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1.Introduction1,3,5-triazine-2,4,6-triamine commercially known as melamine, , is generally used in laminates, coatings, or glass wares as melamine formaldehyde resins. However, the high nitrogen content (66% by mass), lured unreliable manufacturers to use it to fake the protein content, indicated by nitrogen, in infant milk formula and petfood. Melamine and cyanuric acid, or any other melamine related compounds such as ammeline, ammelide, and 1-(2-mercaptoethyl)-1,3,5-triazinane-2,4,6 trione (MTT),1–3 may produce complexes in the human body4–6 when they combine together via hydrogen bonds. At higher concentrations (more than for child and for adult) those complexes will aggregate in the kidneys and form kidney stones4,5,7 causing urinary system inflammation4,5 or urolithiasis. The World Health Organization (WHO) estimated the “tolerable daily intake,” to be 0.2°mg per kg of body mass.8 Such toxic additives have to be detected quickly and mass production of food items has to be controlled by authorities. This calls for reliable and accurate sensing techniques and materials with reasonable ease-of-use. Conventionally, melamine is detected by high performance liquid chromatography (HPLC),9,10 liquid chromatography coupled mass spectroscopy (LC-MS),11 LC-MS/MS, gas chromatography,9,12,13 matrix assisted laser desorption/ionization mass spectrometry,14 variety of ionization mass spectrometry,15,16 commercial enzyme linked immunosorbent assay technology,17 and infrared spectroscopy.18 These laboratory-based techniques, although reliable and accurate, are time consuming, and challenging for on-site common use. Relatively easier methods include optical absorption19–23 and Raman spectroscopy (RS), including surface-enhanced Raman spectroscopy (SERS).24–27 Recently, optical absorption studies are being used to detect melamine using MTT functionalized gold nanoparticles (AuNP).22 MTT attaches at one end to the AuNPs, by the thiol bond, and upon exposure to melamine bind to it through hydrogen bonding, thus agglomerating the AuNPs into clusters. The agglomeration will alter the surface plasmon absorption wavelength from 520 nm, for MTT stabilized AuNPs, to for the melamine exposed AuNPs. The shift, a function of melamine concentration, in this absorption frequency, observable by naked eye, is used for colorimetric sensing of melamine. However, such studies always used functionalized or modified AuNPs. Similar colorimetric determination of the presence of melamine can be done using magnetic NPs with 2.5 ppm detection levels.23 Recently, SERS is also being used for the sensing purpose.24 For SERS noble metal (Au, Ag) NP decorated substrates were used to enhance the scattering cross-section of melamine and hence lowering the detection limit. SERS is a technique that can be used on-site with relatively smaller degree of difficulty. In the present work, we demonstrate how the target analyte, melamine, itself induces agglomeration in unmodified gold nanoparticles, resulting in fractals on solid support in air, enabling target detection by SERS. Using finite difference time domain (FDTD) optical simulation we provide a preferred condition of plasmon distribution on the Au-fractal substrate that would be necessary for the sensing. 2.Experimental2.1.Synthesis of Gold NanoparticlesAuNPs were prepared by the conventional wet chemical method reducing a 10 mMchloroauric acid () (ACROS-411070010) solution, in DI water, with 1% trisodium citrate (Na3C6H5O7, ACROS-227130010) at 100°C.28,29 The reducing agent and its concentration is the main ingredient controlling the resultant AuNPs size. A colloidal solution of AuNPs in water is thus obtained. 2.2.Melamine Contaminated Water and Milk Sample ExtractionAqueous solutions of melamine were obtained by adding calculated amounts of melamine in DI water to attain target concentrations. These solutions were used for the AuNP fractal generation when dispersed on AuNP coated silicon surface. Melamine containing milk extracts were derived by mixing calculated amounts of melamine to commercial liquid milk to achieve concentrations () of 10, 1, 0.1, and 0.01 ppm concentrations, and then using citric acid to separate the protein in an ultra-centrifuge working at 10000 revolutions per minute, and collecting the supernatant. Proteins and fat components are removed for collection of the melamine contaminated supernatant. This will remove any effect of milk composition on the AuNPs. 