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Particle Size Sensitivity Dependence of Nanocomposites for Plasmonic-Based All-Optical Sensing Applications Phillip H. Rogers† and Michael A. Carpenter* College of Nanoscale Science and Engineering, UniVersity at AlbanysState UniVersity of New York, 257 Fuller Road, Albany, New York 12203 ReceiVed: February 10, 2010; ReVised Manuscript ReceiVed: May 20, 2010
Two Au nanoparticle embedded ytria-stabilized zirconia (Au-YSZ) nanocomposite thin films were physical vapor deposited and annealed to achieve films of different average Au nanoparticle (AuNP) sizes. Shifts in the peak position and width of the localized surface plasmon resonance (LSPR) for the AuNPs were observed upon changing gas concentrations which had a strong dependence on particle size. An electrochemical model has been developed which assumes that shifts in the peak position are due to charge exchange occurring between the AuNPs and the gas exposure modified interfacial environment. This model also takes into account the AuNP size dependence and predicts that the smallest AuNP containing nanocomposite thin films will have the greatest sensitivity in LSPR peak position shift. From the electrochemical model we also find that there is a 160 meV difference in equilibrium energies between surface adsorbed oxygen ions and oxygen ions incorporated into vacancies in the YSZ matrix. Introduction Nanocrystalline thin films are of great interest to a wide variety of industries due to the ongoing research that continues to reveal new ways that these materials can both enhance many of the products used today and for the potential they possess for the development of future products. Proposed applications for these materials include: self-cleaning surfaces,1,2 antiwear coatings,3-5 and sensors6-8 just to name a few. Thin film nanocomposites containing metal nanoparticles embedded in a dielectric matrix are a specific set of nanocrystalline materials that are being explored for their unique optical properties due to the localized surface plasmon resonance (LSPR) of the metal nanoparticles. Possible applications for these thin films include: surface enhanced Raman scattering (SERS),9 wave guides,10 and plasmonic-based sensors.11-14 The spectral shape of the LSPR is extremely sensitive to the local environment of the metal nanoparticles (NPs) making these materials ideal for harsh environment sensing applications where degradation of ohmic contacts and material defects can plague conventional field effect and resistive chemical sensors.15,16 Furthermore, by embedding the metal NPs in a metal oxide matrix and placing this nanocomposite within a highly reactive environment, the LSPR signal becomes strongly dependent on interfacial catalytic reactions and both the ionic and electrical conductivity properties of the metal oxide. Interpretation of this convoluted signal and development of this new sensing technology will likely be complementary to metal oxide based mixed potential sensors with the added benefit of this being a wireless approach for harsh environment monitoring applications.17,18 How the local environment affects the LSPR for these nanocomposites is an area of active research, and there have been many publications which demonstrate the sensitivity of these types of nanocomposites to the exposure environment, but there are only a few * To whom correspondence should be addressed. E-mail: mcarpenter@ uamail.albany.edu. † Current address: National Institute of Standards and Technology, 100 Bureau Drive, MS-8362, Gaithersburg, MD 20899.
which attempt to model the mechanisms which result in the observed transduction.19-21 In our previous work, we proposed a model to describe the mechanism behind high temperature gas sensing in gold nanoparticle embedded yttria-stabilized zirconia (Au-YSZ).22,23,34 The observed change in the LSPR peak position as a function of exposure to O2/H2, O2/NO2, and air/CO exposures was linked to electrochemical charge transfer reactions occurring within the Au-YSZ nanocomposite. More recently, there has been plasmonic based thin film gas sensing work published by other groups which attribute observed LSPR shifts to extrinsic matrix effects, rather than intrinsic changes occurring to the AuNPs.11,24,25 Depending on the material system and experimental design it is expected that LSPR shifts could be attributed to matrix effects and/or electrochemical reactions resulting in charged gold nanoparticles. In such that the materials and operating conditions for the experiments outlined in this current study are much closer to that of the cathode within a solid oxide fuel cell (i.e., the composite interface consists of an oxygen ion conducting matrix and catalytic surface particles at an operating temperature greater than that required for oxygen ion diffusion), it is assumed that charge exchange does occur and is