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METHOD FOR TEST-IDENTIFICATION OF MULTI-COMPONENT GASEOUS MIXTURES OF BENZENE, TOLUENE, PHENOL, FORMALDEHYDE, ACETONE AND AMMONIA

机译:鉴定苯,甲苯,苯酚,甲醛,丙酮和氨的多组分气态混合物的方法

摘要

FIELD: chemistry.;SUBSTANCE: method for test-identification of multi-component gaseous mixtures of benzene, toluene, phenol, formaldehyde, acetone and ammonia involves forming an array of piezo sensors with different selectivity towards the analysed components. The method also involves preparing and collecting samples of equilibrium gaseous phases of sorbates and then putting them into a detection cell. The method also involves picking up and processing sorption analytical signals, calibrating sensors and constructing 'visual fingerprints' of standard and analysed mixtures. To identify benzene, toluene, phenol, formaldehyde, acetone and ammonia, an array of six different sensors is formed. To this end, electrodes of piezo crystal resonators from sorbent solutions are coated with films of Apiezon-N, a mixture of Triton X-100 with an extract of higher mycelial fungus Pleurotus Ostreatus, polyethylene glycol adipate, polyethylene glycol sebacate, polyvinyl pyrrolidone and dinonylphthalate with mass of 15-25 mcg. After injecting samples into the detection cell, the sensors are polled in the following order: the sensor with the Apiezon-N film is polled after 5 and 10 s, sensors based on the mixture of Triton X-100 with an extract of higher mycelial fungus Pleurotus Ostreatus after 20, 25, 30 s, polyethylene glycol adipate after 55 s, polyethylene glycol sebacate after 60 s, polyvinyl pyrrolidone after 70, 75 s and dinonylphthalate after 80, 85, 90 s. To predict 'visual fingerprints' of standard mixtures, a unidirectional three-layer neural network is used, which is trained based on sorption results on each sensor and physical-chemical properties of components of the mixture: molar mass, molar refraction coefficients, permittivity, density of sorbates, boiling point, pressure of saturated analyte vapour, presence and number of oxygen and nitrogen atoms and CH3 groups or other substitutes in the molecule. During analysis of real gas systems containing benzene, toluene, phenol, formaldehyde, acetone and ammonia, the obtained 'visual fingerprints' are compared with those in the 'visual fingerprint' data base of standard mixtures. The degree of similarity and qualitative composition of the analysed mixture are determined from the shape of the fingerprints, and the area of the diagram is a quantitative criterion.;EFFECT: method for test-identification of multi-component gaseous mixtures of benzene, toluene, phenol, formaldehyde, acetone and ammonia, which enables to identify multi-component mixtures of benzene, toluene, phenol, formaldehyde, acetone and ammonia in different combinations, simple procedures for obtaining standard visual fingerprints of mixtures and short duration of analysis.;3 tbl, 3 dwg
机译:领域:化学;物质:苯,甲苯,苯酚,甲醛,丙酮和氨的多组分气体混合物的测试鉴定方法涉及形成一系列对所分析组分具有不同选择性的压电传感器。该方法还涉及制备和收集平衡的山梨酸盐气相样品,然后将其放入检测池中。该方法还包括拾取和处理吸附分析信号,校准传感器以及构建标准和分析混合物的“可视指纹”。为了识别苯,甲苯,苯酚,甲醛,丙酮和氨,形成了六个不同传感器的阵列。为此,用吸附剂溶液将压电谐振器的电极涂上Apiezon-N膜,即Triton X-100与高级菌丝菇侧耳提取物,聚乙二醇己二酸酯,聚乙二醇癸二酸酯,聚乙烯吡咯烷酮和邻苯二甲酸二壬酯的混合物。质量为15-25 mcg。将样品注入检测池后,按以下顺序轮询传感器:带有Apiezon-N膜的传感器在5和10 s后被轮询,基于Triton X-100与高级菌丝提取物的混合物的传感器平菇20、25、30 s后,己二酸乙二醇酯55 s,聚癸二酸酯60 s,聚乙烯吡咯烷酮70、75 s,邻苯二甲酸二壬酯80、85、90 s。为了预测标准混合物的“视觉指纹”,使用了一个单向三层神经网络,该网络基于每个传感器上的吸附结果和混合物成分的物理化学性质进行训练:摩尔质量,摩尔折射系数,介电常数,吸附物的密度,沸点,饱和分析物蒸气的压力,分子中氧原子和氮原子以及CH 3 或其他取代基的存在和数量。在分析包含苯,甲苯,苯酚,甲醛,丙酮和氨的实际气体系统时,将获得的“视觉指纹”与标准混合物的“视觉指纹”数据库中的图像进行比较。根据指纹图谱的形状确定被分析混合物的相似程度和定性组成,图的面积为定量标准。效果:苯,甲苯,苯酚,甲醛,丙酮和氨,可以鉴定不同组合的苯,甲苯,苯酚,甲醛,丙酮和氨的多组分混合物,简单的程序即可获得混合物的标准目视指纹图,并且分析时间短; 3 tbl 3 dwg

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