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The electrified cleaning agent requires a moderate volatilization rate, low ozone-depleting substances value, non-flammable, non-explosive and other characteristics. This study performed a whole life cycle assessment on a hydrocarbon-based electrified cleaning agent. The life cycle model is cradle-to-grave, and the background data sets include power grid, transportation, high-density polyethylene, chemicals, etc. The analysis shows that the global warming potential (GWP) of the life cycle of 1 kg of electrified cleaning agent is 2.08 kg CO2 eq, acidification potential (AP) is 9.49E-03 kg SO2 eq, eutrophication potential (EP) is 1.18E-03 kg PO43-eq, respirable inorganic matter (RI) is 2.13E- 03 kg PM2.5 eq, ozone depletion potential (ODP) is 4.91E-05 kg CFC-11 eq, photochemical ozone formation potential (POFP) is 2.89E-02 kg NMVOC eq, ionizing radiation-human health potential (IRP) is 3.16E-02 kg U235 eq, ecotoxicity (ET) is 2.69E-01 CTUe, human toxicity-carcinogenic (HT-cancer) is 4.32E-08 CTUh, and human toxicity-non-carcinogenic (HT-non cancer) is 2.31E-07 CTUh. The uncertainty of the results is between 3.46-9.95%. The four processes of tetrachloroethylene production, D40 solvent oil production, tetrachloroethylene environmental discharge during product use, and electricity usage during product disposal have substantial effects on each LCA indicator, so they are the focus of process improvement. Changes in power consumption during production and transportation distance of raw materials have little effect on total carbon emissions. Compared with the production process of single-solvent electrified cleaning agent tetrachloroethylene and n-bromopropane, the production of the electrified cleaning agent developed in this study has its own advantages in terms of carbon footprint and other environmental impact indicators. Carbon emissions mainly come from the power consumption of each process, natural gas production and combustion, and other energy materials for heating. It is recommended to use renewable raw materials instead of crude oil to obtain carbon credits based on geographical advantages, and try to use production processes with lower carbon emissions, while the exhaust gas from the traditional production process is strictly absorbed and purified before being discharged.

Microalgae are a renewable source of dietary supplements, bioactive compounds, and potential energy. Once harvested, the microalgal medium is dewatered to form a slurry for downstream processing. This article outlines a process design for pumping the microalgae slurry. The pump requirements for delivering the Chlorella slurry with 5, 10 or 20 wt% solids at one tonne per hour (1,000 kg/h) and 10 bar were calculated. The 5 wt% microalgae slurry is a Newtonian fluid with a viscosity of 1.95 mPaA—s. The 10 wt% and 20 wt% microalgae slurries are non-Newtonian fluids, whose viscosity depends on the shear rate (g). The viscosity of 10 wt% and 20 wt% microalgae slurries is 1.504 (g = 50 s -1 )/1.155 (g = 100 s -1 ) and 1.844 (g = 50 s -1 )/1.219 (g = 100 s -1 ) mPaA—s, respectively. The pump power requirements are mainly governed by the delivery pressure. The effect of the pipe length and the number of elbows is negligible. The effective power of the pump is calculated as 0.267-0.275 kW. To fulfill this duty, a ZGB type single-stage single-suction centrifugal slurry pump can be selected, which would provide enough shear rate to reduce the viscosity of the microalgae slurry and give required shaft power. Citation: Li, J., Qu, Y., Gong, Y., Yang, C., Yang, B., Liu, P., Zhang, B., and Ding, Y. (2020). Process Design of Microalgae Slurry Pump. Trends in Renewable Energy, 6(3), 234-244. DOI: 10.17737/tre.2020.6.3.00120