a dominant factor in the observed LSPR shifts. Specifically, when YSZ is exposed to oxygen and temperatures above ∼350 °C, oxygen molecules dissociate and form O2- ions which diffuse and fill the oxygen vacancies within the metal oxide matrix.26 Since the matrix is also comprised of Au nanoparticles, the electrons exchanged during O2- formation are likely to come from the metal rather than the metal oxide component, thus creating a Au nanoparticle with a lower free electron density and a characteristically redshifted plasmon peak. Subsequent interfacial charge transfer reactions involving the O2- ions and the Au nanoparticle can be monitored via changes in the plasmon peak. However, upon filling the YSZ oxygen vacancies with O2- ions, there will likely be an increase in polarizability of the matrix and in so doing the dielectric function of the nanocomposite should also increase. As outlined in the equations to follow, this would also cause a red shift in the plasmon band. Therefore, in all likelihood, LSPR
10.1021/jp101299k 2010 American Chemical Society Published on Web 06/04/2010
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shifts observed upon environmental changes (at elevated temperatures) for Au-YSZ and other plasmonic particle containing nanocomposites are due to a combination of both charging effects and changes in the dielectric constant. One future method for measuring both of these contributions would be to adopt a method of measuring both the absorption cross section and the scattering cross section of nanocomposite films at these elevated temperatures.27 Both measurements are predicted to have different dependences on the charge and dielectric constant, and by modeling both components of the extinction spectrum, changes in charge and dielectric constant might be separable. However, for the present work, we approach the issue of LSPR shifts observed upon environmental gas exposure changes for Au-YSZ nanocomposite thin films at 500 °C with a detailed AuNP charge exchange model, which upon experimental deconvolution of the charging and dielectric effects can be expanded to include both contributions. Therefore, with this current study we develop a more general electrochemical charge exchange model from our original model for charge exchange within Au-YSZ nanocomposites which can easily be adapted to other systems. One addition that comes from this more general model is the separation of surface reactions and reactions which result in the incorporation of oxygen ions into the YSZ matrix. A prediction that comes from this work, which is important to the development of these materials as real world sensors, is the LSPR peak position sensitivity dependence on the particle size of AuNPs embedded in YSZ nanocomposites. Gas exposure data obtained for two different particle size films, 8 and 18 nm AuNPs, will be used for comparison to the model. The titration experiments performed were to varying exposures of O2 and H2 in N2 at 500 °C. Not only are H2 and O2 ideal gases for observing benchmark type electrochemical reactions, but these gases are also model environments for conditions found in harsh environment combustion related applications. Experimental Methods Au-YSZ thin films have been deposited using rf comagnetron confocal physical vapor deposition (PVD) using deposition parameters similar to those published previously.21 After deposition, films are removed from the deposition chamber and were placed into an annealing chamber. The small and large particle films were then annealed at ∼900 °C for 2 and 3 h, respectively, under 2000 sccm flow of Ar at atmospheric pressure. TEM microscopy was used to approximate average grain sizes for the Au-YSZ nanocomposite thin films. The small particle film had an average particle size of 8 nm and the large particle film had an average particle size of 18 nm. After annealing and characterization, each Au-YSZ film is placed in a Macor sample holder centered in an optically transparent quartz flow cell. The quartz flow cell is placed in a tube furnace and collimated light was transmitted through the Au-YSZ film and analyzed using an Oriel Instruments (Stratford, CT) MS257 monochromator equipped with a Peltier cooled CCD. Only half of the 1 cm diameter sapphire substrate is deposited with a Au-YSZ film. This deposition coverage is achieved with the use of a shadow mask during the PVD process and allows for online background data correction using the uncoated region for collection of the background spectrum. The total gas flow was held at 2000 sccm and the gas mixture composition was controlled by a fully automated gas flow manifold equipped with MKS mass flow controllers and pneumatic valves. The Au-YSZ nanocomposite thin films used in these experiments were deposited on separate sapphire substrates and underwent individualized exposure experiments to O2 and H2 in backgrounds of N2.
