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Research Papers

Nanoparticle-Assisted Heating Utilizing a Low-Cost White Light Source OPEN ACCESS

[+] Author and Article Information
Robert A. Taylor

Mem. ASME
School of Mechanical
and Manufacturing Engineering,
University of New South Wales,
Sydney, NSW 2052, Australia
e-mail: Robert.Taylor@UNSW.edu.au

Jun Kai Wong, Sungchul Baek, Yasitha Hewakuruppu

School of Mechanical
and Manufacturing Engineering,
University of New South Wales,
Sydney, NSW 2052, Australia

Xuchuan Jiang, Chuyang Chen

School of Materials Science and Engineering,
University of New South Wales,
Sydney, NSW 2052, Australia

Andrey Gunawan

School for Engineering of Matter,
Transport and Energy,
Arizona State University,
Tempe, AZ 85287-6106

1Corresponding author.

Manuscript received December 13, 2013; final manuscript received May 2, 2014; published online May 30, 2014. Assoc. Editor: Yogesh Jaluria.

J. Nanotechnol. Eng. Med 4(4), 040903 (May 30, 2014) (6 pages) Paper No: NANO-13-1086; doi: 10.1115/1.4027643 History: Received December 13, 2013; Revised May 02, 2014

In this experimental study, a filtered white light is used to induce heating in water-based dispersions of 20 nm diameter gold nanospheres (GNSs)—enabling a low-cost form of plasmonic photothermal heating. The resulting temperature fields were measured using an infrared (IR) camera. The effect of incident radiative flux (ranging from 0.38 to 0.77 W·cm−2) and particle concentration (ranging from 0.25–1.0 × 1013 particles per mL) on the solution's temperature were investigated. The experimental results indicate that surface heat treatments via GNSs can be achieved through complementary tuning of GNS solutions and filtered light.

FIGURES IN THIS ARTICLE
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Hyperthermia treatment, particularly plasmonic photo-thermal therapy (PPTT), has become a promising means of cancer therapy[1]. Biocompatible nanoparticles of controlled size and shape can be used to strongly absorb visible or near-infrared light and convert it to heat through surface plasmon resonance [1,2]. This causes a temperature rise in nearby tissues, which, based on the position and loading of the nanoparticles, can potentially kill cancerous cells while sparing healthy ones [3]. Various types of gold nanoparticles (e.g., nanorods, nanoshells, and nanospheres) are generally used in PPTT because they have proven to be biocompatible [2-4] and are optically tunable through controlled size and morphology [2,5-8]. Monodisperse samples can be fabricated to possess strong visible (380–750 nm) and near-infrared (750–1400 nm) light absorption over a short wavelength band. Although several authors have proposed novel methods and models for PPTT [3,6,9,10], relatively few experimental studies have been reported to date. Deviations from these idealized models may affect experiments, due to nonuniform particle size through agglomeration, changes in optical properties, particle motion from thermophoresis, and other higher order effects. Additionally, much of the work to date has been based around expensive lasers as a heat source [1,2,11-13].

This study adds to literature with a transient experimental investigation of volumetric heating of plasmonic nanoparticles. An experiment was built to obtain quantitative measurements of temperature in water which contains 20 nm (nominal diameter) GNS dispersions. Various particle concentrations are exposed to filtered irradiation from a low cost, white light source. A simple model is also developed to describe the phenomena observed in the experiments. The model employs a volumetric heat absorption calculation combined with a lumped capacitance model to obtain results which match well with the experiments.

In the experimental setup (shown in Fig. 1) a white lamp was focused through a plano-convex lens and then filtered as some of the light transmits through a band pass filter. Intense green light was then incident on a cuvette test cell contains de-ionized water and various concentrations of GNS. During light illumination, thermal images of the solution were recorded with an IR camera, which was oriented perpendicular to the direction of light propagation (shown in Fig. 1(a)). Cuvette temperatures were then determined from the IR images using Altair software.

The position selected for temperature measurement is shown in Fig. 2. The experimental setup can be divided into four components: the light input system, the test cell, the test sample, and the temperature measuring system, which are discussed in more detail below.

