Optimized gold nanoshell ensembles for biomedical applications
© Sikdar et al.; licensee Springer. 2013
Received: 4 March 2013
Accepted: 16 March 2013
Published: 28 March 2013
We theoretically study the properties of the optimal size distribution in the ensemble of hollow gold nanoshells (HGNs) that exhibits the best performance at in vivo biomedical applications. For the first time, to the best of our knowledge, we analyze the dependence of the optimal geometric means of the nanoshells’ thicknesses and core radii on the excitation wavelength and the type of human tissue, while assuming lognormal fit to the size distribution in a real HGN ensemble. Regardless of the tissue type, short-wavelength, near-infrared lasers are found to be the most effective in both absorption- and scattering-based applications. We derive approximate analytical expressions enabling one to readily estimate the parameters of optimal distribution for which an HGN ensemble exhibits the maximum efficiency of absorption or scattering inside a human tissue irradiated by a near-infrared laser.
KeywordsHollow gold nanoshells Lognormal distribution Absorption Scattering Biomedical applications
The biocompatibility of gold nanoparticles, along with their tunable plasmon resonances and the ability to accumulate at targeted cancer sites, has proven them to be very effective agents for absorption-based photothermal therapy and scattering-based imaging applications [1–8]. Amongst the commonly used gold nanoparticles, silica-core gold nanoshells exhibit larger photothermal efficiency as compared to gold nanorods of equal number densities , whereas hollow gold nanoshells (HGNs) absorb light stronger than the silica-core gold nanoshells do [9, 10]. Furthermore, HGNs are comparatively less harmful to healthy tissues neighboring a cancer site , which makes them prospective for both photothermal and imaging applications. Although different tissue types and excitation wavelengths were analyzed before to determine the optimal dimensions of a nanoshell [10, 11], no optimization has ever been performed for a nanoshell ensemble with a real size distribution. In this Letter, we fill this gap by conducting the first theoretical study of the distribution parameters of the lognormally dispersed HGNs exhibiting peak absorption or scattering efficiency. In particular, we comprehensively analyze the dependence of these parameters on the excitation wavelength and optical properties of the tissue, giving clear design guidelines.
where x=r or h is the radius or thickness of the nanoshell, μ X = ln(Med[X]) and σ X are the mean and standard deviation of lnX, respectively, and Med[X] is the geometric mean of the random variable x=r or H.
where Q α (r,h) is expressed through Mie coefficients for a coated sphere [9, 22, 23], which are the functions of the excitation wavelength, refractive index of the tissue, and permittivities of the nanoshell constituents.
It is seen that the average absorption and scattering efficiencies of a nanoshell ensemble, excited at a fixed wavelength, are functions of the four parameters: Med[R], Med[H], σ R , and σ H . This poses the problem of finding, and studying the properties of, the optimal distribution parameters for which the nanoshell ensemble exhibits the maximum absorption or scattering efficiency.
Results and discussions
The effects of the excitation wavelength on the optimal distributions of the core radius and shell thickness are shown in Figures 1(c)– 1(f). Equal σ R and σ H (σ R =σ H =σ) correspond to the situation of similar (scalable) shapes of the two distributions. It is seen that the increase in the excitation wavelength shifts the optimal distribution f(r;μ R ,σ) towards larger radii for both absorption [Figure 1(c)] and scattering [Figure 1(e)]. This trend is opposite to the behavior of the optimal distributions f(h;μ H ,σ) in Figures 1(d) and 1(f), which shifts towards thinner shells with λ. Since the increase in Med[R] is larger than the reduction in Med[H], the optimal excitation of ensembles with larger HGNs require lower-frequency sources.
The parameters of the optimal lognormal distribution also vary with the type of human tissue. Figures 3(d)–3(f) show such variation for the entire span of refractive indices of human cancerous tissue [9, 19], λ=850 nm, and three typical shapes of the distribution. It is seen that the peak efficiencies of absorption and scattering by an HGN ensemble grow with n regardless of the shape parameter σ. The corresponding geometric mean of the core radii reduces with n and may be approximated as Med[R]≈n(−51σ2+87σ−65)+72σ2−136σ+147 for absorption, and as Med[R]≈n(−94σ2+142σ−87)+114σ2−179σ+178 for scattering. In contrast, the optimal geometric mean of the shell thicknesses is almost independent of n and approximated by the polynomial Med[H]≈2σ2−3σ+10 in the case of absorption, and as Med[H]≈26σ2−41σ+40 in the case of scattering. These expressions allow estimation (with an accuracy of about ±1 nm) of the optimal distribution parameters of an HGN ensemble excited at λ=850 nm for 0.1≤σ≤1 and 1.35≤n≤1.7. Numerical calculations show that the optimal dependencies Med[R](n) and Med[H](n) have almost constant slopes for 650 nm≤λ≤1000 nm. This feature allows one to use Figure 3 to roughly estimate the optimal lognormal distributions of HGNs to be delivered to any human tissue illuminated by a near-infrared laser.
In summary, we have studied the optimal distributions of lognormally dispersed hollow gold nanoshells for different excitation wavelengths and human tissues. Shorter-wavelength, near-infrared sources were found to be most effective for in vivo biomedical applications. The analytical expressions obtained may be used to estimate the optimal distribution of the nanoshells providing the maximum efficiency of their absorption or scattering of near-infrared radiation inside human tissue.
Hollow Gold Nanoshell
- Med[ X ] Median of the random variable X:
The work of D. Sikdar is supported by the Department of Business and Innovation of the Victorian Government, through its Victoria India Doctoral Scholarship Program (managed by the Australia India Institute). The work of I. D. Rukhlenko and M. Premaratne is supported by the Australian Research Council, through its Discovery Early Career Researcher Award DE120100055 and Discovery Grant scheme under Grant DP110100713, respectively. The work of W. Cheng is supported the Australian Research Council, through its Discovery Grant scheme under Grant DP120100170.
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