- Nano Express
- Open Access
Compositional Analysis of Ternary and Binary Chemical Mixtures by Surface-Enhanced Raman Scattering at Trace Levels
© Hou et al. 2015
- Received: 13 October 2015
- Accepted: 3 November 2015
- Published: 9 November 2015
Surface-enhanced Raman scattering has been proven a powerful means in the fast detection and recognition of chemicals at trace levels, while quantitative analysis especially the compositional analysis of trace chemical mixtures remains a challenge. We report here a “triangle-rule” based on the principal component analysis (PCA) of surface-enhanced Raman scattering spectra, to calculate the composition of individual component of ternary chemical mixtures at trace levels, which can be simplified into the “balance-rule” for binary mixtures. We demonstrated the validity of the triangle-rule and balance-rule in estimating the composition of ternary and binary mixtures of methyl orange, methylene blue, and crystal violet with different molecular structures, and the validity for ternary and binary mixtures of three isomers of monochlorobiphenyl with very similar molecular structures. This idea might be also applicable to mixtures of more components at the trace levels.
- Principal component analysis
- Compositional analysis
- Surface-enhanced Raman scattering
Trace chemical detection is of great importance in the fields of environmental science, food science and medicine, etc. Recently, surface-enhanced Raman scattering (SERS) has been considered a powerful means as it is simple, fast, and is capable of recognizing molecules according to their vibrational fingerprints which are unique for a specific molecule [1–6]. It has been found that when a molecule is adsorbed on the surface of nanostructures of noble metals like Au and Ag, its Raman cross section can be greatly enhanced due to the localized surface plasmon resonance (LSPR) and the charge transfer between the molecule and nanostructure, namely the electromagnetic and chemical enhancements [7–11]. This leads to a great magnification of Raman signals of the molecule and makes it detectable at trace levels by Raman scattering [12, 13]. Therefore, SERS has become a promising qualitative tool in detecting and recognizing molecules and chemicals down to trace levels [14, 15].
In recent years, chemometrics methods, e.g., the principal component analysis (PCA), the hierarchical cluster analysis (HCA), partial least squares discriminant analysis (PLS-DA), etc., have been employed to identify components of the analyte with SERS spectra [16–19]. For example, Zhang et al. confirmed the existence of furazolidone and malachite green in fish products by the PCA of the SERS spectra . Lin et al. discriminated the blood serum of colorectal cancer patients from that of healthy subjects by principal component analysis-linear discriminant analysis (PCA-LDA) of the SERS spectra . Rivera-Betancourt et al. compared the validity of PCA, HCA, and PLS-DA in identifying mycobacteria . In addition, chemometrics methods such as partial least squares regression (PLSR) and principal components regression (PCR) have been employed to correlate the amount of a molecule to its SERS spectra . For instance, Zhai et al. measured ractopamine in swine urine with PLSR, and 0.4 μg/mL ractopamine could be detected . Manikas et al. measured the SERS spectra of mitoxantrone solutions and found that their concentration can be well predicted in a range of 0 to 13 ng/mL by PLSR of the SERS spectra . Both methods, however, are complicated and time-consuming, as the SERS spectra of a great amount of standard samples of various concentrations should be measured for the modeling process. New methodologies are therefore highly demanded for the quantitative analysis especially for the compositional analysis of chemical mixtures at trace levels by SERS.
In this study, we reported a simple method to calculate the compositions of ternary and binary chemical mixtures at trace levels by the PCA of the SERS spectra, which has been used previously to identify qualitatively the components in chemical mixtures. Based on the PCA analysis of the SERS spectra, we proposed a “triangle-rule” and a “balance-rule” for the ternary and binary mixtures, respectively, and demonstrated the validity of two rules in calculating the composition of two ternary model systems.