The Light Input System.

The light source is a high power lamp source (Thorlabs HPLS-30 Series-04), with a visible light (400–750 nm) output of 10.2 W. The light is focused through a plano-convex lens (f = 37 mm) and then passed through a band-pass filter (center wavelength = 500 nm, full width at half max = 40 nm). Using this arrangement, a 6 mm diameter focused green light beam was achieved. The intensity of the focused light can be controlled through the range between 0 and 0.77 W·cm−2 with the built-in controller and neutral density filters. The power of the focused light was measured using an optical power meter (Thorlabs S314C) as shown in Fig. 1(b). It should be noted that if lower cost and/or longer wavelengths are desired, a 1000 W PAR64 lamp with a very narrow spot bulb could easily replace the solid-state plasma light used in this study.

The Test Cell.

A 3 mm × 10 mm × 45 mm rectangular tube cuvette made of fused silica (SiO2-IR grade) was used (see Fig. 2) to contain the nanofluid. The internal thickness of the fluid sample inside the cuvette is 1 mm. This cuvette was chosen as the test cell because it has smooth flat surfaces that allow light input and thermal images to be recorded with the IR camera. Due to the fact that these cuvettes are made from high purity quartz (designed for optical properties measurements), they are very transparent over the considered spectral region. However, the light reflection off the surface of the cuvette (at both air-glass and glass-fluid interfaces) cannot be neglected, as is discussed below.

The Test Samples.

The GNS solution (of monodisperse gold nanospheres) was prepared “in-house” based on the reduction of gold chloride with sodium citrate in an aqueous solution [4]. As such, gold chloride, HAuCl4 (0.01% by weight, solution I) and sodium citrate, Na3-citrate (1% by weight, solution II) were mixed in various ratios to control the size of GNSs. Solution I was heated to boiling and then 0.5 mL of solution II was added. After a few minutes, the solution turned faintly blue (indicating nucleation of small particles). Later, the solution changed to a red color (indicating the formation of monodispersed spherical particles) at which point the reduction of gold chloride is complete [4]. Although these single-step GNSs are relatively stable, the samples were sonicated prior to testing to ensure the particles were evenly distributed throughout the base fluid (de-ionized water). Particle agglomeration must be minimized to ensure the light is absorbed volumetrically throughout the solutions. Four different concentrations were used in this study—0 C, 0.25 C, 0.5 C, and 1.0 C, where C was measured as 1 × 1013 particles per mL using a Nanosight LM14. The 0 C sample is pure, de-ionized water and the 0.25 C and 0.5 C concentrations were prepared by dilution of the 1.0 C sample with pure de-ionized water. As seen in Fig. 3(a), the GNS solution has a changing opacity as a function of particle concentration. In several months since testing, these nanofluids are still observationally well dispersed. Figures 3(b) and 3(c) show that although the Transmission Electron Microscopy (TEM) image gives a monodistribution of particle sizes, there is some size variation of the GNS when tested in the nanosight after the samples were aged.

The Temperature Measurement System.

Two methods of temperature measurement were used in testing the fluids: thermocouples (P1, placed as shown in Fig. 2), and an IR camera. Thermocouple measurements (using a T-type Delta OHM HD2128.2) are limited, since the metallic probes of the thermocouples can be heated by the light source. In other words, the probe must be placed outside the irradiated zone to avoid direct heating. Therefore, the nonirradiated thermocouple is used solely for calibration and to ensure accuracy of the primary IR camera-based temperature measurement. In this work, a Cedip Titanium 560 M IR camera was used. This camera supports 640 × 512 pixel images at a 100 Hz frame rate. The pixels are square with dimensions of 24 μm × 24 μm. The CCD chip in the camera is sensitive to wavelengths between 3.6 and 5.1 μm, and thus does not “see” the filtered light input. With the calibration file used, the temperature range is narrowed so that the IR camera accurately measures in the range expected for the experiment, namely 0–60 °C. This ensures that the temperature measured by the IR camera is reliable and accurate, but the error is approximated at ±0.25 °C. It should also be noted that the temperature observed by the IR camera is only the first 100 μm of the fluid's depth (from the cuvette's wall) because the average absorption coefficient for water between 3.6 and 5.1 μm is 288 cm−1. Thus, more than 95% of IR emission signal in this spectral range is absorbed in a 100 μm thickness of water [8,14].

