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[en] The application of nanotechnology in agriculture, pesticide delivery and other related fields increases the occurrence of engineered nanoparticles (ENPs) in soil. Since ENPs have larger surface areas and normally a high adsorption capacity for organic pollutants, they are thought to influence the transport of pesticides in soils and thereafter influence the uptake and transformation of pesticides. The adsorption pattern of racemic-metalaxyl on agricultural soils including kinetics and isotherms changed in the presence of nano-SiO2. The adsorption of racemic-metalaxyl on agricultural soil was not enantioselective, in either the presence or the absence of SiO2. The adsorption of racemic-metalaxyl on SiO2 decreased to some extent in soil-SiO2 mixture, and the absolute decrease was dependent on soil properties. The decreased adsorption of metalaxyl on SiO2 in soil-SiO2 mixture arose from the competitive adsorption of soil-dissolved organic matter and the different dispersion and aggregation behaviors of SiO2 in the presence of soil. Interactions between SiO2 and soil particles also contributed to the decreased adsorption of metalaxyl on SiO2, and the interactions were analyzed by extended Derjaguin–Landau–Verwey–Overbeek theory. The results showed that the presence of nano-particles in soils could decrease the mobility of pesticides in soils and that this effect varied with different soil compositions. - Highlights: • Adsorption of rac-metalaxyl on soil is enhanced by the addition of nano-SiO2. • SiO2 changed nonenantioselective adsorption isotherm from Henry to Freundlich. • SiO2 loses its adsorption capacity after entering soil and the decrease is soil dependent. • Competitive adsorption, different dispersion behavior leads its decreased adsorption. • Interactions between SiO2 and soil particles is quantified by EDLVO calculation. - Nano-SiO2 enhanced the adsorption of metalaxyl in soil and the dispersion behaviors of SiO2 changed in soil accompanied by a change in the adsorption capacity of SiO2.
[en] Accurate estimation of battery pack state-of-charge plays a very important role for electric vehicles, which directly reflects the behavior of battery pack usage. However, the inconsistency of battery makes the estimation of battery pack state-of-charge different from single cell. In this paper, to estimate the battery pack state-of-charge on-line, the definition of battery pack is proposed, and the relationship between the total available capacity of battery pack and single cell is put forward to analyze the energy efficiency influenced by battery inconsistency, then a lumped parameter battery model is built up to describe the dynamic behavior of battery pack. Furthermore, the extend Kalman filter-unscented Kalman filter algorithm is developed to identify the parameters of battery pack and forecast state-of-charge concurrently. The extend Kalman filter is applied to update the battery pack parameters by real-time measured data, while the unscented Kalman filter is employed to estimate the battery pack state-of-charge. Finally, the proposed approach is verified by experiments operated on the lithium-ion battery under constant current condition and the dynamic stress test profiles. Experimental results indicate that the proposed method can estimate the battery pack state-of-charge with high accuracy. - Highlights: • A novel space state equation is built to describe the pack dynamic behavior. • The dual filters method is used to estimate the pack state-of-charge. • Battery inconsistency is considered to analyze the pack usage efficiency. • The accuracy of the proposed method is verified under different conditions.
[en] The state-of-energy is an important evaluation index for energy optimization and management of power battery systems in electric vehicles. Unlike the state-of-charge which represents the residual energy of the battery in traditional applications, state-of-energy is integral result of battery power, which is the product of current and terminal voltage. On the other hand, like state-of-charge, the state-of-energy has an effect on terminal voltage. Therefore, it is hard to solve the nonlinear problems between state-of-energy and terminal voltage, which will complicate the estimation of a battery's state-of-energy. To address this issue, a method based on wavelet-neural-network-based battery model and particle filter estimator is presented for the state-of-energy estimation. The wavelet-neural-network based battery model is used to simulate the entire dynamic electrical characteristics of batteries. The temperature and discharge rate are also taken into account to improve model accuracy. Besides, in order to suppress the measurement noises of current and voltage, a particle filter estimator is applied to estimate cell state-of-energy. Experimental results on LiFePO_4 batteries indicate that the wavelet-neural-network based battery model simulates battery dynamics robustly with high accuracy and the estimation value based on the particle filter estimator converges to the real state-of-energy within an error of ±4%. - Highlights: • State-of-charge is replaced by state-of-energy to determine cells residual energy. • The battery state-space model is established based on a neural network. • Temperature and current influence are considered to improve the model accuracy. • The particle filter is used for state-of-energy estimation to improve accuracy. • The robustness of new method is validated under dynamic experimental conditions.
