Michael J Trujillo1, Jon P Camden1. 1. Department of Chemistry and Biochemistry, University of Notre Dame, 251 Nieuwland Science Hall, Notre Dame, Indiana 46556, United States.
Abstract
Surface-enhanced hyper-Raman scattering (SEHRS), the nonlinear analog of surface-enhanced Raman scattering (SERS), provides unique spectral signatures arising from the molecular hyperpolarizability. In this work, we explore the differences between SERS and SEHRS spectra obtained from surface-bound uranyl ion. Exploiting the distinctive SEHRS bands for trace detection of the uranyl ion, we obtain excellent sensitivity (limit of detection = 90 ppb) despite the extreme weakness of the hyper-Raman effect. We observe that binding the uranyl ion to the carboxylate group of 4-mercaptobenzoic acid (4-MBA) leads to significant changes in the SEHRS spectrum, whereas the surface-enhanced Raman scattering (SERS) spectrum of the same complex is little changed. The SERS and SEHRS spectra are also examined as a function of both substituent position, using 2-MBA, 3-MBA, and 4-MBA, and the carbon chain length, using 4-mercaptophenylacetic acid and 4-mercaptophenylpropionic acid. These results illustrate that the unique features of SEHRS can yield more information than SERS in certain cases and represent the first application of SEHRS for trace analysis of nonresonant molecules.
Surface-enhanced hyper-Raman scattering (SEHRS), the nonlinear analog of surface-enhanced Raman scattering (SERS), provides unique spectral signatures arising from the molecular hyperpolarizability. In this work, we explore the differences between SERS and SEHRS spectra obtained from surface-bound uranyl ion. Exploiting the distinctive SEHRS bands for trace detection of the uranyl ion, we obtain excellent sensitivity (limit of detection = 90 ppb) despite the extreme weakness of the hyper-Raman effect. We observe that binding the uranyl ion to the carboxylate group of 4-mercaptobenzoic acid (4-MBA) leads to significant changes in the SEHRS spectrum, whereas the surface-enhanced Raman scattering (SERS) spectrum of the same complex is little changed. The SERS and SEHRS spectra are also examined as a function of both substituent position, using 2-MBA, 3-MBA, and 4-MBA, and the carbon chain length, using 4-mercaptophenylacetic acid and 4-mercaptophenylpropionic acid. These results illustrate that the unique features of SEHRS can yield more information than SERS in certain cases and represent the first application of SEHRS for trace analysis of nonresonant molecules.
Surface-enhanced hyper-Raman
scattering (SEHRS), the nonlinear
analog of surface-enhanced Raman scattering (SERS), has primarily
been used to probe the physical properties of molecules. SEHRS can,
for example, reveal the mode-specific enhancements from resonance
with different electronic states,[1−3] the molecular orientation
of molecules on metal surfaces,[4] and identify
local chemical effects, which do not appear in SERS data.[5] Its usefulness as an analytical technique, however,
has been limited by the weakness of the hyper-Raman scattered light
relative to the Raman scattered light.[6−8] SEHRS-based studies,
therefore, mostly utilize highly polarizable dye molecules, such as
rhodamine derivatives[2,4] and triphenylmethane dyes,[3,9] as the combination of large hyperpolarizability and resonance enhancement
yields large signal, even allowing for single-molecule detection.[9] It is worth noting that although hyper-Raman
scattering is weaker than Raman scattering, surface enhancement can
significantly shrink the gap between the two because the SEHRS enhancement
can be several orders of magnitude greater than the SERS enhancement.[6,7]Several recent studies have explored applications of SEHRS,
such
as imaging[10,11] and measurement of biologically
relevant small molecules.[12,13] Aqueous pH measurement[14] and pH measurement of cellular environments[15] using scattering signal from the protonated
and deprotonated forms of carboxylate-functionalized nanoparticles
have also been reported. The SEHRS signal, excitingly, shows sensitivity
to a larger pH range than the similarly constructed SERS probes. The
measurement of pH, however, relies on signal arising from a large
number of species on the nanoparticle surface, and does not require
a trace detection scheme.Extending SEHRS to trace analyte detection
(sub-ppm) would add
to the already existing advantages, such as large surface enhancement,
use of longer wavelengths for deeper sample penetration while still
yielding signal at easily detectable wavelengths,[16] and complementary information available with respect to
SERS. Herein, we exploit the unique and complementary aspects of SEHRS
spectra to demonstrate trace (90 ppb) detection of uranyl (UO22+) in aqueous solutions. Furthermore, the high
symmetry of the uranyl ion yields fundamental insights into the differences
between the SERS and SEHRS spectra of identical analytes.Detection
of uranium is also interesting in its own right, due
to the importance of maintaining safe drinking water and to identify
potentially trafficked radioactive material.[17] Recently, concerns of increased mobility of the uranyl ion, due
to liberal application of nitrate rich fertilizers,[18] have increased fears of uranium-contaminated drinking water.