The lumped capacitance method is a simple technique used to calculate the transient temperature of an object with the assumption that it has a spatially uniform temperature [15]. Figure 4 below shows the energy transfer for the cuvette samples. Qin is the energy supplied to this system by absorbing the filtered light source and Qout is the energy that leaves the system through convection losses to the surroundings. Note that radiative losses are neglected due to the small temperature difference between the cuvette and the ambient. The lumped energy balance (neglecting radiation and conductive losses) for the sample can thus be written as follows [15]:

Here, h is the convective heat loss coefficient and As is the surface area of the object. The temperature, T, is for that of the lumped object, Ta is the ambient temperature, and t is the time. Cp and m are the specific heat capacity and mass of the system, respectively. Integrating Eq. (1) over time gives the following relationship for θ = (T − Ta).Display Formula

(2)θ=QinhAs-(QinhAs-θi)exp(-hAstmCp)

where θi = (Ti − Ta) and Ti is the initial temperature of the object. The values of the parameters required for this calculation are given in Table 1.

The object heated in this case consists of both quartz glass and the nanofluid. Due to the fact that we are lumping these together in our analysis, the heat capacity of the composite object (mCp) can be calculated by simply adding the heat capacities of each material as shown belowDisplay Formula

(3)mCp=mfluidCp,fluid+mglassCp,glass

It is also important to check the validity of using the lumped capacitance method by checking that the Biot's (Bi) number is less than 0.1 [15]Display Formula

(4)Bi=hLck0.1

Lc is the characteristic length of the cuvette (1.16 mm) obtained by dividing the test volume of the object by its surface area (As). Using natural convection correlations for air rising on an isothermal vertical plate [16], we can find one estimate for the heat transfer coefficient, h, to be 4.4–5.4 W m−2 K−1. This gives a Biot number less than 0.01. Another, more reasonable, estimate is to assume forced convection from air flow of 0.5 m/s due to air conditioning vents in the testing area, which gives a convective heat transfer coefficient, h, of 20 W m−2 K−1. Using the lesser of the material thermal conductivities, e.g., k = 0.58 W m−1 K−1 for water, the maximum value for the Biot number was found to be 0.04. Important note: Since we did not actually measure the heat transfer coefficient, h, it is possible that during some of the testing conditions we have Biot numbers on the order of 0.1. Thus, the lumped capacitance approach is assumed to provide only a rough estimate.

The final parameter required to proceed with the transient temperature calculations is Qin. The extent to which volumetric absorption of incoming radiation by the test sample occurs determines heat input, Qin. As the dimension of the irradiated area is several times larger than the thickness of the fluid, the 1D radiative transfer equation (RTE) can be used to calculate the volumetric power absorption. The 1D RTE with irradiated and shaded boundaries is given by the following [10]:Display Formula

(5)μIλ(z,μ)z+βIλ(z,μ)=σλtr2-11Iλ(z,μ)dμ
Display Formula
(6)Iλ(0,μ)=Rλ,1Iλ(0,-μ)+(1-Rλ,1,c)Ieλ,δ(1-μ)
Display Formula
(7)Iλ(z¯,-μ)=Rλ,2Iλ(z¯,μ)

Here, Iλ is the spectral radiation intensity and μ is the cosine of the angle between the direction of radiation intensity and y-axis. βλ and σtrλ are, respectively, the spectral optical extinction and transport scattering coefficients of the medium at the considered spatial coordinate. z is the axis along the fluid depth. Here, Ieλ is the incident spectral solar radiation intensity, and δ is the Dirac delta-function. Rλ,1,c is the spectral reflection coefficient of the incident collimated radiation at the irradiated surface. z¯ is the total depth of the fluid-layer. Rλ,1 and Rλ,2 are, respectively, the effective spectral reflection coefficients (reflection of diffuse radiation) at the irradiated (z=0) and back (z=τλ¯) surfaces. Note that all multiple-reflections at the fluid-air and fluid-glass boundaries were considered and calculated according to the method given in Ref. [17].