Presently, many regeneration processes of waste lubricating oil, such as catalytic hydrogenation, are available. However, some of these processes are highly costly and not suitable for Chinese economic conditions, and some may produce contaminated impurities such as acid slag, which cannot meet environmental protection requirements. This study aims to develop a green process for the regeneration of waste lubricating oil into a base oil, which should meet the requirements of green chemistry, have the characteristics of simple operation, low cost, less pollution and high recovery rate, and turn wastes into renewable resources. The new process developed via this research has three stages. First, mechanical and large particle impurities in the waste lubricating oil were removed by pretreatment. Second, most of the colloid and asphaltene were removed by thermal extraction and sedimentation. Finally, the activated bleaching earth was used to further purify the waste lubricating oil. The performance evaluation of the finally obtained lubricating base oil conformed to the standard of the HVI-100 lubricating oil. The total recovery rate of the process was about 63.5%. Citation: Wu, J., Li, B., Wang, W., Yang, S., Liu, P., Yang, C., and Ding, Y. (2019). Green Refining of Waste Lubricating Oil: A China Perspective. Trends in Renewable Energy, 5, 165-180. DOI: 10.17737/tre.2019.5.2.0084

Short Retraction Notice This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. Please see the article page for more details. The full retraction notice in PDF is preceding the original paper which is marked "RETRACTED".

Regardless of online or offline learning, there are operational difficulties in “facing all students”, and it is very difficult to pay attention to the “individual differences” between students. As we all know, students are developing people. During the teaching process, students' mentality, knowledge, and abilities will change, which may shouldn't be taken into account by static grouping. In this study, neural network model was used to construct the mapping relationship between students' characteristics and heterogeneous grouping, and the trained model was used to predict the grouping position at the next moment. This dynamic grouping algorithm can ensure that every student is in a heterogeneous group for a long time. Finally, we propose a heterogeneous dynamic grouping teaching pattern.

With the development of the digital age, “digital learning and innovation” is becoming more and more important in the core literacy of information technology discipline. Through the elaboration of relevant concepts, this paper explores the connotation and concrete performance of “digital learning and innovation” literacy of senior high school students, and then obtains its three manifestations: the collection and management of digital learning resources, the adaptation of digital environment, the application and innovation of digital learning resources. On this basis, a questionnaire survey was designed to understand the status of “digital learning and innovation” literacy of high school students in S Middle School of Anhui Province, and the data results were analysed. It was found that senior high school students generally have this literacy, but some students still have some problems and need teachers’ timely guidance. Therefore, this study further proposes strategies for achieving high school students’ “digital learning and innovation” literacy to assist teachers in reminding students of “digital learning and innovation literacy” in teaching.

Mental models have been deeply concerned by researchers and practitioners since it plays a crucial role in problem-solving. In this study, we proposed mental models for random sampling word problems. On basis of the proposed mental models, we further performed a mental simulation with a rule-based mental reasoning method and a template-based approach to generate human-style explanations. And then we established an experiment on a prototype intelligent tutoring system. Experimental results showed that: the proposed mental models were available for most random sampling word problems; and a solution with human-style explanations to the problem encoded in mental models was produced effectively by means of mental reasoning. Based on these results, we concluded that our mental models can be used to encode essential information for solving random sampling word problems effectively, and it is profitable to take mental models into account when developing intelligent tutoring systems.

Artificial neural networks (ANN) based on learning the features of the entire measured gamma energy spectrum has been used for radioisotope identification and proved promising especially for gamma-ray spectroscopy with low energy resolution. The implementation of ANN method, however, requires tedious experimental measurement process in generation of training data for various radioisotopes. In this work, we propose an ANN-based radioisotope identification method with simulated training data. Gamma energy spectra of 27 different radioisotopes were generated with Monte Carlo simulation. A detector energy response model was proposed to match the energy spectra generated from simulation and measured from experiment, thus “pseudo” measured energy spectra of various radioisotopes transformed from simulation can be used for ANN training, which eliminates the tedious experimental measurement process for training data generation. To reduce the complexity of the training process, the principal component analysis (PCA) method was used for dimension reduction of the input energy spectra in ANN and the channel number of the energy spectra was reduced from 2000 to 50. The trained ANN was further used to identify experimentally measured gamma energy spectra of various radioisotopes including 60Co., 137CS., 18F, 131I, 226Ra and 232Th at 103, 104 and 105 count levels. In single isotope identification test, with increased count level, higher correct identification rate is achieved and at 105 count level, all the isotopes are correctly identified for all the samples. In mixed isotope identification test, at 105 count level, all the radioisotope combinations can be identified with a correct identification rate larger than 98%, which demonstrates the feasibility and accuracy of the ANN method. To conclude, the proposed ANN method with simulated training data features good radioisotope identification capability with greatly simplified training data generation process and is feasible for gamma spectroscopy with relatively poor energy resolution.

