Enhancement Of The Performance Of Lignin-Derived Hard Carbons For Battery Applications By Chemical Pretreatment

Because of lignin\u27s renewable and low-cost characteristics, lignin-derived hard carbons have been extensively studied as electrode materials for energy storage applications. However, the formation of solid electrolyte interface (SEI) during the first cycle in electrode materials and the loss of lithium/sodium ions during long-term cycling has a fatal impact on the performance of batteries. Recent technology is needed to improve lignin-based electrode materials\u27 initial Coulombic efficiency (ICE). In this study, pre-lithiation/pre-sodiation through the spontaneous chemical reaction between the aryl etherification reagent was used to improve the low ICE of the lignin-based anode material. Our results show that the ICE of the lignin-based anode material can be significantly improved with only a few minutes of treatment. It indicates that the treated is a promising renewable electrode material for battery applications. It can be used in electrochemical energy storage and conversion devices, such as supercapacitors, fuel cells, etc

DeepTransport: Learning Spatial-Temporal Dependency for Traffic Condition Forecasting

Predicting traffic conditions has been recently explored as a way to relieve traffic congestion. Several pioneering approaches have been proposed based on traffic observations of the target location as well as its adjacent regions, but they obtain somewhat limited accuracy due to lack of mining road topology. To address the effect attenuation problem, we propose to take account of the traffic of surrounding locations(wider than adjacent range). We propose an end-to-end framework called DeepTransport, in which Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) are utilized to obtain spatial-temporal traffic information within a transport network topology. In addition, attention mechanism is introduced to align spatial and temporal information. Moreover, we constructed and released a real-world large traffic condition dataset with 5-minute resolution. Our experiments on this dataset demonstrate our method captures the complex relationship in temporal and spatial domain. It significantly outperforms traditional statistical methods and a state-of-the-art deep learning method

A Real-time Nonlinear Model Predictive Controller for Yaw Motion Optimization of Distributed Drive Electric Vehicles

This paper proposes a real-time nonlinear model predictive control (NMPC) strategy for direct yaw moment control (DYC) of distributed drive electric vehicles (DDEVs). The NMPC strategy is based on a control-oriented model built by integrating a single track vehicle model with the Magic Formula (MF) tire model. To mitigate the NMPC computational cost, the continuation/generalized minimal residual (C/GMRES) algorithm is employed and modified for real-time optimization. Since the traditional C/GMRES algorithm cannot directly solve the inequality constraint problem, the external penalty method is introduced to transform inequality constraints into an equivalently unconstrained optimization problem. Based on the Pontryagin’s minimum principle (PMP), the existence and uniqueness for solution of the proposed C/GMRES algorithm are proven. Additionally, to achieve fast initialization in C/GMRES algorithm, the varying predictive duration is adopted so that the analytic expressions of optimally initial solutions in C/GMRES algorithm can be derived and gained. A Karush-Kuhn-Tucker (KKT) condition based control allocation method distributes the desired traction and yaw moment among four independent motors. Numerical simulations are carried out by combining CarSim and Matlab/Simulink to evaluate the effectiveness of the proposed strategy. Results demonstrate that the real-time NMPC strategy can achieve superior vehicle stability performance, guarantee the given safety constraints, and significantly reduce the computational efforts

Zero-voltage ride-through capability of single-phase grid-connected photovoltaic systems

Distributed renewable energy systems play an increasing role in today’s energy paradigm. Thus, intensive research activities have been centered on improving the performance of renewable energy systems, including photovoltaic (PV) systems, which should be of multiple-functionality. That is, the PV systems should be more intelligent in the consideration of grid stability, reliability, and fault protection. Therefore, in this paper, the performance of single-phase grid-connected PV systems under an extreme grid fault (i.e., when the grid voltage dips to zero) is explored. It has been revealed that combining a fast and accurate synchronization mechanism with appropriate control strategies for the zero-voltage ride-through (ZVRT) operation is mandatory. Accordingly, the representative synchronization techniques (i.e., the phase-locked loop (PLL) methods) in the ZVRT operation are compared in terms of detection precision and dynamic response. It shows that the second-order generalized integrator (SOGI-PLL) is a promising solution for single-phase systems in the case of fault ride-through. A control strategy by modifying the SOGI-PLL scheme is then introduced to single-phase grid-connected PV systems for ZVRT operation. Simulations are performed to verify the discussions. The results have demonstrated that the proposed method can help single-phase PV systems to temporarily ride through zero-voltage faults with good dynamics

Research on Heat Transfer Inside the Furnace of Large Scale CFB Boilers

Field tests in one unit of 135MWe and two units of 300MWe commercial Circulating Fluidized bed (CFB) boilers (A&B) with different structures were carried out. The influence of operating conditions on the thermal boundary layer, local heat transfer coefficient and peripheral distribution of heat transfer coefficient were studied. It was found that, in the 135MWe and 300MWe-A CFB furnace, the thickness of the thermal boundary layer was almost constant, about 100mm, and independent of the height above the distributor and the boiler load. The local heat transfer coefficient increased with increasing load as well as the coal feeding rate and air volume in both the 135MWe and 300MWe-A CFB boilers. The boiler structure and heating surface layout had a great influence on the distribution of the heat transfer coefficient in the large-scale CFB boilers. In both the 135MWe furnace and the 300MWe-B CFB boilers, the heat transfer coefficient was lower in the center than near the corner due to higher suspension density in the corner. In the 300MWe-B CFB with heating surfaces in the furnace, because of the uneven layout of the heating surface and the mal-distribution of gas-solid flow caused by the asymmetric arrangement of cyclones, heat transfer coefficients tended to be higher in the middle part than at the walls