The 1D RTE was used to calculate the heat absorbed in a tumor by Dombrovsky et al. [10] with additional tools such as the transport and modified two flux approximations. The same procedure is adapted here for the current problem. In the present case, a major difference is that the mean wavelength of the filtered light (520 nm) and the full width half max (40 nm) were used to calculate the spectral intensity of source. The energy absorption at each different wavelength is calculated separately and integrated over the wavelength range of the filtered light to calculate the energy absorbed from the whole spectrum. Following this, the volumetric power at each spatial point can be integrated over the irradiated volume to calculate the total power supplied to the system (Qin). The Mie theory code by Dombrovsky [18] is used in the current work to calculate the spectral optical properties of the gold nanospheres. The reader is referred to Ref. [6] for more details on calculating the optical spectral optical properties of a nanofluid using Mie theory and [10] for the full RTE solution to calculate spectral volumetric power absorption.

Absorption Spectra.

Figure 5 shows the absorption/scattering spectra of a low concentration GNS sample, measured with a Perkin Elmer Lambda 1050 spectrophotometer equipped with a 150 mm integrating sphere. It can be seen in Fig. 5 that the gold nanoparticles have a very large absorption to scattering ratio in the resonant (500–540 nm) wavelength range. This suggests the GNSs can absorb and convert most of the filtered light into heat. Note that the basefluid, water, absorbs very little for these short wavelengths [19].

GNS Heating Studies.

The first test was carried out to investigate the effect of GNSs on the heating of the samples. This was conducted by measuring the difference between the temperature rise of de-ionized water and GNS solution (concentration = 1.0 C) at the maximum 0.77 W·cm−2 irradiation. Figure 6 shows the resulting thermal images of this study using the IR camera.

It is evident that there is a significant temperature rise in the GNS solution compared to de-ionized water. The maximum temperature rise occurs at the region where light hits the test samples (refer to Fig. 2). This measurement also clearly shows that the lumped capacitance approach is only applicable as a curve fitting estimation to capture the transient temperature rise.

Figure 2 indicates that the GNSs are the dominant heat absorbing agents in the samples (as expected) and that this allows for selective heating in which only regions which contain nanoparticles will be heated in a hyperthermia treatment. Additionally, the extent of the heating can potentially be controlled through either the incident light intensity or the particle concentration.

Comparison Between Experiment and Model.

Experiments were also conducted for 25 min of continuous heating so that they can be compared with the heat transfer model's predictions. Figure 7 shows the comparison between the experimental results and predictions from lumped capacitance method for the 0.1 C GNS solutions exposed to different incident radiative fluxes.

The model predictions match reasonably well with experimental results. At lower heating rates the model under-predicts the measurements by up to ∼0.5 °C, but over-predicts at the higher irradiance by ∼0.5 °C. Both the initial heating profile and the steady state temperature of the experimental are within these margins. It should be noted that thermal stratification of the samples (seen in Fig. 6) is likely the cause of the mismatch. The lumped capacitance approach does not take this into account and represents an average temperature for the sample.

Figure 8 shows the comparison between the experimental results and model's predictions for testing fluids with different GNS concentrations exposed to light with an incident radiative flux of 0.6 W·cm−2. The theoretical predictions, in this case, are again within approximately 1 °C of the measured temperature.

The experimental data suggests that the achievable temperature rise is proportional to the concentration of GNSs. These tests also show that heating times of approximately 600 s are sufficient to approach the steady state temperature. This indicates that while our 10.2 W white light is capable of achieving a sizable temperature rise, a 1000 W lamp could achieve the same order of heating in ∼6 s (depending on heat losses).

Effect of GNS Concentration and Radiative Flux.

The maximum experimental temperature rise (steady state) of the samples was chosen as a key parameter to investigate the effect of changing GNS concentration and radiative flux. This essentially represents the light-induced heating potential of these combinations. For comparison on this basis, two graphs are plotted: a graph of maximum temperature rise against incident radiative flux (Fig. 9), and a graph of the maximum temperature rise as a function of the concentration of GNSs (Fig. 10).