Laser technology and laser system has more and more important implication in spacecraft engineering. But different from ground environments, space laser system will encounter space environments include vacuum, extreme temperature and thermal cycling, vibration, space radiation environments such as electron, proton, heavy ions, ultraviolet, contamination, and so on. These space environments may have damage or threaten to the space laser system, especially to their optical devices. In this paper, space environments and effects are introduced firstly, and then the influence of space environments such as vacuum, temperature, energetic particles, contamination and vibration on space laser system are analyzed. At last, some advices are proposed to improve the reliability of space laser system are given.

Mining personality traits online plays an important role in obtaining user personality characteristics, which can indirectly affect online behavior, especially in online learning context. However, traditional researches on personality traits are mainly based on self-assessment, with the disadvantages of being subjective, not scalable and requiring lots of workload. This paper proposed an online personality traits mining approach on Sina microblog social platform by using Gaussian Mixture Model algorithm for data mining and cluster analysis. Through analysis and comparison of online user text features and behavioral characteristics, a 14-cluster personality traits model was constructed and unified in the Big Five-Factor Model by quantifying the correlation between personality traits and characteristics. With the advantages of accuracy, objectivity and strong scalability, the approach proposed in this paper provides new ideas for online personality traits mining and can be used in multiple application scenarios.

The process technologies for conversion of bio-feedstocks such as vegetable oils, animal fats, and algal oil into renewable diesel have been developed and commercialized during the last decade. The global annual production capacity of renewable diesel is approaching to 5.5 million tons per year. The refining process generally includes pretreatment of the renewable feedstock to remove impurities, hydroprocessing and isomerization to produce hydrocarbons, and distillation to produce a fuel suitable for use as diesel or jet fuel. This article reviews recent development in the commercial production of renewable diesel, pretreatment technologies, chemistry of deoxygenation and cracking of triglycerides, the effect of reaction parameters on the relative activities of different reaction pathways, catalyst development, and the technical details of commercial processes for refining bio-feedstocks.

Increasing demand for high-quality transportation fuels and stringent environmental standards have resulted in the significantly increased quantity of spent hydroprocessing catalysts, which require the sustainable management. To minimize the generation of hazardous wastes, the spent hydroprocessing catalysts can be regenerated via oxidative regeneration or reactivated via the rejuvenation process. If the catalytic activity cannot be restored, it can be utilized as a source of other useful materials, and/or metals in the spent catalyst are recovered. Finally, the stabilized residues shall be disposed by using an environmentally sound method. Citation:  Yang, C., Wu, J., Wang, W., Li, B., Zhang, B., and Ding, Y. (2018). Sustainable Management of Spent Hydroprocessing Catalyst. Trends in Renewable Energy, 4(1), 90-95. DOI:10.17737/tre.2018.4.1.0061

The energy requirements for converting one tonne (1,000 kg) of Chlorella slurry of 20 wt% solids via fast pyrolysis, microwave-assisted pyrolysis (MAP), and hydrothermal liquefaction (HTL) were compared. Drying microalgae prior to pyrolysis by using a spray drying process with a 50% energy efficiency required an energy input of 4,107 MJ, which is higher than the energy content (4,000 MJ) of raw microalgae. The energy inputs to conduct fast pyrolysis, MAP, and HTL reactions were 504 MJ (50% efficient), 1,057 MJ (~25% efficient), and 2,776 MJ (50% efficient), respectively. The overall energy requirement of fast pyrolysis is theoretically about 1.6 times more than that of HTL. The energy recovery ratios for fast pyrolysis, MAP, and HTL of microalgae were 78.7%, 57.2%, and 89.8%, respectively. From the energy balance point of view, hydrothermal liquefaction is superior, and it achieved a higher energy recovery with a less energy cost. To improve the pyrolysis process, developing drying devices powered by renewable energies, optimizing the pyrolysis process (specifically microwave-assisted), and improving the energy efficiency of equipment are options. Citation: Zhang, B., Wu, J., Deng, Z., Yang, C., Cui, C., and Ding, Y. (2017). A Comparison of Energy Consumption in Hydrothermal Liquefaction and Pyrolysis of Microalgae. Trends in Renewable Energy , 3(1), 76-85. DOI: 10.17737/tre.2017.3.1.0013