2.3.InstrumentationOptical images of the AuNPs colloid was taken with a Canon 7d (Japan) camera equipped with a 17 to 50 mm, f 2.8, Sigma lens. The AuNPs are characterized by transmission electron microscope (TEM, JEM-2000EX II, JEOL Corp., Japan) and high resolution scanning electron microscope (HRSEM, JEOL 5700F, Japan) for its size. The surface plasmon absorption peak of the AuNPs solution is measured by absorption spectroscopy using a double beam spectrophotometer (JASCO V-670, JASCO Corp., Japan). For accurate determination of the AuNPs size distribution, a dynamic light scattering (DLS) Nanosizer (Zetasizer Nano ZS90, Malvern Instruments Ltd. UK) was used. This machine is equipped with a 4 mW He-Ne laser (632.8 nm) and a temperature controller from 0°C to 90°C. The Raman spectra were obtained using a commercial Jobin Yvon LabRAM HR800 (HORIBA Ltd., Japan) equipped with an Olympus BX-41 microscope and a liquid nitrogen cooled CCD detector. An excitation of 633nm laser was used. The spectral resolution of the machine was . The SERS substrates were prepared using standard crystalline silicon wafer on which 30 μL of the AuNPs solution was dispersed. 2.4.FDTD SimulationNumerical simulations using the FDTD method (FDTD solutions, Version 7, Lumerical Solutions Inc., Canada) were performed to determine the role of the AuNPs size and interparticle distance on the resulting plasmonic properties of the as-dispersed and melamine induced agglomerated AuNPs. In order to mimic the experimentally obtained AuNPs distribution (before and after melamine introduction), a model for the FDTD simulation was developed by extracting the () coordinates of the AuNPs from a representative SEM top-view image. The model layout resembles the sectioned Au cluster, together with the particle size and interparticle separation, and introduced to the optical simulation software by the image import option. Simulation parameters include time step of 0.001 fs, mesh size of 1 nm (in all three directions, dx, dy, and dz), background index of 1.0, and 1.33, and known index of gold. Perfectly matched layer boundary conditions were used in all three directions. 3.Results and DiscussionFor colorimetric22,23 or Raman spectroscopic detection24,30,31 of melamine, noble metal or magnetic NPs are generally used. In this case also we have used AuNPs, but without any cumbersome functionalization, for the detection using SERS. Figure 1 contains the details of the AuNP properties. The size control of AuNPs, prepared by the Turkevich method,29 was achieved by varying the concentration of the reactants to obtain distinctive AuNP colloids with purple, red, and orange colors. An optical image of the AuNP colloid and its size distribution, measured by Zetasizer, is shown in Fig. 1(a) and 1(b), respectively. The particle size was predominantly in the 20 to 30 nm range with a distribution as expected of the Turkevich reaction. Representative TEM images of the AuNPs, on the TEM grid, as dispersed and after exposure to 50 ppm melamine is shown in Fig. 1(c), and 1(d), respectively. The AuNPs showed triangular and hexagonal features, and readily agglomerated upon exposure to melamine. Representative SEM image of the AuNPs after melamine exposure is shown in Fig. 1(e). Absorption spectra of the as-grown AuNP colloid, and those after addition of 50 and 100 ppm of melamine is shown in Fig. 1(f). The results showed a surface plasmon absorption peak at . When melamine with different was added to the AuNP solution, the absorption peak intensity, at 530 nm, decreased [Fig. 1(f)] but no new peak, at higher wavelengths, found in the colorimetric detection methods, was observed that would imply significant agglomeration of the AuNPs in the solution. This is expected since the electrostatic repulsion of the Cl- surface coverage resisted the agglomeration. This is why MTT22 or riboflavin20 functionalization of the AuNPs was done. However, if sufficient amount of melamine is added (50 to 100 ppm) to the AuNP solution such an agglomeration could be actually observed even in unmodified AuNPs but they are too weak to trigger the second peak at a higher wavelength. This proves that melamine have this inherent tendency to weakly agglomerate nonfunctionalized AuNPs even in solution. The use of MTT22 for AuNP agglomeration is prohibitive for three reasons. First, the production yield of MTT is low, secondly, its production cost is high, and lastly, it introduces an additional functionalization step in the whole detection process. Hence, our method aimed at discarding this step for the detection purpose. We tried to enhance the agglomeration effect on dry substrates that are devoid of the polar solvent, in this case, water. We dispersed 30 μL of the as-grown AuNPs on hydrofluoric