Figure 9 shows the maximum temperature rise increases almost linearly with radiative flux for all GNS solution concentrations. Similarly, this linear relationship was observed in Fig. 10 when the concentration of GNSs increases. This implies that both concentration and incident radiative flux of light are important parameters in determining the temperature rise of GNS solution. Note that the maximum temperature rise of the testing fluids at different GNS concentrations varies significantly as radiative flux increases (see Fig. 9). Deviations might be due to localized agglomeration of GNSs at high levels of radiative flux which can reduce the total light-to-heat conversion [20], resulting in a lower maximum temperature achieved in higher concentration GNS solutions.

This study shows, through experimental investigations of the temperature rise of GNS solution using filtered white light illumination, that a significant temperature rise can be achieved with relatively inexpensive set-up. This represents a significantly different approach to most of the literature which was focused on expensive laser sources. This study adds to the limited body of experimental results using “in-house” prepared nanofluid samples. It compares the measurements to a simple lumped theoretical model, which is provides reasonable agreement. A key finding of this study is the extent to which both the concentration of GNSs and the radiative flux of incident light increase the resulting temperature of the test fluid. By controlling both parameters, the optimum effective temperature range (40–44 °C [12,15]) can be achieved with low-cost light sources for hyperthermia treatments using GNSs. It should be noted that the GNSs used in this experiment are only applicable to the surface treatments (e.g., skin cancer) since they absorb outside the so-called therapeutic window. However, the low-cost experimental set-up described herein is suitable for use with other spectral ranges using other nanoparticle types (nanoshells, nanorods, etc.) and light sources.

The authors gratefully acknowledge the support of the University of New South Wales ‘Taste of Research’ Summer Scholarship Program.

 

 Nomenclature
  • As =

    surface area (m2)

  • C =

    concentration of GNSs, (particle per mL)

  • Cp =

    heat capacity (J kg−1 K−1)

  • CW =

    central wavelength (nm)

  • f =

    focal length (mm)

  • FWHM =

    full width half max (nm)

  • h =

    convective heat loss coefficient (W m−2 K−1)

  • I =

    radiative intensity (W cm−2)

  • Ie =

    incident radiative flux (W cm−2)

  • k =

    thermal conductivity (W m−1 K−1)

  • Lc =

    characteristic length (m)

  • m =

    mass (kg)

  • Q =

    power

  • R =

    reflectance

  • t =

    time (min)

  • T =

    temperature (K)

  • z =

    coordinate along the fluid depth

 
 Subscripts and Superscripts
  • c =

    for collimated radiation

  • fluid =

    value of nanofluid

  • glass =

    value of glass cuvette

  • i =

    initial value

  • in =

    input

  • out =

    output

  • st =

    stored

  • tr =

    transport

  • 1 =

    at irradiated surface of nanofluid

  • 2 =

    at shadow surface of nanofluid

  • λ =

    spectral

 
 Greek Symbols
  • β =

    extinction coefficient (1/m)

  • Δ =

    change

  • δ =

    small change

  • θ =

    temperature difference (K)

