Quantifying figures of merit for localized surface plasmon resonance applications: a materials survey

Brock DoironA, Monica MotaA, Matthew P. WellsB, Ryan BowerB, Andrei MihaiB, Yi LiA, Lesley F. CohenA, Neil McN. AlfordB, Peter K. PetrovB, Rupert F. OultonA, Stefan A.

MaierD,A

A Department of Physics, Imperial College London, London, UKB Department of Materials, Imperial College London, London, UK

D Nanoinstitut München, Chair in Hybrid Nanosystems, Faculty of Physics, Ludwig-Maximilians Universität München, München, Germany

ABSTRACT

Using localized surface plasmon resonances (LSPR) to focus electromagnetic radiation to the nanoscale shows the promise of unprecedented capabilities in optoelectronic devices, medical treatments and nanoscale chemistry, due to a strong enhancement of light-matter interactions. As we continue to explore novel applications, we require a systematic quantitative method to compare suitability across different geometries and a growing library of materials. In this work, we propose application-specific figures of merit constructed from fundamental electronic and optical properties of each material. We compare seventeen materials from four material classes (noble metals, refractory metals, transition metal nitrides, and conductive oxides) considering eight topical LSPR applications. Our figures of merit go beyond purely electromagnetic effects and account for the materials’ thermal properties, interactions with adjacent materials, and realistic illumination conditions. For each application we compare, for simplicity, an optimized spherical antenna geometry and benchmark our proposed choice against the state-of-the-art from the literature. Our propositions suggest the most suitable plasmonic materials for key technology applications and can act as a starting point for those working directly on the design, fabrication and testing of such devices.

Keywords: Plasmonics, Mie Theory, Material Characterization, Hot Electron Devices, Photothermal Applications

1

The strong interaction between light and the free electrons of metals gives rise to extraordinary phenomena not possible with conventional dielectric photonic systems. The oscillating electric field of light can resonantly drive the oscillation of these free electrons in what is called a surface plasmon resonance (SPR) due to the generation of interfacial charges that coherently exchange energy with the electromagnetic field. From the coining of the term “surface plasmon” as a quantization of plasma oscillation in the late 1950s in thin metal foils, 1 plasmonics has developed into an active area of research2. With recent developments in nanofabrication techniques, it is possible to fabricate metallic particles with sizes below the wavelength of light that still readily interact with incident radiation. This excitation is termed a localized surface plasmon resonance (LSPR) distinguished from a propagating surface plasmon polariton (SPP) in thin metal films. The ability to confine and control light on length scales below the diffraction limit was unprecedented and stimulated a surge of proposed novel applications3 including integrated photonic circuits3, imaging4,5 and sensing6,7. Although these and many other plasmonic applications have been demonstrated experimentally, they have yet to be integrated into widespread industrial settings as is seen with photonics and electronics with the exception of surface enhanced Raman scattering (SERS) substrates.8 This is primarily due to the incompatibility with industrial fabrication techniques due to the relatively low melting temperatures of conventional plasmonic metals resulting in diffusion into silicon9 and the difficulty of patterning inert metals using gas phase chemical etching10 . In addition, the large absorptive losses at visible wavelengths result in pronounced heating, which can speed up the degradation of surrounding components.11 Recently, there has been particular interest in alternative materials and the development of non-radiative applications12,13 to circumvent these issues without compromising performance.

We divide the diverse range of materials currently being investigated into four classes: noble metals, refractory (high-temperature stable) metals, transition metal nitrides, and conductive oxides. The extensive range of physical properties (hardness, heat tolerance, thermal dissipation) and electronic characteristics (free carrier concentration, effective mass) are taken into account to examine materials which will facilitate plasmonic devices that can be efficiently implemented across the ultraviolet (UV), visible and infrared (IR) regimes. The summary of the operation ranges and advantageous properties is summarized in Table 1. The most widely used and well-studied materials in plasmonics are silver (Ag), gold (Au), and copper (Cu). These noble metals were originally preferred due to their stability and high conductivity resulting in sharp resonances. However, these materials are also plagued by low melting temperatures (<1000° C) and a fixed free carrier concentration resulting in operation being restricted to the ultraviolet and higher frequency end of the visible spectrum. Less common metals have been explored including palladium (Pd), magnesium (Mg), and yttrium hydride (YH2) for their sensitivity to particular gases (for example H2)14–16 and rhodium (Rh) due to its comparable optical properties to Al but with resistance to oxidation.17 In this group we also include aluminum (Al), which although is not strictly a noble metal, has comparably low-loss and operation range.18,19 For high temperature applications, the refractory metals molybdenum (Mo),20 niobium (Nb),21 nickel (Ni),22 tungsten (W)23, and titanium (Ti)24 are being exploited in plasmonics for their high melting temperature and red-shifted resonances compared to the noble metals. However, due to the fixed carrier concentration in mono-atomic metals, tuning of the plasmon resonance requires change of the geometry for these materials. A relatively new class of a materials, transition metal nitrides, are conductive ceramics (XN, X=Ti, Zr, Hf, Nb) with variable stoichiometry allowing for tunable carrier concentration by varying deposition conditions in addition to high thermal stability. 25,26 The ability to substitute nitrogen atoms with more electronegative oxygen atoms allows for tunable properties between metal and semiconductor, as has been observed with the intermediate titanium oxynitride (TiON).27 However, the transition metal nitrides have high optical losses, making them ideal broadband absorbers 28,29 but poor light scatterers. For low-loss plasmonics, conductive metal oxides such as Al and Ga doped ZnO and ITO30 are currently being explored; however, they are only metallic in the infrared (above 1500 nm). For visible and near-infrared applications, recent developments in strontium-based oxides including strontium molybdate (SrMoO3; SMO)31, strontium niobate (SrNbO3; SNO)32 and strontium ruthenate (SrRuO3; SRO)33 have allowed for reduced loss while still maintaining plasmonic properties in the visible regime.

With the advantages and limitations of each material class and the range of material properties within each class, it is clearly not straightforward to determine the best route forward in the development of commercially-viable plasmonic applications. This issue is well-recognized within the plasmonics community and has resulted in proposals of universal “quality factors” for localized and propagating SPRs, which simply consider the ratio of the real and imaginary parts of the bulk dielectric permittivity. 34,35 Although useful as a first step, this fails to capture the interaction of the particle with its environment, the effects of geometry, and specifications of particular applications. Since 2015, several groups have addressed this issue, quantifying and comparing figures of merit for localized heating36 and solar energy harvesting37. However, such investigations have relied on the electrostatic approximation, which limits the validity of the estimations to spheres below 10 nm is size due to the exclusion of retardation effects.38 Such small nanoparticles are challenging to fabricate in planar geometries but are also not relevant for many applications where particle sizes exceed 100 nm. As such, a more rigorous electromagnetic treatment is required that can account for the geometric effects underpinning one of the most critical advantages of plasmonics: tuning the resonance by particle size.

2

In this work, we propose figures of merit for broad industrially-relevant applications, where the material selection and geometry of plasmonic devices are simultaneously optimized using only standard optical thin film characterization. First, using conventional Drude-Lorentz fitting procedures of the measured spectroscopic ellipsometry data, we can extract properties of both free and bound electrons while accounting for both material quality and the presence of interfacial oxide layers. Next, using Mie theory calculations, we analytically describe the size and dipolar resonance mode of a metallic sphere for a range of radii and wavelengths as well as the corresponding scattering and absorption cross-sections. As these two processes underpin a considerable number of plasmonic applications, we review the underlying physics of each application then develop a figure of merit for the considered applications using these cross-sections. The simplicity of this approach (shown schematically in Figure 1) allows for a straightforward and systematic characterization of each application with directly applicable results as well as easy expansion to new materials and related applications.

Low Loss

Thermal Stability

Tunable Carrier

ConcentrationUV Visible Near-IR

NobleMetals

Refractory Metals

Transition Metal Nitrides

Conductive Oxides

Table 1 | Material properties and operation ranges. Each class of materials possess advantages including low loss, thermal stability, and a tunable carrier concentration. As a first step, the potential materials can be selected based on the required properties and the operation range (UV, visible or near-IR).

Figure 1 | Overview of our approach. Starting from rigorous characterization of the electronic behaviour of thin films, we develop robust figure of merits for specific applications allowing a convenient and direct comparison of suitability of a large library of materials for a specific application. The procedure begins with a measurement of a thin film’s optical properties by fitting experimental spectroscopic ellipsometry to a Drude-Lorentz permittivity model. Subsequently, the figures of merit are calculated using Mie theory calculations with the measured optical properties as inputs.

