JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY
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2018
·Vol. 33
·期 11
·1910-1916
·
IF 3.608
Airui Zhang,Hai Wang,Pengfei Zha,Meiling Wang,Haifeng Wang,Bingqi Fan,Danhua Ren,Yanxiang Han,Sitian Gao
An analytical method of microwave induced combustion (MIC) combined with ICP-OES and TXRF is proposed to determine elemental impurities in graphene. Optimized MIC conditions (e.g. sample mass up to 30 mg, microwave irradiation 900 W for 10 min, and oxygen pressure 2 MPa) can achieve the rapid and complete digestion of graphene. Analytical results show that this method can accurately determine elemental impurities such as S, Fe, Cr, Mn and Ni in graphene, and that ICP-OES and TXRF data are comparable. The validity of this method is also verified using three different CRMs for cellulose nanocrystal powder and single-wall carbon nanotubes. The limits of detection (LODs) using MIC combined with ICP-OES are 5.4, 10.6, 7.3, 0.7 and 2.7 μg kg−1 for Fe, S, Cr, Mn and Ni, respectively. The LODs using MIC coupled with TXRF are 30.2, 215, 21.3, 9.5 and 15.8 μg kg−1 for Fe, S, Cr, Mn and Ni, respectively. The experimental results are also compared with those from three other pretreatment methods including dry ashing coupled with acid digestion (DA-AD), microwave-assisted digestion (MWAD) and DA-MWAD, which shows that MIC is superior to the other procedures due to the incomplete digestion and/or escape of volatile S of the latter. The MIC digestion combined with ICP-OES or TXRF could be one of the most promising procedures for the accurate determination of some elemental impurities in carbon nanomaterials with stable structures like graphene.
研究领域:
分析化学
·
材料科学
✓ 已验证
DOI
高影响因子
TALANTA
·
2024
·
IF 5.6
Yongsheng Zhang,Jian Yuan,Rui Gao,Yang Zhao,Zefu Ye,Zhujun Zhu,Peihua Zhang,Lei Zhang,Wangbao Yin,Suotang Jia
Ash content, as a crucial indicator of coal quality, its rapid and accurate determination is pivotal to improve the energy utilization of coal and reduce environmental pollution. Traditional spectroscopic methods face significant challenges in acquiring accurate information from coal samples due to the notorious matrix effects arising from their complex composition, vast molecular structure, and diverse coal types. In this study, the feasibility of total reflection X-ray fluorescence (TXRF) combined with partial least squares (PLS) for the determination of coal ash was firstly investigated based on the TXRF being unaffected by matrix effects. Firstly, coal samples were prepared as suspensions, and the effects of sample particle size and different dispersants on the results of TXRF analyses were evaluated. The accuracy and applicability of the chosen sample preparation strategies were further validated using inductively coupled plasma mass spectrometry (ICP-MS) and two certified reference materials (CRMs). Subsequently, based on the analysis of 19 coal samples, the impact of three different predictive variables on the performance of the PLS model was investigated: (a) TXRF full spectrum normalized by the net intensity of the internal standard; (b) net intensity of characteristic peaks for 12 elements (Al, Si, K, Ca, Ti, Fe, Cr, Mn, Cu, Ni, and Sr) normalized by the net intensity of the internal standard; (c) concentrations of the aforementioned 12 elements. The results demonstrate that the PLS model constructed usingthe TXRF full spectrum normalized by the net intensity of the internal standard exhibits the best predictive capabilities, with the determination coefficient of calibration set (R 2 ) and mean square error (MSE) of the prediction set reaching 0.9736 and 0.99 %, respectively. Moreover, the measurement accuracy of this model was six times greater than that obtained with traditional X-ray fluorescence (XRF). Presented analytical results display the possibilities of combining TXRF with PLS for coal quality evaluation.
研究领域:
分析化学
·
环境科学
·
能源资源
✓ 已验证
产品关联
DOI
PubMed
高影响因子
ANALYTICAL LETTERS
·
2023
·
IF 2
Xinlei Zhang,Wenbao Jia,Xinru Tang,Qing Shan,Qiyan Chen,Can Cheng,Jinfa Shao,Yongsheng Ling,Daqian Hei
Teas of the same type in a small growing area are generally similar, and identification of their detailed geographic origin is challenging and interesting. In this study, a convenient method for distinguishing Pu-erh teas from nearby locations was developed by combining two spectroscopic techniques with chemometric methods. The distinction was based on the difference in the mineral elements and organic metabolites from tea infusions. First, Pu-erh tea was infused with water at 90 °C for 30 min. Total reflection X-ray fluorescence and ultraviolet-visible (UV-Vis) spectroscopies were used to determine the elements (P, S, K, Ca, Mn, and Ni) and organic metabolites (caffeine and polyphenols), respectively. Chemometric methods were applied to classify the origin based on the component. The proposed method was used to test samples collected from 10 mutually adjacent high-altitude villages in Mengku, Lincang, Yunnan, China. The developed user-friendly method was successfully used for the rapid evaluation of the composition, enabling the identification of the geographic origins of Pu-erh tea. Mn, caffeine, and polyphenols were found to be the key origin markers. Compared to principal component analysis, linear discriminant analysis models exhibited high discrimination performance with 100% predictive ability to distinguish the geographic origins of Pu-erh teas over a small production area. This rapid and simple method may be used to solve classification problems in tea quality control and management.
研究领域:
食品科学
·
分析化学
✓ 已验证
产品关联
DOI
高影响因子
危险品化学品经营许可证（带存储）