Blocked crystallization in capped ultrathin polymer films studied by molecular simulations

The crystallization of capped ultrathin polymer films is closely dependent on film thickness and interfacial interaction. Using dynamic Monte Carlo simulations, the crystallization behaviors of polymer films confined between two substrates were investigated. The crystallization rate of confined polymers is reduced with high interfacial interactions. Above a critical strength of interfacial interaction, polymer crystallization in the thin film is inhibited within the simulation time scales. An increase in film thickness leads to a rise in critical interfacial interaction. In thicker films, the chains have more space to change conformation to form crystal stems. In addition, there are fewer absorbed segments in confined chains for the thicker films, and thus the chains have stronger ability to adjust their conformation. Therefore an increase in film thickness can cause a reduction in the entropic barrier required for the formation of crystals and thus an increase in the critical interfacial interaction. © 2018 Society of Chemical Industry     

Macroscopic and Microscopic Structures of Cesium Lead Iodide Perovskite from Atomistic Simulations

A first‐principles‐based effective Hamiltonian is developed and employed to investigate finite‐temperature structural properties of a prototype of perovskite halides, that is CsPbI₃. Such simulations, when using first‐principles‐extracted coefficients, successfully reproduce the existence of an orthorhombic Pnma state and its iodine octahedral tilting angles around room temperature. However, they also yield a direct transformation from Pnma to cubic $Pm\overline{3}m$ upon heating, unlike measurements that reported the occurrence of an intermediate long‐range‐tilted tetragonal P4/mbm phase in‐between the orthorhombic and cubic phases. Such disagreement, which may cast some doubts about the extent to which first‐principle methods can be trusted to mimic hybrid perovskites, can be resolved by “only” changing one short‐range tilting parameter in the whole set of effective Hamiltonian coefficients. In such a case, some reasonable values of this specific parameter result in the predictions that i) the intermediate P4/mbm state originates from fluctuations over many different tilted states; and ii) the cubic $Pm\overline{3}m$ phase is highly locally distorted and develops strong transverse antiphase correlation between first‐nearest neighbor iodine octahedral tiltings, before undergoing a phase transition to P4/mbm under cooling.     

高精度薄壁钢套类零件制造工艺

薄壁钢套类零件是机械制造中常碰到的一类难加工零件,由于其不同的功能用途和典型结构特点,其制造有一定难度,在实际生产过程中,经常出现加工制造后的零件尺寸精度、形状精度、形位精度达不到使用及设计要求。本文较系统地阐述了薄壁钢套类零件的典型制造工艺方法以及在制造过程中的变形分析和应对措施。     

基于深度学习的秀丽隐杆线虫显微图像分割方法

利用计算机实现自动、准确的秀丽隐杆线虫(C.elegans)的各项形态学参数分析,至关重要的是从显微图像上分割出线虫体态,但由于显微镜下的图像噪声较多,线虫边缘像素与周围环境相似,而且线虫的体态具有鞭毛和其他附着物需要分离,多方面因素导致设计一个鲁棒性的C.elegans分割算法仍然面临着挑战。针对这些问题,提出了一种基于深度学习的线虫分割方法,通过训练掩模区域卷积神经网络(Mask R-CNN)学习线虫形态特征实现自动分割。首先,通过改进多级特征池化将高级语义特征与低级边缘特征融合,结合大幅度软最大损失(LMSL)损失算法改进损失计算;然后,改进非极大值抑制;最后,引入全连接融合分支等方法对分割结果进行进一步优化。实验结果表明,相比原始的Mask R-CNN,该方法平均精确率(AP)提升了4.3个百分点,平均交并比(mIOU)提升了4个百分点。表明所提出的深度学习分割方法能够有效提高分割准确率,在显微图像中更加精确地分割出线虫体。     

植物基人造肉的营养特性与食用安全性

植物肉的出现为动物肉类食品供应短缺和养殖业环境污染问题带来希望。食品加工技术的快速发展弥补了植物基肉制品外观和口感的不足, 但其营养价值和安全性也应引起重视。本文综述了以植物蛋白为主要原料所制肉类替代品的营养价值, 包括植物肉中碳水化合物、蛋白质、脂肪、水分、维生素和矿物质的相对含量和营养性质。分析了植物肉在生产及食用过程中可能出现的物理、化学、生物因素在内的安全问题, 并探讨目前植物肉发展所存在的局限性与挑战, 以期为我国植物蛋白肉制品的研发与推广提供理论参考。