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We developed an accurate and efficient machine learning potential with DFT accuracy and applied it to the silicon dry/wet oxidation process to investigate the underlying physics of thermal oxidation of silicon (001) surfaces. The accuracy of the potential was verified by comparing the melting point and structural properties of silicon, the structural properties of a-SiO2, and the adsorption properties on the silicon surface with experiment and DFT data. In subsequent thermal oxidation simulations, we successfully reproduced the accelerated growth phenomenon of the wet oxidation in the experiment, discussed the oxide growth process in detail, and elucidated that the accelerated growth is due to hydrogen in the system that both enhances the adsorption of oxygen on the silicon surface and promotes the migration of oxygen atoms. Finally, we annealed the oxidized structure, counted the defect information in the structure before and after annealing, and analyzed the defect evolution behavior during the annealing process. [ABSTRACT FROM AUTHOR]

Herein, the efficiently high‐power pulsed Raman lasers with wavelength above 2.1 μm are experimentally demonstrated relying on the stimulated Raman scattering. A tailored high‐power noise‐like pulse (NLP) fiber laser system centered at ≈1953 nm with a maximum output power of ≈10.9 W is served as the pump source. By directly pumping a section of highly Ge‐doped silica fiber, the first pulsed Raman laser (centered at≈2139 nm) and the second pulsed Raman laser (centered at ≈2353 nm) with maximum output powers of ≈3.8 and ≈0.25 W are obtained, respectively, which represent the highest output powers of NLP at these wavelength regions, to the best of knowledge. Moreover, a high spectral purity of ≈94.3% of the first Raman laser is obtained, which indicates the significantly potential application of NLP in pulsed Raman laser. The midinfrared NLP fiber laser source will have potential applications in transparent polymer materials processing and midinfrared spectroscopy. [ABSTRACT FROM AUTHOR]

Fipronil is a widely used insecticide. Exposure of humans to fipronil can cause harmful health effects. The aim of the present work is to develop a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the rapid detection of fipronil and its metabolites in eggs and environmental matrices (soil, feed, and chicken feed bags). Solvent extraction was performed with a mixture including water, acetonitrile, and sodium chloride, followed by purification using a solid-phase extraction column. The LC separation was accomplished on a C18 column, and the detection was performed with a triple quadrupole mass spectrometer using electrospray ionization in multiple reaction monitoring (MRM) mode. The results showed a good linear relationship between fipronil and its metabolites in the range of 0.01 to 20 ng/mL, and the linear correlation coefficients ([R.sup.2]) were all greater than 0.999. The detection and quantification limits of the method for all analytes were 0.01 and 0.05 ng/mL, respectively. The precision expressed as coefficients of variation (n = 3) for assay of fipronil and its metabolites ranged from 8.4% to 13.2% at three levels (0.1 ng/mL, 1 ng/mL, and 10 ng/mL). The recoveries ranged from 81.3% to ~119.5%. Finally, we successfully employed the method to a case of fipronil contamination, and found residues of fipronil and its metabolites in eggs and the environmental matrix., Fipronil is a type of benzopyrazole insecticide developed in 1987 by Bayer Scientific Crops Co. Ltd. (1), and is widely used to control crop pests in vegetables, rice, tobacco, cotton, [...]

Tapered fiber (TF) and D-shaped fiber (DF) are two types of widely investigated devices in facilitating evanescent-field interactions with external materials. Although they have been found to be particularly useful in various ultrafast regimes, to date there is still no clear or systematic investigation on their local nonlinearities as well as the exerted influences on ultrafast behaviors. Herein, we present such thorough investigation through local nonlinearity engineering on TF and then in contrast with a DF as a reference. Optically deposited black phosphorus quantum dots (BPQDs) are used for saturable absorption. The nanometer-scale extremely small sizes of the BPQDs helpfully eliminate size-induced uncertainties or distortions during both device fabrication and the latter light–matter interaction. For the TF, in the experiment, it is found that the local nonlinear effect starts to be rather appreciable as the TF shrinks to a moderate thickness. Remarkably in comparison, the local nonlinearity of the DF itself can even be neglected reasonably, but after coating with BPQDs, it possesses a much larger modulation depth than any of the used BPQDs-coated TFs with different thicknesses/lengths. Further, we theoretically analyze the related locally nonlinear effects and reveal, for the first time, the direct origin of saturable absorption with evanescent-field-based general structures.

