Ternary type BaY2ZnO5: Eu3+ deep-red phosphor for possible latent fingerprint,security ink and WLED applications

Pc-WLEDs are considered to play a spectacular role in future generation light sources in view of their outstanding energy efficiency. In this regard, Eu³⁺ activated BaY₂ZnO₅ phosphor was prepared and investigated by XRD, PL and SEM analyses. Rietveld refinement analysis was carried out to confirm the structure of the synthesized phosphor. The prepared phosphor shows an intense red emission around 627 nm under excitation by near UV light. The ⁵D₀-⁷F₂ transition intensity of the prepared phosphor is three times higher compared to the commercial (Y,Gd)BO₃:Eu³⁺ red phosphor. The CIE colour coordinates of BaY₂ZnO₅:Eu³⁺ (9mol%) phosphor corresponds to be (0.6169, 0.3742) and it has a high 97.9 % colour purity. The obtained results reveal the utility of BaY₂ZnO₅:Eu³⁺ phosphor as an efficient red component in WLEDs, anti-counterfeiting and fingerprint detection applications.     

Molecular fingerprint and machine learning to accelerate design of high-performance homochiral metal–organic frameworks

Computational screening was employed to calculate the enantioseparation capabilities of 45 functionalized homochiral metal–organic frameworks (FHMOFs), and machine learning (ML) and molecular fingerprint (MF) techniques were used to find new FHMOFs with high performance. With increasing temperature, the enantioselectivities for (R,S)-1,3-dimethyl-1,2-propadiene are improved. The “glove effect” in the chiral pockets was proposed to explain the correlations between the steric effect of functional groups and performance of FHMOFs. Moreover, the neighborhood component analysis and RDKit/MACCS MFs show the highest predictive effect on enantioselectivities among the four ML classification algorithms with nine MFs that were tested. Based on the importance of MF, 85 new FHMOFs were designed, and a newly designed FHMOF, NO₂-NHOH-FHMOF, with high similarity to the optimal MFs achieved improved chiral separation performance, with enantioselectivities of 85%. The design principles and new chiral pockets obtained by ML and MFs could facilitate the development of new materials for chiral separation.     

贵长猕猴桃皮HPLC指纹图谱及抗氧化谱效关系研究

目的:研究贵长猕猴桃皮HPLC指纹图谱与抗氧化活性的关系。方法:采用高效液相色谱法建立10批不同来源地贵长猕猴桃皮的指纹图谱,采用SPSS 13.0进行样品聚类分析和主成分分析;并通过DPPH和ABTS法测定其抗氧化活性,以EC50与共有峰峰面积数据为基础,应用皮尔逊相关分析法和逐步回归分析法研究谱效关系。结果:建立了10批贵长猕猴桃皮HPLC指纹图谱,确定了14个共有峰,相似度均>0.90。采用对照品比对方法指认了其中6个峰:2号峰没食子酸,5号峰原儿茶酸,9号峰表儿茶素,10号峰二氢槲皮素,11号峰4-香豆酸,12号峰落新妇苷,样本可聚为3类。皮尔逊相关分析与逐步回归分析结果显示:5号峰(原儿茶酸)和9号峰(表儿茶素)峰面积变化与贵长猕猴桃皮抗氧化活性呈显著正相关,对其抗氧化活性贡献度较大。结论:贵长猕猴桃皮具有较高的体外抗氧化活性,抗氧化活性的物质基础初步确定为贵长猕猴桃皮开发利用、质量评价提供依据。     

基于星座图对射频指纹识别方法的研究

针对星座图的射频(RF)指纹识别方案中,低信噪比环境下识别准确率低的问题,提出一种基于欧式距离与幅度距离的二维识别算法来进行RF指纹识别。该方案通过对星座图进行优化处理,可从优化后的星座图中提取识别性能更好的RF指纹,再通过二维识别算法来提高识别准确率。仿真结果表明:与仅用欧式距离作为判断依据的方法相比,所提出的二维识别算法的识别准确率最高可提升8%,在设备容量为50组的情况下识别准确率为77.8%,并且从优化后的星座图中所提取的RF指纹具有更好的唯一性和稳定性。     

Fingerprint optimization method for the indoor localization system

The accuracy of the indoor localization is influenced directly by the quality of the fingerprint. But the indoor localization algorithms in existence are almost conducted based on the original fingerprint which is not optimized. The k-means is introduced to optimize the fingerprint in this paper. And deleting the collected bad-points through the theory of cluster could make the fingerprint more accurate for the indoor localization algorithm. Compared with the indoor localization systems in existence, the result of experiments shows that the optimized fingerprint can increase the accurate of indoor localization with a higher probability.     

