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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]

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]

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.