2 MODELLING AND CHARACTERIZATION

The optical response of a film contains all the information needed to extract the scattering and absorption abilities of a particle made of the same material. The frequency-dependant optical permittivity (ϵ (ω )) is a

3

quantitative description of a material’s electronic response to an incident electromagnetic wave. The bound electrons in a material respond to an applied field by inducing microscopic dipoles, with the lattice atom and surrounding electron density being driven in opposite directions due to the opposing charges. For metals, in addition to the bound electrons, there are delocalized conduction electrons. There is some degree of Coulombic interaction between these electrons and the positive lattice atoms, but simultaneously the screening due to the valence (bound) electrons allows these to be treated as effectively free due to the low net force on the electron.39

2.1 Drude-Lorentz Model for the Optical Properties of Metals

The optical response of the free electrons in a metal is described by the Drude model for electrical conduction where these electrons undergo frequent collisions with lattice ions. In an oscillating field the conduction electron density will oscillate about the positive atoms to a maximum amplitude of x0 and induce an additional polarization on the material PDrude=−ne x0, where n is the electron number density and e the charge of the electron. Through the Drude model of AC conductivity39, the maximum amplitude and oscillation frequency can be related to the driving electric field via the plasma frequency of the material defined as ω p

2=n e2/ϵ 0 m¿. Combining the Drude permittivity with N Lorentz oscillators to account for interband electron transition results in the Drude-Lorentz model for electric permittivity:

ϵ (ω )=ϵ∞+∑j=1

N f j ω0 j2

ω0 j2 −ω2+i Γ j ω

−ωp

2

ω2− iωγ

4

a b

c d

Figure 2 | Drude-Lorentz model fits to spectroscopic ellipsometry data. Spectroscopic ellipsometry measurements of thin films, divided into real (left-hand plots) and imaginary (right-hand plots) parts of the permittivity divided into the material classes: (a-b) noble metals, (c-d) refractory metals, (e-f) transition metal nitrides, (g-h) conductive metal oxides. A detailed explanation of the measurement and fitting procedure can be found in Supplementary Section S7.

2.2 Electronic and Optical Property Determination

To measure the optical response of the thin films in the visible and near-infrared regions (300-1600 nm), a variable-angle spectroscopic ellipsometer was used. Using the ratio of the reflected intensities of s- and p-polarized light, the ellipsometric parameters (ψ , Δ¿ are determined via R=rs /r p=tan ψ ei Δ. Although the permittivity can be calculated directly from these parameters40, the measured reflectivity includes additional reflections introduced by the substrate and surface oxide (if present). To account for this, we describe the metallic layer using a Drude-Lorentz oscillator model and fit the parameters to the experimental data using a Marquandt-Levenberg algorithm to minimize the mean squared error (MSE). A detailed example of how fitting is performed to extract the optical parameters is presented in Supplementary Section S7 along with the MSE values shown in Supplementary Table S7-2. In addition to being more accurate, this gives improved physical intuition of the behaviour of the electrons separating it into individual interband and Drude contributions. Figure 2 shows the fitted permittivities of all materials considered in this work separated into real and imaginary contributions which characterize the induced polarization (conduction) and absorption (loss), respectively. Upon inspection it is clear that, among the materials investigated, there is high variability between the degree of losses (characterized by the magnitude of the imaginary part of the permittivity) and the regions where metallic behaviour onset occurs (characterized by the point where the real part of the permittivity changes from positive to negative).

As a result of the variability, it is not straightforward to understand how to efficiently implement these materials in specific applications. To start we present Table 2, which organizes the relevant fitted and measured parameters of the films for a direct comparison. The operation range of a plasmonic device in air is determined roughly by the point at which is satisfies the Fröhlich condition (ℜ {ϵ }=−2), explained in detail in the subsequent section. Our library of materials allows for operation from the ultraviolet (Al, Cu, Pd, Rh, Ni) through the visible (Ag, Au, NbN, TiN, CuxOy) and into the infrared (Mo, W, Ti, TiON, SMO, SNO, SRO). We

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e f

g h

also show the Drude loss term (in femtoseconds) which describes the mean time between electron collisions due to electron-electron and electron-phonon scattering, as well as with impurities and defects as defined by Matthiessen’s Rule.39 The fitted background permittivity (ϵ∞ ¿and interband transition properties are also presented, which are relevant to the design of experimental procedures including hot-carrier generation and local heating. Finally, literature values for volumetric heat capacity (CV) and work function (ϕ M¿are given, where available, for use in subsequent calculations. Deposition details of the each thin film used in this work can be found in Supplementary Section S8.

  ENZ(nm)

λℜ {ϵ }=−2(nm)

Drude Loss (fs)

ϵ∞

Oxide Layer (nm)

Interband 1 Interband 2 Interband 3 Heat Capacity

(MJ m-3K-

1)

Work Function

(eV)Energy

(eV)Width (eV)

Energy (eV)

Width (eV)

Energy (eV)

Width

(eV)

Nob

le M

etal

s

Ag <300 360 125.0 2.9 2.9 3.47 0.15 4.20 0.27 4.58 0.33 2.5414.3-4.642

Al <300 <300 25.6 0.7 3.0 1.57 0.42 1.79 1.26 4.33 3.54 2.4414.343

Au <300 495 17.1 3.5 - 2.73 0.39 3.09 0.73 4.11 1.80 2.5415.443

Cu <300 330 59.1 5.17 1.9 2.561 0.53 3.61 1.55 - - 3.541 4.444

Pd <300 <300 22.9 1.6 1.3 0.83 2.59 5.19 8.22 - - 2.941 5.145

Rh <300 <300 13.7 2.2 - 1.20 2.23 2.76 1.52 5.36 2.05 3.041 5.045

Ref

ract

ory

Met

als

Mo 885 960 23.1 -0.2 - 0.94 0.54 2.34 1.43 5.40 12.3 25.741 4.0-4.346

Ni <300 350 10.9 1.2 - 1.36 2.31 5.43 5.25 - - 4.041 4.444

W 755 1060 1.3 1.6 - 0.57 0.08 2.24 4.81 6.42 1.51 2.641 4.546

Ti 700 1095 0.6 0.8 2.8 0.26 0.30 3.54 1.00 - - 2.441 3.6-4.344

Met

al N

itrid

es NbN 3901345

4801255 1.5 2.3 2.5 0.93 1.56 4.87 1.54 6.01 6.86 - 4.7-4.847

TiN48 495 540 9.4 1.8 6.4 3.96 0.73 5.61 3.99 - - 3.249 3.2-4.428,50,51

TiON48 625 720 2.7 2.4 10.2 3.75 1.04 5.62 3.72 - - 3.249 3.2-4.428,50,51

Con

duct

ive

Oxi

des SMO 555 875 11.8 2.1 4.5 1.77 1.06 3.46 0.35 - - - -

SNO 765 1005 1.5 3.5 6.1 0.40 0.31 1.95 1.50 4.09 0.63 15.852 -

SRO 1125 1355 10.9 2.9 - 3.15 0.73 4.09 1.144 4.61 53.4 - 4.6-4.953

CuxOy

<300 555 50.3 2.4 4.8 1.67 0.86 2.51 0.56 3.56 2.50 3.541 4.4-4.854

Table 2| Drude-Lorentz fitting parameters and material properties. Included are the wavelengths for the epsilon-near-zero (ENZ) point and Fröhlich condition (ℜ {ϵ }=−2) relevant for several plasmonic applications. For the noble metals, Ni, and CuxOy these occur at wavelengths beyond the range of our ellipsometer (<300 nm). Also provided are the Drude loss term (in fs), the background permittivity (ϵ∞), oxide layer thickness and the interband transition center energy and width. Also included are the heat capacity and work functions found in literature where possible, shown in olive font. Details of the deposition procedures for the films can be found in Supplementary Section S8.

2.3 Localized Surface Plasmon Resonances

If the size of the nanostructure is less than the wavelength of light being used to excite the particle, all of the free electrons can be driven coherently in what is termed a localized surface plasmon resonance (LSPR). This is distinguished by an enhanced field inside the particle, leading to higher absorption, and a strong electric field surrounding the particle. For a sphere of radius a with permittivity ϵ (ω ) in a dielectric medium with permittivity ϵ s in the quasi-static approximation (a≪ λ), a resonant condition arises when the denominator of the polarizability approaches zero (ϵ (ω )=−2 ϵ s) called the Fröhlich condition. In real metals, the denominator never reaches zero due to losses (the imaginary part of the permittivity) being nonzero. These losses lead to a reduction of intensity and broadening of the frequency range where the plasmonic enhancement occurs. This spectral range defines where plasmonic enhancements can be best exploited. As the incident light (an

6

electromagnetic field) is driving the free electrons of the material, the interaction area of a metallic particle with light will extend beyond its physical cross section. Thus, plasmonic particles have the ability to scatter and absorb more energy than is directly incident on them. To quantify the efficiency of the respective processes due to the plasmonic modes we take the ratio of the interaction cross sections with the respective geometric cross sections Qi=σ i /σ g. This directly quantifies the plasmonic enhancement irrespective of size. With an incident power of P0:

QScat=PScat

P0Q

|¿|=P|¿|

P0Q Ext=

P Ext

P0¿¿

Figure 3 | Analytical resonance behavior: Electrostatic limit versus Mie theory. (a) The variation of the wavelength-dependent scattering cross-section (QScat) of the dipolar mode of a gold sphere with various radii under the electrostatic approximation. (b) The same variation of scattering cross-section with Mie theory calculations showing a pronounced red-shift and broadening for larger particle sizes (shown with dotted lines). The failure of the electrostatic approximation is clearly observed beyond 20 nm. The wavelength and particle size where the maximum (c) normalized scattering cross-section (QScat) and (d) normalized absorption cross-section (Q|¿|¿) occurs for each material showing the center of the operation range where the materials plasmonic properties can be best exploited. The colour scale shows the maximum enhancement factor achieved for the materials. The library of materials included in this work span the ultraviolet, visible and near-infrared.