Rogers and Carpenter The absorption spectra acquired are composed of two parts: (1) photon absorption by interband electrons and (2) photon absorption by the quasi-free electrons in the metal nanoparticle;28 this research relies on monitoring the latter. The forced oscillation of quasi-free electrons by absorption of electromagnetic radiation results in the LSPR, which can be approximated as a Lorentzian function for metal nanoparticles. Lorentzian functions were only fit to the LSPR band between 550 and 800 nm, which limits the influence of the high energy photon absorption by the Au interband electrons on the LSPR. The change in both the peak position and fwhm were used to characterize the sensing response of the Au-YSZ nanocomposite. Theoretical Calculations To accurately model how the LSPR peak position varies upon changes in gas exposure environment and to predict its corresponding sensitivity dependence as a function of AuNP size, the peak position dependence on the number of free electrons per nanoparticle is first explored. A solution for the peak position is derived from the Drude approximation for particles of sizes much smaller than optical wavelengths
Ω)
N0e2 (1 + 2εm + χib(Ω))ε0me
(1)
In the equation above, Ω is the LSPR peak position, N0 is the quasi free electron density for the bulk metal, e is the fundamental charge, εm is the matrix dielectric constant, χib is the dielectric contribution of the interband transitions, ε0 is the permittivity of free space, and me is the electron mass. Since this model is intended to accurately predict the AuNP LSPR peak position over a wide range of particle sizes and materials we have added the contribution of the interband transitions, calculated using tabulated values of the dielectric constants for bulk gold by Johnson and Christy,29 to the total dielectric constant. We model the expected absorption cross section, σ ) ω(εm)1/2ImR/c, where the parameter R is the polarizability of the nanoparticle and can be described as
R ) R3
ε(ω) - εm ε(ω) + 2εm
(2)
where R is the nanoparticle radius. The dielectric function, ε(ω), was calculated from the classical Drude model for spherical particles with the addition of the interband transitions, as outlined by Pinchuk et al.30
ε(ω) ) 1 -
ωp2 ω2 + iωγ
+ χib(ω)
(3)
where ωp is the plasmon frequency of bulk gold and γ is the frequency of electron collisions and is proportional to the broadening observed in the LSPR band. The first guess of χib(Ω) is calculated by peak fitting the absorption cross section equation calculated using eqs 2 and 3 in the region of the LSPR while assuming a γ value of 0.3 eV, which is an approximate value corresponding to that observed in the measured LSPR peaks. This value of γ is larger than what is expected for metal nanoparticles of a single size or of narrow size distributions (∼(2 nm), but PVD thin film deposition and grain growth via
Plasmonic-Based All-Optical Sensing Applications thermal annealing processes results in larger grain size distributions, as will be mentioned later. Additionally, phonon scattering is a contributor to LSPR broadening and is another cause of peak broadening in this study. From the standpoint of modeling the LSPR peak position using the method chosen for this study, the value of γ has no contribution to the modeled value of the LSPR peak position. The theoretical LSPR peak position is calculated and compared with experimental values, and through an iterative process χib(Ω) is determined. Once all of the terms in eq 1 can be accounted for, the theoretical change in the LSPR peak position is calculated using the change in the number of electrons per AuNP (NAuNP). The second step in this model is to determine the change in NAuNP as a function of the reaction environment, which requires the development of an electrochemical model accounting for the oxygen and hydrogen reactions. In earlier attempts to model the electrochemical exchange of electrons to and from the embedded AuNPs and the exposure gases, the contribution of the interband transitions to the expected optical absorption properties were not included. Likewise, a distinction was not made between adsorbed surface bound oxygen ions and matrix incorporated oxygen ions, even though the formation of both results in charge removal from the AuNP. The current work accounts for both interband transitions and the surface and matrix bound oxygen anion species. Decoupling the surface reactions from the matrix incorporation reactions provides two benefits, the first being that the equilibrium constants acquired for both will reflect the relative reaction energies associated with each reaction. Second, deconvolution of the two reaction types results in a separation of the static charge into surface and matrix components. This apportionment of electrostatic charge will allow the LSPR optical model to probe charge dependencies as a function of the AuNP local environment and the resultant effects on LSPR peak position and the dampening properties of the LSPR. The decoupling of these reactions makes the implicit assumption that the surface and incorporation reactions occur as independent and parallel reactions. This assumption, while it oversimplifies the reaction processes, is valid if there no limiting barrier to oxygen ion incorporation. Table 1 outlines the oxidation and reduction reactions for adsorption and incorporation of oxygen ions due to hydrogen and oxygen exposures using the Kro¨ger-Vink notation. An addition to this model is that species with a subscripted “O(s)” address the surface states available for adsorption on the surface of the nanocomposite film. It should also be noted that the quantities discussed from this point on will correspond to the average amount per AuNP and corresponding average matrix volume per AuNP. We can combine both the oxygen and hydrogen reactions in terms of two equilibrium constants, KAds and KInc, which are dependent on the filled and vacant oxygen states, partial pressures of H2O, O2, and N2, and [eAuNP′], the number of electrons per AuNP.