acid (HF) cleaned commercial Si wafers and dried them in vacuum to get a clean two-dimensional (2-D) dispersion. Large population density of AuNPs is avoided (1) to restrict three-dimensional (3-D) clustering that would obstruct the agglomeration phenomenon, and (2) to simplify the optical simulations done to construct the plasmon distribution design (discussed later). There is no chemical bond between the Si substrate and the AuNPs covering it. Figure 2 contains SEM images of AuNPs before and after the exposure to different amounts of melamine. The as-dispersed AuNPs (dry), on Si in air, showed a density of [Fig. 2(a)]. SEM was repeated [Fig. 2(a), all panels] at different magnifications and areas to verify the distribution that predominantly depended on the volume of the AuNPs solution and the wetting properties of the HF cleaned Si surface that showed a water contact angle of 43 deg at room temperature. Figure 2(b) to 2(d) showed the AuNPs distribution after exposure to 10, 1, and 0.1 ppm of melamine, respectively. As melamine is introduced, these AuNPs readily agglomerates forming an interconnected fractal-like network32 leaving polygonal islands in between with less than [Fig. 2(b) and 2(c)]. Such kind of fractal structures were previously obtained where a chain aggregate was constructed by sharing faces, corners, and edges of a polygon.33,34 These edges, corners, or faces are the areas expected to have high SERS enhancement and ideal for melamine sensing that we would soon demonstrate. The peripheries of these islands are 400 to 600 nm thick containing chained and agglomerated AuNPs with a high 2-D spatial density approaching an ideal SERS enhancement condition35 of where is the interparticle separation and is the radii of the AuNPs. In other words, the SERS efficiency is pronounced when AuNPs are nearly touching each other. The AuNP agglomeration was pronounced for , but the clustering weakens and the continuity of the fractal-network is broken as is reduced to 0.1 ppm with the island boundaries thinning to when present at all [Fig. 2(d)]. In comparison, the AuNPs chains on the island boundaries were [Fig. 2(b)] and 350 nm [Fig. 2(c)] thick when 10 and 1 ppm of melamine was introduced, respectively. The density of the AuNPs, counted manually by making meshes on 10 large area SEMs and neglecting meshes with fewer than (as-dispersed density), were , , and for exposures of , 1, and 0.1 ppm, respectively. In the large number of SEM images studied, we found very few 3-D clustering, which is not ruled out, but most of the melamine-induced agglomeration resulted in 2-D clustering under the given experimental conditions. Figure 3(a) to 3(e) contain detailed SERS data of melamine (with , 5, 1, 0.5, and 0.1 ppm) dispersed on the AuNPs coated Si. For comparison, the RS data (not SERS) of melamine is shown for bare Si substrates (without the AuNPs) [Fig. 3(f) to 3(j)]. Spectra were obtained on different points on each substrate with a focus on the signature melamine (bulk) peak at (Fig. 4). Repeated scans and their relative standard deviations (rsd) are shown for each melamine concentration. To have a qualitative estimate of the efficacy of the AuNP-fractals in enhancing the signal, corresponding Raman data of melamine is provided on bare Si substrates [Fig. 3(f) to 3(j)] on which the signal was only visible for and 5 ppm. The region of interest being around the strongest signal from melamine, 650 to , is marked in each plot in Fig. 3 scanned from 550 to . The signal (integrated area ) could be identified unambiguously down to the limit of 0.1 ppm [Fig. 3(e)] [with a signal: noise ratio () above 3:1] although its intensity decreased with decreasing [Fig. 3(a) to 3(e)]. The rsd is used to estimate the repeatability (precision) of the measurements. Along different regions of the spectrum (550 to ) the rsd varied between 10% to 30%, however, in the region of interest, 650 to , the rsd was and flat indicating a small deviation of the signal intensity compared to other parts of the spectrum. The weak non-SERS spectra of melamine on bare Si substrates reveal qualitatively the efficacy of the AuNP-fractals in enhancing the signal. The variation of the average as a function of is shown in Fig. 5, for both the SERS (on AuNP fractals) and non-SERS (reference plot, on bare silicon) cases. The slope of this plot (Fig. 5) is indicative of the sensitivity of detection in the studied concentration range. It is to be noted that the integrated signal intensity is not only a function of , but also a function of the number of SERS active sites () within the illuminated region () and with some