Abstract

Nonlinear optical interactions are of fundamental significance for advanced photonic applications, but usually the nonlinearity magnitude is insufficient. Here we review recent progresses to boost the optical nonlinearity of metal or semiconductor nanostructures via the combination of Mie resonance and coupled photothermal/thermo-optical effects. In plasmonic and silicon nanoparticles, the effective photothermal nonlinear index n2 is enhanced by 103 and 105 times over that of bulk, respectively. The large nonlinearities enable applications of not only all-optical switch, but also super-resolution imaging based on suppression of scattering, saturation (sub-linearity) and reverse saturation (super-linearity).

© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. Introduction

Nonlinear optical effect is essential in various photonic applications such as optical switching, wavelength conversion, and ultrashort pulse generation [14]. In the field of optical microscopy, several super-resolution techniques are developed by exploiting the nonlinear light-material interaction between illumination light and contrast probes [57]. However, because the nonlinear optical effect is intrinsically weak, high laser powers are typically required for the excitation, resulting in potential sample damage. Therefore, it is highly desirable to improve the efficiency of nonlinear optical effects.

Plasmonic effect is one well-known approach to significantly enhance optical nonlinearities [1,8,9]. Through surface plasmon resonance (SPR), the collective oscillation of conductive electrons on the metal structure couples with the excitation light and produces a strong local electric field, leading to immensely enhanced nonlinearity, as demonstrated by second harmonic generation [10,11] and four-wave mixing [12].

Another approach to induce strong nonlinear optical effect is through non-instantaneous light-matter interactions, including intraband transition, interband transition, hot electrons, and hot lattice [13,14]. Pump-probe spectroscopy has been extensively applied to investigate these ultrafast interactions in metallic nanostructures, such as single layer films [15,16], bilayer films [17], nanospheres [18] and nanorods [19]. These studies focus on nonlinear optical responses on the picosecond time scale, where carrier generation and relaxation dynamics dominate. By measuring the absorption cross-section of these materials in spatial modulation spectroscopy, the density of excited carriers can be precisely calculated, and the nonlinearity of the optical response is quantified [17,20]. On the other hand, there are nonlinear nanophotonics studies using nanosecond pulses [21], where the hot lattice shall play a major role. In this review, we mainly address hot lattice induced nonlinear responses excited via continuous-wave lasers.

Typically, non-instantaneous nonlinearity is characterized by the variation of refractive index n = n0+n2I, where n0 is the linear refractive index, I is the intensity of incident light and n2 is the nonlinear refractive index coefficient. The nonlinear index n2 of bulk gold ranges from 10−7 µm2/mW (intraband) to 10−3 µm2/mW (hot lattice) [13]. Although the hot lattice nonlinearity, i.e., photothermal nonlinearity, is much larger than the instantaneous Kerr nonlinearity (effective n2 ∼ 10−7 µm2/mW), the meaning of 10−3 µm2/mW is that to achieve index modulation of 50%, i.e., n0 = n2I, the excitation intensity needs to be on the order of 103 mW/µm2. Therefore, considerable efforts to enhance the nonlinear optical effect have been demonstrated, e.g., the uses of waveguide structures to accumulate nonlinear response along with beam propagation [1]. In the past few years, we have shown that by combining plasmonic field enhancement with photothermal/thermo-optical interactions, the nonlinear optical response of a metallic nanostructure can reach n2 of ∼1 µm2/mW, which is three orders of magnitude higher than that of bulk, and allows operation with a low-power continuous-wave laser in a single nanoparticle. Note that n2 is not an inherent parameter of the material because the value of n2 may change depending on the measurement system and material structures. The reason we adopt n2 here is to provide a convenient magnitude comparison of nonlinear responses between bulk and nanostructures.

Before we dive into the nonlinearity review, the readers should be aware that the photothermal effect does not necessarily induce nonlinear optical responses. It is well known that “linear” photothermal effect of metallic nanoparticles has been utilized for high sensitivity optical imaging [22], biological treatment, and various other applications [23]. One particular emphasis is photothermal microscopies, including thermal lens imaging [24], photothermal interference contrast imaging [25], and photothermal heterodyne imaging [2628], construct the image contrast by detecting the photothermally induced refractive index variation of the medium surrounding the nanoparticle. Photothermal microscopy techniques are capable of detecting a single nanoparticle with size as small as 5 nm [29], and study molecular dynamics such as the membrane proteins with unprecedented precision and speed by using small nanoparticles as imaging probes [3032].

Another important application field of the linear photothermal effect is optical thermometry with metallic nanoparticles. For example, the measurement of anti-Stokes emission spectrum from a metallic nanoparticle helps to determine its absolute temperature in a direct way [3336]. Other methods take more indirect approaches of either detecting the thermal lens effect surrounding the hot nanoparticle [3739], or observing the thermally induced fluorescence property variation, such as depolarization, from fluorescence molecules around the nanoparticle. [4042].

In the following, we review recent advances in characterizing photothermal “nonlinearity” of plasmonic nanostructures, including different materials (gold, silver) and geometries (sphere, rod, shell, bowtie). The nonlinearity is identified through the power dependences of scattering on excitation intensities. Typically, the nonlinear power dependences are acquired either by increasing laser irradiation gradually or by retrieving from the signal distribution of the nanoparticle image. The latter method is denoted as “x-scan”, i.e., laser scanning microscopy, which is useful to quantify nonlinear scattering and absorption [43,44]. Similar to z-scan [45], a focused Gaussian beam is required, but different from z-scan, the focused beam scans laterally across a single nanoparticle, which is much smaller than the focal spot. When there is no nonlinear response, a scanning image with Gaussian distribution is expected (in z-scan, it is constant transmission). When nonlinearity takes place, the image intensity distribution profile deviates from the Gaussian profile, and the deviation directly facilitates the nonlinear coefficient characterization.

In Section 2, we present the mechanism of the photothermal/thermo-optical nonlinearity of plasmonic particles. In Section 2.1 and 2.2, two application examples will be given. The first one is high-efficiency all-optical switching, which is a long-standing goal in the field of nonlinear optics. The second one is super-resolution microscopy, which is much less considered in typical nonlinear optics literature, and we hope to stimulate more interesting applications from our efforts. In addition to plasmonics, in Section 3, we introduce our recent discovery of giant photothermal nonlinearity in silicon nanostructures, featuring five orders of magnitude enhancement over silicon bulk photothermal nonlinearity, as well as the corresponding applications. Section 4 offers discussion of overall potentials and limitations of photothermal/thermo-optical nonlinearity in future applications.

