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The positioning accuracy of the indoor personnel positioning system is low, which cannot meet the needs of an intelligent transformer substation. Therefore, a wireless positioning method for indoor personnel based on the Elman neural network (ENN) using chaotic whale optimization algorithm (CWOA) was proposed. Firstly, a certain number of sample fingerprint databases were collected by wireless terminals in the wireless network on indoor personnel. Secondly, CWOA was used to optimize the weights and self-connected feedback gain factor of the ENN. Thirdly, the fingerprint database was used to train and test the optimized ENN, and the position algorithm model of the neural network was established. Finally, the real-time position was achieved with the neural network location algorithm model through the fingerprint data of the position point collected by the wireless terminal. The results show that the average position error of this indoor wireless positioning method is 1.24 m; ENN position algorithm by the CWOA has a stronger global search ability and is more suitable for the application in the time-varying indoor environment.

MoS2/Ga2O3 heterostructures with strong intrinsic ferroelectrics are highly promising for novel devices with designed electronic properties.

Ga2O3 is a wide-bandgap semiconductor of emergent importance for applications in electronics and optoelectronics. However, vital information of the properties of complex coexisting Ga2O3 polymorphs and low-symmetry disordered structures is missing. In this work, we develop two types of kernel-based machine-learning Gaussian approximation potentials (ML-GAPs) for Ga2O3 with high accuracy for β/κ/α/δ/γ polymorphs and universal generality for disordered structures. We release two versions of interatomic potentials in parallel, namely soapGAP and tabGAP, for excellent accuracy and exceeding speedup, respectively. We systematically show that both the soapGAP and tabGAP can reproduce the structural properties of all the five polymorphs in an exceptional agreement with ab initio results, meanwhile boost the computational efficiency with 5×102 and 2×105 computing speed increases compared to density functional theory, respectively. The results show that the liquid-solid phase transition proceeds in three different stages, a "slow transition", "fast transition", and "only Ga migration". We show that this complex dynamics can be understood in terms of distinct behavior of O and Ga sublattices in the interfacial layer.

Winter jujube originated from China and had an extremely high nutritional value. In 2021, symptomatic winter jujube fruits were collected from eight locations in Zhanhua District of Binzhou City, Shandong Province. In total, 108 fungal isolates were obtained and grouped into 11 species based on morphological characteristics and multilocus phylogenetic analysis, including Nothophoma quercina (43.52%), Fusarium lateritium (20.37%), Alternaria alternata (12.03%), F. proliferatum (7.41%), F. graminearum (4.63%), Botryosphaeria dothidea (3.70%), Fusarium sp. (2.78%), A. tenuissima (2.78%), Diaporthe eres (1.85%), Nigrospora oryzae (0.93%), and Cercospora nicotianae (0.93%). All fungal isolates obtained in this study showed aggressiveness on detached winter jujube fruits except N. oryzae and C. nicotianae isolates, of which F. proliferatum was the most virulent, while A. alternata isolates, which have been considered the major pathogen of winter jujube fruit rot, showed a relatively low-level virulence in this study. Furthermore, D. eres, F. graminearum, F. lateritium, and an unclassified Fusarium species were first reported as causal agents of winter jujube fruit rot. The typical symptoms of winter jujube fruit rot observed in this study could be distinguished into two types. N. quercina, A. alternata, A. tenuissima, Fusarium sp., D. nobilis, and F. lateritium isolates caused reddish brown to dark gray lesions on the peel, while B. dothidea, F. graminearum, and F. proliferatum isolates caused peel and pulp decay, resulting in red to reddish brown and water-soaked lesions. In addition, haplotype analysis of N. quercina isolates obtained in this study and validly published articles showed that there were 11 haplotypes worldwide; the isolates obtained in the current study were grouped into three haplotypes (Hap 1, Hap 2, and Hap 11), and two of them (Hap 2 and Hap 11) were confirmed as new haplotypes.

In this work, we study the gate leakage mechanisms of E-mode ${p}$ - ${n}$ junction/AlGaN/GaN (PNJ) high electron mobility transistors (HEMTs), which have been shown to deliver low gate leakage and wide safe operating gate-bias range. The intrinsic gate leakage through the PNJ-gate was found to be limited by the transport of holes through the ${p}$ -GaN layer, which occurs via Poole-Frenkel emission and phonon-assisted tunneling in low and high gate bias region, respectively. In addition, lateral leakage current and the role of variable hopping process (VRH) are also discussed. Gate leakage current models based on the revealed mechanisms can quantitatively reproduce the gate-leakage behavior in the entire relevant range of gate biases and temperatures.