A variety of SERS-based schemes have been developed that address these
concerns.[19−24] SEHRS-based methods, however, have not yet been explored. In this
work, we show that SEHRS-based detection schemes are viable and further
use this model system to explore the differences between SERS and
SEHRS.
Results and Discussion
Figure shows the
SEHRS and SERS spectra that result upon addition of uranyl nitrate
solution to 4-mercaptobenzoic acid (4-MBA)-functionalized silver particles.
The presence of uranyl nitrate dramatically changes the relative intensities
of many vibrational bands in the SEHRS spectrum, whereas the SERS
spectra derived from the exact same sample demonstrate almost no change.
Interestingly, three new bands appear in the SEHRS spectra between
800 and 900 cm–1: 830, 855, and 900 cm–1, which can be seen in an expanded view in Figure S1. The 830 and 900 cm–1 bands are attributed
to the symmetric (νs) and asymmetric (νas) stretching of the uranyl ion, respectively. The uranyl
modes in the SEHRS (νas, 900 cm–1) and SERS (νs, 830 cm–1) spectra
are shifted lower by approximately 30 cm–1 with
respect to the Raman and IR positions obtained from solid uranyl nitrate
hexahydrate,[25] indicating the binding of
the uranyl ion by the 4-MBA ligand.[23]
Figure 1
Left:
SEHRS spectra of 4-MBA-functionalized silver nanoparticles
before (red) and after (black) addition of uranyl nitrate solution.
Right: SERS spectra of 4-MBA-functionalized silver nanoparticles before
(red) and after (black) addition of uranyl nitrate solution. All spectra
were background subtracted and normalized by dividing by the maximum
intensity. The SERS spectrum of the particles has minor changes in
the presence of uranyl, whereas the SEHRS spectrum changes dramatically
after addition of uranyl.
Left:
SEHRS spectra of 4-MBA-functionalized silver nanoparticles
before (red) and after (black) addition of uranyl nitrate solution.
Right: SERS spectra of 4-MBA-functionalized silver nanoparticles before
(red) and after (black) addition of uranyl nitrate solution. All spectra
were background subtracted and normalized by dividing by the maximum
intensity. The SERS spectrum of the particles has minor changes in
the presence of uranyl, whereas the SEHRS spectrum changes dramatically
after addition of uranyl.For molecules with a center of inversion, e.g., linear UO22+, the activities of its vibrational modes are
mutually
exclusive between Raman and hyper-Raman scattering.[26] If the uranyl ion retains D∞ symmetry, the symmetric stretch is Raman active
and hyper-Raman inactive, whereas the asymmetric stretch is Raman
inactive and hyper-Raman active. The symmetric stretch (830 cm–1), however, appears in both the SERS and SEHRS spectra,
indicating that the symmetry of the uranyl ion must be altered upon
binding.The third band (855 cm–1) must either
correspond
to a shifted nitrate or 4-MBAcarboxylate mode. SEHRS spectra of 4-MBA
with added uranyl acetate were therefore measured to determine the
855 cm–1 signal origin. Appearance of the same modes
in the SEHRS spectrum of 4-MBA particles with uranyl acetate and additional
rinsing steps ensures that the 855 cm–1 is indeed
a shifted 4-MBAcarboxylate mode (see Supporting Information and Figure S2 for more detail).[27] The shift of the carboxylate mode, from 840 to 855 cm–1, is also observed in the SERS spectrum in the presence
of uranyl (Figure , right). It is interesting that the 4-MBA mode at 855 cm–1 becomes SEHRS active upon uranyl binding, whereas there is little
change in activity in the SERS spectrum (Figure ). The four 4-MBA bands between 1100 and
1500 cm–1 in the SEHRS spectrum have previously
been observed in low pH solutions of 4-MBA-coated nanoparticles.[15] The presence of these bands in low pH solution
indicates the protonated form of the carboxylate. It is not surprising
that the same bands appear in the presence of uranyl, where a single
carboxylateoxygen is likely bound to a uranyl ion instead of a proton,
similar to the reported crystal structure of uranyl bound to a single