Fabrication of SERS Substrate
SERS substrate used in this research is silica nanorod (NR) array decorated with gold nanoparticles (NPs). SiO2 NRs were deposited on wafer with a DZS-500 electronic beam evaporation system (SKY Technology Development Co., Ltd. Chinese Academy of Sciences). To fabricate NRs perpendicular to wafer, glancing angle deposition (GLAD) technique was adopted. The incident angle of SiO2 beam was 86°, and the wafer kept in-plane rotation in the speed of 2 rpm. The SiO2 NRs were about 150 nm in height, with a diameter of around 30 nm. Au NPs were then sputtered on the NR array by a SBC-12 vacuum ion coater (KYKY Technology Co., Ltd.). The sputtering current was 10 mA, and the depositing time was 120 s. Consequently, the top and sidewall parts of SiO2 NRs were covered with great amount of Au NPs. The morphology of SiO2 NRs@Au NPs SERS substrate was characterized by scanning electron microscope (SEM, JEOL-JMS-7001F) and high-resolution transmission electron microscope (HRTEM, JEOL-2011).
Preparation of Analytes
Real compositions of the dye mixture samples
MO composition (%)
MB composition (%)
CV composition (%)
X MO:X MB:X CV
Measurements of the SERS Spectra
SERS spectra of all the probe molecules above were measured with an optical fiber micro-Raman system (i-Raman Plus, B&W TEK Inc.), using a 785-nm laser as the excitation source. The laser power was 300 mW, and the beam spot was about 85 μm in diameter. Before Raman spectra of dyes were acquired, the SERS substrate was immersed in the solution for 30 min to make the dye molecules adsorbed, and dried naturally in air. The integral time of the dyes’ spectra was 5 s. CB molecules were adsorbed on the “hot spots” through the process of dropping 3 μL solution on every piece of SERS substrate. SERS spectra were obtained after the acetone volatilized completely, and the integral time was 20 s. SERS spectra were acquired at ten different areas randomly selected on each sample so that more accurate chemometrics model could be established basing on these data.
The mole fraction and its error of each component in all dye mixtures
MO composition (%)
Error of MO composition (%)
MB composition (%)
Error of MB composition (%)
CV composition (%)
Error of CV composition (%)
To further validate the “triangle-rule,” we calculated the compositions of ternary mixtures using the “balance-rule.” For example, as shown by Fig. 3b, d, the ternary mixture (sample A6) can also be considered as a mixture of CV and sample A1 (which is a 1:1 mixture of MO and MB). Similarly, sample A6 can also be considered as a binary mixture of MB and sample A2 (a 1:1 mixture of MO and CV) or a binary mixture of MO and sample A3 (a 1:1 mixture of MB and CV). Therefore, the composition of sample 6 (a ternary mixture) can be calculated using the “balance-rule.” Considering it as a mixture of CV and sample A1, using the “balance-rule,” the CV composition was estimated to be ~24.25 % (very close to ~23.42 % calculated by the “triangle-rule”). The compositions of MO and MB were estimated to be ~40.71 and ~35.04 %, which are calculated to be ~37.42 and ~38.30 %, respectively, by the “triangle-rule.” The agreement between the two calculations confirms the validity of the “triangle-rule” and the “balance-rule” in calculating the composition of binary and ternary mixtures from the PCA, which could be used as a semi-quantitative approach for SERS.
The mole fraction and its error of each component in all monochlorobiphenyl mixtures
Concentration ratio of components
2-CB composition (%)
Error of 2-CB composition (%)
3-CB composition (%)
Error of 3-CB composition (%)
4-CB composition (%)
Error of 4-CB composition (%)
X 2-CB:X 3-CB = 1:1
X 2-CB:X 3-CB:X 4-CB = 1:1:1
In conclusion, we demonstrated that the PCA of the SERS spectra can be used as an effective way to distinguish the molecules in chemical mixtures qualitatively, and that it can be developed into a semi-quantitative approach to calculate the composition of binary/ternary mixtures of chemicals, using the “balance-rule” or the “triangle-rule” proposed here. Using ternary systems of MO, MB, and CV and 2-CB, 3-CB, and 4-CB as examples, we showed that the compositions of their mixtures can be calculated according to the two rules by the PCA of their SERS spectra, within acceptable errors. This study may provide a promising way to do quantitative analysis of chemical mixtures using SERS at trace levels.
The authors are very grateful to the financial support by the National Basic Research Program of China (973 program, Grant No. 2013CB934301), the National Natural Science Foundation of China (Grant Nos. 51228101 and 51531006), the Research Project of the Chinese Ministry of Education (Grant No. 113007A), and the Tsinghua University Initiative Scientific Research Program.
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