2.4 Mie Theory

Beyond the electrostatic approximation (a>10 nm), retardation effects due to the variation of the electric field invalidate the expression for polarizability described above and require a more rigorous electromagnetic treatment. Using Mie Theory55 we solve the wave equation using expansions of the incident, internal and scattered fields as an infinite series of vector spherical harmonics (VSHs). The coefficients of this expansion (

7

a b

c d

an , bn , cn , dn) can be related to the resonance conditions of the dipolar and higher order modes (shown in detail in Supplementary Section S1). Using the polarizability within the electrostatic approximation and that of Mie theory we can directly compare the predictions of the respective models for spherical gold particles (Figure 3a-b). The failure to predict the broadening and red-shifting of the dipole plasmon resonance restricts the applicable sizes to those less than 10 nm.

Although Mie theory overcomes the size-restrictions imposed by the electrostatic approximation, it is still limited to spherical particles of a single homogeneous material. This excludes some of the rich physics brought about by using nanoparticle arrays or complexes56–58, core-shell structures19,59,60 and partial embedding of nanoparticles in a substrate.61–63 Furthermore, the shape of the particle can be used to further tune the plasmon resonance and has been thoroughly studied in previous work. 64,65 The role of these factors has been studied extensively and can serve as an extension to this work. However, a spherical system is a straightforward platform to explore the physics that underpins the enhancements brought about by plasmon resonances and narrow down materials to be investigated further. As is clear from Figures 3b and 3d, there is a small range (of particle size and operation wavelength) where the plasmonic enhancement is maximum and thus, can be best exploited. In Figure 3c-d we show, for each material, the particle size that gives the largest enhancement in scattering and absorption along with the associated plasmon resonance peak. We now have a comprehensive material library spanning a wide range of operation regimes.

With such a straightforward method of calculating the plasmonic enhancements from only the electronic properties of the material, it is easy to include additional materials into the analysis or extend to include materials with plasmonic behaviour further into the IR to include the transparent conducting oxides (TCOs): ITO Al:ZnO and Ga:ZnO.30 These materials are of particular interest for low-loss infrared plasmonics66,67 but are beyond the scope of this work. However, using the tabulated values of the Drude parameters can be used to extend the permittivity deeper into the IR, beyond the measurement range of our ellipsometer and the same figures of merit can be used as the underlying physics remains the same. However, care must be taken if extrapolating the permittivity as additional interband transitions may be present and in the far-infrared, atomic and phonon absorption can lead to additional variations of the permittivity that are not accounted for in Mie theory. As such, the range is limited to that of the ellipsometer (300-1700 nm) for this work. Additional classes of material, such as dielectrics68, are increasingly important in hybrid plasmonic systems as they provide unique functionalities and lower losses than metal plasmonics 69–71 important for sensing and surface enhanced spectroscopy applications. Such materials can also be incorporated using a similar approach, but care must be taken to include both dielectric and magnetic resonances.

3 HOT-CARRIER DEVICES

A significant amount of energy is transferred from incident light to a nanoparticle’s electrons upon LSPR excitation due to the resonant coupling as outlined in Section 2. The coherent oscillation of electron density has a corresponding energy distribution of electrons associated with their proximity to the lattice ion. 72 Higher energy electrons have a lower oscillation frequency than lower energy electrons, which then gradually grow out of phase in a process known as Landau damping. As the LSPR decays within a few femtoseconds 73, the energy can be lost into two distinct pathways: radiative decay (emission of a photon) or nonradiative decay (generation of an electron-hole pair through interband or intraband electron transition74). Although the nonradiative pathway can be deleterious to device performance due to the eventual rise in lattice temperature, a wealth of hot carrier devices have used the energy stored in the plasmon-excited electrons before they thermalize with the lattice. 75,76 Such devices circumvent the typical loss problems characteristic to plasmonic devices and give a larger window to harness the energy extracted from light. Such devices include photodetectors and photovoltaic devices that operate below the bandgap of the involved semiconductor as well as photocatalytic applications.

3.1 Sub-Bandgap Photodetection

Conventional semiconductor-based photodetectors are a staple in most optics and photonics applications and rely on an incident photon exciting an electron across the bandgap of the semiconductor. As such, only photons whose energy is above the bandgap are detected, restricting the operation range. For silicon detectors this cutoff is at 1100 nm, preventing any detection at telecommunication wavelengths (1530-1565 nm). This can be circumvented by exploiting the band-bending behaviour at metal-semiconductor interfaces.77 Upon contacting a metal and a semiconductor there could in certain cases be a net migration of electrons from the metal to the surface of the semiconductor, forming an accumulation layer at the semiconductor surface. These electrons act as barrier for subsequent electrons to cross into the semiconductor in what is called a Schottky barrier of particular height ϕ B determined by the properties of the two materials involved (Figure 4a). This acts as a rectifying diode where hot electrons with sufficient energy to cross the barrier will remain in the

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semiconductor’s conduction band due to the electric field formed at the interface. This process is termed internal photoemission78 and allows sub-bandgap energy photons to excite electrons in the metal and be harvested as a current, effectively increasing the absorption range to lower energies not possible with the semiconductor alone. This process is described by Fowler theory79 and decomposes the electron momentum into tangential and normal components to more accurately quantify the efficiency of injection. Furthermore, the use of plasmon resonances to increase absorption has the potential to enhance the overall efficiency of the internal photoemission process.

Although Schottky barrier photodetectors have been used for over a decade,80,81 in 2011 the collection of hot electrons resulting from the decay of plasmon resonances in gold nanoparticles was experimentally demonstrated.82 Using the Schottky barrier formed between the n-Si substrate and Ti adhesion layer, the excited electrons are harvested as a photocurrent at photon energies below 1650 nm. However, the responsivity (photocurrent extracted per unit of input laser power) is much lower when the plasmon resonance is tuned into the IR simply due to the material limitation of gold. Nevertheless, this spawned an enthusiastic response with the application of this concept to different metals (Ag83, Al18,84) and many different geometries82,84–86. There is a recent comprehensive review of these hot electron photodetectors87 which goes beyond metal-semiconductor interfaces to look at using 2D materials for electron collection. The review subdivides the Schottky detectors into free space and on-chip devices, the latter of which are interfaced with conventional Si photonic waveguides. In each case, silicon plays a critical role and will be the focus of our calculations in this section.

We investigate the development of a plasmonic-enhanced hot electron photodetector operating at 1550 nm comprised of a spherical metal particle embedded in n-Si. As such, we need a metal that forms a Schottky barrier with Si with height that is lower than the energy of the exciting photons (0.8 eV). With the electron affinity of Si ( χ Si¿ being treated as a fixed quantity (4.05 eV), it is the metal work function (ϕ M) that determines the barrier height through ϕ B

e =ϕM− χ Si.77 If we require the barrier to be greater than 0 (to form a

Schottky barrier) and below 0.8 eV this imposes the restriction4.05 eV <ϕMe <4.85 eV . In addition to the

electron Schottky barrier formed with n-Si, it is also possible to harvest energetic holes using a Schottky barrier formed with the valence band of p-Si (Figure 4b). In some materials, such as gold, interband transitions result in higher energy holes than electrons based on the band and these holes can be harvested at a Schottky barrier. 88 The Schottky barrier in this case is defined as ϕ B

h =Eg+ χSi−Φ M.77 Using the bandgap of Si (1.1 eV), the

metal work function is then restricted within the range 4.35 eV <ϕMh <5.15 eV to form the required Schottky

barrier. Figure 4c shows the range of work function values in literature for each of the materials used in this study with shading corresponding to the whether it forms an n-type (red), p-type (blue), or either p- or n-type Schottky (purple) with barrier below 0.8 eV.

Knowing the compatible materials, we now look to quantify a figure of merit for the corresponding operation of the embedded sphere in the Si. We seek efficient generation of carriers within the particle resulting from the generation and decay of the plasmon resonance as well as maximal collection at the semiconductor interface. Through Mie theory, the electron excitation is quantified by the absorbed power via the absorption efficiency (Q|¿|¿). The collection efficiency at an energy E above the fermi level (here assumed to be 0.8 eV corresponding to 1550 nm) can be estimated using the modified Fowler yield79, where EF is the Fermi energy of the material.

Y F ( E )=( E−ϕB )2

8 EF E

This quantifies the injection probability taking into account the relative energy between the electron, the barrier, and the electronic properties of the material through EF. To quantify the entire process, we look at overall photodetection efficiency at 1550 nm (ηPD=Q|¿|Y F¿) shown in Figures 4e and 4f for n-type and p-type Schottky contact respectively. This does not account for any shape-related effects89, electron tunneling90 or interfacial states91 that may increase the electron yield measured in experiments. When comparing the total figure of merit and the absorption cross-section at 1550 nm, shown in Figure 4d, it is apparent that it is imperative to include the Fowler factor. As the extraction probability scales with the square of the difference between the electron energy and Schottky barrier height, the work function of the material is the most critical factor in determining the overall efficiency. This is exemplified with SRO in that, even with the large absorption cross-section, its large barrier limits its effectiveness particularly in the n-type configuration. Through efficient infrared absorption and low Schottky barriers, Mo, Ti, TiN and TiON can each form a low barrier with n-Si (ϕ B

n 0.5 eV ) for photodetection at 1550 nm. Although the work function of Ti, TiN and TiON can vary over a

9

wide range, the ability to tune this value has been demonstrated for use in field effect transistors (FETs)92. For hole based photodetection at this telecom wavelength, Pd has the highest figure of merit, again due to the low Schottky barrier formed (ϕ B

p 0.1 eV ¿. We also note the use of bimetallic material stacks such as Ti/Au82, in literature. Although not included in this study for simplicity, one can easily extend our model to account for these conditions.