carboxylateoxygen of isonicotinic acid.[28] As a control (Figure ), SEHRS spectra of 4-MBA-functionalized particles were recorded
at low pH (pH = 1) and no signal was obtained between 800 and 900
cm–1 where our analysis is done for the presence
of the uranyl ion. Furthermore, no SEHRS signal is observed between
800 and 900 cm–1 when the 4-MBA particles are exposed
to uranyl, indicating that at low pH the competition between the proton
and the uranyl favors the protonated form of the carboxylate (Figure ). As expected, the
basic (pH = 12) and neutral pH 4-MBASEHRS spectra are identical to
the neutral pH spectrum, as both neutral and basic pHs are higher
than the pKa of the carboxylate group
(Figure ). The formation
of more complex uranyl species at higher pH inhibits uranyl binding
resulting in the black spectrum in Figure and is consistent with previous reports.[29] Integration under the curves in the 800–900
and 1050–1100 cm–1 regions are tabulated
as a function of uranyl concentration, and a calibration curve is
constructed (Figure ). This peak-area method was chosen as the ratio of the signal to
a reference band accounts for fluctuations in enhancement, commonly
seen in SERS detection schemes.[30,31] These results indicate
that SEHRS can deliver quantitative detection of uranyl with a limit
of detection (LOD) of 90 ppb. Here, we calculate the LOD from 3σ/m, where σ is the standard deviation obtained from
three replicate measurements of five independently prepared samples
each and m is the slope of the calibration curve.
Figure 2
Left:
SERS spectra of 4-mercaptobenzoic acid (4-MBA)-functionalized
silver nanoparticles at acidic (top) and basic (bottom) pH, both with
(blue) and without (red) added uranyl. Right: SEHRS spectra of 4-MBA-functionalized
particles in acidic (top) and basic (bottom) pH and with (black) and
without (green) added uranyl ion. At both low and high pH values (pH
1, 12 respectively), presence of uranyl ion in solution does not change
the resulting spectra.
Figure 3
Left: representative SEHRS spectra of 4-MBA (red) and 4-MBA in
the presence of uranyl nitrate at a concentration of 400 ppb (black)
and 800 ppb (green). Right: integration of the region from 800 to
900 cm–1 relative to the integrated area of the
1100 cm–1. 4-MBA mode as a function of concentration
yields a calibration curve (red trace) with a limit of detection of
90 ppb.
Left:
SERS spectra of 4-mercaptobenzoic acid (4-MBA)-functionalized
silver nanoparticles at acidic (top) and basic (bottom) pH, both with
(blue) and without (red) added uranyl. Right: SEHRS spectra of 4-MBA-functionalized
particles in acidic (top) and basic (bottom) pH and with (black) and
without (green) added uranyl ion. At both low and high pH values (pH
1, 12 respectively), presence of uranyl ion in solution does not change
the resulting spectra.Left: representative SEHRS spectra of 4-MBA (red) and 4-MBA in
the presence of uranyl nitrate at a concentration of 400 ppb (black)
and 800 ppb (green). Right: integration of the region from 800 to
900 cm–1 relative to the integrated area of the
1100 cm–1. 4-MBA mode as a function of concentration
yields a calibration curve (red trace) with a limit of detection of
90 ppb.Determining what characteristics
of ligands lead to the largest
change in the SEHRS spectrum could lead to the design of high-performance
ligands for SEHRS-based detection. We specifically studied the effect
of the benzene ring on the enhanced 4-MBAcarboxylate band (855 cm–1) by changing the number of carbons separating the
carboxylate from the phenyl ring. Adding uranyl to a suspension of
4-mercaptophenylacetic acid (4-MPAA)-functionalized particles resulted
in SEHRS spectrum similar to that observed with 4-MBA (Figure ) although the intensity of
the signal is decreased by 40% relative to that of 4-MBA. Identical
experiments were done using 4-mercaptophenylpropionic acid (4-MPPA);
the resulting spectra surprisingly show no response in the 800–900
cm–1 in the presence of uranyl ion (Figure ). These experiments demonstrate
that separating the carboxylate from the phenyl ring by a single carbon
greatly decreases the observed signal.