We use molecular dynamics (MD) simulation with numerical characterisation and statistical analysis to study the mechanisms of damage evolution and p-type doping efficiency by aluminum (Al) ion implantation into 3C silicon carbide (SiC) with subsequent annealing. By incorporating the electronic stopping power for implantation, a more accurate description of the atomic-scale mechanisms of damage evolution and distribution in SiC can be obtained. The simulation results show a novel observation that the recrystallization process occurs in the region below the subsurface layer, and develops from amorphous-crystalline interface to the damage center region, which is a new insight into previously published studies. During surface recrystallization, significant compressive stress concentration occurs, and more structural phase transition atoms and dislocations formed at the damage-rich-crystalline interface. Another point of interest is that for low-dose implantation, more implantation-induced defects hamper the doping efficiency. Correspondingly, the correlation between lattice damage and doping efficiency becomes weaker as the implant dose increases under the same annealing conditions. Our simulation also predicts that annealing after high temperature (HT) implantation is more likely to lead to the formation of carbon vacancies (V-C).

Purple Passion fruit (Passiflora edulis) is widely cultivated in many regions of southern China as an edible tropical fruit with excellent nutritional value and high economic value. In July 2021, postharvest fruit rot was observed on 20-25% of purple passion fruit in several fruit markets of Dehong City in Yunnan Province. Symptoms on infected fruits were irregular, pink-brown, soft, and water-soaked lesions, which enlarged and formed sunken patches with time as well as producing a small amount of white mycelium. To isolate the causal organism, five diseased fruits were collected from different fruit markets. A conidial mass from an individual sorus observed on an infected fruit was isolated and cultured on potato dextrose agar (PDA) supplemented with 50 μg ml-1 of streptomycin, and five fungal isolates were obtained. These isolates were morphologically similar and produced pale pink colonies on PDA for 7 days containing several conidiophores with abundant conidia. Mycelia were hyaline, 2 µm in diameter, and conidiophores were simple or branched (100 to 286 × 1.5 to 2.5 µm, n=50). Conidia were pyriform, ovate, with papillary protuberances at one end. Almost all conidia were two-celled and single-septate (5.8 to 9.1 × 1.7 to 4.9 µm, n=50). The morphology of the fungi resembled Trichothecium roseum as reported previously (Inácio et al. 2011). To further confirm the fungal species, isolate PASF4 was selected for molecular identification by amplifying and sequencing the ribosomal internal transcribed spacer (ITS) and large subunit (LSU) genes. Primers and PCR amplification were described by Fell et al. (2000). Results showed that both the ITS (GenBank accession OL336243) and LSU (OL336242) gene sequences had 100% similarity to T. roseum in NCBI database (MH856757 and MH868278). Maximum likelihood tree was constructed using MEGA 7 (Felsenstein, 1981) based on concatenated sequences (ITS and LSU) of isolate PASF4 and reference strains. Phylogenetic analysis showed that isolate PASF4 belonged to T. roseum clade. Based on morphological characteristics and phylogenetic analysis, isolate PASF4 was identified as T. roseum (Inácio et al. 2011). To confirm their pathogenicity, healthy purple passion fruits (cv. Tainong-1) were disinfected in 0.5% NaClO solution for 2 min, and then washed with sterile water. After wounding with a sterile needle, the fruits were inoculated by placing mycelium agar plugs on the wounds, and mock inoculation with mycelium-free PDA plugs served as control. Five fruits were used in each treatment. All fruits were maintained in plastic boxes at 25 °C. Disease symptoms appeared after inoculation for 4-7 days on all inoculated fruits, which were similar to those observed in fruit markets. No symptoms were observed on fruits used as control. The Trichothecium isolates were re-isolated from symptomatic fruits thus fulfilling Koch's postulates. Trichothecium roseum has been reported to cause fruit rot of tomato, apple and orange in Pakistan (Hamid et al., 2014) and fruit rot of pepper in China (Lin et al., 2016). To our knowledge, this is the first report of T. roseum causing fruit rot on purple passion fruit worldwide, and these data will provide useful information for developing effective control strategies.