The metal–insulator transition (MIT) of vanadium dioxide (VO2), which involves significant changes in electrical, optical, and other properties, has attracted widespread attention. Here, we report a triboelectric nanogenerator (TENG)-based self-powered VO2 phase transition. With the TENG-induced ionic gel gating, the hydrogen ion insertion/detachment in the VO2 lattice can be modulated at room temperature to cause phase transitions that control light transmittance. The phase transition behavior is characterized by X-ray diffraction and Raman spectroscopy. Under the continuous power supply from TENG, the X-ray diffraction peak of VO2 shifts, and the Raman intensities of characteristic peaks decrease, accompanied by a color change from brown to translucent. The electrical conductivity undergoes a significant change by two orders of magnitude and persists overnight, indicating an excellent duration of the phase transition. In addition, a raindrop TENG-induced VO2 phase transition is demonstrated. The infrared transmittance of VO2 is decreased dramatically by 28.1% due to the phase transition, achieving a heat preservation effect that holds promise for adaptive thermal insulation in smart windows during rainfall through raindrop power generation. This work has realized the TENG-based self-powered VO2 phase transition, holding significant application potential in smart homes. [ABSTRACT FROM AUTHOR]

Highlights: A flexible tribotronic artificial synapse with bioinspired neurosensory behaviour was demonstrated, which establishes an active interaction mechanism with the environment. The device can well exhibit tuneable synaptic behaviours by changing the mechanical input modes, including excitatory postsynaptic current, paired-pulse facilitation, and the hierarchical memorial process. The device has excellent mechanical flexibility that can exhibit stable synaptic functions even under strain conditions with a bending radius of 20 mm after 1000 bending cycles. As key components of artificial afferent nervous systems, synaptic devices can mimic the physiological synaptic behaviors, which have attracted extensive attentions. Here, a flexible tribotronic artificial synapse (TAS) with bioinspired neurosensory behavior is developed. The triboelectric potential generated by the external contact electrification is used as the ion-gel-gate voltage of the organic thin film transistor, which can tune the carriers transport through the migration/accumulation of ions. The TAS successfully demonstrates a series of synaptic behaviors by external stimuli, such as excitatory postsynaptic current, paired-pulse facilitation, and the hierarchical memory process from sensory memory to short-term memory and long-term memory. Moreover, the synaptic behaviors remained stable under the strain condition with a bending radius of 20 mm, and the TAS still exhibits excellent durability after 1000 bending cycles. Finally, Pavlovian conditioning has been successfully mimicked by applying force and vibration as food and bell, respectively. This work demonstrates a bioinspired flexible artificial synapse that will help to facilitate the development of artificial afferent nervous systems, which is great significance to the practical application of artificial limbs, robotics, and bionics in future. [ABSTRACT FROM AUTHOR]

With the rapid development of Internet technology, the network information data is exploding, and society has entered the era of cloud data. Cloud data provides a lot of data support for people's life and work, but because of its large number, multifarious types and huge value, there are some problems such as private data leakage and abuse of sensitive information. Stocking of biomedical material at one place only, can cause delay in sending important lifesaving material to needy patients. On the one hand, it is an important content of engineering scheduling theory and method; On the other hand, in medical field, a lot of materials are usually consumed to protect the life of patients. Biomedical informatics and computer vision techniques have been combined in a variety of inter‐multidisciplinary disciplines during the past few decades. We are all aware that inadequate or insufficient cloud access management and controls can expose a corporation to a range of issues. The work that follows offers intelligent supply chain, an upgraded service management control telephone network architecture. If we can acquire according to the patient demands and retain the ideal inventory such that the patient requirement and interest can be safe, the overall cost will be lowered greatly. The experimental results show that R1 orders 31 times, and the total cost is 1,259,520 CNY. R2 ordered 24 times, with a total cost of 982,034 CNY; R3 orders 22 times, and the total cost is 990,146 CNY. Finally, the optimal solution of the total cost after schedule optimization is 3,231,700 CNY. It is proved that the optimal cost finally obtained by forecasting supply chain inventory information based on cloud data environment is also more practical for engineering practice. [ABSTRACT FROM AUTHOR]

This paper presents a multi-scale numerical method to study the electrolyte material BaZrO3 (BZO) and gives numerical implementations and results. At the microscopic level, molecular dynamics (MD) is used to model the atomic structure of BZO. At the macroscopic level, the finite element method is used for loading and numerical solution. To bridge the microscopic and macroscopic scales, the concept of coarse-grained and coupled algorithms was used to establish a relationship between the atomic mass and the number of nodes in a continuous medium by means of a weighted residual method. This approach takes into account the anisotropy of the atomic structure of BZO and determines an intrinsic nature law through detailed modelling of the microstructure. We first describe the principle of the Atom-to-Continuum (AtC) multiscale approach and verify the accuracy of the multiscale calculation method by comparing the stress–strain curves of BZO with a central crack under the AtC method and MD simulations. The mechanical response of the crack under macroscopic and microscopic calculations is then observed and discussed by combining it with finite element software. Under the finite element simulations, the crack extends forward in a cleavage manner, while in the MD simulations the results show a clear directional dependence: the (100) surface fracture involves in-plane slip, with the crack propagating forward perpendicular to the plane between Zr and O; in the (110) surface the crack is unstable as it extends, resulting in a zigzag crack extension path, with the final crack remaining in the same direction as the initial direction remains the same. Our study not only reveals the fracture mechanism of perovskite oxide BZO but also presents a multi-scale approach that allows for large-scale calculations, providing a new way of studying the material design and applications. [ABSTRACT FROM AUTHOR]