Figure 4
Surface-enhanced hyper-Raman
spectra of 4-mercaptobenzoic acid
(4-MBA) particles (top), 4-mercaptophenylacetic acid (4-MPAA) particles
(middle), and 4-mercaptophenylpropionic acid (4-MPPA) particles (bottom),
before and after addition of uranyl nitrate solution (red and black
traces, respectively). It is clear that at constant concentration
(800 ppb), the signals from the uranyl ion and carboxylate group (800–900
cm–1) dramatically decrease with additional carbons
separating the carboxylate from the benzene ring.
Surface-enhanced hyper-Raman
spectra of 4-mercaptobenzoic acid
(4-MBA) particles (top), 4-mercaptophenylacetic acid (4-MPAA) particles
(middle), and 4-mercaptophenylpropionic acid (4-MPPA) particles (bottom),
before and after addition of uranyl nitrate solution (red and black
traces, respectively). It is clear that at constant concentration
(800 ppb), the signals from the uranyl ion and carboxylate group (800–900
cm–1) dramatically decrease with additional carbons
separating the carboxylate from the benzene ring.The location of the carboxylate on the phenyl ring may also
be
a factor in the enhancement of the 4-MBA band. Therefore, additional
experiments were performed using 2-mercaptobenzoic acid (2-MBA) and
3-mercaptobenzoic acid (3-MBA) in the place of the 4-MBA. Interestingly,
a comparison of the SERS spectra of 3-MBA and 4-MBA, both without
and with added uranyl nitrate, shows that uranyl can be detected with
a greater spectral change using 3-MBA (Figure ). This is consistent with our previous work
suggesting that changes in the 3 position of the benzene ring yield
more dramatic changes in the SERS spectra than changes in the 4 position.[32] The differences between the 3-MBA and 4-MBASEHRS spectra indicate that hyper-Raman may detect changes in the
4 position with more sensitivity than changes in the 3 position (Figure ). No change is observed
upon addition of uranyl to 2-MBA functionalized particles (Figure S3). This is likely due to orientation
effects or less efficient packing on the surface arising from steric
interaction of the carboxylate groups leading to significantly weaker
signal.
Figure 5
Left: SERS spectra of 4-MBA (top) and 3-MBA (bottom) before and
after addition of uranyl nitrate solution (red and black traces, respectively).
Right: SEHRS spectra of 4-MBA (top) and 3-MBA (bottom) before and
after addition of uranyl nitrate solution (red and black traces, respectively).
These spectra indicate that different parameters must be optimized
for maximum sensitivity in SEHRS-based schemes than those of SERS-based
schemes.
Left: SERS spectra of 4-MBA (top) and 3-MBA (bottom) before and
after addition of uranyl nitrate solution (red and black traces, respectively).
Right: SEHRS spectra of 4-MBA (top) and 3-MBA (bottom) before and
after addition of uranyl nitrate solution (red and black traces, respectively).
These spectra indicate that different parameters must be optimized
for maximum sensitivity in SEHRS-based schemes than those of SERS-based
schemes.
Conclusions
We demonstrate the first
trace detection assay based on surface-enhanced
hyper-Raman scattering (SEHRS). Our model system using 4-mercaptobenzoic
acid-functionalized silver nanoparticles provides a LOD of 90 ppb
for uranyl and suggests future viability of SEHRS-based assays. We
additionally present data demonstrating that SEHRS can be more sensitive
to the local structure and chemical environment than SERS obtained
with identical conditions, especially when the carboxylate is present
in the para position of the benzene ring. This sensitivity combined
with the benefits of nonlinear spectroscopies, such as greater sample
penetration and less interference from fluorescence, suggests that
SEHRS has great potential for further application in analytical sciences.