  • μ =

    cosine of angle

  • σ =

    transport scattering coefficient

Terentyuk, G. S., Maslyakova, G. N., Suleymanova, L. V., Khlebtsov, N. G., Khlebtsov, B. N., Akchurin, G. G., Maksimova, I. L., and Tuchin, V. V., 2009, “Laser-Induced Tissue Hyperthermia Mediated by Gold Nanoparticles: Toward Cancer Phototherapy,” J. Biomed. Opt., 14(2), p. 021016. [CrossRef] [PubMed]
Choi, W. I., Sahu, A., Kim, Y. H., and Tae, G., 2012, “Photothermal Cancer Therapy and Imaging Based on Gold Nanorods,” Ann. Biomed. Eng., 40(2), pp. 534–546. [CrossRef] [PubMed]
Soni, S., Tyagi, H., Taylor, R. A., and Kumar, A., 2013, “Role of Optical Coefficients and Healthy Tissue-Sparing Characteristics in Gold Nanorod-Assisted Thermal Therapy,” Int. J. Hyperthermia, 29(1), pp. 87–97. [CrossRef] [PubMed]
Frens, G., 1973, “Controlled Nucleation for the Reuglation of the Particle Size in Monodisperse Gold Suspensions,” Nat. Phys. Sci., 241, pp. 20–22. [CrossRef]
An, W., Zhu, Q., Zhu, T., and Gao, N., 2013, “Radiative Properties of Gold Nanorod Solutions and Its Temperature Distribution Under Laser Irradiation: Experimental Investigation,” Exp. Therm. Fluid Sci., 44, pp. 409–418. [CrossRef]
Hewakuruppu, Y. L., Dombrovsky, L. A., Chen, C., Timchenko, V., Jiang, X., Baek, S., and Taylor, R. A., 2013, “Plasmonic “Pump—Probe” Method to Study Semi-Transparent Nanofluids,” Appl. Opt., 52(24), pp. 6041–6050. [CrossRef] [PubMed]
Taylor, R. A., Otanicar, T. P., Hewakerrppu, Y., Bremond, F., Rosengarten, G., Hawkes, E., Jiang, X., and Coulombe, S., 2013, “Feasibility of Nanofluid-Based Optical Filters,” Appl. Opt., 52(7), pp. 1413–1422. [CrossRef] [PubMed]
Taylor, R. A., Phelan, P. E., Adrian, R. J., Gunawan, A., and Otanicar, T. P., 2012, “Characterization of Light-Induced, Volumetric Steam Generation in Nanofluids,” Int. J. Therm. Sci., 56, pp. 1–11. [CrossRef]
Dombrovsky, L. A., Timchenko, V., and Jackson, M., 2012, “Indirect Heating Strategy for Laser Induced Hyperthermia: An Advanced Thermal Model,” Int. J. Heat Mass Transfer, 55, pp. 4688–4700. [CrossRef]
Dombrovsky, L. A., Timchenko, V., Jackson, M., and Yeoh, G. H., 2011, “A Combined Transient Thermal Model for Laser Hyperthermia of Tumors With Embedded Gold Nanoshells,” Int. J. Heat Mass Transfer, 54(25–26), pp. 5459–5469. [CrossRef]
Huang, X., Jain, P. K., El-Sayed, I. H., and El-Sayed, M. A., 2006, “Determination of the Minimum Temperature Required for Selective Photothermal Destruction of Cancer Cells With the Use of Immunotargeted Gold Nanoparticle,” Photochem. Photobiol., 82(2), pp. 412–417. [CrossRef] [PubMed]
Pattani, V. P., and Tunnell, J. W., 2012, “Nanoparticle-Mediated Photothermal Therapy: A Comparative Study of Heating for Different Particle Types,” Lasers Surg. Med., 44(8), pp. 675–684. [CrossRef] [PubMed]
Taylor, R. A., Coulombe, S., Otanicar, T. P., Phelan, P. E., Gunawan, A., Lv, W., Rosengarten, G., Prasher, R. S., and Tyagi, H., 2013, “Small Particles, Big Impacts: A Review of the Diverse Applications of Nanofluids,” J. Appl. Phys., 113, p. 011301. [CrossRef]
Taylor, R. A., Phelan, P. E., Otanicar, T., Adrian, R. J., and Prasher, R. S., 2009, “Vapor Generation in a Nanoparticle Liquid Suspension Using a Focused, Continuous Laser Beam,” Appl. Phys. Lett., 95(16), p. 161907. [CrossRef]
Bergman, T. L., Lavine, A. S., Incropera, F. P., and DeWitt, D. P., 2011, Fundamentals of Heat and Mass Transfer, Wiley, Hoboken, NJ.
Churchill, S. W., and Chu, H. H. S., 1975, “Correlating Equations for Laminar and Turbulent Free Convection From a Vertical Plate,” Int. J. Heat Mass Transfer, 18(11), pp. 1323–1329. [CrossRef]
Ganesan, K., Dombrovsky, L. A., Oh, T.-S., and Lipiński, W., 2013, “Determination of Optical Constants of Ceria By Combined Analytical and Experimental Approaches,” JOM, 65(12), pp. 1694–1701. [CrossRef]
Dombrovsky, L. A., and Baillis, D., 2010, Thermal Radiation in Disperse Systems: An Engineering Approach, Begell House, New York.
Taylor, R. A., Phelan, P. E., Otanicar, T. P., Adrian, R., and Prasher, R., 2011, “Nanofluid Optical Property Characterization: Towards Efficient Direct Absorption Solar Collectors,” Nanoscale Res. Lett., 6:225. [CrossRef]
Huang, H.-C., Rege, K., and Heys, J. J., 2010, “Spatiotemporal Temperature Distribution and Cancer Cell Death in Response to Extracellular Hyperthermia Induced by Gold Nanorods,” ACS Nano, 4(5), pp. 2892–2900. [CrossRef] [PubMed]
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References

