气相色谱-质谱法同时测定纺织品中5种己二酸酯类增塑剂

建立了气相色谱-质谱法同时测定纺织品中5种己二酸酯类增塑剂的分析方法。采用超声协助二氯甲烷提取,选择离子模式检测,外标法定量。在优化的前处理和测定条件下,5种目标化合物的平均回收率均为84.0%~102.5%,相对标准偏差在0.39%~4.33%的范围内。该方法快速、简便、灵敏、准确,适用于纺织品中己二酸酯类增塑剂含量的测定。     

气相色谱-质谱法测定纺织品中N-乙基全氟辛烷磺酰胺

提出了用气相色谱-质谱法测定纺织品中N-乙基全氟辛烷磺酰胺的方法。试样经甲醇超声提取后,在旋转蒸发仪中浓缩至5 mL,通过DB-5MS色谱柱分离,采用选择离子监测模式检测,定性离子为m/z69,108,131,169,448,定量离子为m/z108。N-乙基全氟辛烷磺酰胺的质量浓度在0.2~20.0 mg.L-1范围内与峰面积呈线性关系,检出限(3S/N)为0.69μg.L-1。用标准加入法做回收试验,测定平均回收率为97%。     

Superhydrophobic conductive textiles with antibacterial property by coating fibers with silver nanoparticles

Silver nanoparticles (Ag NPs) were produced on cotton fibers by reduction of [Ag(NH₃)₂]⁺ complex with glucose. Further modification of the fibers coated by Ag NPs with hexadecyltrimethoxysilane led to superhydrophobic cotton textiles. Scanning electron microscopy images of the textiles showed that the treated fibers were covered with uniform Ag NPs, which generate a dual-size roughness on the textiles favouring the formation of superhydrophobic surfaces, and the Ag NPs formed dense coating around the fibers rendering the intrinsic insulating cotton textiles conductive. Antibacterial test showed that the as-fabricated textiles had high antibacterial activity against the gram-negative bacteria, Escherichia coli. These multifunctional textiles might find applications in biomedical electronic devices.     

Functionalization of PET and PA6.6 woven fabrics

In the present work as received woven fabrics of polyethylene terephthalate (PET) and polyamide 6.6 (PA6.6) were exposed to a continuous dielectric barrier discharge (DBD), in air at atmospheric pressure, at selected discharge power values and conveyor speeds. The chemical modification of the fabric surface was studied by contact angle analysis, attenuated total reflection (ATR)-FTIR spectroscopy and X-ray photoelectron spectroscopy (XPS). The results confirmed that the treatment changed the fabric surface chemistry, increasing its wettability by polar liquids and its oxygen content. Contact angle results showed different behaviour of the two polymer fabrics toward ageing effects; while PET showed a contact angle increase along the subsequent days of treatment, the PA6.6 fabric maintained its hydrophilicity even 15 days after treatment. The surface morphology analysed by scanning electron microscopy (SEM), did not show any significant difference before and after treatment.     

纺织品近红外光谱定性分析的一种新方法

近红外光谱分析技术可用于对样本的快速无损检测,在人们的生产和生活中发挥着越来越重要的作用。支持向量机是建立定性分析模型的常用方法,可通过寻找最优分类超平面将两类样本分开。在小样本情况下,支持向量机方法有其独特的优势。主成分分析是常用的数据降维方法,可将数据降维之后作为支持向量机方法的输入变量,简化模型并提高模型识别的准确性。因此,基于主成分分析的支持向量机(简称PCA-SVM)适合用于建立近红外光谱定性分析模型。多模型方法是人们使用较少的建模方法,用该方法建立的模型一般具有较好的稳定性。将多模型方法与PCA-SVM方法成功结合形成了新方法。以棉锦混合、棉涤混合纺织品为例,用新方法建立了这两类纺织品样本的近红外光谱定性分析模型。建模时将光谱数据按照波长分为4组,用每组光谱数据建立一个子模型,将子模型的输出值进行加权平均便得到最终的预测结果。这样可以更充分地使用光谱数据中所包含的信息。为了便于对比不同的方法,仍使用上述校正集和验证集,又用PCA-SVM方法建立了这两类纺织品样本的近红外光谱定性分析模型。对预测结果做交叉验证,用新方法所建模型判别的正确率的平均值为85.49%,正确率的标准差为0.066 7, 用PCA-SVM方法所建模型判别的正确率的平均值为83.34%,正确率的标准差为0.109 6。研究结果表明用新方法所建模型的分类效果好于用PCA-SVM方法所建模型的分类效果;用新方法建立的模型的稳定性明显高于用PCA-SVM方法建立的模型的稳定性。用PCA-SVM方法所建模型的预测效果受校正集构成情况的影响较大,而用新方法所建模型的预测效果则相对稳定。对废旧纺织品进行分类回收可大量节约纺织原材料,但采用人工分拣方式效率低且成本高。采用近红外光谱分析方法对纺织品进行分类,为废旧纺织品的大规模精细分拣和分级奠定了一定的基础。该新方法有望用于某些其他类型样本的分类。     