Experimental
Section
Silver nitrate, sodium citrate tribasic, uranyl nitrate,
uranyl
acetate, sodium nitrate, hydrochloric acid, nitric acid, sodium hydroxide,
sodium bromide, 4-mercaptobenzoic acid (4-MBA), 3-mercaptobenzoic
acid (3-MBA), 2-mercaptobenzoic acid (2-MBA), and 4-mercaptophenylacetic
acid (4-MPAA) were purchased from Sigma. 4-Mercaptophenylpropionic
acid (4-MPPA) was purchased from Santa Cruz Biotechnology. All reagents
were used as received without further purification. Silver colloids
were prepared using the Lee and Meisel method.[33] Specifically, 91.8 mg of silver nitrate was added to 200
mL of water and brought to boiling. Tribasic sodium citrate (115 mg)
was added to reduce the silver, forming spherical silver nanoparticles
approximately 70 nm in diameter, verified by dynamic light scattering.4-MBA-functionalized particles were prepared by adding 15.6 μL
of 1.6 mM 4-MBA in methanol solution to 5 mL of prepared silver colloids.
The resulting suspension was then stirred by vortex mixer. Sodium
bromide (1 mL, 1 M) was added causing the particles to aggregate.
The aggregated particles were allowed to settle, and the supernatant
was removed to eliminate unwanted complexation of the uranyl by citrate
in solution. 4-MBA-functionalized particles were then resuspended
in water. Varying volumes of a 21 ppm uranyl nitrate stock solution
were then added to the resuspended particles, resulting in final uranyl
concentrations between 200 and 1000 ppb, which were then aggregated
using 1 M NaBr. Samples were then ready for analysis.SERS data
were acquired using a 633 nm HeNe laser (Thorlabs) aligned
into an inverted microscope system (Nikon Ti-U). The beam, typically
50 μW at the objective, was then focused onto the sample using
a 20× objective (Nikon, NA = 0.5). Backscattered light was then
collected through the same objective, passed through a Rayleigh rejection
filter (Semrock), and analyzed using a dispersive imaging spectrometer
(Princeton Instruments, Acton SP2300, 1200 g mm–1) operated using Winspec software (Princeton Instruments).SEHRS spectra were acquired using an optical parametric oscillator
light source (picoEmerald, Applied Physics & Electronics) with
an idler wavelength of 1266 nm. The beam was pulsed (approximately
5 ps pulse width) at 80 MHz. The beam was then aligned into the same
inverted microscope system, analyzed in a dispersive imaging spectrometer
(Princeton Instruments, SP2300, 1200 g mm–1), and
detected using a back-illuminated deep-depletion CCD (PIXIS, Spec-10,
Princeton Instruments). SEHRS spectra were obtained with an average
laser power measured at the objective of approximately 2 mW and acquisitions
of 2 min. All presented spectra were background corrected and normalized
to the maximum intensity.
Authors: Judith Langer; Dorleta Jimenez de Aberasturi; Javier Aizpurua; Ramon A Alvarez-Puebla; Baptiste Auguié; Jeremy J Baumberg; Guillermo C Bazan; Steven E J Bell; Anja Boisen; Alexandre G Brolo; Jaebum Choo; Dana Cialla-May; Volker Deckert; Laura Fabris; Karen Faulds; F Javier García de Abajo; Royston Goodacre; Duncan Graham; Amanda J Haes; Christy L Haynes; Christian Huck; Tamitake Itoh; Mikael Käll; Janina Kneipp; Nicholas A Kotov; Hua Kuang; Eric C Le Ru; Hiang Kwee Lee; Jian-Feng Li; Xing Yi Ling; Stefan A Maier; Thomas Mayerhöfer; Martin Moskovits; Kei Murakoshi; Jwa-Min Nam; Shuming Nie; Yukihiro Ozaki; Isabel Pastoriza-Santos; Jorge Perez-Juste; Juergen Popp; Annemarie Pucci; Stephanie Reich; Bin Ren; George C Schatz; Timur Shegai; Sebastian Schlücker; Li-Lin Tay; K George Thomas; Zhong-Qun Tian; Richard P Van Duyne; Tuan Vo-Dinh; Yue Wang; Katherine A Willets; Chuanlai Xu; Hongxing Xu; Yikai Xu; Yuko S Yamamoto; Bing Zhao; Luis M Liz-Marzán Journal: ACS Nano Date: 2019-10-08 Impact factor: 15.881