Terentyuk, G. S., Maslyakova, G. N., Suleymanova, L. V., Khlebtsov, N. G., Khlebtsov, B. N., Akchurin, G. G., Maksimova, I. L., and Tuchin, V. V., 2009, “Laser-Induced Tissue Hyperthermia Mediated by Gold Nanoparticles: Toward Cancer Phototherapy,” J. Biomed. Opt., 14(2), p. 021016. [CrossRef] [PubMed]
Choi, W. I., Sahu, A., Kim, Y. H., and Tae, G., 2012, “Photothermal Cancer Therapy and Imaging Based on Gold Nanorods,” Ann. Biomed. Eng., 40(2), pp. 534–546. [CrossRef] [PubMed]
Soni, S., Tyagi, H., Taylor, R. A., and Kumar, A., 2013, “Role of Optical Coefficients and Healthy Tissue-Sparing Characteristics in Gold Nanorod-Assisted Thermal Therapy,” Int. J. Hyperthermia, 29(1), pp. 87–97. [CrossRef] [PubMed]
Frens, G., 1973, “Controlled Nucleation for the Reuglation of the Particle Size in Monodisperse Gold Suspensions,” Nat. Phys. Sci., 241, pp. 20–22. [CrossRef]
An, W., Zhu, Q., Zhu, T., and Gao, N., 2013, “Radiative Properties of Gold Nanorod Solutions and Its Temperature Distribution Under Laser Irradiation: Experimental Investigation,” Exp. Therm. Fluid Sci., 44, pp. 409–418. [CrossRef]
Hewakuruppu, Y. L., Dombrovsky, L. A., Chen, C., Timchenko, V., Jiang, X., Baek, S., and Taylor, R. A., 2013, “Plasmonic “Pump—Probe” Method to Study Semi-Transparent Nanofluids,” Appl. Opt., 52(24), pp. 6041–6050. [CrossRef] [PubMed]
Taylor, R. A., Otanicar, T. P., Hewakerrppu, Y., Bremond, F., Rosengarten, G., Hawkes, E., Jiang, X., and Coulombe, S., 2013, “Feasibility of Nanofluid-Based Optical Filters,” Appl. Opt., 52(7), pp. 1413–1422. [CrossRef] [PubMed]
Taylor, R. A., Phelan, P. E., Adrian, R. J., Gunawan, A., and Otanicar, T. P., 2012, “Characterization of Light-Induced, Volumetric Steam Generation in Nanofluids,” Int. J. Therm. Sci., 56, pp. 1–11. [CrossRef]
Dombrovsky, L. A., Timchenko, V., and Jackson, M., 2012, “Indirect Heating Strategy for Laser Induced Hyperthermia: An Advanced Thermal Model,” Int. J. Heat Mass Transfer, 55, pp. 4688–4700. [CrossRef]
Dombrovsky, L. A., Timchenko, V., Jackson, M., and Yeoh, G. H., 2011, “A Combined Transient Thermal Model for Laser Hyperthermia of Tumors With Embedded Gold Nanoshells,” Int. J. Heat Mass Transfer, 54(25–26), pp. 5459–5469. [CrossRef]
Huang, X., Jain, P. K., El-Sayed, I. H., and El-Sayed, M. A., 2006, “Determination of the Minimum Temperature Required for Selective Photothermal Destruction of Cancer Cells With the Use of Immunotargeted Gold Nanoparticle,” Photochem. Photobiol., 82(2), pp. 412–417. [CrossRef] [PubMed]
Pattani, V. P., and Tunnell, J. W., 2012, “Nanoparticle-Mediated Photothermal Therapy: A Comparative Study of Heating for Different Particle Types,” Lasers Surg. Med., 44(8), pp. 675–684. [CrossRef] [PubMed]
Taylor, R. A., Coulombe, S., Otanicar, T. P., Phelan, P. E., Gunawan, A., Lv, W., Rosengarten, G., Prasher, R. S., and Tyagi, H., 2013, “Small Particles, Big Impacts: A Review of the Diverse Applications of Nanofluids,” J. Appl. Phys., 113, p. 011301. [CrossRef]
Taylor, R. A., Phelan, P. E., Otanicar, T., Adrian, R. J., and Prasher, R. S., 2009, “Vapor Generation in a Nanoparticle Liquid Suspension Using a Focused, Continuous Laser Beam,” Appl. Phys. Lett., 95(16), p. 161907. [CrossRef]
Bergman, T. L., Lavine, A. S., Incropera, F. P., and DeWitt, D. P., 2011, Fundamentals of Heat and Mass Transfer, Wiley, Hoboken, NJ.
Churchill, S. W., and Chu, H. H. S., 1975, “Correlating Equations for Laminar and Turbulent Free Convection From a Vertical Plate,” Int. J. Heat Mass Transfer, 18(11), pp. 1323–1329. [CrossRef]
Ganesan, K., Dombrovsky, L. A., Oh, T.-S., and Lipiński, W., 2013, “Determination of Optical Constants of Ceria By Combined Analytical and Experimental Approaches,” JOM, 65(12), pp. 1694–1701. [CrossRef]
Dombrovsky, L. A., and Baillis, D., 2010, Thermal Radiation in Disperse Systems: An Engineering Approach, Begell House, New York.
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Huang, H.-C., Rege, K., and Heys, J. J., 2010, “Spatiotemporal Temperature Distribution and Cancer Cell Death in Response to Extracellular Hyperthermia Induced by Gold Nanorods,” ACS Nano, 4(5), pp. 2892–2900. [CrossRef] [PubMed]

