82B高速线材拉拔过程中显微组织的演变分析

借助扫描电子显微镜(SEM)观察分析研究了82B线材在拉拔过程中显微组织和芯部马氏体的演变规律。分析认为:由于索氏体属于细片状珠光体,拉拔变形时,承受滑移的铁素体相不易引起应力集中;渗碳体相为细薄片层形态,也能够发生塑性变形,经过多道次的拉拔,索氏体基体变形量较大,没有出现任何裂纹。而芯部由偏析形成的马氏体,其塑性变形能力明显低于索氏体,基本无变形,在基本拉应力和附加拉应力的共同作用下,在早期拉拔时就在芯部出现裂纹,在后期拉拔过程中,裂纹沿着拉拔方向不断扩展。为减少断丝,可采用加大吹风量、扩大连铸坯、控制钢水过热度、增加电磁搅拌等工艺,来提高索氏体含量和细化渗碳体片层及预防马氏体的形成,以提高拉拔性能。     

Liquid crystalline elastomer actuators with dynamic covalent bonding: Synthesis,alignment, reprogrammability,and self-healing

Liquid crystalline elastomers (LCEs) have demonstrated tremendous potential in applications such as soft robotics, biomedical materials, electronics, sensors, and biomimetic systems. The physical properties of LCEs are controlled by the degree of crosslinking, nature of the mesogens, and mesogen orientation in the LCE network structure. A wide range of dynamic covalent bonds (DCBs) capable of dynamic bond exchange reactions (DBERs) have been introduced into LCE structures to obtain intelligent materials in recent decades. In this review article, we discuss the molecular constitution, macrostructure, morphing mechanism, recent advances in LCEs with dynamic covalent bonds, the influence of DCBs on self-healing, reprogramming and reprocessing properties of LCE actuators, and challenges and opportunities in incorporating dynamic chemistry in the field of LCE actuators.     

High-efficiency of novel hierarchical 3D macroporous g-C3N4 material on solar-driven photocatalytic water-splitting for hydrogen evolution

The use of multi-pore nanostructured g-C₃N₄ photocatalysts is an efficient approach to separate photogenerated charge carriers and increase visible light photocatalytic performance. Recent progress has yielded nanostructured material through hard templating, which limits potential applications. Integrating the 2D building block into multidimensional porous structures remains a significant challenge in scalable production. Herein, a novel technique based on P407 bubble clusters templating and fixation by freezing is described for the first time to fabricate a 3D opened-up macroporous g-C₃N₄ nanostructures for photocatalytic H₂ evolution. Three-dimensional hierarchical nanostructures provide more contact active sites and synergistically promote the creation of heterogeneous catalytic interfaces. This feature is very useful for understanding the transfer path of photoinduced charges as well as the origins of the high charge separation efficiency in photocatalytic reactions, thus yielding a remarkable visible light-induced H₂ evolution rate of 4213.6 μmol h⁻¹ g⁻¹, which is nearly 5.6 times (716 μmol h⁻¹ g⁻¹) higher than that of lamellar bulk g-C₃N₄. This newly developed approach offers a promising alternative to synthesize broad-spectral response 3D hierarchal g-C₃N₄ nanostructures and can be extended to assemble other functional nanomaterials as building blocks into macroscopic configurations coupled with electronic modulation strategy simultaneously.     

Non Sub-Sampled Contourlet with Joint Sparse Representation Based Medical Image Fusion

Medical Image Fusion is the synthesizing technology for fusing multimodal medical information using mathematical procedures to generate better visual on the image content and high-quality image output. Medical image fusion represents an indispensible role in fixing major solutions for the complicated medical predicaments, while the recent research results have an enhanced affinity towards the preservation of medical image details, leaving color distortion and halo artifacts to remain unaddressed. This paper proposes a novel method of fusing Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) using a hybrid model of Non Sub-sampled Contourlet Transform (NSCT) and Joint Sparse Representation (JSR). This model gratifies the need for precise integration of medical images of different modalities, which is an essential requirement in the diagnosing process towards clinical activities and treating the patients accordingly. In the proposed model, the medical image is decomposed using NSCT which is an efficient shift variant decomposition transformation method. JSR is exercised to extricate the common features of the medical image for the fusion process. The performance analysis of the proposed system proves that the proposed image fusion technique for medical image fusion is more efficient, provides better results, and a high level of distinctness by integrating the advantages of complementary images. The comparative analysis proves that the proposed technique exhibits better-quality than the existing medical image fusion practices.