Practice makes perfect in almost all perceptual tasks, but how perceptual improvements accumulate remains unknown. Here, we developed a multicomponent theoretical framework to model contributions of both long- and short-term processes in perceptual learning. Applications of the framework to the block-by-block learning curves of 49 adult participants in seven perceptual tasks identified ubiquitous long-term general learning and within-session relearning in most tasks. More importantly, we also found between-session forgetting in the vernier-offset discrimination, face-view discrimination, and auditory-frequency discrimination tasks; between-session off-line gain in the visual shape search task; and within-session adaptation and both between-session forgetting and off-line gain in the contrast detection task. The main results of the vernier-offset discrimination and visual shape search tasks were replicated in a new experiment. The multicomponent model provides a theoretical framework to identify component processes in perceptual learning and a potential tool to optimize learning in normal and clinical populations.

As a promising material for quantum technology, silicon carbide (SiC) has attracted great interest in materials science. Carbon vacancy is a dominant defect in 4H-SiC. Thus, understanding the properties of this defect is critical to its application, and the atomic and electronic structures of the defects needs to be identified. In this study, density functional theory was used to characterize the carbon vacancy defects in hexagonal (h) and cubic (k) lattice sites. The zero-phonon line energies, hyperfine tensors, and formation energies of carbon vacancies with different charge states (2−, −, 0,+ and 2+) in different supercells (72, 128, 400 and 576 atoms) were calculated using standard Perdew-Burke-Ernzerhof and Heyd-Scuseria-Ernzerhof methods. Results show that the zero-phonon line energies of carbon vacancy defects are much lower than those of divacancy defects, indicating that the former is more likely to reach the excited state than the latter. The hyperfine tensors of VC+(h) and VC+(k) were calculated. Comparison of the calculated hyperfine tensor with the experimental results indicates the existence of carbon vacancies in SiC lattice. The calculation of formation energy shows that the most stable carbon vacancy defects in the material are VC2+(k), VC+(k), VC(k), VC−(k) and VC2−(k) as the electronic chemical potential increases.

We present evidence of homogenization of atomic diffusion properties caused by C and N interstitials in an equiatomic single-phase high entropy alloy (FeMnNiCoCr). This phenomenon is manifested by an unexpected interstitial-induced reduction and narrowing of the directly experimentally determined migration barrier distribution of mono-vacancy defects introduced by particle irradiation. Our observation by positron annihilation spectroscopy is explained by state-of-the-art theoretical calculations that predict preferential localization of C/N interstitials in regions rich in Mn and Cr, leading to a narrowing and reduction of the mono-vacancy size distribution in the random alloy. This phenomenon is likely to have a significant impact on the mechanical behavior under irradiation, as the local variations in elemental motion have a profound effect on the solute strengthening in high entropy alloys. (C) 2021 The Authors. Published by Elsevier Ltd on behalf of Acta Materialia Inc.

${\mathrm{Ga}}_{2}{\mathrm{O}}_{3}$ is a wide-band-gap semiconductor of great interest for applications in electronics and optoelectronics. Two-dimensional (2D) ${\mathrm{Ga}}_{2}{\mathrm{O}}_{3}$ synthesized from top-down or bottom-up processes can reveal new heterogeneous structures and promising applications. In this paper, we study phase transitions among three low-energy stable ${\mathrm{Ga}}_{2}{\mathrm{O}}_{3}$ monolayer configurations using density functional theory and a machine learning Gaussian approximation potential, together with solid-state nudged elastic band calculations. Kinetic minimum energy paths involving direct atomic jump as well as concerted layer motion are investigated. The low phase transition barriers indicate feasible tunability of the phase transition and orientation via strain engineering and external electric fields. Large-scale calculations using the trained machine learning potential on the thermally activated single-atom jumps reveal the clear nucleation and growth processes of different domains. The results provide useful insights into future experimental synthesis and characterization of 2D ${\mathrm{Ga}}_{2}{\mathrm{O}}_{3}$ monolayers.

