结合中红外光谱快速硝酸盐传感的衰减全反射硅晶体。

IF 4.3 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
ACS Omega Pub Date : 2024-11-19 eCollection Date: 2024-12-03 DOI:10.1021/acsomega.4c06701
Liping Xu, Fei Ma, Jianmin Zhou, Changwen Du
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引用次数: 0

摘要

快速检测 NO3 -N 对于应对粮食安全、环境退化和气候变化的挑战至关重要。检测水中 NO3 -N 的传统方法需要预处理和化学试剂,耗时耗钱。因此,傅立叶变换红外衰减全反射(FTIR-ATR)光谱已被广泛应用于测定 NO3-N。然而,传统的 ATR 晶体,即硒化锌(ZnSe)和金刚石,由于 ZnSe 材料相对较软,而金刚石相对昂贵,因此在持续时间或成本方面存在弱点。本研究对比硒化锌-ATR 和金刚石-ATR,开发了硅基 ATR(Si-ATR)配件,并结合数学算法探讨了其在检测 NO3-N 方面的适用性和稳定性。研究发现,偏最小二乘回归(PLSR)与主成分分析(PCA)和线性回归(LR)算法相比具有良好的性能,推荐用于定量检测 NO3-N。ZnSe-ATR 的残差预测偏差(RPD)大于 1.80,判定系数(R 2)大于 0.7725,均方根误差(RMSE)小于 2.73 mg L-1。金刚石-ATR 的 RPD 大于 1.76,R 2 大于 0.7309,均方根误差小于 8.22 mg L-1。Si-ATR 的 RPD 大于 1.42,R 2 为 0.5198,RMSE 小于 11.02 mg L-1。结果表明,对于高浓度的硝酸盐,这三种 ATR 均可用于定量水中的 NO3-N。然而,对于低硝酸盐浓度(0-1 mg L-1 NO3-N)的定量,ZnSe-ATR 和 diamond-ATR 的精度相同,而 Si-ATR 的精度较低。使用解卷积算法对基于 Si-ATR 的光谱进行预处理,可以提高预测低 NO3-N 的准确度。此外,利用 Si-ATR 开发了一种 Si-ATR 附件,该附件具有成本低、耐用性长等优点,可用于水中 NO3-N 浓度的可靠定量。总的来说,硝酸盐浓度较高的样品意味着所有晶体的预测结果更可靠,综合来看,推荐 ZnSe-ATR 用于检测低硝酸盐浓度;推荐 Diamond-ATR 用于检测强酸或强碱腐蚀的样品;而对于检测相对较高的硝酸盐浓度(如天然水体中的硝酸盐浓度),Si-ATR 因其成本低和相对较长的使用寿命而更为经济。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Attenuated Total Reflectance Crystal of Silicon for Rapid Nitrate Sensing Combining Mid-Infrared Spectroscopy.

Rapid detection of NO3 --N is critical to address the challenges of food security, environmental degradation, and climate change. Conventional methods for sensing NO3 --N in water demand pretreatments and chemical reagents, which are time- and cost-consuming. Consequently, Fourier transform infrared attenuated total reflectance (FTIR-ATR) spectroscopy has been well applied for the determination of NO3 --N. However, the conventional ATR crystals, i.e., zinc selenide (ZnSe) and diamond, showed a weakness in duration or cost since the ZnSe material was relatively soft and diamond was relatively expensive. In this study, comparing with ZnSe-ATR and diamond-ATR, a silicon-based ATR (Si-ATR) accessory was developed and used to explore the applicability and stability for sensing NO3 --N combining mathematic algorithms. It was found that partial least-squares regression (PLSR) showed a good performance comparing with the algorithms of principal component analysis (PCA) and linear regression (LR), and it was recommended for quantifying NO3 --N. For ZnSe-ATR, the residual prediction deviation (RPD) was more than 1.80, the determination coefficient (R 2) was more than 0.7725, and the root-mean-square error (RMSE) was less than 2.73 mg L-1. For diamond-ATR, the RPD was more than 1.76, the R 2 was more than 0.7309, and the RMSE was less than 8.22 mg L-1. For Si-ATR, the RPD was more than 1.42, the R 2 was 0.5198, and the RMSE was less than 11.02 mg L-1. It was confirmed that all three types of ATR could be applied in the quantification of NO3 --N in water for high nitrate concentrations. However, for the quantification of low nitrate concentrations (0-1 mg L-1 NO3 --N), ZnSe-ATR and diamond-ATR acquired the same accuracy, while Si-ATR had a lower accuracy. The pretreatment of Si-ATR-based spectra using the deconvolution algorithm could improve the prediction accuracy compared to water deduction for predicting low NO3 --N. Furthermore, a Si-ATR accessory was developed using Si-ATR, which was reliable for NO3 --N concentration quantification in water with the advantage of its low cost and long durability. Totally, samples with high nitrate concentrations implied a more reliable prediction for all crystals, and comprehensively, ZnSe-ATR was recommended for sensing low nitrate concentrations; diamond-ATR was recommended for samples with strong acid or base corrosion; and for sensing relatively high nitrate concentrations, such as in natural water bodies, Si-ATR was more economical because of its low cost and relatively long use life.

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来源期刊
ACS Omega
ACS Omega Chemical Engineering-General Chemical Engineering
CiteScore
6.60
自引率
4.90%
发文量
3945
审稿时长
2.4 months
期刊介绍: ACS Omega is an open-access global publication for scientific articles that describe new findings in chemistry and interfacing areas of science, without any perceived evaluation of immediate impact.
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