Bio-Based,Self-Crosslinkable Eucommia ulmoides Gum/Silica Hybrids with Body Temperature Triggering Shape Memory Capability

At present, the synthesis of body temperature triggering shape memory polymers usually requires elaborate structural design, which limits their wide application. Herein, starting from bio-based Eucommia ulmoides gum (EUG), a series of EUG/silica hybrids (ESHs) are prepared through a facile one-pot process, in which EUG is epoxied and then self-crosslinked with SiO₂ by epoxy ring-open reaction. Varying the amount of H₂O₂, the shape memory transition temperature (T_trans) of ESHs is adjusted to 47.4–36.6 ℃, which is close to human body temperature (37 ℃). Among them, ESH-17 exhibited the best body temperature triggering shape memory ability (T_trans = 36.6 ℃), which can restore the permanent shape within 60 s at 37 ℃ with a shape fixity ratio of 99% and shape recovery ratio near 100%. In addition, the shape memory mechanism is discussed and shows some application scenarios of ESHs. The as-produced materials can be used as smart biomaterials such as self-tightening sutures, self-sealing root canal filling materials, and so on.     

High-Throughput Screening for Phase-Change Memory Materials

Phase change memory (PCM) is an emerging non-volatile data storage technology concerned by the semiconductor industry. To improve the performances, previous efforts have mainly focused on partially replacing or doping elements in the flagship Ge-Sb-Te (GST) alloy based on experimental “trial-and-error” methods. Here, the current largest scale PCM materials searching is reported, starting with 124 515 candidate materials, using a rational high-throughput screening strategy consisting of criteria related to PCM characteristics. In the results, there are 158 candidates screened for PCM materials, of which ≈68% are not employed. By further analyses, including cohesive energy, bond angle analyses, and Born effective charge, there are 52 materials with properties similar to the GST system, including Ge₂Bi₂Te₅, GeAs₄Te₇, GeAs₂Te₄, so on and other candidates that have not been reported, such as TlBiTe₂, TlSbTe₂, CdPb₃Se₄, etc. Compared with GST, materials with close cohesive energy include AgBiTe₂, TlSbTe₂, As₂Te₃, TlBiTe₂, etc., indicating possible low power consumption. Through further melt-quenching molecular dynamic calculation and structural/electronic analyses, Ge₂Bi₂Te₅, CdPb₃Se₄, MnBi₂Te₄, and TlBiTe₂ are found suitable for optical/electrical PCM applications, which further verifies the effectiveness of this strategy. The present study will accelerate the exploration and development of advanced PCM materials for current and future big-data applications.     

核临界事故报警系统布置分析方法研究

本文阐述了布置核临界事故报警系统的意义和原则,分析了核临界事故可能发生的机理,初步建立了一套核临界事故情景假设分析方法。研究了最小临界事故源项计算方法以及三维剂量场分布计数的方法,采用各设备最小临界事故剂量场分布最小值等高线图的方法来从众多剂量场分布图中优化选取合适的核临界事故报警系统布置点位,以确保其可以覆盖到每个具有核临界事故风险的设备,并对核临界事故报警系统探头类型选择的原则和方法进行了分析。     

VVER-1000型机组正常运行气液态流出物源项计算

田湾3、4号机组采用俄方设计制造的VVER-1000型反应堆,其正常运行气液态流出物排放源项是检验核电厂设计是否满足国家相关环境标准的重要指标,是辐射防护最优化设计的重要内容之一。以我国压水堆核电厂源项框架体系为基础,通过分析田湾核电站相关工艺系统流程,选取合适的工艺回路部件数学模型,采用电厂设计以及实际运行经验参数,分别计算了设计与现实排放源项,并与俄方计算结果进行对比,说明采用新源项框架体系下气液态放射性流出物的变化情况。     

高熵形状记忆合金的研究进展

高熵形状记忆合金是在等原子比NiTi合金的基础上,结合高熵合金的概念,逐渐发展起来的一种新型高温形状记忆合金。近年来,已开发出了综合性能优异的(TiZrHf)50(NiCoCu)50系和(TiZrHf)50(NiCuPd)50系高熵形状记忆合金,引起了广泛的关注和研究兴趣。本文从物相组成、微观组织、马氏体相变行为、形状记忆效应和超弹性等角度出发,综述了高熵形状记忆合金的研究进展,并对高熵形状记忆合金未来的研究重点进行了展望。     

4D Printing of Shape Memory Materials for Textiles: Mechanism,Mathematical Modeling,and Challenges

Shape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.     