simplifying assumptions we can write . One has to note that all AuNPs are not SERS active.36 Given the increasing coverage (area) of AuNP clustering with (Fig. 2), we expect an increase in too, and hence a stronger was observed [Fig. 3(a)]. In fact, Doering and Nie,37 while comparing metallic single particle and aggregates for single molecule SERS, observed that the active sites or hot spots are most likely to be at the junction of two single particles in metallic aggregates. This supports our finding why the AuNP fractals helped in the detection. It is difficult to estimate the SERS enhancement factor (, being the Raman scattering cross-section) since the number of melamine molecules and within the excited area, and the value of , are all unknown.38,39 However, with some approximation, a rough estimate of the EF can still be made using the following equation:38,40 where and denote the signal strength of a particular Raman mode () of the analyte, melamine, in the presence of the AuNP fractals and on bare silicon, respectively. and denote the number of melamine molecules, in the illuminated volume during Raman measurement, of bulk powder on bare silicon, and adsorbed on the AuNP fractals at different concentrations, respectively. The calculation of the intensity ratio () is straightforward from the Raman measurement. can be calculated assuming bulk melamine density (), and illuminated volume (laser beam area signal collection depth) during the measurement. Here, a signal collection depth of 0.1 mm was assumed for 633 nm laser on melamine powder, while the laser beam area was . The calculation of is tricky and requires simplifying assumptions. From the given concentration of melamine in the 30 μL water volume used to disperse the analyte on the AuNP fractals, an estimate of number of melamine molecules per unit volume is possible assuming complete and uniform dispersion on the substrate surface. Under such assumptions and approximation, the EFs were calculated to be , , , , and for the AuNP fractals with , 5, 1, 0.5, and 0.1 ppm, respectively. If we assume the SERS signal originating only from the AuNPs, and not from melamine adsorbed on silicon, then the above EF will increase following a decreased on the AuNPs only.In order to determine why the melamine detection was possible, even without functionalization of the AuNPs, the FDTD simulations (Figs. 6 and 7) were carried out. The presentation of the FDTD results begins with a representative SEM image of a given AuNP distribution. A replica, in size and density, of a section of this AuNP distribution is constructed theoretically. This AuNP distribution model when imported into the FDTD software, the optical extinction spectrum could be calculated. This spectrum will show the surface plasmon absorption peaks of the AuNP distribution at specific wavelengths. A single peak for individual unagglomerated AuNP and two or more peaks for agglomerated AuNPs will be obtained under orthogonal polarization directions (, ) of the electric field () of the incident light. Next, the software scans the replica of the AuNP distribution, constructed previously, with incident light wavelength in resonance with that of the surface plasmon absorption peaks obtained in the respective extinction spectrum. This would result in the surface plasmon -field mapping of the entire AuNP distribution. This procedure is repeated for the two polarization directions (, ) and with either one or two wavelengths depending on the respective surface plasmon absorption peaks calculated. In addition, the -field mapping of the AuNP distribution was also performed with incident wavelength of 633 nm that was used for the Raman measurement. Figures 6 and 7 contain comparative FDTD optical simulations of the AuNP distribution that were used to detect melamine. A representative SEM image () of highly agglomerated AuNPs () [Fig. 6(a)] was used to create exact theoretical replica [Fig. 6(b)] that yielded the extinction spectra (scattering cross-section) using two perpendicular polarizations ( and ) of the electric field of the incident light [Fig. 6(c) and 6(d)] propagating along the -direction. The extinction spectra showed double peaks at 525 and (agglomerated AuNPs surface plasmon) [Fig. 6(c) and 6(d)]. Such double peaks in the spectra are present even for the 0.1 ppm melamine exposed AuNPs showing weak agglomeration. Surface plasmon maps of the AuNP distribution shows stronger E-field distribution under 525 nm excitation than under 633 nm, under both vertical [, Fig. 6(e) and 6(f)] and horizontal polarization [, Fig. 6(g) and 6(h)]. This is due to the lower surface plasmon