2. Photothermal nonlinearity of plasmonic scattering

It is well known that plasmonic nanoparticles display saturable and reverse saturable absorption [4648]. In 2014, it was discovered that scattering intensity from a plasmonic nanoparticle exhibits saturation behavior [49,50]. The effect can be illustrated by considering the scattering cross-section of a plasmonic nanoparticle, based on quasi-static approximation of the classical Mie theory, as below:

$${\sigma _{sca}}(T )= \frac{8}{3}\pi {\kappa ^4}{r^6}{\left|{\frac{{{\varepsilon_p}(T )- {\varepsilon_m}}}{{{\varepsilon_p}(T )+ 2{\varepsilon_m}}}} \right|^2},$$
where σsca is the scattering cross-section, k is the wave vector, r is the nanoparticle radius, εp is the complex relative permittivity of the nanoparticle, and εm is the relative permittivity of the surrounding lossless medium, T is the temperature of the nanoparticle. We assumed continuous-wave illumination in this calculation. Thus, T represents both electron and phonon temperatures of the nanoparticle, as the difference between electron and phonon temperatures was shown to be small under continuous illumination [51,52]. We also assumed that the thermal conductivity of the surrounding medium is much lower than that of the nanoparticle, so the temperature rise of the surrounding medium is much smaller than that of the nanoparticle, and the permittivity of the surrounding medium is constant. At the SPR peak, the real part of the denominator vanishes, i.e., Re(εp+ 2εm) = 0, so σsca is inversely proportional to the imaginary part of εp. Because the imaginary part of εp increases with temperature rise [53], under strong light illumination, the SPR peak is broadened and σsca reduces through photothermal effect, resulting in a slow down of the increase of scattering intensity. It was shown that the change of the imaginary part of εp reaches several tens of percent [54]. Figure 1(a) shows the real and imaginary part of εp of the single gold nanoparticle under different CW laser excitation intensities. Up to a few tens of percent change in the imaginary part of εp leads to the very strong scattering nonlinearity. The corresponding scattering intensity saturation is presented in the simulation of Fig. 1(b).

 figure: Fig. 1.

Fig. 1. Analytical and numerical analysis of the photothermal nonlinearity. (a) Real and imaginary parts of the permittivity of gold nanoparticles (Diameter=100 nm) under CW laser illumination at 564 nm. The blue dots indicate the permittivities calculated by the linear temperature model. The solid black line indicates the analytical solution of the coupled heat and Maxwell equations. (b) Relationship between excitation and scattering intensity of the single gold nanoparticle (Diameter=80 nm) under CW laser illumination at 560 nm. The green dashed line and black solid line are the numerical results by solving the coupled equations with the absorption cross-section calculated by quasi-static approximation and the Mie theory, respectively. The red dots are from the experiment result in [50]. (a) and (b) were reproduced from [55] © 2020 American Physical Society.

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Experimentally, Figs. 2(a) and 2(b) show that scattering intensity from the single gold nanoparticle significantly reduces as the temperature increases via the irradiation of CW laser and heating of a hot plate, respectively [56], confirming the photothermal nature of the saturation behavior. Figure 2(c) presents saturation of scattering (SS) from a single gold nanosphere, with three excitation wavelengths. The 532 nm one is close to the SPR peak (∼580 nm), and the required excitation intensity to induce SS is the lowest. The 671 nm one is located at the tail of the broad SPR band, so SS is still observable. Nevertheless, the 405 nm is outside the SPR band, and no saturation is found even at high intensity, manifesting the strong correlation between SS and localized SPR.

 figure: Fig. 2.

Fig. 2. Photothermal nonlinearity of scattering intensity from plasmonic nanostructures. (a,b) Scattering spectra from a single gold nanosphere (Diameter=100 nm), which is (a) irradiated with a 561 nm CW laser or (b) heated by a thermal plate. (c) Dependencies of scattering on excitation intensity of a gold nanosphere (Diameter=80 nm), measured at wavelengths of 405 nm, 532 nm, and 671 nm. The dotted lines indicate extrapolated linear slopes. (d-f) Relationships between excitation and scattering intensity from (d) a silver nanosphere, (e) a gold nanorod, and (f) a gold nano-bowtie. The red lines represent linear extrapolations of scattering intensity at low excitation intensity (Se), and ΔS denotes the difference between the experimental data (dots) and Se. The nonlinear deviation ratio (NDR) is defined as ΔS/Se (color in dots). (a) and (b) were reproduced from [56]. (c) was reproduced with permission from [49] © 2014 American Physical Society. (d) and (e) were reproduced with permission from [43] © 2016 American Chemical Society.

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To account for the photothermal/thermo-optical effect, a self-consistent model is developed [54], via solving Maxwell and heat equations iteratively with experimentally measured temperature-dependent permittivity of metal [53,57]. More recently, by relaxing the quasi-static approximation with a purely numerical approach, the theory approaches better quantitative agreement with experimental results as shown in Fig. 1(b) [55]. Through considering the host medium heating, it improves the agreement between the theory and the experimental result. One useful approach is the effective medium technique at nanoscale heating, as manifested in a pioneer study [58]. In this linear photothermal study, they consider the effective dielectric constant as the ratio of volume-averaged electric displacement to volume-averaged electric field. This should be included in future theoretical explorations.

The nonlinearity of plasmonic scattering is observed not only for a gold nanosphere but also for various materials and structures. The photothermal effects of particles with non-spherical shapes and of different materials may be studied with the aforementioned numerical approach [55]. Figure 2(d-f) respectively show ubiquitous nonlinear scatterings from silver nanosphere, gold nanorod, and gold nano-bowtie [43]. The red lines in the figures represent linear extrapolation of scattering at low excitation intensity (Se), and the value ΔS denotes the difference between the experimental data and Se at high excitation intensity. The nonlinear deviation ratio (NDR) is defined as ΔS/Se, and it serves as an intuitive indication of the nonlinear magnitude. As the excitation intensity increases, the NDRs of each nanostructure show negative values, reaching at least 50%, indicating strong SS. Interestingly, in Figs. 2(d) and 2(e), at high excitation intensities, we found reverse saturation of scattering (RSS), which may directly modulate the scattering images in x-scan (Section 2.2.3). In the subsections below, we present photonic applications, including all-optical switching and various super-resolution imaging, based on SS and RSS [50].

2.1 Application 1: all-optical switching

We utilized the SS of plasmonic nanoparticles to realize all-optical switching of scattering response from plasmonic nanoparticles. When SS is induced, the nanoparticle scattering intensity does not increase with growing illumination photons, creating an effective “off-state”. The photothermal suppression of scattering is valid within the whole SPR spectrum, as shown in Figs. 2(a) and 1(b). This inspires us to use two simultaneous illumination wavelengths, as shown in Fig. 3: one (λ=543 nm) induces scattering, and the other (λ=592 nm) suppresses scattering, to achieve all-optical switching in a single gold nanoparticle.

 figure: Fig. 3.

Fig. 3. All-optical switching of plasmonic scattering from a single gold nanoparticle. (a) Scattering intensity from a single gold nanosphere (Diameter=80 nm) at the wavelength of 543 nm, irradiated with two beams at the wavelength of 543 nm and 592 nm. The blue and green regions indicate linear and nonlinear responses, respectively. In the nonlinear region, the 543 nm scattering is strongly suppressed by the 592 nm laser. (b) Scattering response of gold nanoparticles at the wavelength of 543 nm, under the repeated switching on and off of the beam at the wavelength of 592 nm. These figures were reproduced from [56].

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In Fig. 3(a), when the intensity of the 592 nm beam is low, i.e., in the linear regime (blue region), the scattering of the 543 nm beam is not affected by the irradiation of the 592 nm beam, as expected. Interestingly, when the 592 nm beam is strong enough to induce SS of the nanoparticle (green region), the scattering intensity of the 543 nm beam drops quickly as the 592 nm beam intensity increases. Figure 3(b) shows that the all-optical modulation depth is up to 90%, and is fully reversible and repeatable.

