Influence of thermal runaway in styrene–acrylonitrile bulk copolymerization revealed by computational fluid dynamics modeling

The computational fluid dynamics (CFD) and kinetic-based moment methods coupled approach is adopted to simulate the bulk copolymerization of styrene–acrylonitrile (SAN) in a stirred tank reactor. Numerical simulations are carried out to investigate the impacts of impeller speed, monomer ratio, initiator ratio, and initial reaction temperature on the copolymerization process and product properties. Particularly, the Chaos theory is selected as a criterion for evaluating the occurrence of the thermal runaway. The Flory's and Stockmayer's distributions are employed to calculate chain length distribution and copolymer composition distribution of copolymer. The simulation results highlight that the appearance of thermal runaway can be postponed by properly increasing the rotation speed, decreasing the initiator loadings, initial acrylonitrile contents and initial reactor temperature. Furthermore, significant differences exist in the product properties that predicted by the ideal and non-ideal models, which demonstrates that the temperature heterogeneity plays a crucial role in SAN copolymerization. This study could offer references for the safe operation and design of polymerization processes.     

Improved thermal stability of the near-infrared Al-modulated Zn3Ga2GeO8: Cr3+ phosphors for plant growth applications

The exploration of the high thermal stability near-infrared (NIR) phosphors is significantly crucial for the development of plant lighting. However, NIR phosphors suffer from the poor chemical and thermal stability, which severely limits their long-term operation. Here, the successful improvement of luminous intensity (149.5%) and thermal stability at 423 K of Zn₃Ga₂GeO₈ (ZGGO): Cr³⁺ phosphors is achieved for the introduction of Al³⁺ ions into the host. The release of carriers in deep traps inhibits the emission loss for the thermal disturbance. Furthermore, an NIR light emitting diodes (LEDs) lamp is explored by combining the optimized Zn₃Ga_1.1675Al_0.8GeO₈: 0.0325Cr³⁺ phosphors with a commercial 460 nm blue chip, and the emission band can match well with the absorption bands of photosynthetic pigments and the phytochrome (P_R and P_FR) of plants. The explored LEDs lamp further determines the growth and the pheromone content of the involved plants for the participation of the NIR emission originated from Cr³⁺ ions. Our work provides a promising NIR lamp as plant light with improved thermal stability for long-term operation.     

As the number falls,alternatives to the Hagberg–Perten falling number method: A review

This review examines the application, limitations, and potential alternatives to the Hagberg–Perten falling number (FN) method used in the global wheat industry for detecting the risk of poor end-product quality mainly due to starch degradation by the enzyme α-amylase. By viscometry, the FN test indirectly detects the presence of α-amylase, the primary enzyme that digests starch. Elevated α-amylase results in low FN and damages wheat product quality resulting in cakes that fall, and sticky bread and noodles. Low FN can occur from preharvest sprouting (PHS) and late maturity α-amylase (LMA). Moist or rainy conditions before harvest cause PHS on the mother plant. Continuously cool or fluctuating temperatures during the grain filling stage cause LMA. Due to the expression of additional hydrolytic enzymes, PHS has a stronger negative impact than LMA. Wheat grain with low FN/high α-amylase results in serious losses for farmers, traders, millers, and bakers worldwide. Although blending of low FN grain with sound wheat may be used as a means of moving affected grain through the marketplace, care must be taken to avoid grain lots from falling below contract-specified FN. A large amount of sound wheat can be ruined if mixed with a small amount of sprouted wheat. The FN method is widely employed to detect α-amylase after harvest. However, it has several limitations, including sampling variability, high cost, labor intensiveness, the destructive nature of the test, and an inability to differentiate between LMA and PHS. Faster, cheaper, and more accurate alternatives could improve breeding for resistance to PHS and LMA and could preserve the value of wheat grain by avoiding inadvertent mixing of high- and low-FN grain by enabling testing at more stages of the value stream including at harvest, delivery, transport, storage, and milling. Alternatives to the FN method explored here include the Rapid Visco Analyzer, enzyme assays, immunoassays, near-infrared spectroscopy, and hyperspectral imaging.     

Effect of relaxation time on the squeezed correlations of bosons for evolving sources in relativistic heavy-ion collisions

The squeezed back-to-back correlation（SBBC）of a boson–antiboson pair is sensitive to the time distribution of the particle-emitting source, and the SBBC function for an evolving source is expected to be affected by the relaxation time of the system. In this study, we investigated the effect of relaxation time on the SBBC function. We propose a method for calculating the SBBC function with relaxation-time approximation for evolving sources. SBBC functions of D⁰D^-0in relativi...     