Dislocations are important for their effects on the chemical, electrical, magnetic, and transport properties of oxide materials, especially for electrochemical devices such as solid fuel cells and resistive memories, but these effects are still under-studied at the atomic level. We have developed a quantum mechanical/molecular mechanical (QM/MM)-based multiscale simulation program to reveal the diffusion properties of protons on 〈100〉 edge dislocations in BaZrO3 perovskite oxide. We find that the large free space and the presence of hydrogen bonds in the dislocation core structure lead to significant trapping of protons. The diffusion properties of protons in dislocation cores were investigated, and no evidence of pipeline diffusion was found from the calculated migration energy barriers, which not only did not accelerate ion diffusion but rather decreases the conductivity of ions. The proton diffusion properties of Y-doped BaZrO3 (BZY), with a dislocation core structure (BZY-D) and with a grain boundary structure (BZY-GB) were also compared. In all three structures, local lattice deformation occupies an essential part in the proton transfer and rotation processes. The change in bond order is calculated and it is found that the interaction with oxygen and Zr ions during proton transfer and rotation controls the energy barrier for local lattice deformation of the O–B–O motion, which affects the proton diffusion in the structure. Our study provides insight into proton diffusion in dislocations in terms of mechanical behavior, elucidates the origin of the energy barrier associated with proton diffusion in dislocations, and provides guidance for the preparation and application of proton conductors. [ABSTRACT FROM AUTHOR]

In order to effectively solve the problem of vehicle routing, a design and implementation method of an energy-saving logistics management system oriented to routing optimization is proposed. From the perspective of optimal calculation, this research uses the improved Dixie algorithm and clustering algorithm to design and implement a logistics company's distribution center location and distribution path planning system. First of all, the authors analyze the common models of the LRP problem in detail and give the mathematical model and calculation method of positioning rationing and the transportation route planning problem. Secondly, in view of the shortcomings of traditional evolutionary algorithms, the authors propose a series of improvement measures. The authors adopt a natural number coding scheme combined with an adaptive crossover mutation operator to improve the search ability of the solution space; the authors also introduce a penalty function to deal with constraints and take corresponding measures for illegal individuals generated in the evolution process, reducing premature convergence. Possibility. It has been verified that the design and development of the system saves investment costs for small and medium-sized logistics enterprises and reduces the cost of goods distribution by 80%. The effect is remarkable, which verifies the effectiveness, accuracy, and superiority of the algorithm. [ABSTRACT FROM AUTHOR]

With the extensive application of wireless sensing nodes, the demand for sustainable energy in unattended environments is increasing. Here, we report a self-powered and autonomous vibrational wake-up system (SAVWS) based on triboelectric nanogenerators and micro-electromechanical system (MEMS) switches. The energy triboelectric nanogenerator (E-TENG) harvests vibration energy to power the wireless transmitter through a MEMS switch. The signal triboelectric nanogenerator (S-TENG) controls the state of the MEMS switch as a self-powered accelerometer and shows good linearity in the acceleration range of 1–4.5 m/s2 at 30 Hz with a sensitivity of about 14.6 V/(m/s2). When the acceleration increases, the S-TENG turns on the MEMS switch, and the wireless transmitter transmits an alarm signal with the energy from E-TENG, using only 0.64 mJ. Using TENGs simultaneously as an energy source and a sensor, the SAVWS provides a self-powered vibration monitoring solution for unattended environments and shows extensive applications and great promise in smart factories, autonomous driving, and the Internet of Things. [ABSTRACT FROM AUTHOR]

Tapered fiber (TF) and D-shaped fiber (DF) are two types of widely investigated devices in facilitating evanescent-field interactions with external materials. Although they have been found to be particularly useful in various ultrafast regimes, to date there is still no clear or systematic investigation on their local nonlinearities as well as the exerted influences on ultrafast behaviors. Herein, we present such thorough investigation through local nonlinearity engineering on TF and then in contrast with a DF as a reference. Optically deposited black phosphorus quantum dots (BPQDs) are used for saturable absorption. The nanometer-scale extremely small sizes of the BPQDs helpfully eliminate size-induced uncertainties or distortions during both device fabrication and the latter light–matter interaction. For the TF, in the experiment, it is found that the local nonlinear effect starts to be rather appreciable as the TF shrinks to a moderate thickness. Remarkably in comparison, the local nonlinearity of the DF itself can even be neglected reasonably, but after coating with BPQDs, it possesses a much larger modulation depth than any of the used BPQDs-coated TFs with different thicknesses/lengths. Further, we theoretically analyze the related locally nonlinear effects and reveal, for the first time, the direct origin of saturable absorption with evanescent-field-based general structures. [ABSTRACT FROM AUTHOR]