Figure 4 | Schottky barrier figure of merit. Schematic of (a) n- and (b) p-type Schottky barriers formed between a metal with fermi level EF

M and a semiconductor with bandgap energy Eg and fermi level EFS . When

the two Fermi levels are equated, a barrier forms due to the interfacial charge layer for either electrons ϕ Bn or

holes ϕ Bp . (c) Reported work functions of the respective materials. Blue (red) shaded region shows range of

possible work functions that form a hole (electron) Schottky barrier with silicon with barrier heights less than 0.8 eV (1550 nm). (d) Optimized absorption cross-sections at 1550 nm and their corresponding barrier

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a b

c d

e f

formation with Si: blue (p-type), red (n-type), purple (either p- or n-type) and grey (neither/unknown). The final optimized figure of merit taking into consideration both absorption and injection probability for (e) n-type and (f) p-type Schottky contact.

3.2 Plasmon-Enhanced Solar Energy Conversion

We are at a critical point in time where our dependence on fossil fuels must be reduced in favor of clean, renewable sources of energy to combat the effects of climate change and global warming. The strong interaction of the free electrons in metals with visible and ultraviolet light make plasmonics an ideal platform for this endeavor. The spectral irradiance of sunlight at sea level is shown in Figure 5a. An ideal metal would have broadband absorption across this range with a plasmon resonance peak in the range of 500-700 nm. Three exemplary absorption cross sections are shown in Figure 5a for Ag (red), Au (blue) and TiN (green) spheres in air with radii of 80 nm. The broadband absorption of TiN allows infrared light to be harvested in addition to the efficient visible absorption offering direct advantages over gold at this particular size, which has been demonstrated experimentally28. As it is critical to understand the interaction with sunlight to best implement a material, each figure of merit will be weighted by the sun’s spectral irradiance denoted by E ( λ ).

A previous review of refractory conductive plasmonics37 considered this problem and introduced a figure of merit of an integrated absorption cross section I Q|¿|¿ defined as:

I Q|¿|= ∫

300nm

1300nm

Q|¿|( λ ) E ( λ )dλ ¿¿

where Q|¿|( λ ) ¿ is the absorption cross section at a particular radius as a function of wavelength. As this characterizes the efficiency of collecting energy in the form of energetic electrons, it is important to understand how this energy is then utilized for energetic applications. In this work we examine two methods: storing energetic electrons in chemical bonds, for instance to catalyze H2O resulting in H2 fuel, and using plasmonic particles to enhance the absorption of photovoltaic cells. Use of this figure of merit does not account for variations in carrier mobility and electron-phonon scattering times, which can limit the number of electrons reaching the operative surface. However, as absorption is assumed to be related to the internal field generated by the surface plasmon mode, electrons are excited throughout the volume of the nanoparticle with the highest generation occurring at the nanoparticle surface. As such, this can still act as a useful comparison of materials for such applications as a larger I Q|¿|¿ will result in more carriers excited at the interface but may underestimate the efficiency of high mobility materials.

In water splitting applications, energy from sunlight is converted into chemical energy. Both plasmon-excited electrons and holes participate in the photocatalytic reaction of converting H 2O to O2 and H2 gases, the latter of which can be used as a fuel. During the reaction, photo-excited holes are responsible for the generation of the O2 gas whereas the electrons participate in the generation of H2. The reaction proceeds as follows93–95:

H2O+2h+¿ →2 H+¿+1

2O2 ¿

¿

2 H+¿+2 e−¿ →H 2¿ ¿

Through the use of co-catalysts, this reaction can occur spontaneously and has led to the development of autonomous photosynthetic devices.96 Again, this relies on efficient generation of electrons within the plasmonic component using visible light and we look to the I Q|¿|¿ to quantify this. Figure 5b shows the optimized values for spherical nanoparticles submerged in water where I Q|¿|¿ is maximized by varying the particle size. Not surprisingly, the noble metals are out performed by all other material groups as their high carrier concentrations and correspondingly high plasma frequencies make it difficult to absorb infrared light without more complex geometries. 97,98 We observe that the partially oxidized CuxOy has the highest integrated absorption efficiency in water as a result of its broader resonance (increased Drude loss term) and red-shifted crossover wavelength compared to pure copper due to incorporation of oxygen and decrease in the free carrier concentration. A similar behaviour is also observed between TiN and TiON. Although, this was framed in the context of solar water splitting, it can be extended to catalysis of environmental pollutants such as CO 2 by changing the surrounding refractive index to air (n=1). The results of this are shown in Supplementary Section S2.

In silicon-based photovoltaic cells, the inefficient absorption of the indirect bandgap requires thick layers (hundreds of microns99) to achieve competitive conversion efficiencies which remain the largest cost in solar cell production. The inclusion of plasmonic particles can compensate for the weak infrared absorption and has the potential to make a considerable impact in the development of thin film photovoltaic cells100,101. The

11

broad absorption of plasmonic particles can be used to harness energy from photons with insufficient energy to excite electrons across the semiconductor bandgap102–104 or to scatter light into the active layer.105–108 For sub-bandgap absorption and collection using hot carriers, we use the integrated collection efficiency:

ICE= ∫300nm

1300nm

Q|¿|( λ ) E ( λ )Y F (λ)dλ ¿

Similar to the sub-bandgap photovoltaics, this figure of merit does not account for any shape-related effects 89, electron tunneling90 or interfacial states91 that may increase the electron yield measured in experiments. Figure 5c shows ICE for the materials forming a Schottky barrier with n-type Silicon embedded in the semiconductor. Embedded particles provide the maximum collection area as transfer can occur at any surface leading to improved collection efficiencies.62 The high refractive index of silicon dramatically changes the resonance behaviour of the sphere. The Fröhlich condition, for example, is now at the wavelength where ϵ ≈−7 rendering most of the oxides (SMO, SNO, SRO), W, and Ti inoperative due to their low magnitude of the real part of the permittivity. However, this new condition is advantageous for the noble metals as this redshifts the resonance giving a higher overall absorption, which gives Ag the highest figure of merit.

To examine the suitability of materials for light trapping via scattering, we must consider the relative amount of light scattered to absorbed and define our scattering efficiency as:

Δ P= ∫300 nm

1300nm

¿¿

We define the σ Sca and σ|¿|¿ for a spherical particle embedded in silicon and vary the particle radius between 10 nm and 200 nm to find the highest Δ P. The optimized size for each material is the maximum of the range (R=200 nm) as the scattering cross section scales with the size of the particle and the absorption cross section is much smaller at larger particle sizes. Nevertheless, the absolute value of Δ P does vary between materials by over an order of magnitude. We observe the conventional noble metals (Cu, Au, Al, and Ag) outperforming all other materials due to their weak absorption across the solar spectrum for particles this large. A previous report108 examined arrays of Ag, Au and Al nanoparticles in air for scattering into a GaAs substrate. They restrict their investigation to one particle size, R=80 nm and find that aluminum is superior to Ag and Au. In Supplementary Section S4 we apply our figure of merit calculations under these circumstances and reproduce their conclusion that Al is best using literature values from Palik. Even without including the synergistic effects of exciting closely spaced particles, our analysis can still select the superior material for these applications. Additionally, partially embedding the particles in the substrate can be used to selectively guide the light.

12

a b

d

Figure 5 | Solar energy harvesting figure of merit. (a) Absorption cross sections of R=80 nm particles of Ag (red), Au (blue) and TiN (green) plotted on top of the solar spectrum (grey) demonstrating the advantage of broadband absorption in the visible and near-infrared. (b) Optimized integrated absorption efficiency of particles in water for solar photocatalysis applications. (c) Optimized integrated collection efficiencies (ICE) of particles embedded for silicon for sub-bandgap excitation with sunlight and collection into the conduction band of silicon. (d) Integrated power differential in silicon for R=200 nm particles embedded in silicon for in-plane scattering to enhance semiconductor absorption efficiencies.