The matrix assembly cluster source (MACS) represents a bridge between conventional instruments for cluster beam deposition (CBD) and the level of industrial production. The method is based on Ar+ ion sputtering of a pre-condensed Ar-M matrix (where M, is typically a metal such as Ag). Each Ar+ ion produces a collision cascade and thus the formation of metal clusters is in the matrix, which are then sputtered out. Here we present an experimental and computational investigation of the cluster emission process, specifically its dependence on the Ar+ ion angle of incidence and the cluster emission angle. We find the incidence angle strongly influences the emerging cluster flux, which is assigned to the spatial location of the deposited primary ion energy relative to the cluster into the matrix. We also found an approximately constant angle between the incident ion beam and the peak in the emitted cluster distribution, with value between 99° and 109°.

To investigate the effect of high-order aberrations (HOAs) on pattern-reversal visual evoked potentials (PR-VEPs), we measured PR-VEPs with HOAs either retained or corrected with an adaptive optics (AO) system for 12 subjects. The PR-VEPs at different spatial frequencies were recorded for the dominant eye of each subject. The results indicated that the amplitude of the first positive P1 wave at 1–16 cpd (except 2 cpd) and the second negative N2 wave at 12 and 16 cpd were raised statistically significantly with HOA correction. This confirmed the contributions of the HOAs to the alterations in PR-VEPs, and suggested that HOAs should be corrected to realize accurate PR-VEP testing.

This paper proposes high-efficiency $E$ -band power amplifiers (PAs) in SiGe-BiCMOS based on a common-base output stage. A comparison between common-emitter and common-base configurations proves the latter yields higher output power, enhanced linear range, and robustness against self-heating issues. Furthermore, the base–emitter junction of the BJT in common base can be exploited to implement the current-mode version of the well-known diode voltage clamper, so that the dc current tracks the signal current. This yields an improvement of efficiency, particularly in power back-off. Two PA designs are described: a single-path, two-stage amplifier and a second version delivering higher output power with transformer-based power combining at minimal efficiency degradation. At 80 GHz, the two PAs deliver 18- and 20.5-dBm ${\mathrm {OP}}_{1\,\mathrm {dB}}$ and 19- and 21.5-dBm $P_{\mathrm {sat}}$ . The PAE at ${\mathrm {OP}}_{1\,\mathrm {dB}}$ is 22% and 20%; at 6-dB back-off, it is still 8.5% and 7.2%, respectively. The prototypes demonstrate two—three times higher PAE compared to previously reported silicon PAs with similar output power at the $E$ -band.

A two-dimensional (2D) Ga2O3 monolayer with an asymmetric quintuple-layer configuration was reported as a novel 2D material with excellent stability and strain tunability. This unusual asymmetrical structure opens up new possibilities for improving the selectivity and sensitivity of gas sensors by using selected surface orientations. In this study, the surface adsorptions of nine molecular gases, namely, O2, CO2, CO, SO2, NO2, H2S, NO, NH3, and H2O, on the 2D Ga2O3 monolayer are systematically investigated through first-principles calculations. The intrinsic dipole of the system leads to different adsorption energies and changes in the electronic structures between the top- and bottom-surface adsorptions. Analyses of electronic structures and charge transport calculations indicate a potential application of the 2D Ga2O3 monolayer as a room-temperature NO gas-sensing device with high sensitivity and tunable adsorption energy using plenary strain-induced lattice distortion.

Atomic and close-to-atomic scale fabrication with high yield for the color centers in silicon carbide is critical in developing its applications. Combined with Wigner-Seitz method and identify diamond structure method to consider the structure around the silicon vacancy (VSi), it is found that He ion implantation is more likely to fabricate a small number of silicon vacancies with complete structure but locating deep, while Si ion implantation is more likely to introduce more silicon vacancies with incomplete structure but a large number and closer to the near surface. Therefore, a method of dual ion implantation is proposed in this paper. By adjusting the ratio of He to Si ion concentration for dual ion implantation, the fabrication yield of color centers with depth below 5 nm can be increased compared with that of He implantation after high temperature annealing. Molecular dynamics (MD) simulation is employed to discover the underlying mechanism of VSi color center and damage evolution by helium ion and dual ion implantation into four-hexagonal silicon carbide (4H–SiC) with subsequent annealing. Density-functional theory (DFT) calculation proves that magnetic-spin polarization enhances the stability of carbon anti-vacancy pair (CSiVC) defect, which indicates CSiVC defects are more stable than VSi defects. The evolution of the VSi color centers of different defect models are also calculated at various temperatures by MD, and the dynamic process of VSi defects to CSiVC defects is demonstrated. It is revealed that the decrease of the VSi color center at high temperature annealing is partly due to the transformation of some silicon vacancies to CSiVC defects.