2.2 Application 2: super-resolution imaging

2.2.1 Plasmonic SAX microscopy

By exploiting SS of plasmonic nanoparticles in Fig. 2, we developed plasmonic saturated excitation (p-SAX) microscopy to improve the spatial resolution beyond the diffraction limit [49,59,60], featuring the first super-resolution imaging based on (plasmonic) scattering. In a laser scanning microscope, the illumination focal spot exhibits a Gaussian intensity distribution and thus the center of the focal spot should reach SS before the peripheral [6,61]. The underlying principle of resolution improvement by SAX microscopy is to distinguish between the saturated and linear signals via temporally modulating the excitation intensity, and demodulating the scattering signal at harmonic frequencies [6]. Figure 4(a) shows the SEM image and p-SAX images of gold nanospheres reconstructed by the scattering signals demodulated at fm, 2fm and 3fm, manifesting the improvement of the spatial resolution (highlighted by the arrow) down to λ/8 of excitation wavelength in the image reconstructed by nonlinear signal. The arrowheads indicate aggregated particles whose SPR wavelength may shift toward long wavelength, and 2fm/3fm signal of the 532 nm scattering vanishes, i.e., diminishing nonlinear response. In Fig. 4(b), with a large (aggregated) structure, p-SAX helps to identify localized hot spots with improved resolution, as shown in Fig. 4(b).

 figure: Fig. 4.

Fig. 4. Super-resolution imaging of plasmonic nanoparticles by p-SAX microscopy. (a) SEM image and p-SAX images of gold nanospheres (Diameter=100 nm) reconstructed by signal demodulated at fm, 2fm and 3fm. (b) p-SAX images of a large (aggregated) gold nanostructure. (c) p-SAX images of gold nanoshells distributed in a tissue phantom at the thickness of 80 µm, 240 µm, and 400 µm. The images were reconstructed by the signal demodulated at fm, and 2fm, respectively. (a) and (c) were reproduced with permission from: (a) [49], © 2014 American Physical Society (c) [66], © 2020 American Chemical Society.

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One advantage of p-SAX microscopy is the potential to achieve super-resolution imaging in deep tissue. A long-standing challenge in microscopy is the trade-off between spatial resolution and imaging depth [6264], in particular most super-resolution tools only allow thin cell observations, not thick tissues. SAX microscopy improves spatial resolution via temporal modulation and demodulation, which is less affected by tissue scattering and aberration. It was demonstrated that visible p-SAX microscopy enhances spatial resolution by three folds in biological tissues throughout a 200 µm objective working distance [65]. To further extend the penetration depth, we developed near-infrared p-SAX microscopy based on nonlinear scatterings from gold nanoshells and gold nanorods, providing both contrast and resolution enhancement over 400 µm depth in a tissue phantom, as shown in Figure 4(c) [66].

2.2.2 Suppression of scattering imaging (SUSI)

In Section 2.1, we discussed the all-optical switching application of the nonlinear plasmonic scattering. It is well known that all-optical switching of fluorescence enables super-resolution imaging via stimulated emission depletion (STED) microscopy, which uses a donut beam to suppress spontaneous fluorescence emission [67]. Based on a similar concept and setup, we developed suppression of scattering imaging (SUSI) to achieve super-resolution with scattering [56]. Figure 5(a) and 5(b) show the scattering image of gold nanospheres obtained by using conventional confocal microscopy and SUSI, respectively. As indicated by white arrows in the images, two adjacent gold nanospheres are only distinguishable with SUSI in Fig. 5(b). Figure 5(c) shows that the resolution can be further enhanced via deconvolution.

 figure: Fig. 5.

Fig. 5. Super-resolution imaging by using SUSI. (a-c) Scattering images of gold nanospheres (Diameter=80 nm) obtained by (a) conventional confocal microscopy, (b) SUSI, and (c) SUSI + deconvolution. (d,e) Scattering images of MG-63 cells stained with gold nanospheres (Diameter=60 nm), obtained by (d) confocal microscopy and (e) SUSI. (a-c) were reproduced from [56]. (d) and (e) were reproduced with permission from [69], © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Numerous studies have adopted plasmonic nanoparticles as imaging and biosensing contrast probes for biomedical applications, offering flexible spectral tunability, high signal contrast, non-bleaching, and good biocompatibility [68]. The SUSI approach provides an opportunity to break the diffraction limit in cell/tissue imaging with plasmonic nanoprobes. Figure 5(d) and 5(e) are respectively conventional confocal microscopy and SUSI images of a tumor cell (Human Osteosarcoma MG-63) stained with gold nanospheres, demonstrating the improvement of spatial resolution in SUSI [69].

2.2.3 RSS and super-linearity

In Fig. 2, we have shown that plasmonic scattering of a silver nanosphere and a gold nanorod exhibit RSS. Figure 6(a) presents RSS (the red region) of a gold nanosphere, which has super-linear power dependency that leads to super-resolution capability without additional temporal or spatial modulation [50,70]. In a laser scanning setup, the scattering images of a single nanoparticle show dramatic change due to these nonlinear power dependencies, as illustrated in Fig. 6. Figure 6(b) shows that when the scattering intensity linearly responds to excitation intensity, the signal distribution of the nanoparticle image corresponds to a Gaussian function. In Fig. 6(c), by increasing excitation intensity into the saturation regime (green region in Fig. 6(a)), the image distorts at the center, where the SS starts, resulting in a larger image FWHM than that of Fig. 6(b). Interestingly, near the particle center, deep SS induces side lobes with 40 nm width, which is much smaller than the size of the diffraction limited focal spot (∼200 nm). Figure 6(d) shows that at high excitation intensity, scattering displays super-linear power dependency through RSS, leading to significant FWHM reduction to 100 nm, demonstrating the potential for straightforward super-resolution imaging.

 figure: Fig. 6.

Fig. 6. Laser scanning scattering images of gold nanoparticle showing reverse-saturation of scattering. (a) Intensity dependency between excitation and scattering from a gold nanosphere (Diameter=100 nm). The three colored regions correspond to linear (blue), saturation (green) and reverse saturation (red). (b-d) Confocal scattering images of gold nanospheres and intensity profiles at the white dotted line. These images correspond to (b) linear (6×104 W/cm2), (c) SS (5×105 W/cm2), and (d) RSS (2×106 W/cm2), respectively. These figures were reproduced with permission from [50], © 2014 American Chemical Society.

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3. Photothermal nonlinearity of silicon nanoparticle

In addition to plasmonics, high index dielectric nanomaterials attract lots of interest due to their diverse electromagnetic Mie resonances. Among various materials, silicon receives particular attention because of its natural abundance and its compatibility with modern industrial production lines. However, compared to metals, the nonlinearity of silicon is smaller (Kerr n2 ∼ 10−9 µm2/mW [2], photothermal n2 ∼ 10−6 µm2/mW [71]). Following the discussion in Section 2, Mie resonance may significantly enhance the photothermal nonlinear response through self-induced thermo-optical effect. Since Mie-resonance-enhanced absorption induces temperature rising, temperature rising affects permittivity, and permittivity change in turn causes resonance shift and absorption efficiency variation, it is necessary to develop a recursive analytical model to quantify the local temperature and the absorption/scattering spectra, as shown schematically in Fig. 7 [72].

 figure: Fig. 7.

Fig. 7. Mechanism of the photothermal nonlinearity of dielectric nanoparticles. Here the photothermal effect is triggered by optical heating. Due to temperature-dependent refractive indices, the heating process becomes non-trivial and needs to be solved iteratively. These figures were reproduced from [72].

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Recently, systematic studies were carried out on the photothermal nonlinearity of silicon nanostructures, and discovered a giant nonlinear refractive index n2 ∼ 0.1 µm2/mW, as shown in Fig. 8, featuring five orders of magnitude enhancement over that of bulk silicon [73]. Figure 8 shows the real and imaginary parts of refractive indices under different laser excitation intensities of silicon nanoblocks with different widths. Note that the dependences of refractive indices on excitation intensity are strongly size dependent, thus the usage of the effective photothermal nonlinear index n2 must take into account this structural dependency.

 figure: Fig. 8.