4 THERMOPLASMONIC APPLICATIONS

Conventionally, the heat generated from the nonradiative relaxation of surface plasmon modes is believed to be deleterious to device performance. The elevated temperatures can deform the metallic particles, dramatically altering their performance109 and heat the surrounding materials causing faster device degradation.11 This has required materials with higher thermal stability, termed refractory metals, which includes metal nitrides and metals known to resist high temperatures such as Mo and W. However, recently there has been significant interest in harnessing the unavoidable heating of plasmonic structures for productive purposes. The ability to generate heat in the immediate vicinity of the metal particle has allowed for heating with nanoscale precision. This ability to selectively heat desired areas is of paramount importance to control chemical reactions110 and the response of biological systems111. Here we investigate the use of heated plasmonic particles in nanotherapeutics such as cancer therapy112,113 and in vivo bacterial annihilation114. We also address using plasmonic particles in integrated in vitro studies for compact lab-on-a-chip applications.115

4.1 Photothermal Nanotherapeutics

To maintain optimal functioning, homeostatic mechanisms have evolved in many organisms to maintain ideal conditions for cell function which includes controlling temperature, pH, and osmotic concentrations. Without these in place, cells within the organism can fail to perform their functions116 or degrade altogether due to increased fluidity of the cell membrane.117 The temperature sensitivity of cells is exploited in photothermal nanotherapuetics where nanoparticles selectively bind to the membrane of a targeted cell-type118 and are then heated using pulsed or continuous wave (CW) laser illumination. The heat generated in the vicinity of the nanoparticle has the potential to degrade the cell membrane resulting in the release of cellular contents in a process termed cell necrosis.119,120 It has also been shown that heat generated from these particles can activate natural apoptosis pathways also resulting in cell death.121 The targeted heating of noble metal nanoparticles has already been successfully used in the elimination of bacteria,114 targeted drug delivery,122 and destruction of tumor cells in mammals112,119,121. The selectivity provides a significant advantage over conventional systemic cancer treatments such as radiation and chemotherapy as neighboring tissue remains unharmed.

For such in-vivo applications, laser excitation must be within the biological transparency window (800-1000 nm) where tissue is maximally transmissive. This coincides with absorption minima of water, hemoglobin (Hb) and oxygen-bonded hemoglobin (HbO2) which make up the bulk of tissue. However, even in this regime the penetration depth of the infrared light is only several centimeters.123 Furthermore, the size of the particle plays a critical role in the development vivo treatments. Particles smaller than 10 nm are rapidly cleared via the kidney and do not allow for sufficient accumulation. 124 Particles with diameters between 50 nm and 250 nm

13

c

were shown to be efficiently cleared by the liver without significant accumulation in other organs. 125 As such, the ideal material for such applications is one that is non-toxic to humans and animal life that heats efficiently in the infrared with sizes between 50-250 nm. This requires a close examination of both plasmonic and thermal properties to characterize the associated temperature change. Thus far, gold particles have dominated the field as gold is known to be inert and non-toxic. To improve absorption in the near-infrared, more complex geometries are required such as nanoshells and nanocages.126,127 This can potentially be avoided by looking to non-toxic materials with preferential absorption properties including titanium nitride and titanium oxynitirde.128

Previous work has looked at quantifying a particle’s ability to generate heat for photothermal applications36 and compared between noble metals and transition metal nitrides. However, the ability to generate heat does not directly quantify its applicability to photothermal applications as the relationship between thermal energy and temperature is determined by material-dependent thermal properties. For this reason, we estimate the temperature change corresponding to the energy absorbed by the plasmonic mode in both continuous wave (CW) and pulsed excitation. Under CW illumination, a spherical particle of radius a ≤ 200 nm will reach a steady-state on the order of nanoseconds129 (τ tr ≈ a2CV /3 κ S where CV is the volumetric heat capacity of the particle and κS the thermal conductivity of the surrounding media130). Given an absorbed power P|¿|¿ by a particle of radius a, the steady-state temperature of the particle is calculated using only the surrounding media’s thermal conductivity (κS) by the following expression:131,132

ΔT CW=P|¿|

4 π κ s a¿

The power absorbed is quantified by the absorption cross-section (σ|¿|¿), which gives P|¿|=σ|¿|S0 ¿¿ where again S0 is the incident irradiance in W ⋅m−2. In Figure 6a, we calculate the steady state temperature change ΔT under 830 nm CW illumination for an incident irradiance of 1 mW /μm2 of a particle submerged in water. In addition, we color-coded the plot according to known toxicity to humans with nontoxic materials shown in green, toxic materials in red, and grey for unknown toxicity. The optimized particle size for each of the reported temperature changes is presented in Supplementary Section S9. TiON and Ti show the most promise for photothermal applications due to their low toxicity and efficient infrared absorption showing an order of magnitude larger temperature increase than gold. SMO, SNO, and SRO also show very high equilibrium temperature changes but would be best suited for in vitro biological applications due to the inclusion of strontium, which is known to be toxic to humans.

Under ultrafast pulsed illumination, the thermal properties of the absorbing material strongly influence the maximum change in temperature experienced by the nanoparticle. Due to the absorption throughout the nanoparticle volume and the high thermal conductivity due to the free electrons present, we assume that the heat energy generated inside the particle results in a uniform temperature distribution. For lifetimes shorter than the transient lifetime τ tr mentioned above a large nonthermal electron distribution is generated, which thermalize with other electrons (tens of femtoseconds) and phonons (picoseconds), which then dissipate to the environment. This results in a sharp increase of the maximum temperature compared to CW illumination and the maximum uniform temperature achieved by the illuminated particle is calculated by the energy absorbed and the volumetric heat capacity of the material (CV ¿ as129:

ΔT Pulse=σ|¿|F

V CV¿

where F is the laser fluence of the nanosecond pulse and V the particle volume. In Figure 6b, we show the calculated temperature change under pulsed illumination at 830 nm with a laser fluence of 2.5 mJ /c m2 in water. The volumetric heat capacity values used are shown in Table 1 and the optimized particle size for each of the reported temperature changes is presented in Supplementary Section S9. As there are currently no reported heat capacity values for NbN, SMO nor SRO and as a result these have been omitted from the calculation. Again, titanium is shown to be superior under these particular illumination conditions and with its low toxicity133 has the potential to dramatically improve the efficiency over gold photothermal therapeutic treatments when considering only spherical colloids. It should be noted that special consideration needs to paid to the uptake of the particles into the tumour cells, which is heavily dependent surface conjugation of the particle and the type of cancer. 118

14

Figure 6 | Laser-induced temperature changes for photothermal applications. Single particle temperature changes under (a) continuous wave (CW) [830 nm, 1 mW /μ m2] and (b) pulsed illumination [2.5 mJ /c m2¿. Colour indicates toxicity in humans: green (non-toxic), red (toxic) and grey (toxicity unknown). Lower images show the heating of a dimer system with 10 nm separation under (c) continuous wave (CW) [830 nm, 1mW /μm2] and (d) pulsed illumination [2.5 mJ /c m2¿.

4.2 Thermal Control of Biological Processes

Localized heating remains a common method of controlling the kinetics of chemical reactions by supplying the necessary activation energy. As many biological processes rely on chemical reactions and interactions, the ability to target and heat specific molecules is invaluable to understanding and controlling these complex processes. The strong photothermal conversion of plasmonic particles allows for nanoscale precision heating without influencing surrounding molecules. This specificity has allowed for the selective deletion of genes within a chromosome134, phenotyping of cancerous cells135, and protein manipulation.136 By conjugating the surface of a plasmonic particle with DNA or RNA molecules, these photothermal processes can be reversible by allowing the molecules to naturally recombine with complementary strands.115,137 This can be extended to complex networks of gold-nucleic acid conjugates135 allowing for larger-scale studies of single-cell properties. These applications take advantage of the enhanced absorption and electric field that occurs when the coupled resonance of two closely-spaced nanoparticles is excited, frequently called a plasmonic ‘hot-spot’. 138 The ability to control such processes is of particular interest to cancer probing techniques including DNA/RNA fluorescence in situ hybridization (FISH).139

The coupled resonance of two nanoparticles is a result of the Coulombic repulsion of the electrons of the respective particles acting as an additional driving force. The coupled mode is characterized by an increase in scattering and absorption as well as a red-shifting of the plasmon resonance described by the plasmon ruler equation.140 This coupled interaction increases each of the particles’ interaction with incident light resulting in an increase in the effective polarizability of each particle caused by the presence of the other. We hope to use

15

c

a b

d

this increased absorption to control the heating of two coupled particles previously used in DNA melting and hybridization applications115. In addition, such a process can be used to enhance the efficiency of photothermal nanotherapeutics considered in the previous section or non-biological photothermal processes such as thermophotovoltaics.141 The influence of the coupling on the absorptive properties of the nanoparticles themselves has been studied via this modified polariazibility.142 In this work, they quantify the enhanced power absorption of each particle through an expression depending on a ratio of particle diameter (D) and gap (g). Letting α=D / (D+g) the absorbed power enhancement is given by:

PDimer

PSingle=η=

16 [ ( ϵ r+2 ϵ s )2+ϵ i2 ]

{[4−α3 ] ϵ r+[8+α3 ] ϵ s }2+[ 4−α 3 ]2+ϵ i

2

where ϵ r and ϵ i are the real and imaginary parts of the dielectric function, respectively. Through this we can

now define a dimer enhanced absorption efficiency as Q|¿2|=η Q|¿1|¿ ¿, where Q|¿1|¿ is the absorption cross section of a single sphere. In Supplementary Section S5 we plot the optimized values for the dimer efficiency (η) and enhanced absorption efficiency (Q|¿2|¿for the various materials under 830 nm illumination with a gap of 10 nm. We observe that CuxOy and TiN have the highest absorption enhancement in the presence of an adjacent particle almost over doubling its absorption cross section. However, when considering the resultant absorption cross-section, TiON outperforms TiN due to the proximity of the maximum absorption cross-section to the excitation wavelength.

