Fabrication of paper based carbon/graphene/ZnO aerogel composite decorated by polyaniline nanostructure: Investigation of electrochemical properties

The cellulose derived carbon/graphene/ZnO aerogel composite was prepared as an electrode in order to investigate the electrochemical properties. Carbon aerogel was synthesized using paper as an available cellulose source, and the composite was obtained through a new and simple preparation method including the immersion of monolithic carbon aerogel in graphene oxide/Zn²⁺ suspension and subsequent chemical reduction and freeze drying. The morphology, functional groups and crystalline structure of the samples were studied with Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Diffraction Spectroscopy (XRD), respectively. Electrochemical performance of the prepared binder free electrodes was examined using Cyclic Voltammetry (CV), Galvanostatic Charge-Discharge (GCD) and Electrochemical Impedance Spectroscopy (EIS). The data revealed that flexible carbon/graphene/ZnO composite resulted in a low density (0.035 g cm⁻³) electrode with the capacitance of 900 mF cm⁻² at a high current density of 10 mA cm⁻², lower IR drop and high cyclic stability (capacitance retention of 96%) after 1000 cycles, at 10 mA cm⁻². These features were due to the presence of 3D porous conductive network, highly reduced graphene oxide, and the formation of ZnO nanoparticles on graphene sheets. Moreover, polyaniline (PANI) was introduced to carbon/graphene/ZnO composite electrode using electro-oxidation method at different reaction time and aniline concentration in order to achieve remarkably improved capacitance of 2500 mF cm⁻² (at 10 mA cm⁻²) and low charge transfer resistance. Also, after the supercapacitor device assembly, the capacitance was retained. Based on the results, the synthesized composite is a promising material for new generation of lightweight freestanding electrodes with the high electrochemical performance.     

Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

Impacts of slip and mass transpiration on Newtonian liquid flow over a porous stretching sheet

This article focuses on analytic solutions for Newtonian fluid flow with slip and mass transpiration on a porous stretching sheet using the differential transform method and Pade approximants of an exceptionally nonlinear differential equation. The impacts of different parameters including mass transpiration (suction/injection), Navier's slip, and Darcy number parameters on the velocity of the liquid and tangential stress are discussed. A comprehensive comparison of our results with the previous one in the literature is made, and the results showed good agreement. An investigation is conducted of a combination of magnetic liquids that are conceivably pertinent for wound medicines, skin repair, and astute coatings for natural gadgets. It is found that there is a decrease in the velocity profiles and the boundary layer thickness for the case of suction.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

A new signal processing-based islanding detection method using pyramidal algorithm with undecimated wavelet transform for distributed generators of hydrogen energy

Machine learning-based fault detection methods are frequently combined with wavelet transform (WT) to detect an unintentional islanding condition. In contrast to this condition, these methods have long detection and computation time. Thus, selecting a useful signal processing-based approach is required for reliable islanding detection, especially in real-time applications. This paper presents a new modified signal processing-based islanding detection method (IDM) for real-time applications of hydrogen energy-based distributed generators. In the study, a new IDM using a modified pyramidal algorithm approach with an undecimated wavelet transform (UWT) is presented. The proposed method is performed with different grid conditions with the presence of electric noise in real-time. Experimental results show that oscillations in the acquired signal can be reduced by the UWT, and noise sensitivity is lower than other WT-based methods. The non-detection zone is zero and the maximum detection and computational time is also 75 ms at a close power match.     

Simply constructed highly dispersed cobalt nanoparticles in diverse N-doped graphitic carbon with remarkable performances for water electrolysis

Metal/carbon composite materials are highly promising electrocatalysts for water electrolysis. In this work, three composites of metal cobalt nanoparticles highly dispersed in N-doped carbon materials were facilely constructed by pyrolysis of different phenylenediamine based Schiff base-Co complexes (PDBs). Interestingly, the composites derived from PDBs based on different phenylenediamine exhibited different morphologies. The superior case is that rodlike composite catalyst was derived from o-phenylenediamine based PDBs. The obtained catalyst exhibited remarkable performances for both cathodic hydrogen evolution reaction (HER) and anodic oxygen evolution reaction (OER), as well as overall water electrolysis. Only 172 and 289 mV of overpotentials and 1.57 V of cell voltage were exhibited at 10 mA cm^?2 for HER, OER and water splitting in 1.0 M KOH, respectively. The catalyst also displayed robust stability and high Faraday efficiency, and thus are potential high-performance catalyst for commercial water electrolysis.     

Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

基于滚动摩擦作用下玉米颗粒在模拟筒仓卸料中的力链分析（网络首发、推荐阅读）

针对颗粒滚动摩擦作用对筒仓中玉米颗粒的力链空间分布进行研究，通过EDEM离散元软件建立筒仓模型与仿真玉米颗粒模型进行卸粮仿真模拟，并与筒仓卸料实验作流态对比，验证模型与仿真结果的准确性。通过对模拟仓进行切片观察和数据处理，对比分析了不同摩擦情况下力链的细观参数随时间演化规律。模拟结果表明：颗粒间摩擦系数越大，卸粮完成的最终时间越长；颗粒间滚动摩擦系数越小，颗粒由整体流转变为管状流的时间越早。对于有漏斗的筒仓来说，减小颗粒间摩擦会改变整体流和管状流之间的极限，从而增加产生管状流的面积。标准滚动摩擦系数下玉米颗粒在卸料过程中会出现起拱-塌陷效应；减小滚动摩擦，玉米颗粒卸料较稳定，未出现起拱的应力突增、以及拱塌陷的应力衰减；增大颗粒间滚动摩擦不但会增加拱效应，且出现成拱高度距离漏斗口更高。     

煤基高能量密度燃料的合成及表征

高能量密度燃料是为新型高性能飞行器提供动力保障的关键,其合成及应用研究具有重要的前瞻性和重大战略意义。煤炭是我国的主体能源和重要原料,通过煤直接转化获取的煤基油,充分保留了煤中特有的环状分子化学结构,具有良好的热安定性和较高的能量密度,被认为是高超音速飞行器的优选燃料。以煤直接液化工艺生产的煤液化石脑油馏分为起始原料,通过富集轻质芳烃、化学合成、催化加氢稳定和产物分离提纯等方法制备煤基高能量密度燃料,并对其产物进行分子结构表征和性能评价。结果表明,煤直接液化生产的石脑油馏分是一种优异的催化重整原料,经催化重整富集轻质芳烃后,其轻质芳烃质量分数高达71.05%。Diels-Alder化学合成主产物是由多个封闭环平面组成且具有空间立体构型的二环或三环烃类物质,质量分数为46.18%,因分子内存在较大的张力能,结构紧凑,其拥有更大的密度和体积热值。煤基高能量密度燃料的密度和体积热值分别为0.8990 g/cm3与38.06 MJ/L,均大大超过现行的国内石油基喷气燃料(RP-3和RP-6)、煤基大比重喷气燃料、美国和俄罗斯军用标准。与单一纯物质合成高能量密度燃料(JP-10和T-10)比较,其密度与体积热值偏小。究其原因主要是轻质芳烃的富集度仅为71.05%,需进一步提高其轻质芳烃质量分数。另外,制备的煤基高能量密度燃料种类复杂,其主产物质量分数仅46.18%,下一步可重点调控合成产物的分子构型和纯化分离。