[en] High ductile steel are usually adopted for the piping material. The stress concentration and the plastic deformation can be found at the crack tip for the ductile material under extemal load which make stress and strain of crack tip domain redistributed and the blunting deformation appeared. Based on the relationship of the elastic-plastic material, 1/4 singular elements are used for crack front discretization, under the displacements control, the blunting process are simulated. The hardening zone and the fracture parameter are studied at different loading rates. (authors)
[en] The paper introduces the features of the OO (Object Oriented) approach, the design principal and method of the emulation software used in DD8000 Multi-Detector Multichannel Energy Spectrum Acquisition System, some problems about display of energy spectrum on Windows are also discussed
[en] In this paper nanometer TiN/AlN multilayers have been prepared on silicon substrate by filtered vacuum arc deposition. The structures of the nanometer TiN/AlN multilayer have been studied with X-ray diffraction. The 12 nm TiN/AlN multilayer exhibits (1 1 1) and (2 0 0) texture, and the 6 and 2 nm thick multilayer exhibits only (2 0 0) texture. The multilayer deposited at -100 V bias exhibits a (1 1 1) texture, whilst the multilayer deposited at 0 V bias exhibits a (2 0 0) texture. At higher bias voltage the peaks become sharper and have a higher intensity in low angle X-ray diffraction. The hardness and elastic modulus of multilayer are dependent on period of multilayer. The hardnesses of the TiN/AlN multilayers are higher than the hardness value suggested by a simple rule of mixture. The peaking hardness of nanometer TiN/AlN multilayers at period of 2 nm was about 42 GPa, much higher than that of 12 nm. The wear resistance of the nanometer TiN/AlN multilayers has also been studied
[en] A novel method was developed to prepare functionalized magnetic beads, in which superparamagnetic Fe3O4 core was synthesized with an injection-precipitation method and then was coated with functional groups using one-step suspension polymerization. In the coating and functionalizing process, a unique coupling reagent, bis-(2-hydroxyethyl methacrylate) phosphate, was introduced so that the monomers polymerized only on the surface of the nanocrystals without forming separate nuclei. The thickness of the coating layer and the size and density of the coated nanobeads were controlled by changing the quantity of the coated monomers. The nanobeads were characterized by transmission electron microscopy, light scattering spectrometry, Fourier transformation infrared spectroscopy, X-ray fluorescence spectroscopy and the magnetic hysteresis loop determination method. The carboxyl-modified magnetic nanobeads were employed to simplify the isolation of genomic DNA from human whole blood
[en] Optical emission spectra of the plasma produced by 1.06-µm Nd:YAG laser irradiation of a potassium titanyl phosphate (KTP) crystal were recorded and analyzed in a time- and spatially resolved manner. The composition and evolution of the plasma plume were studied in low vacuum conditions. Emission lines associated with Ti(I), Ti(II) and K(I) were identified in the plasma. The delay times of emission peaks for the ablated species were investigated as a function of the observation distance from the target surface, and the velocities of these species were derived accordingly. Two emission peaks corresponding to a fast and a slow component of ablated Ti(I) were observed by optical time-of-flight spectroscopy. The origins of the two peaks and a possible mechanism for the laser ablation are discussed. - Highlights: • The optical emission spectra of the plasma plume produced by laser ablation of a KTP crystal were studied in a time- and spatially resolved manner. • Two emission peaks, corresponding to a fast and a slow component of ablated Ti(I), were observed. • The velocities of different species in the plasma plume were derived. • The origins of the two-peak emission of Ti(I) are discussed
[en] Fe-Mn binary oxide (FMBO)/activated charcoal (AC) is blended with carbon black (CB) for use as a dual function catalyst for the effective removal of organic pollutants at neutral pH via electro-Fenton-like oxidation. CB, which is composed of micropores and mesopores, acts as an oxygen reduction catalyst to produce H2O2, and the evenly distributed FMBO nanoparticles effectively catalyze the production of hydroxyl radicals using the on-site generated H2O2. As a result, the FMBO-modified electrode exhibits a high catalytic efficiency over a wide pH range from 3–10. The prepared electrode exhibited a hydroxyl radical production rate of 1.3 μM W−1 cm−2 at neutral pH, higher than that obtained with the blank CB electrode and Fe(II) (0.72 μM W−1 cm−2). The removal efficiency of nitrobenzene reached 80 ± 3% at neutral pH with the FMBO/AC/CB electrode compared to 42 ± 7% with Fe(II). The results from various material characterization techniques including X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), transmission electron microscopy (TEM) confirm that FMBO/AC is bound to poly(tetrafluoroethylene) (PTFE) together with CB in the prepared electrode. These results suggest that electrochemical advanced oxidation using this new FMBO/AC/CB electrode represents a promising approach for organic pollutant removal.
[en] Highlights: • Build an active equalization method for lithium-ion batteries. • A bidirectional transformer topology is introduced for active equalization. • The PF method is used for cell SOC estimation to eliminate drift noise of current. • The SOC based equalization algorithm is analyzed with different SOC bounds. - Abstract: Cell inconsistency is inevitable due to manufacturing constraint. Therefore, cell equalization is essentially required. In this paper, we propose a novel active equalization method based on the remaining capacity of cells which is feasible for lithium-ion battery packs in electric vehicles (EVs). The cell models are established based on a combined electrochemical model of lithium-ion batteries. The remaining capacity and state-of-charge (SOC) of cells are observed at the beginning of equalization. The particle filter (PF) method is employed to estimate the cell SOCs during equalization in order to eliminate the drift noise of the current sensor. The first high-SOC cell discharge (FHCD) and first low-SOC cell charge (FLCC) equalization algorithms are proposed and compared with 1% and 3% SOC bounds, respectively. The validation experiment results have shown that the proposed algorithm is suitable for equalization of lithium-ion batteries in EVs