Fig. 8. (a) Real and (b) imaginary parts of the refractive index of silicon nanoblocks with the width of 100 nm (blue), 170 nm (red) and 190 nm (green) under CW laser illumination at 561 nm. These figures were reproduced from [73].

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The photothermal nonlinearities of silicon nanoblocks with 100-200 nm width and 150 nm height are summarized in Fig. 9. Figure 9(a)–9(c) presents various optical nonlinear behaviors, including saturation (sub-linear), reverse saturation (super-linear), and deep saturation (negative slope), respectively, in silicon nanoblocks with different sizes (all excited at 561 nm). The insets show the signal distribution of the nanoparticle image under low and high excitation intensities. NDRs of scattering intensity are calculated by using the same definition in Section 2.

 figure: Fig. 9.

Fig. 9. Photothermal nonlinearity of scattering intensity from silicon nanoblocks. (a-c) Experimentally measured intensity dependencies of scattering from the single silicon nanoblock with the width of (a) 100 nm, (b) 170 nm, and (c) 190 nm, excited by a 561-nm CW laser. The insets show the signal profiles of scattering images of each nanoblocks at low and high excitation intensities, respectively. The structure of the silicon nanoblock is shown in the inset of (a). (d-f) Calculated dependences of scattering intensity from the single silicon nanoblocks with the width of (d) 100 nm, (e) 170 nm, and (f) 190 nm. The color on data points shows the corresponding calculated temperature of the silicon nanoblock. The calculated scattering spectra of the silicon nanoblocks at temperatures of 300K, 500K and 700K are shown in the inset of (d-f). These figures were reproduced from [73].

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Figure 9(d)–9(f) are corresponding simulations based on iterative calculations with Maxwell and heat equations, similar to what we mentioned in Section 2. Exceptionally well correspondences are found between experiments and simulations, manifesting that the underlying mechanism can be fully explained by the spectral red-shift of the Mie resonance (see insets) due to photothermally rising refractive index. That is, if the excitation wavelength is at the blue side of a resonance peak, the scattering exhibits SS (Fig. 9(d) and (f)). On the other hand, if the excitation is at the red side of a peak, the scattering dependency becomes super-linear (Fig. 9(e)).

3.1 Application 1: all-optical switch

Similar to the plasmonic all-optical switch in Section 2.1, the saturation behaviors of a single silicon nanoblock allow efficient all-optical switching based on scattering [73]. Figure 10(a) presents that the 543 nm scattering from a silicon nanoblock is efficiently controlled via a 592 nm suppression beam, showing modulation depth as high as 90%, and full repeatability. Compared to conventional resonant structures, such as microring resonator or photonic crystal [74,75], the Mie-resonant all-optical switches made of plasmonic and silicon both provide greatly reduced footprint, on the order of 0.001µm3.

 figure: Fig. 10.

Fig. 10. Optical switching with silicon nanostructures. (a) Scattering response of the single silicon nanoblock with a 240 nm width, excited at the wavelength of 543 nm, under the repeated switching on/off via the 592 nm suppression beam. (b) Transient response of all-optical switching from the single silicon nanoblock. The black line is experimentally measured data through pump-probe microscopy. The colored dots are simulation results, and the color indicates the calculated temperatures. These figures were reproduced from [73].

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Conventionally, thermo-optical nonlinearity is not preferred in optical modulation applications due to the slow heat dissipation at milli- to microsecond scale [76]. In this work, by reducing the size of silicon structure to the nanoscale, the lifetime of optical switching reduces down to nanoseconds. Figure 10(b) shows the temporal response of the silicon all-optical switch, either measured by pump-probe microscopy (black line) or calculated from the photothermal simulation (color dots). Both the experiment and the simulation manifest that the photothermal relaxation time of silicon nanoblock is about 1 nanosecond, featuring the potential for GHz operation.

3.2 Application 2: super-resolution imaging

3.2.1 SAX microscopy

The nonlinear scattering responses of silicon nanostructures are also applicable to super-resolution imaging. Similar to Section 2.2 of plasmonics, one strategy is to combine SS and SAX microscopy. Figure 11(a) and 11(b) show scattering SAX images of a single silicon nanoblock, reconstructed by the signals demodulated at fm, and 2fm. The image size of a silicon nanoblock reduces 2.3-fold in Fig. 11(b) compared to Fig. 11(a), as quantitatively depicted in Fig. 11(c).

 figure: Fig. 11.

Fig. 11. SAX microscopy with silicon nanostructures. (a,b) Scattering SAX images of the single silicon nanoblock with 100 nm width, reconstructed by the signal demodulated at (a) fm and (b) 2fm. (c) Signal profiles of (a) and (b) along horizontal direction. These figures were reproduced from [73].

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3.2.2 SUSI

Based on the idea of SUSI, Xiangping Li’s group performed super-resolution imaging of silicon nanodiscs by suppressing scattering signals with a donut beam [77]. The donut beam contains azimuthally polarized light, which is capable of efficiently heating up the nanodisk through magnetic dipole resonantly enhanced absorption to suppress the scattering. Figure 12(a) shows the SEM and the scattering images of the silicon nanodisk array, demonstrating better and better resolution obtained at growing intensities of the azimuthally polarized donut beam. Figure 12(b) characterizes the FWHM reduction of silicon SUSI, featuring values down to ∼50 nm.

 figure: Fig. 12.

Fig. 12. Super-resolution imaging of a silicon nanodisk array. (a) SEM and scattering images of a silicon nanodisk array obtained by SUSI. The numbers on each panel are excitation intensities of the donut beam. (b) Signal profiles obtained at the positions indicated by white dotted lines in (a). Red lines are Gaussian fitting. These figures were applied with permission from [77], © 2021 Chinese Laser Press.

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3.2.3 RSS via anapole

As mentioned in Section 2.2.3, the super-linearity with RSS creates a sharp peak in the center, and itself may lead to resolution enhancement. In the case of silicon, which may exhibit anapole resonance that has diminishing scattering, the RSS can be particularly evident, as shown in Fig. 13(a) [78]. Here a silicon nanodisk with 200 nm diameter and 50 nm thickness is excited with a 532 nm laser, which is located at the red side of the anapole resonance. At low laser intensity, the scattering is linearly proportional to excitation. With increasing laser intensity, the nanodisk resonance shifts into anapole, i.e., deep saturation with scattering drops to nearly zero (SS in Fig. 13(a)), and subsequently into bright mode again, leading to sharp RSS.

 figure: Fig. 13.

Fig. 13. Localization of a silicon nanodisk by using RSS. (a) The nonlinear dependency of scattering on irradiance intensities in single Si nanodisks for excitations at the wavelength of 532 nm. (b-d) Scattering images of the single silicon nanodisk obtained at different excitation intensities, showing (b) linear, (c) RSS, and (d) SS, respectively. The reason for placing RSS in front of SS is to visualize the subtraction process (r is a subtractive factor), leading to (e) differential image (denoted as DRSS) that yields a localization precision of 41 nm width. These figures were reproduced from [78].