Recently, algae have been considered as the third-generation biofuel feedstock, which can be converted to the precursor chemicals of drop-in fuels via either the algal lipid upgrading (ALU) pathway or the hydrothermal liquefaction (HTL) pathway. These precursors could be further processed and upgraded to fuels. This article reviews the standards and protocols that are suitable for characterization of drop-in algal biofuels. Applicable ASTM standards and European standards (EN) were summarized. The protocols that have been used by researches and the National Institute of Standards and Technology were also introduced. Citation: Yang, C., Zhang, B., Cui, C., Wu, J., Ding, Y., and Wu, Y. (2016). Standards and Protocols for Characterization of Algae-Based Biofuels. Trends in Renewable Energy, 2(2), 56-60. DOI: 10.17737/tre.2016.2.2.0022

The proposed neutron spectrometer makes use of BLP scintillator to acquire spectrum from those coincidence neutron events who lose most energy through elastic collision(s) and end with a B(n, α)Li reaction by coincidence detection. This technique facilitates a compact, simple, and performance acceptable neutron spectrometer, potential to build portable ones. With a BLP cube equivalent to 3.25cm thick, it achieves an energy range up to 10MeV, with energy resolution 8% to fission sources. The thickness of the detector makes high impact on coincidence detection efficiency, but does not much influence the spectrum resolution.

In this paper, space environments and effects are briefly introduced firstly, and then the demand of a general light integrated exploration on the space environment and effects are analyzed. Thirdly, on the basis of the analysis on foreign integrated detection device for the space environment and effects, the scheme of general lightweight integrated detection for space environment and effect in China was presented. At last, some key technologies, such as overall design, system integration, data acquisition and analysis, ground calibration and verification, spatial environment adaptability evaluation and so on, are put forward.

In the deep space exploration activities, the spacecraft would travel through the interplanetary space and arrive at other planets. The vehicles would be exposed to the harmful space environments during traveling or while orbiting the planet. The radiation environment is one of the most important environmental factors that would affect the spacecraft performance. The radiation environment in the interplanetary space, as well as on Jupiter, Saturn and Mars is described in this paper. Radiation in the interplanetary space consists of galactic cosmic rays and solar protons. Because Jupiter has the strongest magnetic field in the Solar system, the particle energy in its radiation belt is ten times that of the Earth’s radiation belt and its flux is a few orders of magnitude larger than at the Earth. In this harmful radiation environment, many of the materials used in the vehicle design would suffer significant properties degradation or failure. Also the effects of these severe radiation environments on vehicle materials are analyzed in this paper.

Spacecraft in orbit will encounter space radiation environments such as electron, proton, heavy ions, gamma ray, etc; and results in the space radiation effects such as single event effects, total ionizing dose effects, displacement damage effects, surface charging and discharging or electrostatic discharging, internal charging effects. So protection from space radiation should be given to the spacecraft. The protection principle and validity from space environments on spacecraft is introduced firstly, and then mass shielding material, ESD protection material, and radiation hardening functional material, were discussed. At last, some development directions on protection material from space radiation environments are proposed.

This paper presents a comparison study of single and combined space environmental effects by electrons, protons and near ultraviolet (NUV) radiation on thermal control coatings. The space environment includes many hazardous factors. Because of synergistic effects among different environmental factors and the expensive nature of the open space experiments, ground‐based combined environmental test methods are necessary to simulate orbital environmental effects. In many cases, the combined environmental effect from two or more factors is not equal to the sum of single environmental effects. By studying the effects from single environmental factors, a better knowledge of their influence on the degradation of materials could be acquired. Space environmental degradation of thermal control coatings of S781 white paint, SR107‐ZK white paint, silvered FEP, and OSR used on the outer satellite surfaces was simulated by exposing them to combined irradiation with electrons, protons and NUV. In addition, irradiation with single factors with the same parameters was performed for comparison studies. Low energy proton irradiation has been found to affect the thermal control coatings the most. The effects from combined irradiation were found to be lower than from the sum of single environmental factors.