absorption at 633 nm [Fig. 6(c) and 6(d)]. The same presentation scheme was maintained for the case of 0.1 ppm exposed AuNPs (Fig. 7). Since the FDTD calculations depend on the density and the size of the AuNPs, the chosen area of the SEM [Fig. 7(a)] and its theoretical replica [Fig. 7(b)] roughly had similar AuNP distribution () for 0 [Fig. 2(a)] and 0.1 ppm [Fig. 2(d)] melamine exposure. This is assumed for simplicity and no loss of technicality. In this case, only one scattering peak (as expected for mostly individual AuNPs at a low spatial density) is observed at [Fig. 7(c) and 7(d)] for both and . The plasmonic E-field map, at 525 and 633 nm, shows weak local plasmons centered around the individual AuNPs under both polarization conditions [Fig. 7(e) to 7(h)]. SERS-aided detection is a plasmonic phenomenon where the local electric field at the analyte site dictates .41 In other words, a strong plasmon [red color in Figs. 6(e) to 6(h), and 7(e) to 7(h)] field coverage of the detector surface (per unit area) would increase the scattered intensity () to detectable limits. The simulated plasmon mapping shown in Figs. 6(e) to 6(h), and 7(e) to 7(h) was obtained assuming spherical AuNPs. However, the TEM results [Fig. 1(c)] clearly showed that the AuNPs distribution contained triangular and hexagonal AuNPs with sharp corners and edges. The shape dependence of SERS, reported earlier, indicate that though spheres are excellent model systems for simulations, the maximum enhancement comes from aggregates or fractal like structures of ellipsoids.42 However, even the spherical model approximation for the FDTD calculations gives us a lower bound for the plasmon field distributions. In reality, the electric fields would be higher considering the triangular or hexagonal AuNPs. The other usefulness of the FDTD calculations is that it can predict the absorption frequencies for the clusters/fractals under consideration. While a sphere can resonate at one particular frequency (or wavelength), a spheroid can resonate at three different frequencies and a random fractal may resonate at any given frequency over a broad spectral region.43 These localized resonances in fractals increase in number from visible to near-IR increasing the probability of obtaining higher enhancement factors in SERS. Under the given experimental conditions, higher (10 to 1 ppm) could agglomerate the AuNPs so that a strong plasmon field with wide coverage [Fig. 6(e) to 6(h)] could be obtained over the detector surface. Such area of strong plasmon field decreases with decreasing . This is why decreases with decreasing [Fig. 3(a) to 3(e)]. At , such AuNP clusters still remained so that we could detect the melamine signal, though weak, quite consistently [Fig. 3(e)]. However, for AuNPs that did not agglomerate when [Fig. 7(b)] or 0 ppm [Fig. 2(a)], the plasmon field, with an absorption peak at [Fig. 7(c) and 7(d)], is weak with low surface coverage [Fig. 7(e) to 7(h)] and hence detection was either difficult or not possible at all. The scarce presence of red color in Fig. 7(e) to 7(h) only indicates a lower probability of scattering and greater degree of uncertainty in measurement under both 525 or 633 nm excitation. However, the calculated surface plasmon absorption of the AuNP distribution, though strong around 525 nm, was weak at the Raman measurement wavelength of 633 nm [Fig. 6(c) to 6(d); Fig. 7(c) to 7(d)]. Within our experimental rage of (10 to 0.1 ppm), the index of the surrounding medium was assumed to be 1.0 in our FDTD calculations shown in Figs. 6 and 7. If we take into account the presence of melamine within the fractals, then the effective index would be higher than 1.0, depending on its volume fraction, scaling with . Although the exact index cannot be calculated, due to the uncertain coverage, we performed the FDTD calculations with higher representative index of 1.33 under 525 and 633 nm excitation. The results, irrespective of the AuNP distribution and incident field polarization, show an increasing plasmon absorption band around (Figs. 8 and 9) where the actual Raman measurements were performed. Usual red shift, towards higher wavelength, of the absorption bands are expected and observed with increasing index as reported before.44,45 Although the 525 nm band was still the strongest [Figs. 8(a), 8(b), 9(a), and 9(b)], the plasmon field distribution at 525 [Fig. 8(c) and 8(d)] and 633 nm [Fig. 8(e) to 8(f)] excitation was markedly improved at background index of 1.33 compared to calculations done with background index of 1.0 for each excitation wavelength [Fig. 6(e) and 6(h)]. These results can now explain