Life cycle assessment of HFC-134a production by calcium carbide acetylene route in China

HFC-134a is a widely used environment-friendly refrigerant. At present, China is the largest producer of HFC-134a in the world. The production of HFC-134a in China mainly adopts the calcium carbide acetylene route. However, the production route has high resource and energy consumption and large waste emission, and few of the studies addressed on the environmental performance of its production process. This study quantified the environmental performance of HFC-134a production by calcium carbide route via carrying out a life cycle assessment (LCA) using the CML 2001 method. And uncertainty analysis by Monte-Carlo simulation was also carried out. The results showed that electricity had the most impact on the environment, followed by steam, hydrogen fluoride and chlorine, and the impact of direct CO₂ emissions in calcium carbide production stage on the global warming effect also could not be ignored. Therefore, the clean energy (e.g., wind, solar, biomass, and natural gas) was used to replace coal-based electricity and coal-fired steam in this study, showing considerable environmental benefits. At the same time, the use of advanced production technologies could also improve environmental benefits, and the environmental impact of the global warming category could be reduced by 4.1% via using CO₂ capture and purification technology. The Chinese database of HFC-134a production established in this study provides convenience for the relevant study of scholars. For the production of HFC-134a, this study helps to better identify the specific environmental hotspots and proposes useful ways to improve the environmental benefits.     

Neural Emotion Detection via Personal Attributes

There has been a recent line of work to automatically detect the emotions of posts in social media. In literature, studies treat posts independently and detect their emotions separately. Different from previous studies, we explore the dependence among relevant posts via authors' backgrounds, since the authors with similar backgrounds, e.g., "gender", "location", tend to express similar emotions. However, personal attributes are not easy to obtain in most social media websites. Accordingly, we propose two approaches to determine personal attributes and capture personal attributes between different posts for emotion detection: the Joint Model with Personal Attention Mechanism (JPA) model is used to detect emotion and personal attributes jointly, and capture the attributes-aware words to connect similar people; the Neural Personal Discrimination (NPD) model is employed to determine the personal attributes from posts and connect the relevant posts with similar attributes for emotion detection. Experimental results show the usefulness of personal attributes in emotion detection, and the effectiveness of the proposed JPA and NPD approaches in capturing personal attributes over the state-of-the-art statistic and neural models.     

有机元素检测仪器在石油化工行业的需求和应用现状

本文通过对国内外石油及石化产品分析检测相关标准技术的调研与收集,以及相关检测仪器特点的分析,对目前包括润滑油、汽油、柴油、煤油、石蜡、石化聚合物、原油等样品类型,共计80个样品在现有仪器上进行测试,使用标准方法对样品中碳、氢、氮、硫元素进行检测,获取样品的检测时间、含量结果、仪器条件等参数,为相关仪器检测提供数据基础.     

碳纤维原丝含油率测试影响因素研究

利用改进的索氏提取回流法测量碳纤维原丝含油率.研究了溶剂回流温度、回流时间、环境湿度对测试结果的影响,结果表明:随着回流温度的提高,2小时内回流清洗效果不断增强,当回流温度大于54℃,次数大于12次,油剂清洗效果基本保持不变.可通过提高回流温度以提高单位时间内的回流次数,优化纤维含油率测试的准确性和测试效率.环境湿度对索氏提取测纤维含油率有显著影响:控制环境湿度在50～52％RH范围内,可将纤维吸潮质量变化控制在纤维质量的0.005％,油剂相对含量的0.2％～0.6％,可将测试稳定差值降低至≤0.05％,测试方法差值<0.1％,满足油剂测试工艺要求.回流时间≥2 h,回流温度≥54℃,测试环境湿度50～52％RH,索氏提取回流法油剂测试误差<0.05％.     

Fabrication and upconversion luminescence properties of Er:SrF2 transparent ceramics compared with Er:CaF2

SrF₂ transparent ceramic is a promising upconversion material due to the low phonon energy. The effect of different sintering temperatures on Er:SrF₂ transparent ceramics was investigated. The suitable sintering temperature for Er:SrF₂ transparent ceramics was 900 °C by hot-pressed sintering in this study. High quality of Er:SrF₂ transparent ceramics with different doping concentrations were obtained. The upconversion luminescence spectra and decay behavior were compared between Er:SrF₂ and Er:CaF₂ transparent ceramics with different Er³⁺ doping concentration. The green emission of 5 at.% Er:SrF₂ ceramic was much stronger than that of 5 at.% Er:CaF₂ ceramic, while the red emission of Er:SrF₂ ceramic was almost the same as that of Er:CaF₂ ceramic. The upconversion luminescence lifetime of Er:SrF₂ transparent ceramics was longer than that of Er:CaF₂.All the results indicated Er:SrF₂ transparent ceramics was a candidate for green fluorescent upconversion materials.