Nanomaterials undergoing cyclic swelling-deswelling benefit from inner void spaces that help accommodate significant volumetric changes. Such flexibility, however, typically comes at a price of reduced mechanical stability, which leads to component deterioration and, eventually, failure. Here, we identify an optimised building block for silicon-based lithium-ion battery (LIB) anodes, fabricate it with a ligand- and effluent-free cluster beam deposition method, and investigate its robustness by atomistic computer simulations. A columnar amorphous-silicon film was grown on a tantalum-nanoparticle scaffold due to its shadowing effect. PeakForce quantitative nanomechanical mapping revealed a critical change in mechanical behaviour when columns touched forming a vaulted structure. The resulting maximisation of measured elastic modulus (similar to 120GPa) is ascribed to arch action, a well-known civil engineering concept. The vaulted nanostructure displays a sealed surface resistant to deformation that results in reduced electrode-electrolyte interface and increased Coulombic efficiency. More importantly, its vertical repetition in a double-layered aqueduct-like structure improves both the capacity retention and Coulombic efficiency of the LIB. Lithiation of anodes during cycling of lithium-ion batteries generates stresses that reduce operation lifetime. Here, a composite silicon-based anode with a nanoscale vaulted architecture shows high mechanical stability and electrochemical performance in a lithium-ion battery., Communications Materials, 2 (1), ISSN:2662-4443

a novel p-GaN gate topology is proposed to inherently increase threshold voltage (V TH ) and enhance V TH stability. The gate consists of a conventional Schottky-type p-GaN gate and a normally-on p-channel FET bridge connecting source and gate. By modulating the V TH of the p-channel FET, a wide-range positive V TH from 3.6 V to 8.2 V can be achieved without subthreshold voltage degradation. Owing to the well-grounded p-GaN through the normally-on p-FET channel, a stable V TH is also achieved without sacrificing the low gate leakage and large gate swing enabled by the Schottky gate metal/p-GaN contact.

Nanoparticles (NPs), as the most prototypical functional building blocks in nanoscience, exhibit size-, shape-, composition-, and structure-dependent behavior which is different from the corresponding bulk materials. Arguably, the structures and properties of NPs cannot be understood purely from experimental data. Deeper insights can be gained by complementary theoretical or computational modeling. This chapter presents an introduction to simulations of metallic and semiconductor NPs in inert environment using multiscale computational modeling techniques, including density functional theory, classical molecular dynamics, and Monte Carlo methods. We review relevant results obtained with such simulations in the field of cluster beam deposition and comment on several challenges that need to be addressed in future.

Spontaneous growth of complexes consisted of a number of individual nanoparticles in a controlled manner, particularly in demanding environments of gas-phase synthesis, is a fascinating opportunity for numerous potential applications. Here, we report the formation of such core-satellite gold nanoparticle structures grown by magnetron sputtering inert gas condensation. Combining high-resolution scanning transmission electron microscopy and computational simulations, we reveal the adhesive and screening role of H2O molecules in formation of stable complexes consisted of one nanoparticle surrounded by smaller satellites. A single layer of H2O molecules, condensed between large and small gold nanoparticles, stabilizes positioning of nanoparticles with respect to one another during milliseconds of the synthesis time. The lack of isolated small gold nanoparticles on the substrate is explained by Brownian motion that is significantly broader for small-size particles. It is inferred that H2O as an admixture in the inert gas condensation opens up possibilities of controlling the final configuration of the different noble metal nanoparticles.

Atomistic rigid lattice Kinetic Monte Carlo (KMC) is an efficient method for simulating nano-objects and surfaces at timescales much longer than those accessible by molecular dynamics. A laborious and non-trivial part of constructing any KMC model is, however, to calculate all migration barriers that are needed to give the probabilities for any atom jump event to occur in the simulations. We calculated three data sets of migration barriers for Fe self-diffusion: barriers of first nearest neighbour jumps, second nearest neighbours hop-on jumps on the Fe {100} surface and a set of barriers of the diagonal exchange processes for various cases of the local atomic environments within the 2nn coordination shell. Keywords: Copper, Iron, Kinetic Monte Carlo, Surface diffusion, Rigid lattice, Migration barriers, Atomic jumps