why we could still detect melamine with high sensitivity at 633 nm. The limit of detection would have been lower if we could measure at 525 nm because of the strongest surface plasmon absorption at that wavelength in the given AuNP fractal distribution. In short, we demonstrate how 100 ppb of melamine could be reproducibly detected on AuNP-fractals that creates a given plasmon field distribution as shown in Fig. 6(e) to 6(h) and Fig. 8(c) and 8(f). To confirm, whether the strategy will still work when we extract melamine from a milk colloid, we performed similar SERS measurements with samples extracted from real contaminated milk. The extract contained melamine suspended in the liquid of milk with its proteins removed. Figure 10 shows SERS data of milk extracts containing different . Experimental designs and conditions remaining the same, similar results were obtained with the diminishing in intensity with a lowering of . Some background signals from the Si substrate and remnant milk components could be seen as well. The variation of the normalized as a function of (in milk extract) is shown in Fig. 11 whose slope is indicative of the sensitivity of detection in the studied concentration range. Here also, we could detect up to 100 ppb of melamine in milk from the feature at in the SERS spectra (Fig. 10). Lowering to 10 ppb resulted in virtually no signal () (Fig. 10). However, we could say, with confidence, that at least 100 ppb of melamine could be detected with a simple AuNPs distribution, with particle size to 30 nm, which demonstrated a plasmon field as shown in Figs. 6(e) to 6(h) and 8(c) and 8(f). 4.ConclusionsPresence of melamine was detected in raw milk by surface-enhanced Raman scattering using silicon substrates dispersed with unmodified 30 nm AuNPs. Melamine was found to agglomerate the AuNPs with as-dispersed densities of , to predominantly 2-D clusters with densities of (at 10 ppm concentration), that helped to generate a strong plasmonic field under illumination. The absorption and plasmon field strength of the agglomerated AuNPs were simulated by FDTD method. The optical simulations helped to qualitatively estimate the plasmon distribution to enable melamine detection to a limit of 100 ppb. Melamine containing milk extracts when applied to these unmodified AuNPs coated surfaces yielded strong Raman signals at indicating the presence of melamine. The absence of the AuNPs on the same substrates yielded no Raman signals under similar experimental conditions. A limit of detection of 100 ppb could be reproducibly obtained in this technique. AcknowledgmentsThe study was supported by the National Science Council, Taiwan, under grant number NSC 98-2112-M-010-005-MY3 and NSC 101-2112-M-010-003-MY3, and the ATU plan of the Ministry of Education, Taiwan. Additional support from the Biophotonics and Molecular Imaging Research Center, National Yang Ming University, is also gratefully acknowledged. ReferencesB. M. Kuehn,
“Melamine scandals highlight hazards of increasingly globalized food chain,”
J. Am. Med. Assoc., 301
(5), 473
–475
(2009). http://dx.doi.org/10.1001/jama.2009.35 JAMAAP 0098-7484 Google Scholar
C. A. Haller,
“Made in China,”
J. Med. Toxicol., 4
(2), 141
–142
(2008). http://dx.doi.org/10.1007/BF03160969 IOMTE3 1054-044X Google Scholar
Z. C. Y. ChanW. F. Lai,
“Revisiting the melamine contamination event in China: implications for ethics in food technology,”
Trends Food Sci. Technol., 20
(8), 366
–373
(2009). http://dx.doi.org/10.1016/j.tifs.2009.04.005 TFTEEH 0924-2244 Google Scholar
R. ReimschuesselB. Puschner,
“Melamine toxicity-stones vs. crystals,”
J. Med. Toxicol., 6
(4), 468
–469
(2010). http://dx.doi.org/10.1007/s13181-010-0107-5 IOMTE3 1054-044X Google Scholar
A. RanganathanV. R. PedireddiC. N. R. Rao,
“Hydrothermal synthesis of organic channel structures: 1:1 hydrogen-bonded adducts of melamine with cyanuric and trithiocyanuric acids,”
J. Am. Chem. Soc., 121
(8), 1752
–1753
(1999). http://dx.doi.org/10.1021/ja983928o JACSAT 0002-7863 Google Scholar
T. K. ChakrabortyS. TapadarS. K. Kumar,
“Cyclic trimer of 5-(aminomethyl)-2-furancarboxylic acid as a novel synthetic receptor for carboxylate recognition,”
Tetrahedron Lett., 43
(7), 1317
–1320
(2002). http://dx.doi.org/10.1016/S0040-4039(01)02367-X TELEAY 0040-4039 Google Scholar
A. K. C. HauT. H. KwanP. K. T. Li,
“Melamine toxicity and the kidney,”
J. Am. Soc. Nephrol., 20
(2), 245
–250
(2009). http://dx.doi.org/10.1681/ASN.2008101065 JASNEU 1046-6673 Google Scholar
, “Melamine and Cyanuric Acid: Toxicity, preliminary risk assessment and guidance on levels in food,”