For consistency, we calculate the maximum temperature difference of the dimer system in water under 830 nm illumination with both CW and pulsed illumination. Similarly, to the previous section, we use an exemplary CW excitation of 1 mW/μm2 and calculate the steady state temperature of the system, shown in Figure 6c. When accounting for the size of the particle, the most efficient materials at heating under these illumination conditions are CuxOy and TiON for their originally high absorption cross sections and efficient dimer coupling. However, when comparing Figures 6a and 6c the advantage of using a dimer system are apparent, with higher temperature changes under the same illumination conditions, requiring lower laser powers for the same effects and so potentially reducing interference with surrounding biological molecules. With pulsed illumination, again with an example fluence of 25 J/cm2 we see a change in behaviour compared to CW illumination as the thermal properties of the absorbing material are accounted for. Here, we see Ti with the superior performance due to its strong infrared absorption and preferable thermal properties resulting in large temperature changes. Although CW illumination is typically used in biological measurements, pulsed excitation can be extremely useful in monitoring biological processes. This is due to the temporal width of the laser pulse being shorter than the typical timescales of many biological processes, so they can be measured without interference of the externally applied field. Special attention should be paid to the surface damping of the plasmon resonances resulting from ligand or other chemical surfactants that may broaden or shift the plasmon resonance.118,143

5 SENSING AND NEAR-FIELD APPLICATIONS

A breadth of plasmonic applications relies on the interaction of the resonantly driven electrons and the particle’s environment via the generated dipole-like electric field. As outlined when discussing the LSPR resonance condition in Section 2, the spectral position of the resonance peak depends on the contrast between the permittivity of the particle and its surroundings. Not only can this provide a means of tuning the plasmon resonance, but conversely, changes in the dielectric environment can be detected as changes to the plasmon resonance peak. This has led to sensors which can detect the presence of a target molecule ultra-low concentrations144 that can easily be scaled for relatively low cost.145 This principle has also been extended to enhance the functionality of solid state lighting which include light emitting diode (LED) and quantum dot (QD) televisions. By coupling a plasmonic antenna to a nearby emitter (LED, QD) the far field radiation can be enhanced over the efficiency of the emitter alone by emitting via plasmonic modes146. Such applications require both spatial proximity and spectral overlap, as well as a thorough understanding of the near-field properties of the particle.

5.1 Refractive Index Sensing

Metallic nanoparticles can be used to detect minute changes in the vicinity of the particle by exploiting the sensitivity of plasmon resonances to the properties of the surrounding dielectric media. This has proven

16

invaluable in detecting biological molecules as conventional biological detection techniques (using labels147 and mass spectroscopy148) can interfere with or completely destroy the target molecule.149 LSPR biosensing was demonstrated to be an inexpensive, sensitive and high-throughput technique for the detection and observation of a wide range of membrane proteins150 and protein interactions151, cancer cells,152 and bacteria153 even in ultralow concentrations down to ~150 fg/mL.144 By functionalizing the surface of the nanoparticle with specific antibodies, the target cell or molecule can be adsorbed to the surface. As this molecule has a different refractive index to the surrounding solution (Δn) the particle’s plasmon resonance peak shifts by Δλ=m ( Δn ) [1−exp (−2 d / ld ) ] 154 where m is the refractive index sensitivity, d is the distance of the analyte molecule from the surface and ld is the decay length of the electromagnetic field. The refractive index sensitivity is dependent on the material being used as the resonance profile depends on the refractive index contrast between the material and its surroundings. Neglected from this examination is the decrease in sensitivity as the plasmon decays with distance from the particle.6 The length of the surface molecules should be considered when designing a biosensor.

As detection relies on observing a shift in the plasmon resonance, we must consider the extinction profile of the colloidal particles and the ability to monitor these changes in the far-field. To determine the change in resonance wavelength with refractive index we calculate the extinction cross section using our Mie theory calculations with refractive indices at n=1.33 and n=1.4 as an example. Although the change in refractive index is proportional to the change in resonance wavelength, the ability to resolve small changes relies on the sharpness of the far-field extinction profile. To quantify this, we calculate the full-width half-maximum (FWHM) of the resonance in water (n=1.33). We use the following figure of merit and the equivalent calculation in frequency to evaluate our materials6:

F λ=Δλ

FWH M λFω=

ΔωFWH M ω

This ratio is unitless and balances both requirements of a large spectral shift while maintaining a narrow bandwidth for better resolution. Figure 7a shows the refractive index sensitivity in frequency units ( Fω ) with silver outperforming all other materials due to its small FWHM as a result of its low Drude loss compared to other materials. Supplementary Section S6 shows the wavelength sensitivity (F λ) with a lower absolute value but the order of the materials is roughly preserved.

Figure 7 | Near field applications figure of merit. Refractive index sensitivity calculated in terms of frequency for optimized particle size.

5.2 Solid State Lighting

Light-emitting diodes (LEDs) have provided tremendous improvements over traditional incandescent light bulbs in terms of efficiency (lumens per watt), lifetime, cost, and color range. By electrically exciting

17

electrons across a semiconductor bandgap, the subsequent recombination process results in emission of photon with energy equal to the bandgap of the semiconductor. RGB (red-green-blue) LED displays have been developed by choosing semiconductors with appropriate bandgaps where combinations of the three colors can generate the entire visible spectrum. Quantum dots (QDs), semiconductor nanocrystals, have also been used successfully in displays that take advantage of the fine tunability of emission properties with particle size. 155 The overall efficiency of such semiconductor-based systems is determined by three factors: excitation efficiency (ηexc ¿, radiation efficiency (ηrad), and light extraction efficiency from the device (ηext).156 ηexc and ηrad are intrinsic properties of the system corresponding to the generation of excited carriers and the internal quantum efficiency (IQE) respectively. However, the light extraction efficiency into free space (ηext) can be increased through device engineering to prevent subsequent total internal reflection or absorption. The overall emission efficiency can be enhanced further by coupling the semiconductor emitter to metallic antennas for more efficient radiation into the far field from the coupled sytsem.157

By bringing an antenna into close proximity with the emitter, the modification of the local density of states can provide additional far-field radiation channels enhancing the overall radiation efficiency of the coupled system. However, for metallic antennas this also provides additional nonradiative loss channels that must be balanced when including the antenna. 146,158–160 From comprehensive theoretical studies161,162 it is known that the overall fluorescent enhancement can be quantified by the following expression at the emitter wavelength (λEm):

q ( λEm)=ΓRAD /Γ 0

P ( λEm )+1−q0 ( λEm )

q0 ( λEm )

where Γ RAD / Γ0 is the radiation enhancement factor (with the antenna compared to the bare emitter), P is the Purcell factor and q0 is the intrinsic quantum yield. It was recently shown161 that for high-yield emitters (q0≲1¿ the emission of the emitter is quenched by the nonradiative losses of the antenna. In this case, low-loss dielectric antennas outperform metals. However, in the case of low-yield emitters, metals were shown to outperform dielectrics (Si and GaP) and it is to this range we restrict our analysis.

We look to maximize the radiation enhancement factor (Γ RAD / Γ0) by comparing the various materials and particle sizes. Following a previous comparison between dielectric and plasmonic antennas coupled to a dipole emitter163 we describe the radiative efficiency of the dipole-dipole coupled system in terms of the Mie coefficients (a1 and b1) and a modified separation factor ρ=2πd / λ nd, where d is the separation of the dipole to the center of the antenna, λ is the wavelength of the emitter in vacuum and nd is the refractive index of the surrounding media. For parallel (∥) and perpendicular (⊥) orientation of the two dipoles with respect to the dipolar mode of the antenna, the modified radiation efficiency is given by:

ΓRAD⊥

Γ0=9| j1 ( ρ )−a1 h1

(1 ) ( ρ )ρ |Γ RAD

∥

Γ 0=9

4 [| j1 ( ρ )−b1 ( ρ )h1(1) ( ρ )|2+|(ρ j1 ( ρ ) )'−a1 ( ρh1

(1) ( ρ ) )'

ρ |2]

2

where j1 ( ρ ) and h1( 1) ( ρ ) are the spherical Bessel and Hankel function of the first kind and ( f )' denotes the

derivative of f with respect to ρ.By fixing the spacing between the emitter and antenna surface to be 10 nm, we vary the particle radius

to optimize the radiation efficiency of blue (470 nm), green (540 nm), and red (660 nm) dipole emitters oriented perpendicular to the electric dipole of the antenna plotted in Figures 8a, 8b, and 8c, respectively. Silicon is included as a reference to directly compare the performance of a comparable dielectric antenna. The parallel dipole had emission efficiencies below unity, except for Si. As seen for blue light emission (Figure 7b), silver is predicted to be more efficient than aluminum and both are much more efficient than gold. This precisely coincides with experimental results of surface plasmon enhanced light emission of InGaN quantum wells. 164 However, for both green and blue emission Ag outperforms all other materials by a substantial amount due to its low loss and weak dispersion. In red emission enhancement, Au performs the best due to the proximity of the scattering maxima to the target wavelength.

18

Figure 8 | The optimized antenna-enhanced far-field radiation enhancement factor are calculated for (b) blue (470 nm) (c) green (470 nm) and (d) red (660 nm) dipole emitters placed 10 nm from the surface of particle oriented perpendicular to the electric dipole mode of the antenna.

