Oxygen vacancy-induced short-range ordering as a sole mechanism for enhanced magnetism of spinel ZnFe2O4 prepared via a one-step treatment

Despite being difficult to identify, extremely dilute oxygen vacancies have been widely reported to play an important role in enhancing magnetism in ZnFe₂O₄. The mechanisms underlying this enhanced magnetism have not been well understood for a long time and remain controversial because the formation of oxygen vacancy-rich ZnFe₂O₄ can be accompanied by changes in the chemical/physical characteristics, especially the composition, particle size, surface morphology and cation distribution, which can significantly affect the magnetization. An open and important question is whether and to what extent the enhanced magnetization can be attributed only to oxygen vacancies. In this study, the relationship between the magnetization and oxygen vacancies in ZnFe₂O₄ was definitively determined by using a carefully designed “shake-and-heat” treatment to prepare vacancy-rich samples while keeping the other crystal/surface parameters constant. Compared to the nearly vacancy-free paramagnetism samples, the vacancy-rich samples exhibited a higher magnetization of approximately 5 emu/g at both 300 K and 2 K. The Fe³⁺-O^2--Fe³⁺ superexchange paths broken by oxygen vacancies then resulting in the Fe³⁺-Fe³⁺ ferromagnetism configuration. Meanwhile, the oxygen vacancy is highly diluted then the ferromagnetism configuration is confined in a single super-cell, favoring a short-range magnetic ordering at room temperature. The concentration of oxygen vacancies was calculated to be 0.68% by magnetization measurement. Our results may shed a light on how oxygen vacancies affect magnetism.     

BOPET薄膜市场现状分析及发展趋势

基础BOPET全球生产市场需求分析,尤其对中国BOPET的市场需求、市场分布、生产厂家、产能等全方面进行了分析,得出BOPET行业市场发展将向再生利用、生物可降解、绿色改性以及降低单耗等五方面可持续发展.     

Device and Method for Measuring the Efficiency of Spontaneous Imbibition and Displacement in a Low-Permeability Reservoir

Chemistry and Technology of Fuels and Oils - In this paper, the authors have developed a new device and method for measuring the efficiency of spontaneous imbibition and displacement in a low...     

Advanced Understanding of the Electron Transfer Pathway of Cytochrome P450s

Cytochrome P450s are heme-thiolate enzymes that participate in carbon source assimilation, natural compound biosynthesis and xenobiotic metabolism in all kingdoms of life. P450s can catalyze various reactions by using a wide range of organic compounds, thus exhibiting great potential in biotechnological applications. The catalytic reactions of P450s are driven by electron equivalents that are sourced from pyridine nucleotides and delivered by cognate or matching redox partners (RPs). The electron transfer (ET) route from RPs to P450s involves one or more redox center-containing domains. As the rate of ET is one of the main determinants of P450 efficacy, an in-depth understanding of the P450 ET pathway should increase our knowledge of these important enzymes and benefit their further applications. Here, the various P450 RP systems along with current understanding of their ET routes will be reviewed. Notably, state-of-the-art structural studies of the two main types of self-sufficient P450 will also be summarized.     

Solution-Synthesized Multifunctional Janus Nanotree Microswimmer

Synthetic active matters are perfect model systems for non-equilibrium thermodynamics and of great potential for novel biomedical and environmental applications. However, most applications are limited by the complicated and low-yield preparation, while a scalable synthesis for highly functional microswimmers is highly desired. In this paper, an all-solution synthesis method is developed where the gold-loaded titania-silica nanotree can be produced as a multi-functional self-propulsion microswimmer. By applying light, heat, and electric field, the Janus nanotree demonstrated multi-mode self-propulsion, including photochemical self-electrophoresis by UV and visible light radiation, thermophoresis by near-infrared light radiation, and induced-charge electrophoresis under AC electric field. Due to the scalable synthesis, the Janus nanotree is further demonstrated as a high-efficiency, low-cost, active adsorbent for water decontamination, where the toxic mercury ions can be reclaimed with enhanced efficiency.     

A data-driven digital-twin prognostics method for proton exchange membrane fuel cell remaining useful life prediction

Prognostics and health management of proton exchange membrane fuel cell (PEMFC) systems have driven increasing research attention in recent years as the durability of PEMFC stack remains as a technical barrier for its large-scale commercialization. To monitor the health state during PEMFC operation, digital twin (DT), as a smart manufacturing technique, is applied in this paper to establish an ensemble remaining useful life prediction system. A data-driven DT is constructed to integrate the physical knowledge of the system and a deep transfer learning model based on stacked denoising autoencoder is used to update the DT with online measurement. A case study with experimental PEMFC degradation data is presented where the proposed data-driven DT prognostics method has applied and reached a high prediction accuracy. Furthermore, the predicted results are proved to be less affected even with limited measurement data.     

Metaproteomic analysis of enzymatic composition in Baobaoqu fermentation starter for Wuliangye baijiu

Wuliangye is one of the most famous brands of baijiu in China. The typical flavours of Wuliangye baijiu are mainly formed by the multifarious enzymes in fermentation starter (Baobaoqu, BBQ). As the enzymes remained poorly understood, the detailed enzymatic composition of BBQ was analysed by metaproteomics for the first time. It is worth noting that the enzymes from plant, animals and micro-organisms were detected together and oxidoreductases were the dominant enzymes. Next, the analysis of function showed that the enzymes were mainly involved in carbon metabolism and the biosynthesis of amino acids. Additionally, the relationship between differential abundant enzymes and formation of typical flavour substances in premium and normal BBQ was established. Furthermore, the activities of classic enzymes in BBQ were examined to verify the reliability of metaproteomic results. This study will provide clues to further improve the manufacturing technology for Wuliangye baijiu.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

A recurrent neural network using historical data to predict time series indoor PM2.5 concentrations for residential buildings

Due to the severe outdoor PM2.5 pollution in China, many people have installed air-cleaning systems in homes. To make the systems run automatically and intelligently, we developed a recurrent neural network (RNN) that uses historical data to predict the future indoor PM2.5 concentration. The RNN architecture includes an autoencoder and a recurrent part. We used data measured in an apartment over the course of an entire year to train and test the RNN. The data include indoor/outdoor PM2.5 concentration, environmental parameters and time of day. By comparing three different input strategies, we found that a strategy employing historical PM2.5 and time of day as inputs performed best. With this strategy, the model can be applied to predict the relatively stable trend of indoor PM2.5 concentration in advance. When the input length is 2 h and the prediction horizon is 30 min, the median prediction error is 8.3 µg/m³ for the whole test set. For times with indoor PM2.5 concentrations between (20,50] µg/m³ and (50,100] µg/m³, the median prediction error is 8.3 and 9.2 µg/m³, respectively. The low prediction error between the ground-truth and predicted values shows that the RNN can predict indoor PM2.5 concentrations with satisfactory performance.     

基坑开挖对建筑物基础安全性的影响分析

基坑开挖对于建筑工程项目建设非常重要,工程建设中对基坑周围建筑物基础稳定性及安全性产生影响.为提高建筑建设质量及保障人民群众生命财产安全,对实际基坑开挖作业做了调查,进行了深入研究,尤其对建筑物基础安全性产生的影响进行了分析,以期为施工人员进行施工作业提供可靠依据.