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Figure 13(b)–13(d) show the laser scanning scattering images of a single silicon nanodisk, in the state of linear, RSS, and SS, respectively. As we expected, SS creates a scattering zero in the image center and RSS produces a sharp peak in the center, but the latter is surrounded by a donut of linear scattering with comparable scattering strength. Borrowing the idea from differential SAX microscopy [79], Fig. 13(e) presents that the localization precision can be enhanced to ∼40 nm through subtracting Fig. 13(d) from Fig. 13(c), offering an interesting potential for super-resolution imaging of silicon nanostructures.

4. Discussion and summary

In this review, we introduce our recent studies on the photothermal nonlinearity of scattering response from plasmonic and silicon nanostructures. We first review the photothermal nonlinearity that occurred in various kinds of plasmonic material and geometries in Section 2. The combination of the field enhancement by plasmonics and photothermal effect offers giant nonlinearity with n2 approaching ∼1 µm2/mW, leading to potential applications in all-optical switching and super-resolution imaging, as we demonstrated in Section 2.1 and 2.2, respectively.

One concern in the plasmonic nonlinear response is that metal nanoparticles, in particular the non-spherical ones such as the nanorods, might be prone to thermal surface melting and reshaping under intense illumination, and in turn significantly affect the optical properties [80,81]. Currently, there is no direct evidence to ensure no surface reshaping during the nonlinear scattering responses of non-spherical gold nanostructures (Fig. 2(e) and 2(f)). However, the reversibility and the repeatability of the nonlinear scattering in gold nanorod has been experimentally confirmed [43], implying that irreversible damage is not induced. A better morphology characterization through electron microscopy before and after illumination shall be considered in the future. In addition, nano-thermometry based on the measurement of anti-Stokes emission [35] should be an effective method to investigate the temperature rise of the gold nanorod, offering quantitative evaluation of not only photothermal effect, but also the potential of surface reshaping. Recent review by Hashimoto et al. provides a summary of previous studies of nanoparticle reshaping using pulse lasers and shows the required laser power threshold [82]. However, particle reshaping induced by continuous-wave lasers has not been enough studied and remains as a future work.

In Section 3, we present the photothermal nonlinearity of silicon nanoparticles. With the aid of Mie resonance and photothermal nonlinearity, silicon nanostructures exhibit nonlinearity with a comparable magnitude to that of plasmonic materials. In a similar manner to the plasmonic nanostructure, it was demonstrated that the nonlinearities of silicon nanostructures are capable of achieving optical switching and various super-resolution microscopy modalities.

The thermo-optical nonlinearities of both plasmonic and silicon nanostructures are enhanced significantly by Mie resonance. However, the Q-factor of typical Mie-resonance is only on the order of 10, which determines the slope in saturation and reverse saturation in the scattering intensity curves (Figs. 2 and 9). It is envisioned that if high-Q resonant nanostructures are adopted, the effective optical nonlinearity can be further enhanced. For example, symmetry-broken nanostructures may provide Q-factor well above 1000 [83], which could lead to two orders of magnitude enhancement on nonlinear scattering responses, as well as the all-optical switch efficiency.

Although both nonlinear scatterings from metal and silicon nanoparticles are based on the photothermal effect, the dominant factors that affect the nonlinearity could be different. For metal nanoparticles, the SPR peak exhibits mainly amplitude reduction, along with little spectral shift under intense laser illumination (Fig. 2(a) and 2(b)). Therefore, the excited electromagnetic multipole composition keeps the same, implying that the directionality of its scattering remains unchanged. On the other hand, for silicon nanoparticles, the scattering spectrum experienced both amplitude change and spectral red-shift (Fig. 7(d-f) insets), thus the excited multipole composition changes as excitation intensity increases. Therefore, the directionality of scattering waves from the silicon nanoparticle varies at elevated temperature and the nonlinearity of detected scattering intensity is affected by the collection optics.

Another important factor accounting for the nonlinear scattering is the polarization of incident/scattering light. Manipulating the multipole resonances inside the nanostructures by excitation field profile has been a rigorous topic in the field of nanophotonics. For example, tightly focused cylindrical vector beams have the capability to selectively excite electric/magnetic multipoles owing to their unique field profiles [84,85]. Most of the studies introduced in this review focused on non-polarized detection methods. Based on the vectorial scattering behavior of the multipoles, polarization dependent detection may be introduced to tailor the nonlinear signals in the future.

The local intensity of the excitation source may also influence the scattering nonlinearity. In most cases, the full-width-at-half-maximum of the excitation field is much larger than the particle size and there is no intensity gradient sensed by the nanostructure. However, it is possible that when the full-width-at-half-maximum of the excitation field is comparable to nanostructure’s size, the intensity gradient inside the focus affects the scattering behavior owing to the strong field confinement caused by Mie resonance. We expect future studies to unravel the local intensity interactions.

In addition, the optical interference between nanoparticle scattering and the reflection from the substrate shall be considered as another influential factor for signal measurement. In most of the experiments shown in this review, the interface reflection from glass substrate was eliminated by immersing the nanoparticle in index matching oil, and therefore the effect of interference is negligible. On the other hand, it is well known that efficient use of the interference effect enables high sensitivity detection of small scatterers, as demonstrated in interferometric scattering (iSCAT) microscopy [86,87]. More studies would be necessary to further explore how the interference can affect the measurement of nonlinear scattering when observing the nanoparticles under air or water ambiances.

The photothermal/thermo-optical nonlinearities enable several kinds of super-resolution techniques that are capable of reducing imaging FWHM and improving spatial resolution in scattering mapping of plasmonic and silicon nanostructures. These reversible and contactless techniques are expected to facilitate label-free inspections of plasmonic and silicon nano-devices. For example, Fig. 4(b) shows that p-SAX microscopy observes the hotspot regions with highly enhanced near-field intensity in aggregated gold nanoparticles. Figure 12 and 13 present that SUSI and super-linear subtraction resolve a closely packed silicon nanodisk array. In the future, we anticipate that SAX microscopy may similarly resolve the hotspots in complicated silicon nanostructures, i.e., visualizing near-field intensity distribution through far-field imaging. In addition, one most straightforward method to achieve super-resolution imaging is super-linear excitation emission (SEE) microscopy, which has been demonstrated with fluorescence emission [70]. We have shown that the scattering of both plasmonic (Fig. 2(d)–2(f) and 6(a)) and silicon (Fig. 5(b) and 5(e)) nanoparticles exhibit super-linearity, and will combine SEE to improve resolution without the need of image post-processing.

However, practical application of these super-resolution techniques to biological imaging, especially in living specimens, is still a challenging task particularly because of the heat generation from nanoparticle probes. According to experimental [56] and theoretical [54] results, when gold nanosphere scattering saturates, the temperature rise is estimated to be at least over 50 °C, which may induce thermal damage on not only the biological molecules nearby the nanoparticles, but also the surface coating of nanoparticles, such as protein-ligand and polymer. Having said that, in a tissue imaging environment, it is vital to keep in mind that the temperature rise of a surrounding medium shall be significantly lower than that of the nanoparticle itself because the thermal conductivity of the biological tissues is much lower than that of a metallic nanoparticle, and the thermal load might not be as high as expected. To further reduce heat generation from nanoprobes, one potential future direction is to improve the resonance quality factor of the scattering spectrum through engineering the dielectric nanoprobe structure and the material [88]. As we discussed in Section 3, the nonlinear scattering from the dielectric nanoparticle is caused by the photothermal/thermo-optical shift of the scattering spectrum. Therefore, with higher quality factor of the scattering spectrum, the required spectral shift, i.e., temperature rise, to induce the nonlinearity of scattering should become lower.

