beams with energies higher than 750 MeV are observed simultaneously with on axis, continuously injected electrons. Often multiple ring shaped beams with different energies are produced and parametric studies to control the generation and properties of these structures were conducted. Particle tracking and particle-in-cell simulations are used to determine properties of these beams and investigate how they are formed and trapped outside the bubble by the wake produced by on-axis injected electrons. These unusual femtosecond duration, high-charge, high-energy, ring electron beams may find use in beam driven plasma wakefield accelerators and radiation sources.
Agglomerative likelihood clustering
Authors: Yelibi Lionel , Gebbie Tim 
Published: December 2021

Abstract
We consider the problem of fast time-series data clustering. Building on previous work modeling, the correlation-based Hamiltonian of spin variables we present an updated fast non-expensive agglomerative likelihood clustering algorithm (ALC). The method replaces the optimized genetic algorithm based approach (f-SPC) with an agglomerative recursive merging framework inspired by previous work in econophysics and community detection. The method is tested on noisy synthetic correlated time-series datasets with a built-in cluster structure to demonstrate that the algorithm produces meaningful non-trivial results. We apply it to time-series datasets as large as 20 000 assets and we argue that ALC can reduce computation time costs and resource usage costs for large scale clustering for time-series applications while being serialized, and hence has no obvious parallelization requirement. The algorithm can be an effective choice for state-detection for online learning in a fast non-linear data environment, because the algorithm requires no prior information about the number of clusters.
Competences of teachers of natural-physical sciences. An analysis from the perception of the students
Authors: Prada-Núñez R , Ayala E T , Avendaño-Castro W R 
Published: December 2021

Abstract
This article arises as a proposal in view of the need to evaluate the scientific competences promoted by teachers of the subject of physics at the level of basic secondary and secondary technical education. A valid questionnaire was designed from the application of scalar analysis, factorial analysis and content analysis, which is composed of 49 items evaluated by means of a Likert scale with five levels of response. It was applied in a sample of 249 students enrolled in a public educational institution during 2019, characterized by their good results in the area of physics in state tests. The results allowed the identification of strengths in the four dimensions proposed by the Ministerio de Educación Nacional, Colombia (pedagogical, didactic, disciplinary and behavioural), in contrast with some weaknesses within which the evaluation process stands out as the one with the greatest impact, since the students state that this process is assumed by the teacher as a mechanism of pressure and control. When investigating the teachers in a complementary way, positions were determined that were totally opposite to those held by the students, then it is suggested for future research to consider both the students and the teachers as informants and a supervision of the students’ notes as the end of triangulating the results to refine the conclusions, on which future improvement plans will depend.
Design of Controller for Electrical Vehicle to Grid Power
Authors: Baghmare K K , Daigavane P M 
Published: December 2021

Abstract
This paper prescribed the design of controller for electrical vehicle to Grid power, by using this controller improve the power requirement of grid and reactive power compensation capability. Bidirectional converter is very helpful during on peak load demand. During off peak load demand grid will supply the power to the battery and charge the battery. During on peak load demand excess power of battery will supply to the grid. The concept aggregator is depicted in the figure 2. (Aggregator collects the power from all electrical vehicle first then it supply to the grid). This modern electrical vehicle technology proposed the distribution generation Methodology. All the control strategies of modern electrical vehicle to grid is proposed like smart charging or discharging of batteries during off peak load demand and On peak load demand respectively. V2G controller allow the active power it act as an ancillary services to grid. Electrical vehicle controller has ability to exchange the active or reactive power capability. Simulation of bidirectional AC/DC and DC/DC controller and their control circuit are analyzed by using matlab Simulink software.
Image Anonymization using Deep Convolutional Generative Adversarial Network
Authors: Rao K Nitalaksheswara , Jayasree P , Krishna Ch.V.Murali , Sai Prasanth K , Reddy Ch Satyananda 
Published: December 2021

Abstract
Advancement in deep learning requires significantly huge amount of data for training purpose, where protection of individual data plays a key role in data privacy and publication. Recent developments in deep learning demonstarte a huge challenge for traditionally used approch for image anonymization, such as model inversion attack, where adversary repeatedly query the model, inorder to reconstrut the original image from the anonymized image. In order to apply more protection on image anonymization, an approach is presented here to convert the input (raw) image into a new synthetic image by applying optimized noise to the latent space representation (LSR) of the original image. The synthetic image is anonymized by adding well designed noise calculated over the gradient during the learning process, where the resultant image is both realistic and immune to model inversion attack. More presicely, we extend the approach proposed by T. Kim and J. Yang, 2019 by using Deep Convolutional Generative Adversarial Network (DCGAN) in order to make the approach more efficient. Our aim is to improve the efficiency of the model by changing the loss function to achieve optimal privacy in less time and computation. Finally, the proposed approach is demonstrated using a benchmark dataset. The experimental study presents that the proposed method can efficiently convert the input image into another synthetic image which is of high quality as well as immune to model inversion attack.
Multi-class classification for large datasets with optimized SVM by non-linear kernel function
Authors: Sunitha Lingam , Raju M Bal 
Published: December 2021