贝叶斯网络查询语义扩展的专家发现方法

专家发现是实体检索领域的一个研究热点，针对经典专家发现模型存在索引术语独立性假设与检索性能低的缺陷，提出一种基于贝叶斯网络模型的专家发现方法。该方法模型采用四层网络结构，能够实现图形化的概率推理，同时运用词向量技术能够实现查询术语的语义扩展。实验结果显示该模型在多个评价指标上均优于经典专家发现模型，能够有效实现查询术语语义扩展，提高专家检索性能。     

基于并行多通道卷积长短时记忆网络的轴承寿命预测方法

在预测轴承剩余使用寿命时，数据间的时序特性是一个可以利用的重要隐藏信息。为了更好地提取具有时序信息的特征用于预测，提出了一种基于并行多通道卷积长短时记忆网络（PMCCNN-LSTM）的剩余使用寿命预测模型。该模型主要由两部分组成：前端为并行多通道卷积网络（PMCCNN），提取信号特征，挖掘数据的时序特性，并采用逐层训练和微调的方式提升参数的收敛性；后端为长短时记忆（LSTM）网络，基于特征进行剩余使用寿命预测，并采用加权平均的方法对预测结果进行平滑处理。在一个轴承加速寿命实验的公开数据集上使用留一法验证了该模型的准确性，实验结果表明：所提模型的平均误差与最大误差分别比传统的卷积神经网络（CNN）低23.38%和15.84%，比传统的LSTM低24.14%和19.01%，比卷积长短时记忆网络（CNN-LSTM）低30.32%和23.09%。     

活性肽-N对D-半乳糖致衰老小鼠的作用效果

为了探讨一种新型抗衰老活性因子——活性肽-N食用后的抗衰老作用,本研究通过给小鼠连续皮下注射D-半乳糖(200 mg/(kg·d),以体质量计,下同)建立衰老模型,造模的同时开始灌胃2.5、25.0、125.0μg/(kg·d)活性肽-N复乳,连续9周。分别采用旷场实验和Morris水迷宫实验检测小鼠的运动探究能力和学习记忆能力。上述行为学实验后,对小鼠血清中谷胱甘肽过氧化物酶(glutathione peroxidase,GSH-Px)活力、丙二醛(malondialdehyde,MDA)含量及脑组织中的乙酰胆碱酯酶(acetyl cholinesterase,ACh E)活力进行测定。结果表明,与衰老模型组相比,活性肽-N复乳高剂量组能显著提高衰老小鼠的运动探究能力,改善其学习记忆能力,提高血清中的GSH-Px活力28.38%(P0.05),降低MDA含量26.19%(P0.05),同时降低脑组织中的ACh E活力23.26%(P0.05)。综合结果表明该活性肽-N对D-半乳糖致衰老小鼠具有明显的抗衰老作用。     

基于RG 1.183的先进小堆选址源项模型初步研究

在《用于评估核动力反应堆设计基准事故的替代放射性源项》RG 1.183所述的假想事故场景情况下,考虑目前大多数的先进小型压水堆地上-地下布置的设计特点,对传统大型压水堆选址源项计算模型做了改进:在原安全壳内放射性物质守恒方程的基础上,考虑辅助厂房的阻滞作用,建立辅助厂房内放射性物质守恒方程。并以某先进小型反应堆核电厂为例,利用新模型计算了代表核素的释放,与现有模型进行了对比。