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KAds )
KInc )
PH2O[VO(s)×]2[eAuNP]2 PO21/2 [OO(s)]2
PH2
PH2O[VO••]2[eAuNP]4 PO21/2 [OO×]2
PH2
(4)
(5)
In the experiments outlined for this discussion, the only parameters varied were the oxygen and hydrogen concentrations, upon varying their corresponding partial pressures. The equilibrium constants and partial pressure of H2O in eqs 4 and 5 are expected to remain constant for the current model. In order to determine the charge of the AuNP, which determines the value of the peak position of the LSPR, via eq 1, an equation for [eAuNP′] in terms of the gas exposure concentration ratio PH2/ PO21/2 and a set of material constants is obtained by numerically solving eqs 4 and 5 and the following three equations:
[eAuNP′] ) [eAuNP]0 - 2[OO×] - [OO(s)]
(6)
[VO(s)×] ) [VO(s)×]0 - [OO(s)]
(7)
[VO••] ) [VO••]0 - [OO×]
(8)
In the previous equations the terms [eAuNP′]0, [VO(s)×]0, and [VO••]0 correspond to the number of electrons, available surface states, and matrix oxygen ion vacancies per AuNP, respectively, in a Au-YSZ nanocomposite which is completely uncharged by electrochemical charge exchange, i.e., at equilibrium in a completely reducing gas environment. Once solving these equations for the LSPR peak position as a function of gas exposure ratio PH2/PO21/2, we can use this model to make predictions as to how changes in the material system, in particular the nanoparticle radius, will affect the reaction environment dependence of the LSPR peak position. Displayed in Figure 1 is the log of the sensitivity, where sensitivity is defined as the slope of the LSPR peak position versus the gas exposure ratio PH2/PO21/2, or dΩ2/dPH2PO2-1/2, over a range of gas exposures and AuNP average particle radii. The model data shown in Figure 1 is for films that have 8 at. % Au, an yttria doping of 5 wt % in the YSZ matrix, KAds ) 8.0 × 105, KInc ) 2.0 × 108, PH2O ) 10-6, and [VO(s)×]0 ) 24 oxygen ion states per nm2 of film surface area for a 40 nm thick film. All of these values have been chosen due to their proximity in value to parameters that are either experimental constants or are calculated values for the Au-YSZ system using the model fit to the experimental data. As for the number of surface states available per AuNP, this value should scale with AuNP radius and so the number per surface area of nanocomposite film (assuming a planar surface) has been provided which returns values that
TABLE 1: Oxygen and Hydrogen Half Reactions for Redox Reactions Resulting in the Adsorption and Incorporation of Oxygen Ions onto and into the Au-YSZ Nanocomposite Thin Film adsorption oxygen reactions:
hydrogen reactions:
incorporation
1 OO(s) T O2(g) + VO×(s) + eAuNP′ 2 AuNP• + eAuNP′ T AuNP
1 OO× T O2(g) + VO•• + 2eAuNP′ 2 AuNP•• + 2eAuNP′ T AuNP
H2(g) + OO(s) T H2O(g) + VO× + eAuNP′
H2(g) + OO× T H2O(g) + VO•• + 2eAuNP′
AuNP•(s) + eAuNP′ T AuNP
AuNP•• + 2eAuNP′ T AuNP
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Rogers and Carpenter oxygen rich environments, as they are predicted to have nearly 3 orders of magnitude greater change in LSPR peak position as compared to particles with radii >5 nm. This increased sensitivity is not entirely unexpected as charge transfer reactions involving smaller nanoparticles will result in a greater fraction of free electrons exchanged, assuming a constant reaction cross section, as compared to larger nanoparticles. However, it is important to note that this model has for the first time allowed a prediction of the magnitude of this LSPR sensitivity enhancement with respect to the fundamental properties of the catalytically active metal nanoparticles and within this general format the model could be used for any plasmonically active nanocomposite material. Results and Discussion
Figure 1. Contour plot of the log slope of LSPR peak position squared vs gas flow ratio PH2/PO21/2 as a function of nanoparticle radius and change in the gas flow ratio PH2/PO21/2, illustrating the theoretical sensitivity of AuNP charge to changes in H2 and O2 concentration for different AuNP sizes.
closely match the experimental results discussed later. As one proposed application of these materials is within an all-optical plasmonics based sensing environment, this type of sensitivity diagram is a critical element toward the design and development of these functional nanomaterials. One can see from Figure 1 that smaller AuNPs have a greater sensitivity toward exposures of hydrogen in an oxygen containing environment. This is readily observed for nanoparticles with radii