Nonlinear amplifying-loop mirror (NALM) and nonlinear optical loop mirror (NOLM) are two basic Sagnac interferometers widely used in mode-locked fiber lasers. Here we construct a variant by replacing the amplifier in an NALM with an absorber, which forms a type of nonlinear absorbing-loop mirror (NAbLM). The optical waves counter-propagating within an ideal NAbLM possess equal optical powers when they return and interfere inside the used fiber coupler owing to the equal absorptions. Meanwhile, their nonlinear phase shifts can still differ adequately if an asymmetric distribution of the absorber is employed. We theoretically predict that, in comparison to typical NALM and NOLM, the NAbLM can achieve relatively higher extinction ratio and larger modulation depth, resting on the unique equal-power interference. We then first used it as a saturable absorber in a holmium-doped fiber laser and achieved passively mode-locked operations in both normal and anomalous dispersion regimes. In the normal dispersion regime, h-shaped pulse was generated; whereas in the anomalous dispersion regime, both noise-like and dissipative-soliton-resonance-like pulses were achievable with polarization manipulation. NAbLM enables more options in nonlinear fiber optics especially when a high extinction ratio or large modulation depth is required. [ABSTRACT FROM AUTHOR]

Physical parameter sensing largely benefits the lifetime and operational costs of machines and has been widely used for machine fault detection. Herein, in this article, we developed a multinode sensor network, which is fully self-powered by harvesting mechanical vibration energy, to establish a machine fault detection system. A multilayered vibrational triboelectric nanogenerator (V-TENG) was designed to scavenge energy from working machines. Triggered by a vibration motion with the frequency of 8 Hz, the V-TENG can generate an output with power density of 3.33 mW/m3. With a power management module, the microcontrol unit integrated with sensors and a wireless transmitter can be continuously powered by the V-TENG to construct a self-powered vibration sensor node (SVSN). A supporting vector machine algorithm-based machine fault detection system was then established through a three-SVSN network by acquiring acceleration and temperature data from the working machine. Based on the system, different working conditions of the machine were recognized with an accuracy of 83.6%. The TENG-based SVSN for machine fault detection has demonstrated wide prospects in production monitoring, intelligent manufacturing, and smart factory. Moreover, the proposed self-powered sensor network has great potential and wide application in the era of distributed Internet of Things, artificial intelligence, and big data. [ABSTRACT FROM AUTHOR]

The development of the sensor array has received substantial attention due to its enormous potential in artificial intelligences. The development of a sensor array with supernatural functions is of great significance and this paper presents a sort of flexible sensor array capable of recognizing material based on the electrostatic induction and triboelectric effects. In the nature, different materials have different abilities of gaining or donating electrons. When a tested material (including plastic, glass, or metal) approaches or leaves different probe materials integrated in the sensor array, the amplitude and phase of the induced electrical signals, which are related to the inherent feature of the tested material, are detected and analyzed, and then, the tested material can be distinguished. This sort of flexible sensor array has advantages of quick response (70 ms), accurate identification, low cost, and easy fabrication. It has promising application in wearable electronic devices and intelligent robots. [ABSTRACT FROM AUTHOR]

The triboelectric nanogenerator (TENG) is a new energy technology that is enabled by coupled contact electrification and electrostatic induction. The conventional TENGs are usually based on organic polymer insulator materials, which have the limitations and disadvantages of high impedance and alternating output current. Here, a tribovoltaic effect based metal–semiconductor direct‐current triboelectric nanogenerator (MSDC‐TENG) is reported. The tribovoltaic effect is facilitated by direct voltage and current by rubbing a metal/semiconductor on another semiconductor. The frictional energy released by the forming atomic bonds excites nonequilibrium carriers, which are directionally separated to form a current under the built‐in electric field. The continuous average open‐circuit voltage (10–20 mV), short‐circuit direct‐current output (10–20 µA), and low impedance characteristic (0.55–5 kΩ) of the MSDC‐TENG can be observed during relative sliding of the metal and silicon. The working parameters are systematically studied for electric output and impedance characteristics. The results reveal that faster velocity, larger pressure, and smaller area can improve the maximum power density. The internal resistance is mainly determined by the velocity and the electrical resistance of semiconductor. This work not only expands the material candidates of TENGs from organic polymers to semiconductors, but also demonstrates a tribovoltaic effect based electric energy conversion mechanism. [ABSTRACT FROM AUTHOR]