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Abstract Predicting and optimizing radiative thermal properties have been acknowledged as an efficient way to improve thermal insulation performance of fibrous materials with high porosity. Based on experimental investigation of infrared spectral of ultrafine fibrous insulations with diameters of 520–650 nm, a method of calculating radiative thermal properties was presented by combining Rosseland equation, Mie scattering theory, Beer’s law and Subtractive Kramers–Kronig (SKK) relation. To ensure the calculation correct the uniqueness analysis was performed for Poly(vinylidene fluoride) (PVDF) fibers, which indicated the valid fiber diameter was less than 1.06 μm. The calculated thermal radiative conductivities by using the method agreed well with the measured data. The effect of fiber diameter on the thermal properties of the fibrous insulations was also investigated to minimize the radiative thermal conductivity. The results indicated that the minimized radiative thermal conductivities by regulating fiber diameters could be approximately 25% smaller than those for experimental fiber diameters. The method of predicting and minimizing radiative thermal conductivities of fibrous insulations demonstrated in this paper could be of great advantage to thermal engineering applications aiming to reducing heat loss and saving energy.

Reactive power consumption of the modern power system is a very important problem that to solve well. Due to the line commutated current source converter-based (LCC) HVDC system is a multivariable and strong coupling nonlinear system, it is difficult to model reactive power consumption of receiving end of LCC-HVDC by traditional analysis method. This paper proposes the reactive power consumption model of receiving end of LCC-HVDC on account of the radial basis function (RBF) neural network. The model with the turn-off angle for input, with reactive power loss on the inverter side of LCC-HVDC for output, using 500kV, 1000MW LCC-HVDC system PSCAD simulation test data training RBF neural network and testing network generalization ability. The results indicate that the reactive power loss model on account of the RBF neural network has much faster convergence speed and higher convergence precision.

Microwave-assisted alkali pre-treatment of wheat straw and its enzymatic hydrolysis were investigated and compared with the conventional alkali pre-treatment process. First, the effect of microwave power and pre-treatment time on the weight loss and composition of wheat straw was examined. The results show that the higher microwave power with shorter pre-treatment time and the lower microwave power with longer pre-treatment time had the same effect on the weight loss and composition at the same energy consumption. The comparison was then made between the effect of the microwave-assisted alkali pre-treatment and the conventional alkali one on the weight loss and composition of wheat straw. The wheat straw had a weight loss of 48·4% and a composition of cellulose 79·6%, lignin 5·7% and hemicellulose 7·8% after 25 min microwave-assisted alkali pre-treatment at 700 W, compared with a weight loss of 44·7% and a composition of cellulose 73·5%, lignin 7·2% and hemicellulose 11·2% after 60 min conventional alkali pre-treatment. The microwave-assisted alkali pre-treatment removed more lignin and hemicellulose from wheat straw with shorter pre-treatment time compared with the conventional alkali one. Finally, the enzymatic hydrolysis of pre-treated wheat straw (substrate concentration 50 g l−1, enzyme loading 20 mg g−1 substrate) was also investigated and the results indicate that the microwave-assisted alkali pre-treated wheat straw had higher hydrolysis rate, reducing sugar concentration and glucose content in the hydrolysate than the conventional alkali pre-treated one. Microwave-assisted alkali pre-treatment is a potential alternative of wheat straw pre-treatment for its enzymatic hydrolysis.

Interest in the highly efficient energy hub (EH) model has been growing despite the high computational requirements of planning for a multi-energy, multi-device operation. To address both the device size limitation and the multi-scenario issue, we propose a new solution methodology for solving the EH planning problem. In the method, the decision variables are device sizes. First, a dimension reduction technique is proposed to address the curse of dimensionality based on the correlation of unknown variables such as the capacities of different devices in an EH. Second, to avoid local convergence, a solution method called the variable-sized unimodal searching (VUS) approach is proposed to assure a global optimal planning scheme for the one-dimensional non-convex optimization model obtained from the preceding dimension reduction process. The case study indicates that the proposed approach has a higher computing efficiency than the Benders decomposition (BD) algorithm to deal with a scenario-based stochastic planning problem with a large number of scenarios. Thus, the effectiveness of the EH planning approach is verified.

Purpose This paper aims to study the corrosion inhibition behavior of imidazopyridine and its three derivatives on brass. Design/methodology/approach The authors performed weight loss experiments, electrochemical experiments including the polarization curve and electrochemical impedance spectrum, corrosion morphology observation using scanning electron microscope (SEM) and atomic force microscope (AFM) and surface composition analysis via X-ray photoelectron spectroscopy (XPS) to analyze the corrosion inhibition behavior of imidazopyridine and its three derivatives on brass by using quantum chemical calculation (Gaussian 09), molecular dynamics simulation (M-S) and Langmuir adsorption isotherm. Findings According to the results, imidazole-pyridine and its derivatives were found to be modest or moderately mixed corrosion inhibitors; moreover, they were spontaneously adsorbed on the metal surface in a single-layer, mixed adsorption mode. Originality/value The corrosion inhibition properties of pyrazolo-[1,2-a]pyridine and its derivatives on brass in sulfuric acid solution were analyzed through weight loss and electrochemical experiments. Moreover, SEM and AFM were simultaneously used to observe the corrosion appearance. Furthermore, XPS was used to analyze the surface. Then, Gaussian 09 and M-S were combined along with the Langmuir adsorption isotherm to investigate the corrosion inhibition mechanism of imidazole-[1,2-a]pyridine and its derivatives.

To determine the potential for improving biomass enzymolysis, a combined oxidization and liquid ammonia pretreatment (OD-LAT) was employed for bamboo. The effects of oxidant, bamboo ages, and species on the pretreatment effectiveness and subsequent enzymolysis were studied. Under the optimal OD-LAT pretreatment and enzymolysis of the B-NA bamboo Neosinocalamus affinis, the glucan and xylan conversion reached 83.85% and 78.66%, respectively, and approximately 59.7-68.5 g of fermentable sugars can be produced per 100 g of dry bamboo, which was an approximately 5-8 fold increase compared with untreated sample. The H2O2 loading of 1.0 was the optimal oxidant dosage for the OD-LAT process. The OD-LAT pretreatment was only suitable for bamboo under three-year-old, and it significantly improved the enzymolysis of B-NA and B-BM, while it was limited to B-DO and B-PP. The pretreatment effects of bamboo were not only related to composition but also to the bamboo age, species, macro-structures and micro-structures.

A template‐agent can affect defect formation as well as influence interface properties, due to the rapid growth of perovskite film from the solution. Herein, diethylammonium iodide (DAI) is used as an effective template‐agent to control the perovskite crystallization during preparation. It is found that a very small amount of DAI in chlorobenzene (CB) can slow down the perovskite growth of the CH3NH3PbI3 (MAPbI3) film with more large grain size and compacted crystal‐grains resulting in the lesser grain boundaries (GBs) in favor of carrier transport in perovskite solar cells (PSCs). Moreover, some redundant PbI2 can be digested to form DA2PbI4. One part of DA2PbI4 can form the sub‐grains with the composition of (DA2PbI4)0.2(PbI2)0.8 to passivate the GB defects, and other part can cover the surface to passivate the surface defects in large MAPbI3 grains. Using an optimized DAI concentration of 0.5 mg mL−1 in CB solution, the corrsponding MAPbI3 PSC achieves an increased power conversion efficiency of 20.31% with suppressed current–voltage hysteresis. This DAI passivation strategy provides a simple approach to effectively assist the grain‐growth for improved device performance.