Active Disturbance Rejection Control of Thermal Power Unit Coordinated System based on Frequency Domain Analysis

For the multi-input and multi-output, strong-coupling nonlinear features of coordinated system for thermal power unit, it is difficult for traditional PID coordinated control scheme to meet the power grid demand which often participates in peak regulation and frequency modulation. In this paper, Inverse Nyquist array is employed to carry out frequency domain analysis of the plant model. Then Pseudo diagonalization is used to design the static decoupling compensation matrix of the system. Above on these, the linear active disturbance rejection controller of every channel in coordinated system can be designed repectively. Dynamic coupling and system unknown parts are observed by extended state observer of ADRC and is compensated to the system in time. The simulation tests show that the disturbance rejection results of the load and the main steam pressure for the coordinated control system under LADRC is better than that of PID control

Residual characteristics of HCHs and DDTs in soil and dust of some parks in Ulaanbaatar, Mongolia

The residual characteristics of HCHs and DDTs in park soils and dusts in Ulaanbaatar, Mongolia were determined by GC-ECD to evaluate their potential pollution risk. The residual concentrations of total HCHs and DDTs in the park soil samples were ranged in 11.36-53.14 ng·g-1 and 11.96-24.70 ng·g-1 while it was ranged in 32.28-92.68 ng·g-1 and 13.45-24.41 ng·g-1 in the park dust samples, respectively. We have studied the ratio of α-HCH/γ-HCH in order to determine pollution sources which may come from either technical HCHs or lindane. The study revealed that concentration of DDTs in soil has direct correlation on usage rate of the dicofol and technical DDT in the sampling area. The soil pollution assessments based on the single pollution index of HCHs and DDTs indicated that Ulaanbaatar city’s park soil and dust were not polluted with these compounds.The single pollution index of HCHs reached to 1.85 in A park dust samples，indicating the park dust environment was potentially polluted. DOI: http://doi.dx.org/10.5564/mjc.v15i0.315 Mongolian Journal of Chemistry 15 (41), 2014, p15-2

Promoting the Growth of Pinus sylvestris var. mongolica Seedlings and Improving Rhizosphere Fungal Community Structure through Interaction between Trichoderma and Ectomycorrhizal Fungi

In this study, pot experiments were conducted on the seedlings of Pinus sylvestris var. mongolica to study the influence of Trichoderma (Trichoderma harzianum E15) and Ectomycorrhizal fungi (Suillus luteus N94) on the growth of these seedlings. In particular, the effects of these fungi on the fungal community structure in the rhizosphere soil of the seedlings were investigated. Inoculation with Trichoderma harzianum E15 and Suillus luteus N94 significantly (P < 0.05) promoted the growth of the Pinus sylvestris seedlings. The non-metric multidimensional scaling (NMDS) results indicated a significant difference (P < 0.05) between the fungal community structures in the rhizosphere soil of the annual and biennial seedlings. In the rhizosphere soil of annual seedlings, the main fungi were Ascomycota, Basidiomycota, Zygomycota. Ascomycota, Basidiomycota, Mortierellomycota, and p-unclassified-k-Fungi were the main fungi in the rhizosphere soil of biennial seedlings. The dominant genus in the rhizosphere soil and a key factor promoting the growth of the annual and the biennial seedlings was Trichoderma, Suillus, respectively. Both of them were negatively correlated with the relative abundance of microbial flora in the symbiotic environment. Trichoderma had a significant promoting effect on the conversion of total phosphorus, total nitrogen, ammonium nitrogen, nitrate nitrogen, and the organic matter in the rhizosphere soil of the seedlings, while Suillus significantly promoted the conversion of organic matter and total phosphorus

Tetramethyl pyrazine exerts anti-apoptotic and antioxidant effects in a mouse model of MPTP-induced Parkinson's disease via regulation of the expressions of Bax, Bcl-2, Nrf2 and GCLC

Purpose: To investigate the effect of tetramethyl pyrazine (TMP) on MPTP)-mediated neuronal apoptosis and oxidative imbalance in mice, and the mechanism of action involved. Methods: Forty-five mice were assigned evenly to blank control, MPTP and TMP groups. The protein concentrations of Bax, Bcl-2, cytochrome C (Cyt c), Nrf2, GCLC and cleaved caspase-3; and levels of glutathione (GSH) and thiobarbituric acid reactive products (TBARS) were evaluated and compared amongst the groups. Results: Cyt c, Bax, and cleaved caspase-3 protein levels in TMP group were significantly lower than those in MPTP group, while Bcl-2 protein expression was higher in TMP group than in MPTP mice (p &lt; 0.05). Furthermore, TBARS was lower in TMP group than in MPTP group, while GSH level increased, relative to MPTP mice. The levels of Nrf2 and GCLC were significantly higher in TMP group than in MPTP group (p &lt; 0.05). Conclusion: Tetramethyl pyrazine exerts anti-apoptotic and antioxidant effects on MPTP-mediated Parkinsonism via regulation of the expressions of Bax, Bcl-2, Nrf2 and glutamate-cysteine ligase catalytic subunit. Thus, TMP has potential for use in the treatment Parkinson’s disease