(2008) http://advocatingbreastfeeding.wordpress.com/2008/09/30/who-melamine-and-cyanuric-acid-toxicity-preliminary-risk-assessment-and-guidance-on-levels-in-food-for-everyone/ September ). 2008). Google Scholar
S. EhlingS. TeferaI. P. Ho,
“High-performance liquid chromatographic method for the simultaneous detection of the adulteration of cereal flours with melamine and related triazine by-products ammeline, ammelide, and cyanuric acid,”
Food Addit. Contam., 24
(12), 1319
–1325
(2007). http://dx.doi.org/10.1080/02652030701673422 FACOEB 1464-5122 Google Scholar
R. A. Yokleyet al.,
“Analytical method for the determination of cyromazine and melamine residues in soil using LC-UV and GC-MSD,”
J. Agric. Food Chem., 48
(8), 3352
–3358
(2000). http://dx.doi.org/10.1021/jf991231w JAFCAU 0021-8561 Google Scholar
M. S. Filigenziet al.,
“The determination of melamine in muscle tissue by liquid chromatography/tandem mass spectrometry,”
Rapid Commun. Mass Spectrom., 21
(24), 4027
–4032
(2007). http://dx.doi.org/10.1002/(ISSN)1097-0231 RCMSEF 0951-4198 Google Scholar
T. Sugitaet al.,
“Determination of melamine and three hydrolytic products by liquid chromatography,”
Bull. Environ. Contam. Toxicol., 44
(4), 567
–571
(1990). http://dx.doi.org/10.1007/BF01700877 BECTA6 0007-4861 Google Scholar
J. P. TothP. C. Bardalaye,
“Capillary gas chromatographic separation and mass spectrometric detection of cyromazine and its metabolite melamine,”
J. Chromatograph. A, 408 335
–340
(1987). http://dx.doi.org/10.1016/S0021-9673(01)81819-7 JOCRAM 0021-9673 Google Scholar
C. C. Liuet al.,
“Detection of melamine in a human renal uric acid stone by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS),”
Clin. Chim. Acta., 413
(19–20), 1689
–1695
(2012). http://dx.doi.org/10.1016/j.cca.2012.04.016 CCATAR 0009-8981 Google Scholar
H. W. Tanget al.,
“Analysis of melamine cyanurate in urine using matrix-assisted laser desorption/ionization mass spectrometry,”
Anal. Chem., 81
(9), 3676
–3682
(2009). http://dx.doi.org/10.1021/ac802752n ANCHAM 0003-2700 Google Scholar
L. Zhuet al.,
“Rapid detection of melamine in untreated milk and wheat gluten by ultrasound-assisted extractive electrospray ionization mass spectrometry (EESI-MS),”
Chem. Commun., 559
–561
(2009). http://dx.doi.org/10.1039/b818541g CHCOFS 1364-548X Google Scholar
E. A. E. Garber,
“Detection of melamine using commercial enzyme-linked immunosorbent assay technology,”
J. Food Prot., 71
(3), 590
–594
(2008). JFPRDR 0362-028X Google Scholar
L. J. Maueret al.,
“Melamine detection in infant formula powder using near- and mid-infrared spectroscopy,”
J. Agric. Food Chem., 57
(10), 3974
–3980
(2009). http://dx.doi.org/10.1021/jf900587m JAFCAU 0021-8561 Google Scholar
R. K. BeraC. R. Raj,
“Naked eye sensing of melamine using rationally tailored gold nanoparticles: hydrogen-bonding and charge-transfer recognition,”
Analyst, 136
(8), 1644
–1648
(2011). http://dx.doi.org/10.1039/c0an00870b ANLYAG 0365-4885 Google Scholar
B. RoyA. SahaA. K. Nandi,
“Melamine sensing through riboflavin stabilized gold nanoparticles,”
Analyst, 136
(1), 67
–70
(2011). http://dx.doi.org/10.1039/c0an00599a ANLYAG 0365-4885 Google Scholar
C. P. HanH. B. Li,
“Visual detection of melamine in infant formula at 0.1 ppm level based on silver nanoparticles,”
Analyst, 135
(3), 583
–588
(2010). http://dx.doi.org/10.1039/b923424a ANLYAG 0365-4885 Google Scholar
K. L. AiY. L. LiuL. H. Lu,
“Hydrogen-bonding recognition-induced color change of gold nanoparticles for visual detection of melamine in raw milk and infant formula,”
J. Am. Chem. Soc., 131
(27), 9496
–9497
(2009). http://dx.doi.org/10.1021/ja9037017 JACSAT 0002-7863 Google Scholar
N. Dinget al.,
“Colorimetric determination of melamine in dairy products by Fe3O4 magnetic nanoparticles–H2O2–ABTS detection system,”
Anal. Chem., 82
(13), 5897
–5899
(2010). http://dx.doi.org/10.1021/ac100597s ANCHAM 0003-2700 Google Scholar
L. Heet al.,
“A new approach to measure melamine, cyanuric acid, and melamine cyanurate using surface enhanced Raman spectroscopy coupled with gold nanosubstrates,”
Sens. Instrumen. Food Qual., 2
(1), 66
–71
(2008). http://dx.doi.org/10.1007/s11694-008-9038-0 1932-7587 Google Scholar
Y. L. Liuet al.,
“Potential of Raman spectroscopy and imaging methods for rapid and routine screening of the presence of melamine in animal feed and foods,”
Appl. Spectrosc., 63
(4), 477
–480
(2009). http://dx.doi.org/10.1366/000370209787944398 APSPA4 0003-7028 Google Scholar
S. Okazakiet al.,
“Rapid nondestructive screening for melamine in dried milk by Raman spectroscopy,”
Forensic Toxicol., 27
(2), 94
–97
(2009). http://dx.doi.org/10.1007/s11419-009-0072-3 FTOOAU 1860-8965 Google Scholar