6 PERSPECTIVES AND OUTLOOK

For the future development of plasmonics and the wider implementation in industrial settings, the tradeoff between efficiency and price must be considered as well. In Figure 9 we capture this tradeoff by plotting the price (in USD/mm3) against the maximum absorption and scattering cross sections. The low material cost is a primary advantage of some of the novel materials, as conventional materials (Au and Ag) are some of the most expensive. In many applications, the infrared materials (Ti, TiN, TiON, SNO, SRO) provide lower cost along with the ability to use smaller particles may make them more attractive even if it requires sacrificing some efficiency. In this work, we have described both the material and size-dependence of the underlying physical processes of plasmonic applications to evaluate a wide range of materials across many material classes. With an ever-growing library of plasmonic materials and the continued development of novel applications, such a systematic method is critical to unite the material science and device engineering aspects quantitatively. Our quick and inexpensive method allows for such predictions without any need for nanofabrication. It requires only simple descriptions of the electronic and optical properties of a thin film measured using standard optical characterization techniques. From there, we use well-established mode calculations and a deep understanding of some of the cutting-edge plasmonic applications to make direct predictions on device functionality. We have performed the analysis for applications under three overarching categories: hot electron applications,

19

a b

c

photothermal applications, and sensing and near-field applications. We consolidate our results in Table 3 along with benchmark comparisons with the state-of-the-art devices found in literature. Each of the proposed devices offers an advantage over the existing applications though either favourable optical properties, electronic properties, or easier fabrication. To accelerate the development of plasmonic devices to a point where the experimentally and theoretically-predicted advantages can begin to make a meaningful impact on our world, we must unite all aspects of the interdisciplinary research including theoretical modelling, material science, experimental characterization and device engineering.

20

Figure 9| Enhancement and price comparison. The maximum (a) scattering enhancement factor (QScat) and (b) absorption enhancement factor (Q|¿|¿) and the corresponding price in USD per mm3.

Application Figure of Merit

λ(nm)

Current State-of-the-

Art

Estimated FoM

Proposed Material

Radius (nm)

Predicted FoM

Hot Electron Devices and Solar Energy Harvesting

Sub-Bandgap Photodetection

n-type Q|¿|Y F ¿ 1550 Au NP165 r = 31 nm

0.01*(1475 nm) Ti 44 23.4

p-type Q|¿|Y F ¿ 1550 Au Strips166

W = 252 nm 0.12* Pd/SRO 54/47 5.70/3.57

Sub-Bandgap Photovoltaics ICE (n-Si)

300-1300Au on n-Si167

r=2.5 nm 3500* Ag 37 92000

Scattering Enhancement in PV Cells ΔP 300-1300

Al Disk in EY19

r=84nm 32.1* Ag 200 171

Photocatalysis I Q|¿|¿ 300-1300TiN NP168

L=50 nm 901* CuxOy 47 1210

Photothermal Applications

Photothermal Therapy ΔT 830Au Nano-rod169

L=50 nmW=12.5 nm

72 °C* Ti 28 269 °C

DNA/RNA Manipulation

Single Particle ΔT 830 5 nm Cylindrical

Au NP170 2 °C* Mo/Ti 104/100 68 °C/66 °C

Network ΔT 830 Au NP115

r = 30 nm 24 °C* CuxOY/TiON 160/186 104 °C/99 °C

Sensing and Near-Field ApplicationsRefractive Index

Sensing LSPRΔωres

ext

FWH M ω

830 Ag NP171

r = 17.5 nm 2.76 Ag 11 3.22

Solid State Lighting

Red Γ Rad⊥ / Γ0 660 60 nm Au NR in

CuPc172 4.90 Au 80 14.33

Green Γ Rad⊥ / Γ0 540 Au NP in ZnO173

r = 5 nm 1.25 Ag 66 14.73

Blue Γ Rad⊥ / Γ0 470 Al NP174

r = 20 nm 3.30 Ag 55 17.60

Table 3 | Overview and benchmarking of plasmonic applications. For each application the designated figure of merit and operation wavelength are included along with estimated figures of merit for the state-of-the art found in the literature. Finally, the proposed optimal material, particle radius and predicted figure of merit are

21

ba

also presented, showing the possibility of marked improvement over existing devices. Asterisk (*) denotes FDTD calculated parameters.

22

ACKNOWLEDGEMENTS

We acknowledge support from the Engineering and Physical Sciences Research Council (EPSRC) Reactive

Plasmonics Programme (EP/M013812/1), Lee-Lucas Chair in Physics, and the Henry Royce Institute made

through EPSRC grant EP/R00661X/1.

SUPPLEMENTARY INFORMATION

The supplementary information includes a significant amount of range of analytical, experimental and

computational work in addition to raw data. Supplementary Section S1 provides the theoretical background to

Mie theory and provides the equations used to calculate the modes and enhancement factors (via the scattering,

extinction and absorption cross-sections). Supplementary Section S2 shows the integrated absorption efficiency

of particles in air for use in the solar degradation of gaseous pollutants. Supplementary Section S3 compared the

absorption of copper (Cu) and cuprous oxide (CuxOy) particularly for use in solar applications. Supplementary

Section S4 shows a comparison of the integrated power differential fixed at 80 nm, much smaller than what was

used in main body of the text in Section 3.2. Supplementary Section S5 provides the calculated dimer

enhancement factor and dimer-enhanced Q|¿|¿ used to calculate the temperature changes in Section 4.2.

Supplementary Section S6 shows the wavelength-domain counterpart to the frequency-domain refractive index

sensing sensitivity in Section 5.1. Supplementary Section S7 gives a detailed explanation of the determination of

optical parameters using spectroscopic ellipsometry and how the appropriate model is decided along with mean-

squared errors associated with each material. Supplementary Section S8 describes the deposition details for each

of the films in this work. Finally, Supplementary Section S9 provides the raw data used to make the figures of

merit figures including particle radius and exact figure of merit for each application. In supplementary Section

S10 we compare our approach with experimentally measured data from literature.

23

REFERENCES

1. Ritchie, R. H. Plasma Losses by Fast Electrons in Thin Films. Phys. Rev. 106, 874–881 (1957).2. Maier, S. A. et al. Plasmonics-a route to nanoscale optical devices. Adv. Mater. 13, 1501–1505 (2001).3. Gramotnev, D. K. & Bozhevolnyi, S. I. Plasmonics beyond the diffraction limit. Nat. Photonics 4, 83–

91 (2010).4. Simoncelli, S., Li, Y., Cortes, E. & Maier, S. A. Imaging Plasmon Hybridization of Fano Resonances

via Hot-Electron-Mediated Absorption Mapping. Nano Lett. 1–7 (2018). doi:10.1021/acs.nanolett.8b00302

5. Willets, K. A., Wilson, A. J., Sundaresan, V. & Joshi, P. B. Super-Resolution Imaging and Plasmonics. Chem. Rev. 117, 7538–7582 (2017).

6. Li, J. et al. Revisiting the surface sensitivity of nanoplasmonic biosensors. ACS Photonics 2, 425–431 (2015).

7. Brolo, A. G. Plasmonics for future biosensors. Nat. Photonics 6, 709–713 (2012).8. Mosier-Boss, P. Review of SERS Substrates for Chemical Sensing. Nanomaterials 7, 142 (2017).9. Wilcox, W. R. & LaChapelle, T. J. Mechanism of gold diffusion into silicon. J. Appl. Phys. 35, 240–246

(1964).10. Köllensperger, P. A., Karl, W. J., Ahmad, M. M., Pike, W. T. & Green, M. Patterning of platinum (Pt)

thin films by chemical wet etching in Aqua Regia. J. Micromechanics Microengineering 22, 067001 (2012).

11. Zhou, N. et al. Plasmonic near-field transducer for heat-assisted magnetic recording. Nanophotonics 3, 141–155 (2014).

12. Zharov, V. P., Mercer, K. E., Galitovskaya, E. N. & Smeltzer, M. S. Photothermal nanotherapeutics and nanodiagnostics for selective killing of bacteria targeted with gold nanoparticles. Biophys. J. 90, 619–627 (2006).

13. Li, W. & Valentine, J. G. Harvesting the loss: Surface plasmon-based hot electron photodetection. Nanophotonics 6, 177–191 (2017).

14. Tittl, A. et al. Palladium-based plasmonic perfect absorber in the visible wavelength range and its application to hydrogen sensing. Nano Lett. 11, 4366–4369 (2011).

15. Sterl, F. et al. Magnesium as novel material for active plasmonics in the visible wavelength range. Nano Lett. 15, 7949–7955 (2015).