Investigation of natural dyes and ancient textiles from korea using TOF-SIMS

The identification of the colorants used on ancient textiles provides a historical pathway to the understanding of the processes associated with one of the oldest of chemical technologies, namely textile dyeing. In this paper, time-of-flight secondary ion mass spectrometry (TOF-SIMS) was used to detect dyes on textiles avoiding the time-consuming and destructive extraction procedures necessary for the spectrophotometric and chromatographic methods previously used. The plant dyes investigated belong to a variety of chemical groups, which include curcumin, crocin, carthamin, purpurin, alizarin, brazilin, shikonin, and indigo. Reference textile samples were prepared with dye extracts of plants and were characterized by TOF-SIMS. TOF-SIMS spectra for the dyed textiles showed element ions from metallic mordants, specific fragment ions, and molecular ions from organic dyes. Remnant dyes on excavated textiles have also been identified using TOF-SIMS. The ancient textile sample showed the presence of indigo clearly, although the fiber itself had degraded badly. From the results, it was concluded that most of plant dyes can be identified with TOF-SIMS and it is a very promising technique for the archaeology field.     

Determination of aromatic amines from textiles using dispersive liquid–liquid microextraction

A dispersive liquid–liquid microextraction procedure coupled with GC‐MS is described for preconcentration and determination of banned aromatic amines from textile samples. Experimental conditions affecting the microextraction procedure were optimized. A mixture of 30 μL chlorobenzene (extraction solvent) and 800 μL ACN (disperser solvent), 5 min extraction time, and 5 mL aqueous sample volume were chosen for the best extraction efficiency by the proposed procedure. Satisfactory linearity (with correlation coefficients >0.9962) and repeatability (<9.78%) were obtained for all 20 aromatic amines; detection limits attained were much lower than the standardized liquid–liquid method. The proposed method has advantages of being quicker and easier to operate, and lower consumption of organic solvent.     

同位素稀释-超高效液相色谱-串联质谱法测定纺织品中的六溴环十二烷

建立了同时测定纺织品中α-,β-,γ-六溴环十二烷的同位素稀释-超高效液相色谱-串联质谱分析方法.不同类型的纺织品样品采用加速溶剂萃取法,以正己烷-丙酮(体积比1∶1)混合液为萃取溶剂,在10.3 MPa和80℃下,静态循环萃取3次,每次5 min,萃取液经ENVI-CarbⅡ/PSA固相萃取柱净化,收集二氯甲烷-正己烷(体积比2∶3)洗脱液,采用Waters ACQUITY UPLC BEHPhenyl色谱柱(50 mm×2.1 mm,1.7μm),以甲醇-水为流动相梯度洗脱分离后进行UPLC/MS/MS多反应监测模式下的定性及定量分析.结果表明,α-,β-,γ-六溴环十二烷测定方法的定量限为0.5μg/kg,在0.5~10μg/kg浓度范围内,低、中及高3个添加水平的平均回收率为84.2%~93.7%,日内精密度均小于10%,日间精密度均小于12%.本方法准确快速,且灵敏度高,可用于纺织品的实际检验.     

超高效液相色谱-串联质谱法测定纺织品中19种邻苯二甲酸酯

采用超高效液相色谱-串联质谱法(UPLC-MS/MS)测定纺织品中19种邻苯二甲酸酯(PAEs)类化合物。实验采用Waters C_(18)色谱柱(50×2.1 mm,1.7μm),以甲醇-0.1%甲酸溶液为流动相,流速为0.4μL/min,采用梯度模式洗脱;质谱采用正离子电离模式(ESI+),多反应监测模式(MRM)检测。19种PAEs在其线性范围内线性良好(r20.994),定量限(S/N=10)为0.1~0.5mg/kg,回收率为88.8%~112.6%,相对标准偏差(RSDs,n=6)为1.1%~10.9%。实验表明该方法检测速度快,灵敏度高,适合纺织品中增塑剂的检测。