An interesting consideration is the wavelength dependences of the nonlinear strength, as well as the resulting super-resolution capability. As shown in Fig. 2(c), careful wavelength selection is important to obtain optimized nonlinearity. In most of our results, we used 532 nm or 561 nm to excite the gold plasmonic and silicon nanostructures. It is well known that the resonant wavelengths shift with sizes and geometries, and silicon displays a plethora of electric and magnetic multipole resonances. Therefore, we propose that by combining our techniques with a broadband source, such as a super-continuum laser, it is possible to explore nonlinear response and super-resolution observation with various nanostructures, even under the condition of unknown structure and materials.

With this perspective in mind, one important question to solve before practical applications is to understand the fundamental mechanism of scattering-based and photothermal/thermo-optical nonlinear image formation. As shown in Figs. 4(a), 10(a), and 11(e), the super-resolution image sizes can be much smaller than the physical sizes of the nanostructures. In the case of incoherent imaging, such as fluorescence microscopy, the images correspond to the convolution between an intensity point spread function of the microscope and an object, and thus the image never becomes smaller than the size of the object. Nevertheless, in coherent imaging using scattering signals, the image cannot be calculated by intensity convolution, but needs field convolution (amplitude + phase) to take into account the interference effect. The complex image formation due to the coherent nature of scattering signals can be one probable reason to produce images smaller than the physical morphology of the sample.

Another possible explanation is the spatial modulation of scattering cross-section due to the photothermal/thermo-optical nonlinear effect. In a laser-scanning setup, the nanoparticle temperature rise is strongly dependent on the position of the scanning laser spot. Note that in most of our studies, the laser focus spot is larger than the nanoparticle diameters. When the laser focus scans across the nanoparticle, the nanoparticle temperature starts to increase as the focus edge touches the nanoparticle edge, reaches highest temperature as the focal spot aligns with the nanoparticle center, and decreases as the focus moves away to the other edge of the nanoparticle. The temperature variation shall change material refractive index, and result in a modified scattering cross-section. That is, the coupled photothermal and thermo-optical effects are determined by the scanning position, thus leading to scanning-dependent scattering cross-section, similar to the idea of a nonlocal heating effect [89,90]. In this case, the image brightness is more strongly related to the mechanism of nonlinear scattering, such as absorption and local field confinement, rather than the structure of the sample. Therefore, the simple convolution idea in the conventional laser scanning microscopy may no longer be feasible. Further studies are necessary to quantify the nonlinear mechanism and resolution enhancement during laser scanning image formation.

One more unsolved issue, which is worthy of pointing out, is the mechanism behind the RSS of plasmonic nanostructure (note that RSS of silicon nanoparticles is well explained via red shift of Mie resonance at elevated temperature [78]). The change of scattering intensity from the gold nanoparticle under heating, shown in Figs. 2(a) and 2(b), is a direct proof that the photothermal effect is the dominant mechanism in nonlinear scattering from the gold nanoparticle. However, the simplistic photothermal model used so far is not sufficient to explain the RSS shown in Fig. 6(a). Specifically, the excitation intensity to induce the RSS of the scattering/absorption (e.g., 1.5- 2 MW/cm2 for the gold nanosphere of r=40 nm) is much higher than the excitation level in the current theoretical studies [55]. A quantitative agreement from numerical simulation thus probably requires taking into account the slight metal surface melting or size reduction of the nanoparticle under strong excitation. In principle, plasmonic resonance is sensitive to surface modification, and thus the effect may be studied by developing a new system that can acquire full plasmonic scattering spectra when increasing excitation intensity gradually.

Funding

Ministry of Science and Technology, Taiwan (MOST 109-2112-M-002-026-MY3, 110-2119-M-002-010-MBK, 110-2321-B-002-012); The Featured Areas Research Center Program (NTHU and NTU-110L8809) within the framework of the Higher Education Sprout Project co-funded by the MOST and the Ministry of Education, Taiwan (MOE); Japan Society for the Promotion of Science (Core-to-Core Program); National Key Research and Development Program of China (2018YFB1107200); Guangdong Science and Technology Department (2016ZT06D081).

Disclosures

The authors declare no conflicts of interest

Data availability

Data underlying the results presented in this paper may be obtained from the authors upon reasonable request.

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83. X. Yin, T. Sang, H. Qi, G. Li, X. Wang, J. Wang, and Y. Wang, “Symmetry-broken square silicon patches for ultra-narrowband light absorption,” Sci. Rep. 9(1), 17477 (2019). [CrossRef]  

84. T. X. Hoang, X. Chen, and C. J. R. Sheppard, “Multipole theory for tight focusing of polarized light, including radially polarized and other special cases,” J. Opt. Soc. Am. A 29(1), 32–43 (2012). [CrossRef]  

85. P. Woźniak, P. Banzer, and G. Leuchs, “Selective switching of individual multipole resonances in single dielectric nanoparticles,” Laser Photonics Rev. 9(2), 231–240 (2015). [CrossRef]  

86. P. Kukura, H. Ewers, C. Müller, A. Renn, A. Helenius, and V. Sandoghdar, “High-speed nanoscopic tracking of the position and orientation of a single virus,” Nat. Methods 6(12), 923–927 (2009). [CrossRef]  

87. R. W. Taylor and V. Sandoghdar, “Interferometric scattering microscopy: seeing single nanoparticles and molecules via Rayleigh scattering,” Nano Lett. 19(8), 4827–4835 (2019). [CrossRef]  

88. K. Koshelev, S. Kruk, E. Melik-Gaykazyan, J.-H. Choi, A. Bogdanov, H.-G. Park, and Y. Kivshar, “Subwavelength dielectric resonators for nonlinear nanophotonics,” Science 367(6475), 288–292 (2020). [CrossRef]  

89. A. Block, M. Liebel, R. Yu, M. Spector, Y. Sivan, F. J. García de Abajo, and N. F. van Hulst, “Tracking ultrafast hot-electron diffusion in space and time by ultrafast thermomodulation microscopy,” Sci. Adv. 5(5), eaav8965 (2019). [CrossRef]  

90. Y. Sivan and M. Spector, “Ultrafast dynamics of optically induced heat gratings in metals,” ACS Photonics 7(5), 1271–1279 (2020). [CrossRef]  

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2021 (3)

G. Baffou, “Anti-Stokes thermometry in nanoplasmonics,” ACS Nano 15(4), 5785–5792 (2021).
[Crossref]

S.-H. Huang, N. Irawati, Y.-F. Chien, J.-Y. Lin, Y.-H. Tsai, P.-Y. Wang, L.-A. Chu, M.-L. Li, A.-S. Chiang, K. Tsia, and S.-W. Chu, “Optical volumetric brain imaging: speed, depth, and resolution enhancement,” J. Phys. D: Appl. Phys. 54(32), 323002 (2021).
[Crossref]

B. Wang, Y. Che, X. Zhong, W. Yan, and T. Zhang, “Cylindrical vector beam revealing multipolar nonlinear scattering for super-localization of silicon nanostructures,” Photonics Res. 9(6), 950–957 (2021).
[Crossref]

2020 (10)

T. Zhang, Y. Che, K. Chen, J. Xu, Y. Xu, T. Wen, G. Lu, X. Liu, B. Wang, X. Xu, Y.-S. Duh, Y.-L. Tang, J. Han, Y. Cao, B.-O. Guan, S.-W. Chu, and X. Li, “Anapole mediated giant photothermal nonlinearity in nanostructured silicon,” Nat. Commun. 11(1), 3037 (2020).
[Crossref]

