Enhanced photoelectric properties of PbSnSe thin films via quick oxygen ion-implantation sensitization

Journal of Materials Science - Although chalcogenide materials continue to generate considerable interest due to great potentials for various optoelectronic devices, annealing for a long time in...     

VO2/GaAs异质结的制备及其光电特性研究

采用直流磁控溅射和后退火氧化工艺在p型GaAs单晶衬底上成功制备了n-VO_2/pGaAs异质结,研究了不同退火温度和退火时间对VO_2/GaAs异质结性能的影响,并分析其结晶取向、化学组分、膜层质量以及光电特性。结果表明,在退火时间2 h和退火温度693 K下能得到相变性能最佳的VO_2薄膜,相变前后电阻变化约2个数量级。VO_2/GaAs异质结在308 K、318 K和328 K温度下具有较好的整流特性,对应温度下的阈值跳变电压分别为6.9 V、6.6 V和6.2 V,该结果为基于VO_2相变特性的异质结光电器件的设计与应用提供了可行性。     

Comparison of yield and metabolites according to the types of hilling materials utilized during Glehnia littoralis sprout vegetable cultivation

Food Science and Biotechnology - Various hilling materials (rice hulls, pine sawdust, and perlite) were compared to produce sprout vegetables using beach silvertop (Glehnia littoralis Fr. Schm. ex...     

基于全U网络的混凝土路面裂缝检测算法

针对现有的混凝土裂缝检测算法在各种复杂环境中检测精度不够、鲁棒性不强的问题,根据深度学习理论和U-net模型,提出一种全U型网络的裂缝检测算法。首先,依照原U-net模型路线构建网络;然后,在每个池化层后都进行一次上采样,恢复其在池化层之前的特征图规格,并将其与池化之前的卷积层进行融合,将融合之后的特征图作为新的融合层与原U-net网络上采样之后的网络层进行融合;最后,为了验证算法的有效性,在测试集中进行实验。结果表明,所提算法的平均精确率可达到83.48%,召回率为85.08%,F1为84.11%,相较于原U-net分别提升了1.48%,4.68%和3.29%,在复杂环境中也能提取完整裂缝,保证了裂缝检测的鲁棒性。     

Lighting the Path: Light Delivery Strategies to Activate Photoresponsive Biomaterials In Vivo

Photoresponsive biomaterials are experiencing a transition from in vitro models to in vivo demonstrations that point toward clinical translation. Dynamic hydrogels for cell encapsulation, light-responsive carriers for controlled drug delivery, and nanomaterials containing photosensitizers for photodynamic therapy are relevant examples. Nonetheless, the step to the clinic largely depends on their combination with technologies to bring light into the body. This review highlights the challenge of photoactivation in vivo, and presents strategies for light management that can be adopted for this purpose. The authors’ focus is on technologies that are materials-driven, particularly upconversion nanoparticles that assist in “direct path” light delivery through tissue, and optical waveguides that “clear the path” between external light source and in vivo target. The authors’ intention is to assist the photoresponsive biomaterials community transition toward medical technologies by presenting light delivery concepts that can be integrated with the photoresponsive targets. The authors also aim to stimulate further innovation in materials-based light delivery platforms by highlighting needs and opportunities for in vivo photoactivation of biomaterials.     

Optical design of the Lyman alpha based beam emission spectroscopy(LAB)diagnostic on the HL-2A tokamak

In this article, we present the optical design of a novel diagnostic on the HL-2 A tokamak, i.e. the20-channel edge Lyman-alpha beam emission spectroscopy, which is a promising solution for edge density turbulence research on tokamaks, as it offers the possibility of density fluctuation measurement with a 3.3 mm spatial resolution while maintains a high temporal resolution of1 μs. The optical path, including the reflective collection optics, the high-dispersion spectrometer, and the linear detector array, is carefully optimized to obtain a good image quality and a high throughput. The maximum root mean square radius of the collection optics is 64 μm.The detected photon flux is estimated to be about 10~(11) photons/s/channel.     

Ensemble relation network with multi-level measure

Fine-grained few-shot learning is a difficult task in image classification. The reason is that the discriminative features of fine-grained images are often located in local areas of the image, while most of the existing few-shotlearning image classification methods only use top-level features and adopt a single measure. In that way, the localfeatures of the sample cannot be learned well. In response to this problem, ensemble relation network with multi-level measure (ERN-MM) is proposed in this paper. It adds the relation modules in the shallow feature space tocompare the similarity between the samples in the local features, and finally integrates the similarity scores from thefeature spaces to assign the label of the query samples. So the proposed method ERN-MM can use local details andglobal information of different grains. Experimental results on different fine-grained datasets show that the proposedmethod achieves good classification performance and also proves its rationality.     

Effect of PyC interface phase on the cyclic ablation resistance and flexural properties of two-dimensional Cf/HfC composites

Composites based on hafnium carbide and reinforced with continuous naked carbon fiber with and without PyC interface were prepared at low temperature by precursor infiltration and pyrolysis and chemical vapor deposition method. The microstructure, mechanical property, cyclic ablation and fiber bundle push-in tests of the composites were investigated. The results show that after three times ablation cycles, the bending strength of samples without PyC interface decreased by 63.6 %; the bending strength of samples with PyC interface only decreased by 37.8 %. The force displacement curve of the samples with PyC interface presented a well pseudoplastic deformation state. The mechanical behavior difference of two kinds of composites was due to crucial function of PyC interface phase including protection of fiber and weakening of fiber/matrix interface.