Y. Chenget al.,
“Screening melamine adulterant in milk powder with laser Raman spectrometry,”
J. Food Compos. Anal., 23
(2), 199
–202
(2010). http://dx.doi.org/10.1016/j.jfca.2009.08.006 JFCAEE 0889-1575 Google Scholar
J. Kimlinget al.,
“Turkevich method for gold nanoparticle synthesis revisited,”
J. Phys. Chem. B, 110
(32), 15700
–15707
(2006). http://dx.doi.org/10.1021/jp061667w JPCBFK 1520-6106 Google Scholar
J. Turkevichet al.,
“A study of the nucleation and growth in the synthesis of colloidal gold,”
Discuss. Faraday Soc., 11
(4), 55
–75
(1951). http://dx.doi.org/10.1039/df9511100055 DFSOAW 0014-7664 Google Scholar
H. Huanget al.,
“Surface-enhanced Raman spectra of melamine and other chemicals using a 1550 nm (retina-safe) laser,”
J. Raman Spectrosc., 43
(6), 701
–705
(2012). http://dx.doi.org/10.1002/jrs.v43.6 JRSPAF 0377-0486 Google Scholar
X. F. Zhanget al.,
“Detection of melamine in liquid milk using surface-enhanced Raman scattering spectroscopy,”
J. Raman Spectrosc., 41
(12), 1655
–1660
(2010). http://dx.doi.org/10.1002/jrs.2629 JRSPAF 0377-0486 Google Scholar
D. A. WeitzM. Y. LinC. J. Sandroff,
“Colloidal aggregation revisited: new insights based on fractal structure and surface-enhanced Raman scattering,”
Surf. Sci., 158
(1–3), 147
–164
(1985). http://dx.doi.org/10.1016/0039-6028(85)90292-4 SUSCAS 0039-6028 Google Scholar
H. FeilchenfeldO. Siiman,
“Adsorption and aggregation kinetics and its fractal description for chromate, molybdate, and tungstate ions on colloidal silver from surface Raman spectra,”
J. Phys. Chem., 90
(19), 4590
–4599
(1986). http://dx.doi.org/10.1021/j100410a024 JPCHAX 0022-3654 Google Scholar
O. SiimanH. Feilchenfeld,
“Internal fractal structure of aggregates of silver particles and its consequences on surface-enhanced Raman scattering intensities,”
J. Phys. Chem., 92
(2), 453
–464
(1988). http://dx.doi.org/10.1021/j100313a042 JPCHAX 0022-3654 Google Scholar
J. GarciaVidalJ. B. Pendry,
“Collective theory for surface enhanced Raman scattering,”
Phys. Rev. Lett., 77
(6), 1163
–1166
(1996). http://dx.doi.org/10.1103/PhysRevLett.77.1163 PRLTAO 0031-9007 Google Scholar
S. M. NieS. R. Emery,
“Probing single molecules and single nanoparticles by surface-enhanced Raman scattering,”
Science, 275
(5303), 1102
–1106
(1997). http://dx.doi.org/10.1126/science.275.5303.1102 SCIEAS 0036-8075 Google Scholar
E. DoeringS. M. Nie,
“Single-molecule and single-nanoparticle SERS: examining the roles of surface active sites and chemical enhancement,”
J. Phys. Chem. B., 106
(2), 311
–317
(2002). http://dx.doi.org/10.1021/jp011730b JPCBFK 1520-6106 Google Scholar
E. C. Le Ruet al.,
“Surface enhanced Raman scattering enhancement factors: a comprehensive Study,”
J. Phys. Chem. C, 111
(37), 13794
–13803
(2007). http://dx.doi.org/10.1021/jp0687908 1932-7447 Google Scholar
S. Chattopadhyayet al.,
“Surface-Enhanced Raman Spectroscopy Using Self-Assembled Silver Nanoparticles on Silicon Nanotips,”
Chem. Mater., 17
(3), 553
–559
(2005). http://dx.doi.org/10.1021/cm049269y CMATEX 0897-4756 Google Scholar
A. Shalabneyet al.,
“Detailed study of surface-enhanced Raman scattering from metallic nanosculptured thin films and their potential for biosensing,”
J. Nanophoton., 6
(1), 061605
(2012). http://dx.doi.org/10.1117/1.JNP.6.061605 JNOACQ 1934-2608 Google Scholar
F. L. Yapet al.,
“Nanoparticle cluster arrays for high-performance SERS through directed self-assembly on flat substrates and on optical fibers,”
ACS Nano., 6
(3), 2056
–2070
(2012). http://dx.doi.org/10.1021/nn203661n 1936-0851 Google Scholar
E. J. ZemanG. C. Schatz,
“An accurate electromagnetic theory study of surface enhancement factors for silver, gold, copper, lithium, sodium, aluminum, gallium, indium, zinc, and cadmium,”
J. Phys. Chem., 91
(3), 634
–643
(1987). http://dx.doi.org/10.1021/j100287a028 JPCHAX 0022-3654 Google Scholar
V. A. Shubinet al.,
“Local electric and magnetic fields in semicontinuous metal films: beyond the quasistatic approximation,”
Phys. Rev. B, 62
(16), 11230
–11244
(2000). http://dx.doi.org/10.1103/PhysRevB.62.11230 PRBMDO 0163-1829 Google Scholar
J. J. MockD. R. SmithS. Schultz,
“Local refractive index dependence of plasmon resonance spectra from individual nanoparticles,”
Nano Lett., 3
(4), 485
–491
(2003). http://dx.doi.org/10.1021/nl0340475 NALEFD 1530-6984 Google Scholar
Y. H. Leeet al.,
“Refractive index sensitivities of noble metal nanocrystals: the effects of multipolar plasmon resonances and the metal type,”
J. Phys. Chem. C, 115
(16), 7997
–8004
(2011). http://dx.doi.org/10.1021/jp202574r 1932-7447 Google Scholar
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