K. Koshelev, S. Kruk, E. Melik-Gaykazyan, J.-H. Choi, A. Bogdanov, H.-G. Park, and Y. Kivshar, “Subwavelength dielectric resonators for nonlinear nanophotonics,” Science 367(6475), 288–292 (2020).
[Crossref]

Y. Sivan and M. Spector, “Ultrafast dynamics of optically induced heat gratings in metals,” ACS Photonics 7(5), 1271–1279 (2020).
[Crossref]

S. Yoon, M. Kim, M. Jang, Y. Choi, W. Choi, S. Kang, and W. Choi, “Deep optical imaging within complex scattering media,” Nat. Rev. Phys. 2(3), 141–158 (2020).
[Crossref]

K. Nishida, G. Deka, N. I. Smith, S.-W. Chu, and K. Fujita, “Nonlinear scattering of near-infrared light for imaging plasmonic nanoparticles in deep tissue,” ACS Photonics 7(8), 2139–2146 (2020).
[Crossref]

T. V. Tsoulos and G. Tagliabue, “Self-induced thermo-optical effects in silicon and germanium dielectric nanoresonators,” Nanophotonics 9(12), 3849–3861 (2020).
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Y.-S. Duh, Y. Nagasaki, Y.-L. Tang, P.-H. Wu, H.-Y. Cheng, T.-H. Yen, H.-X. Ding, K. Nishida, I. Hotta, J.-H. Yang, Y.-P. Lo, K.-P. Chen, K. Fujita, C.-W. Chang, K.-H. Lin, J. Takahara, and S.-W. Chu, “Giant photothermal nonlinearity in a single silicon nanostructure,” Nat. Commun. 11(1), 4101 (2020).
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2019 (8)

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D. Denkova, M. Ploschner, M. Das, L. M. Parker, X. Zheng, Y. Lu, A. Orth, N. H. Packer, and J. A. Piper, “3D sub-diffraction imaging in a conventional confocal configuration by exploiting super-linear emitters,” Nat. Commun. 10(1), 3695 (2019).
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2018 (4)

J. Xu, T. Zhang, S. Yang, Z. Feng, H. Li, D. Hu, F. Qin, X. Ouyang, Y. Cao, L. Jiang, and X. Li, “Plasmonic nanoprobes for multiplexed fluorescence-free super-resolution imaging,” Adv. Opt. Mater. 6(20), 1800432 (2018).
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2017 (4)

G. Deka, C.-K. Sun, K. Fujita, and S.-W. Chu, “Nonlinear plasmonic imaging techniques and their biological applications,” Nanophotonics 6(1), 31–49 (2017).
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L. Meng, R. Yu, M. Qiu, and F. Javier García de Abajo, “Plasmonic nano-oven by concatenation of multishell photothermal enhancement,” ACS Nano 11(8), 7915–7924 (2017).
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2016 (8)

P.-T. Shen, Y. Sivan, C.-W. Lin, H.-L. Liu, C.-W. Chang, and S.-W. Chu, “Temperature- and roughness-dependent permittivity of annealed/unannealed gold films,” Opt. Express 24(17), 19254–19263 (2016).
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Q. Li, M. Davanço, and K. Srinivasan, “Efficient and low-noise single-photon-level frequency conversion interfaces using silicon nanophotonics,” Nat. Photonics 10(6), 406–414 (2016).
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2015 (2)

Y. He, K. Xia, G. Lu, H. Shen, Y. Cheng, Y.-C. Liu, K. Shi, Y.-F. Xiao, and Q. Gong, “Surface enhanced anti-Stokes one-photon luminescence from single gold nanorods,” Nanoscale 7(2), 577–582 (2015).
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2014 (9)

A. B. Taylor, A. M. Siddiquee, and J. W. M. Chon, “Below melting point photothermal reshaping of single gold nanorods driven by surface diffusion,” ACS Nano 8(12), 12071–12079 (2014).
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2013 (4)

J. S. Donner, S. A. Thompson, C. Alonso-Ortega, J. Morales, L. G. Rico, S. I. C. Santos, and R. Quidant, “Imaging of plasmonic heating in a living organism,” ACS Nano 7(10), 8666–8672 (2013).
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K. Setoura, Y. Okada, D. Werner, and S. Hashimoto, “Observation of nanoscale cooling effects by substrates and the surrounding media for single gold nanoparticles under CW-laser illumination,” ACS Nano 7(9), 7874–7885 (2013).
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S. Hashimoto, D. Werner, and T. Uwada, “Studies on the interaction of pulsed lasers with plasmonic gold nanoparticles toward light manipulation, heat management, and nanofabrication,” J. Photochem. Photobiol., C 13(1), 28–54 (2012).
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M. Selmke, M. Braun, and F. Cichos, “Photothermal single-particle microscopy: detection of a nanolens,” ACS Nano 6(3), 2741–2749 (2012).
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2011 (2)

M. Ren, B. Jia, J.-Y. Ou, E. Plum, J. Zhang, K. F. MacDonald, A. E. Nikolaenko, J. Xu, M. Gu, and N. I. Zheludev, “Nanostructured plasmonic medium for terahertz bandwidth all-optical switching,” Adv. Mater. 23(46), 5540–5544 (2011).
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2010 (2)

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2009 (2)

G. Baffou, M. P. Kreuzer, F. Kulzer, and R. Quidant, “Temperature mapping near plasmonic nanostructures using fluorescence polarization anisotropy,” Opt. Express 17(5), 3291–3298 (2009).
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P. Kukura, H. Ewers, C. Müller, A. Renn, A. Helenius, and V. Sandoghdar, “High-speed nanoscopic tracking of the position and orientation of a single virus,” Nat. Methods 6(12), 923–927 (2009).
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K. Fujita, M. Kobayashi, S. Kawano, M. Yamanaka, and S. Kawata, “High-resolution confocal microscopy by saturated excitation of fluorescence,” Phys. Rev. Lett. 99(22), 228105 (2007).
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D. Lasne, G. A. Blab, S. Berciaud, M. Heine, L. Groc, D. Choquet, L. Cognet, and B. Lounis, “Single nanoparticle photothermal tracking (SNaPT) of 5-nm gold beads in live cells,” Biophys. J. 91(12), 4598–4604 (2006).
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H. I. Elim, J. Yang, J.-Y. Lee, J. Mi, and W. Ji, “Observation of saturable and reverse-saturable absorption at longitudinal surface plasmon resonance in gold nanorods,” Appl. Phys. Lett. 88(8), 083107 (2006).
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2005 (2)

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S. Berciaud, L. Cognet, G. A. Blab, and B. Lounis, “Photothermal heterodyne imaging of individual nonfluorescent nanoclusters and nanocrystals,” Phys. Rev. Lett. 93(25), 257402 (2004).
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L. Cognet, C. Tardin, D. Boyer, D. Choquet, P. Tamarat, and B. Lounis, “Single metallic nanoparticle imaging for protein detection in cells,” Proc. Natl. Acad. Sci. 100(20), 11350–11355 (2003).
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D. Boyer, P. Tamarat, A. Maali, B. Lounis, and M. Orrit, “Photothermal imaging of nanometer-sized metal particles among scatterers,” Science 297(5584), 1160–1163 (2002).
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Data availability

Data underlying the results presented in this paper may be obtained from the authors upon reasonable request.