SRS: Spatial-tagged radio-mapping system combining LiDAR and mobile-phone data for indoor location-based services

One of the most challenging issues in radio received signal strength (RSS)-based localization systems is the generation and distribution of a radio map with a coordinate system linked with spatial information in a large indoor space. This study proposes a novel spatial-tagged radio-mapping system (SRS) that effectively combines the heterogeneous properties of LiDAR and mobile phones to simultaneously perform both spatial and radio mappings. The SRS consists of synchronization, localization, and map building processes, and enables real-time spatial and radio mapping. In the synchronization process, the distance range, motion data, and radio signals obtained through the LiDAR and mobile phone are collected in nodal units according to the sensing time. In the localization process, a feature variance filter is used to control the number of features generated from LiDAR and estimate the positions at which the nodes are generated in real time according to the motion data and radio signals. In map building, the estimated positions of the nodes are used to extract spatial and radio maps by using a unified location coordinate system. To ensure mobility, the SRS is manufactured in the form of a backpack supporting LiDAR and a mobile phone; the usefulness of the system is experimentally verified. The experiments are performed in a large indoor shopping mall with a complex structure. The experimental results demonstrated that a common coordinate system could be used to build spatial and radio maps with high accuracy and efficiency in real time. In addition, the field applicability of the SRS to location-based services is experimentally verified by applying the constructed radio map to well-known fingerprinting algorithms using the heterogeneous mobile phones.     

有机-无机联合矿井突水水源判别方法

溶解性有机质(Dissolved Organic Matter,DOM)在随地下水运移过程中,不同含水层水中DOM含量、类别、荧光强度等均存在较明显差异,因此结合无机水化学,开展了有机-无机联合的矿井突水水源判别方法研究,结果表明:地下水中无机组分浓度分布具有垂向分带性,利用pH、矿化度(TDS),HCO3,SO4等无机指标,可以判别浅部含水层和深部含水层水化学特征差异; DOM进入含水层后发生氧化还原反应强烈,其浓度(TOC含量和UV254)变化快、差异大,可以识别地表水与第四系水的水化学特征;第四系与白垩系含水层,以及覆岩破坏范围内的细分含水层,水中无机组分和有机组分含量非常接近,而荧光指纹技术灵敏度高,可以根据3DEEM光谱图分析DOM类型和荧光峰强度等差异,区分相邻含水层的水化学特征差异。陷落柱等地质异常体作为特殊的地质环境体,其内部水体中DOM相对丰富,其DOM含量和荧光指纹特征与奥灰水差异显著。将有机-无机联合开展不同含水层水化学特征分析,能够很好地区分不同水源,为矿井突水事故发生时快速判别水源提供科学依据。     

利用非糖物质快速鉴别单花蜂蜜

本文利用非糖物质快速鉴别四种常见的单花蜂蜜(枸杞蜂蜜、荆条蜂蜜、枣花蜂蜜和洋槐蜂蜜)。利用固相萃取除糖提取蜂蜜非糖物质,并用高效液相色谱(HPLC)结合化学计量学进行蜂蜜花源的判定。发现了四种单花蜂蜜的非糖特征标志物。芦丁、丁香酸甲酯、阿魏酸的含量在四种蜂蜜中差异最大。对羟基苯甲酸和脱落酸在枸杞蜂蜜中平均含量分别为0.59μg/g和0.42μg/g,可作为枸杞蜂蜜的花源标志物;对香豆酸和肉桂酸在荆条蜂蜜中平均含量为0.08μg/g和0.05μg/g,可作为荆条蜂蜜的潜在花源标志物;阿魏酸、异阿魏酸是枣花蜂蜜的特征标志物,平均含量分别为0.40μg/g和0.76μg/g;洋槐蜂蜜的特征标志物是芦丁和丁香酸甲酯,平均含量为0.08μg/g和0.14μg/g。利用高效液相色谱指纹图谱结合化学计量学方法(主成分分析和判别分析),四种单花蜂蜜依据其花源被成功区分。本研究对蜂蜜真实性判定有重要参考价值,为后续蜂蜜真伪鉴别奠定基础。     

A review of phosphorescent and fluorescent phosphors for fingerprint detection

Currently, the efficient detection of fingerprints is essential for the crime investigations. Revealing fingerprints is commonly achieved with fluorescent organic compounds but they are not efficient for fingerprint detection on porous or reflective surfaces. In order to solve the problem of collecting fingerprints on porous/reflective surfaces, inorganic phosphors have been employed, since they have characteristics of variable color emission, afterglow, high chemical stability and nano-size, which allow the fingerprint detection on any porous or non-porous surfaces. Due to these last properties, this review presents a summary about the use of phosphorescent and fluorescent phosphors for the detection of latent fingerprints. First, we discussed the main physical and chemical characteristics of the fingerprints which permit their detection and collection from any surface. After this, we presented the main morphological, structural and luminescent properties of the phosphorescent and fluorescent phosphors that allow their use for fingerprint detection. Later, we demonstrated with pictures of fingerprints (with and without light emission from the phosphors deposited on them) that both, phosphorescent and fluorescent phosphors can be used to visualize fingerprints with high resolution and high contrast without interference of the background surface, which is ideal for its collection and registration in the Automated Fingerprint Identification System (AFIS). We believe that this review could be useful to understand how to select an appropriate phosphorescent or fluorescent material for fingerprint detection depending on the type of surface (porous or non-porous, reflective or not reflective) where the fingerprint is deposited.