Abstract
Most important part of Support Vector Machines(SVM) are the kernels. Although there are several widely used kernel functions, a carefully designed kernel will help improve the accuracy of SVM. The proposed work aims to develop a new kernel function for a multi-class support vector machine, perform experiments on various data sets, and compare them with other classification methods. Directly it is not possible multiclass classification with SVM. In this proposed work first designed a model for binary class then extended with the one-verses-all approach. Experimental results have proved the efficiency of the new kernel function. The proposed kernel reduces misclassification and time. Other classification methods observed better results for some data sets collected from the UCI repository.
Designing of Lithium - Ion Battery Pack Rechargeable on a Hybrid System with Battery Management System (BMS) for DC Loads of Low Power Applications – A Prototype Model
Authors: Bhukya Ramu , Nalli Praveen Kumar , Kadali Kalyan Sagar , Bade Mahendra Chand 
Published: December 2021

Abstract
Now a days, Li-ion batteries are quite possibly the most exceptional battery-powered batteries; these are drawing in much consideration from recent many years. M Whittingham first proposed lithium-ion battery technology in the 1970s, using titanium sulphide for the cathode and lithium metal for the anode. Li-ion batteries are the force to be reckoned with for the advanced electronic upset in this cutting-edge versatile society, solely utilized in cell phones and PC computers. A battery is a Pack of cells organized in an arrangement/equal association so the voltage can be raised to the craving levels. Lithium-ion batteries, which are completely utilised in portable gadgets & electric vehicles, are the driving force behind the digital technological revolution in today’s mobile societies. In order to protect and maintain voltage and current of the battery with in safe limit Battery Management System (BMS) should be used. BMS provides thermal management to the battery, safeguarding it against over and under temperature and also during short circuit conditions. The battery pack is designed with series and parallel connected cells of 3.7v to produce 12v. The charging and releasing levels of the battery pack is indicated by interfacing the Arduino microcontroller. The entire equipment is placed in a fiber glass case (looks like aquarium) in order to protect the battery from external hazards to design an efficient Lithium-ion battery by using Battery Management System (BMS). We give the supply to the battery from solar panel and in the absence of this, from a regular AC supply.
Uplink and Downlink Variation in Drone Technology for Cloud, Edge, Fog and Smart Dust Integrated IoT Architecture: Demonstrated Over WSNs
Authors: Dorave Jayantkumar , Sadiwala Ritesh 
Published: December 2021

Abstract
IoT concepts are heavily applicable in drone communication integrated with different network architecture for optimization. Distributing the burden allows more IoT devices to execute calculations, rather than everything being done on the cloud. There are numerous IoT designs that have emerged as a result of this. By relocating calculations away from the cloud, these designs make use of the enhanced processing capacity of the devices. Based on our needs, we’ve limited it down to four architectures, each of which we have discussed for optimized flow useful in drone technology. We have also applied the one live dataset for the test drone using raspberry pi processor system powered with for end-to-end drone communication establishment. The analysis of downlink and uplink were studied for time analysis for IoT architecture using drone cell characteristics. New technology makes it possible to implement drone cell (DC) connectivity, which is highly flexible and cost-effective for the gathering of Internet-of-things (IoT) data when terrestrial networks are not yet accessible. DC’s flight path has a substantial impact on data collecting systems.
Experimental investigation of bending characteristics of hybrid composites fabricated by hand layup method
Authors: Sadashiva M , Praveen Kumar S , Yathish M K , Satish V T , Srinivasa MR , Sharanraj V 
Published: December 2021

Abstract
The extensive applications of hybrid composite materials in the field of transportation and structural domine provide prominent advantages in the order of stiffness, strength even cost. However extend the advantages of hybrid campsites in several field such as aviation and marine even more additional properties should be inculcate in them. During production of such profitable composites poses some problems at time at decompose and processing. It’s better to develop environment friendly and reusable composites, bio hybrid composite materials such of the one. In this paper, focused on development of Eco-friendly hybrid bio composites with the ingredients of drumstick fibers, glass fiber along with polyester resin. This hybrid bio composites subjected to bending test and evaluate the characteristics of bending properties, this research evident that bending characteristics of hybrid composites with longitudinal fiber orientation better than transverse.