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Figures (13)

Fig. 1.
Fig. 1. Analytical and numerical analysis of the photothermal nonlinearity. (a) Real and imaginary parts of the permittivity of gold nanoparticles (Diameter=100 nm) under CW laser illumination at 564 nm. The blue dots indicate the permittivities calculated by the linear temperature model. The solid black line indicates the analytical solution of the coupled heat and Maxwell equations. (b) Relationship between excitation and scattering intensity of the single gold nanoparticle (Diameter=80 nm) under CW laser illumination at 560 nm. The green dashed line and black solid line are the numerical results by solving the coupled equations with the absorption cross-section calculated by quasi-static approximation and the Mie theory, respectively. The red dots are from the experiment result in [50]. (a) and (b) were reproduced from [55] © 2020 American Physical Society.
Fig. 2.
Fig. 2. Photothermal nonlinearity of scattering intensity from plasmonic nanostructures. (a,b) Scattering spectra from a single gold nanosphere (Diameter=100 nm), which is (a) irradiated with a 561 nm CW laser or (b) heated by a thermal plate. (c) Dependencies of scattering on excitation intensity of a gold nanosphere (Diameter=80 nm), measured at wavelengths of 405 nm, 532 nm, and 671 nm. The dotted lines indicate extrapolated linear slopes. (d-f) Relationships between excitation and scattering intensity from (d) a silver nanosphere, (e) a gold nanorod, and (f) a gold nano-bowtie. The red lines represent linear extrapolations of scattering intensity at low excitation intensity (Se), and ΔS denotes the difference between the experimental data (dots) and Se. The nonlinear deviation ratio (NDR) is defined as ΔS/Se (color in dots). (a) and (b) were reproduced from [56]. (c) was reproduced with permission from [49] © 2014 American Physical Society. (d) and (e) were reproduced with permission from [43] © 2016 American Chemical Society.
Fig. 3.
Fig. 3. All-optical switching of plasmonic scattering from a single gold nanoparticle. (a) Scattering intensity from a single gold nanosphere (Diameter=80 nm) at the wavelength of 543 nm, irradiated with two beams at the wavelength of 543 nm and 592 nm. The blue and green regions indicate linear and nonlinear responses, respectively. In the nonlinear region, the 543 nm scattering is strongly suppressed by the 592 nm laser. (b) Scattering response of gold nanoparticles at the wavelength of 543 nm, under the repeated switching on and off of the beam at the wavelength of 592 nm. These figures were reproduced from [56].
Fig. 4.
Fig. 4. Super-resolution imaging of plasmonic nanoparticles by p-SAX microscopy. (a) SEM image and p-SAX images of gold nanospheres (Diameter=100 nm) reconstructed by signal demodulated at fm, 2fm and 3fm. (b) p-SAX images of a large (aggregated) gold nanostructure. (c) p-SAX images of gold nanoshells distributed in a tissue phantom at the thickness of 80 µm, 240 µm, and 400 µm. The images were reconstructed by the signal demodulated at fm, and 2fm, respectively. (a) and (c) were reproduced with permission from: (a) [49], © 2014 American Physical Society (c) [66], © 2020 American Chemical Society.
Fig. 5.
Fig. 5. Super-resolution imaging by using SUSI. (a-c) Scattering images of gold nanospheres (Diameter=80 nm) obtained by (a) conventional confocal microscopy, (b) SUSI, and (c) SUSI + deconvolution. (d,e) Scattering images of MG-63 cells stained with gold nanospheres (Diameter=60 nm), obtained by (d) confocal microscopy and (e) SUSI. (a-c) were reproduced from [56]. (d) and (e) were reproduced with permission from [69], © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Fig. 6.
Fig. 6. Laser scanning scattering images of gold nanoparticle showing reverse-saturation of scattering. (a) Intensity dependency between excitation and scattering from a gold nanosphere (Diameter=100 nm). The three colored regions correspond to linear (blue), saturation (green) and reverse saturation (red). (b-d) Confocal scattering images of gold nanospheres and intensity profiles at the white dotted line. These images correspond to (b) linear (6×104 W/cm2), (c) SS (5×105 W/cm2), and (d) RSS (2×106 W/cm2), respectively. These figures were reproduced with permission from [50], © 2014 American Chemical Society.
Fig. 7.
Fig. 7. Mechanism of the photothermal nonlinearity of dielectric nanoparticles. Here the photothermal effect is triggered by optical heating. Due to temperature-dependent refractive indices, the heating process becomes non-trivial and needs to be solved iteratively. These figures were reproduced from [72].
Fig. 8.
Fig. 8. (a) Real and (b) imaginary parts of the refractive index of silicon nanoblocks with the width of 100 nm (blue), 170 nm (red) and 190 nm (green) under CW laser illumination at 561 nm. These figures were reproduced from [73].
Fig. 9.
Fig. 9. Photothermal nonlinearity of scattering intensity from silicon nanoblocks. (a-c) Experimentally measured intensity dependencies of scattering from the single silicon nanoblock with the width of (a) 100 nm, (b) 170 nm, and (c) 190 nm, excited by a 561-nm CW laser. The insets show the signal profiles of scattering images of each nanoblocks at low and high excitation intensities, respectively. The structure of the silicon nanoblock is shown in the inset of (a). (d-f) Calculated dependences of scattering intensity from the single silicon nanoblocks with the width of (d) 100 nm, (e) 170 nm, and (f) 190 nm. The color on data points shows the corresponding calculated temperature of the silicon nanoblock. The calculated scattering spectra of the silicon nanoblocks at temperatures of 300K, 500K and 700K are shown in the inset of (d-f). These figures were reproduced from [73].
Fig. 10.
Fig. 10. Optical switching with silicon nanostructures. (a) Scattering response of the single silicon nanoblock with a 240 nm width, excited at the wavelength of 543 nm, under the repeated switching on/off via the 592 nm suppression beam. (b) Transient response of all-optical switching from the single silicon nanoblock. The black line is experimentally measured data through pump-probe microscopy. The colored dots are simulation results, and the color indicates the calculated temperatures. These figures were reproduced from [73].
Fig. 11.
Fig. 11. SAX microscopy with silicon nanostructures. (a,b) Scattering SAX images of the single silicon nanoblock with 100 nm width, reconstructed by the signal demodulated at (a) fm and (b) 2fm. (c) Signal profiles of (a) and (b) along horizontal direction. These figures were reproduced from [73].
Fig. 12.
Fig. 12. Super-resolution imaging of a silicon nanodisk array. (a) SEM and scattering images of a silicon nanodisk array obtained by SUSI. The numbers on each panel are excitation intensities of the donut beam. (b) Signal profiles obtained at the positions indicated by white dotted lines in (a). Red lines are Gaussian fitting. These figures were applied with permission from [77], © 2021 Chinese Laser Press.
Fig. 13.
Fig. 13. Localization of a silicon nanodisk by using RSS. (a) The nonlinear dependency of scattering on irradiance intensities in single Si nanodisks for excitations at the wavelength of 532 nm. (b-d) Scattering images of the single silicon nanodisk obtained at different excitation intensities, showing (b) linear, (c) RSS, and (d) SS, respectively. The reason for placing RSS in front of SS is to visualize the subtraction process (r is a subtractive factor), leading to (e) differential image (denoted as DRSS) that yields a localization precision of 41 nm width. These figures were reproduced from [78].

Equations (1)

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σ s c a ( T ) = 8 3 π κ 4 r 6 | ε p ( T ) ε m ε p ( T ) + 2 ε m | 2 ,