Figures

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Fig. 1

Experimental setup of: (1) PC for thermal imaging, (2) IR camera, (3) thermometer thermocouple, (4) lamp source, (5) plano-convex lens, (6) band-pass filter, (7) cuvette with testing fluids, and (8) optical power meter

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Fig. 2

Schematic of rectangular cuvette test configuration, P1 = thermocouple, h1 = 3.5 mm

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Fig. 3

GNSs used in the experiments—(a) photograph, (b) nanosight size distribution, and (c) TEM image

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Fig. 4

Schematic of the cuvette with nanofluids showing energy transfer

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Fig. 5

Absorption and scattering spectra of 20 nm GNSs

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Fig. 6

Thermal images of de-ionized water and 1.0 C GNS solution at 5, 10, 15, 20, and 25 min using 0.77 W cm−2 light irradiation

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Fig. 7

Temperature rise of a 1.0 °C GNS solution exposed to 0.38, 0.6, and 0.77 W cm−2 irradiation, as measured by the IR camera (markers), and predictions from the heat transfer model (lines)

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Fig. 8

Temperature rise of 1.0 °C, 0.5 °C, 0.25 °C, and de-ionized water exposed to an incident radiative flux of 0.6 W cm−2 measured by IR camera (markers), and predictions from heat transfer models (lines)

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Fig. 9

Maximum temperature rise—GNS solution concentration versus incident radiative flux

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Fig. 10

Maximum temperature rise at different light irradiation versus concentration of GNS solution

Tables

Table Grahic Jump Location
Table 1 Parameters required for lumped capacitance calculations

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