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Nondestructive optical testing of 3D disperse systems with micro- and nano- particles

机译:具有微米和纳米粒子的3D分散系统的无损光学测试

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Nondestructive testing and analysis of three-dimensional (3D) disperse systems (DS) with micro- and nano-particles of different nature by complex of optical compatible methods can provide further progress in on-line control of water and air. The simultaneous analysis of 3D-DS by refractometry, absorbency, fluorescence and by different types of light scattering can help to elaborate the sensing elements for specific impurity control. In our research we have investigated by complex of optical methods different 3D-DS such as: proteins, nucleoproteids, lipoproteids, liposomes, viruses, virosomes, lipid emulsions, blood substitutes, latexes, liquid crystals, biological cells with various form and size (including bacterial cells), metallic powders, clays, kimberlites, zeolites, oils, crude oils, etc., and mixtures - proteins with nucleic acids, liposomes and viruses, liquid crystals with surfactants, mixtures of clay with bacterial cells, samples of natural and water-supply waters, etc. This experience suggests that the set of optical parameters of so called second class is unique for each 3D-DS. In another words each DS can be characterized by n-dimensional vector in n-dimensional space of optical parameters. Mixtures can be considered as polycomponent and polymodal 3D-DS (such as natural water and air). Due to the fusion of various optical data it is possible to indicate by information statistical theory the inverse physical problem on the presence of impurities in mixtures (viruses, bacteria, oil, metallic particles, etc.), and in this case polymodality of particle size distribution is not an obstacle. Bank of optical data for 3D-DS is the base for analysis by information-statistical method.
机译:通过复杂的光学兼容方法对具有不同性质的微米和纳米粒子的三维(3D)分散系统(DS)进行无损测试和分析,可以为水和空气的在线控制提供进一步的进展。通过折光率,吸收率,荧光和不同类型的光散射对3D-DS进行同时分析,可以帮助完善用于特定杂质控制的传感元件。在我们的研究中,我们通过多种光学方法研究了不同的3D-DS,例如:蛋白质,核蛋白,脂蛋白,脂质体,病毒,病毒体,脂质乳剂,血液替代品,胶乳,液晶,具有各种形式和大小(包括细菌细胞),金属粉末,粘土,金伯利岩,沸石,油,原油等,以及混合物-带有核酸,脂质体和病毒的蛋白质,带有表面活性剂的液晶,粘土与细菌细胞的混合物,天然和水样品-供应水等。此经验表明,所谓的第二类光学参数集对于每个3D-DS都是唯一的。换句话说,每个DS可以通过光学参数的n维空间中的n维向量来表征。混合物可以视为多组分和多峰3D-DS(例如天然水和空气)。由于各种光学数据的融合,可以通过信息统计理论指出与混合物(病毒,细菌,油,金属颗粒等)中杂质的存在有关的逆物理问题,在这种情况下,还涉及粒度的多峰性发行不是障碍。 3D-DS的光学数据库是通过信息统计方法进行分析的基础。

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