16. Strohfeldt, N. et al. Yttrium hydride nanoantennas for active plasmonics. Nano Lett. 14, 1140–1147 (2014).

17. Watson, A. M. et al. Rhodium nanoparticles for ultraviolet plasmonics. Nano Lett. 15, 1095–1100 (2015).

18. Gong, T. & Munday, J. N. Aluminum-based hot carrier plasmonics. Appl. Phys. Lett. 110, 1–6 (2017).19. Lee, M. et al. Aluminum Nanoarrays for Plasmon-Enhanced Light Harvesting. ACS Nano 9, 6206–6213

(2015).20. Lombardo, S. et al. Plasmonic modes in molybdenum ultra-thin films suitable for hydrogenated

amorphous silicon thin film solar cells. Energy Procedia 44, 216–222 (2014).21. Bagheri, S. et al. Niobium as Alternative Material for Refractory and Active Plasmonics. ACS

Photonics 5, 3298–3304 (2018).22. Pirzadeh, Z., Pakizeh, T., Miljkovic, V., Langhammer, C. & Dmitriev, A. Plasmon-Interband Coupling

in Nickel Nanoantennas. ACS Photonics 1, 158–162 (2014).23. Vorobyev, A. Y. & Guo, C. Femtosecond laser-induced periodic surface structure formation on

tungsten. J. Appl. Phys. 104, (2008).24. Hsun Su, Y., Hsu, C. Y., Chang, C. C., Tu, S. L. & Shen, Y. H. Ultra-thin titanium nanolayers for

plasmon-assisted enhancement of bioluminescence of chloroplast in biological light emitting devices. Appl. Phys. Lett. 103, (2013).

25. Patsalas, P., Kalfagiannis, N. & Kassavetis, S. Optical properties and plasmonic performance of titanium nitride. Materials (Basel). 8, 3128–3154 (2015).

26. Li, W. et al. Refractory plasmonics with titanium nitride: Broadband. Adv. Mater. 26, 7959–7965 (2014).

27. Braic, L. et al. Titanium Oxynitride Thin Films with Tunable Double Epsilon-Near-Zero Behavior for Nanophotonic Applications. ACS Appl. Mater. Interfaces 9, 29857–29862 (2017).

28. Naldoni, A. et al. Broadband Hot-Electron Collection for Solar Water Splitting with Plasmonic Titanium Nitride. Adv. Opt. Mater. 5, 1601031 (2017).

29. Guler, U. et al. Local heating with lithographically fabricated plasmonic titanium nitride nanoparticles. Nano Lett. 13, 6078–6083 (2013).

24

30. Naik, G. V., Kim, J. & Boltasseva, A. Oxides and nitrides as alternative plasmonic materials in the optical range. Opt. Mater. Express 1, 1090–1099 (2011).

31. Wells, M. P. et al. Tunable, Low Optical Loss Strontium Molybdate Thin Films for Plasmonic Applications. Adv. Opt. Mater. (2017). doi:10.1002/adom.201700622

32. Wan, D. Y. et al. Electron transport and visible light absorption in a plasmonic photocatalyst based on strontium niobate. Nat. Commun. 8, 1–9 (2017).

33. Braic, L. et al. Optimizing Strontium Ruthenate Thin Films for Near-Infrared Plasmonic Applications. Sci. Rep. 5, 1–5 (2015).

34. West, P. R. et al. Searching for better plasmonic materials. Laser Photonics Rev. 4, 795–808 (2010).35. Kim, S., Kim, J. M., Park, J. E. & Nam, J. M. Nonnoble-Metal-Based Plasmonic Nanomaterials: Recent

Advances and Future Perspectives. Adv. Mater. 1704528, 1–24 (2018).36. Lalisse, A., Tessier, G., Plain, J. & Baffou, G. Quantifying the Efficiency of Plasmonic Materials for

Near-Field Enhancement and Photothermal Conversion. J. Phys. Chem. C 119, 25518–25528 (2015).37. Kumar, M., Umezawa, N., Ishii, S. & Nagao, T. Examining the Performance of Refractory Conductive

Ceramics as Plasmonic Materials: A Theoretical Approach. ACS Photonics 3, 43–50 (2016).38. Le Ru, E. C., Somerville, W. R. C. & Auguié, B. Radiative correction in approximate treatments of

electromagnetic scattering by point and body scatterers. Phys. Rev. A - At. Mol. Opt. Phys. 87, 1–13 (2013).

39. Ashcroft, N. W. & Mermin, N. D. Solid State Physics. (Brooks/Cole, 1976).40. Tompkins, H. G., Irene, E. A., Hill, C. & Carolina, N. Handbook of Ellipsometry. (2005).

doi:10.1007/3-540-27488-X41. James, F., Shackelford, E. J. F. & Alexander, W. Materials Science Engineering Hand Book. Materials

Science and Engineering Handbook 232, (2001).42. Uda, M., Nakamura, A., Yamamoto, T. & Fujimoto, Y. Work function of polycrystalline Ag, Au and

Al. J. Electron Spectros. Relat. Phenomena 88, 643–648 (1998).43. Uda, M., Nakamura, A., Yamamoto, T. & Fujimoto, Y. Work function of polycrystalline Ag, Au and

Al. J. Electron Spectros. Relat. Phenomena 88, 643–648 (1998).44. Wilson, R. G. Vacuum thermionic work functions of polycrystalline Be, Ti, Cr, Fe, Ni, Cu, Pt, and type

304 stainless steel. J. Appl. Phys. 37, 2261–2267 (1966).45. Michaelson, H. B. The work function of the elements and its periodicity. J. Appl. Phys. 48, 4729–4733

(1977).46. Wilson, R. G. Vacuum thermionic work functions of polycrystalline Nb, Mo, Ta, W, Re, Os, and Ir. J.

Appl. Phys. 37, 3170–3172 (1966).47. Gotoh, Y., Tsuji, H. & Ishikawa, J. Measurement of work function of transition metal nitride and

carbide thin films. J. Vac. Sci. Technol. B Microelectron. Nanom. Struct. 21, 1607 (2003).48. Doiron, B. et al. Optimizing hot electron harvesting at planar metal-semiconductor interfaces with

titanium oxynitride thin films. ArXiv 1–21 (2018).49. Chase, M.W., J. NIST-JANAF Themochemical Tables, Fourth Edition. J. Phys. Chem. Ref. Data

Monograph, 1614 (1998).50. Nakamoto, M. & Moon, J. Suitability of low-work-function titanium nitride coated transfer mold field-

emitter arrays for harsh environment applications. J. Vac. Sci. Technol. B, Nanotechnol. Microelectron. Mater. Process. Meas. Phenom. 29, 02B112 (2011).

51. Didden, A., Battjes, H., MacHunze, R., Dam, B. & Van De Krol, R. Titanium nitride: A new Ohmic contact material for n-type CdS. J. Appl. Phys. 110, (2011).

52. Leitner, J. et al. Heat capacity, enthalpy and entropy of strontium niobate Sr2Nb2O7and calcium niobate Ca2Nb2O7. Thermochim. Acta 475, 33–38 (2008).

53. Hartmann, A. J., Neilson, M., Lamb, R. N., Watanabe, K. & Scott, J. F. Ruthenium oxide and strontium ruthenate electrodes for ferroelectric thin-films capacitors. Appl. Phys. A Mater. Sci. Process. 70, 239–242 (2000).

54. Assimos, J. A. & Trivich, D. The photoelectric threshold, work function, and surface barrier potential of single‐crystal cuprous oxide. Phys. Status Solidi 26, 477–488 (1974).

55. Ru, E. C. Le & Etchegoin, P. G. in Principles of Surface-Enhanced Raman Spectroscopy 589–628 (Elsevier, 2009). doi:https://doi.org/10.1016/B978-0-444-52779-0.00022-2

56. Fang, Z. et al. Graphene-antenna sandwich photodetector. Nano Lett. 12, 3808–3813 (2012).57. Sanchot, A. et al. Plasmonic nanoparticle networks for light and heat concentration. ACS Nano 6, 3434–

3440 (2012).58. Meinzer, N., Barnes, W. L. & Hooper, I. R. Plasmonic meta-atoms and metasurfaces. Nat. Photonics 8,

889–898 (2014).59. Li, J. et al. Ag@Cu2O core-shell nanoparticles as visible-light plasmonic photocatalysts. ACS Catal. 3,

47–51 (2013).

25

60. Liu, S. et al. Au/Ag core-shell nanocuboids for high-efficiency organic solar cells with broadband plasmonic enhancement. Energy Environ. Sci. 9, 898–905 (2016).

61. Tan, S. et al. Plasmonic coupling at a metal/semiconductor interface. Nat. Photonics 11, 806–8012 (2017).

62. Knight, M. W. et al. Embedding plasmonic nanostructure diodes enhances hot electron emission. Nano Lett. 13, 1687–1692 (2013).

63. Kumari, S. & Moirangthem, R. S. Development of cost-effective plasmonic biosensor using partially embedded gold nanoparticles for detection of immunoglobulin proteins. Mater. Res. Express 5, (2018).

64. Nehl, C. L. & Hafner, J. H. Shape-dependent plasmon resonances of gold nanoparticles. J. Mater. Chem. 18, 2415–2419 (2008).

65. Yaremchuk, I. Y. et al. Plasmon resonance of the silver nanoparticles with different shape. 2015 IEEE 35th Int. Conf. Electron. Nanotechnology, ELNANO 2015 - Conf. Proc. 185–187 (2015). doi:10.1109/ELNANO.2015.7146868

66. Traviss, D., Bruck, R., Mills, B., Abb, M. & Muskens, O. L. Ultrafast plasmonics using transparent conductive oxide hybrids in the epsilon-near-zero regime. Appl. Phys. Lett. 102, (2013).

67. Koch, U., Hoessbacher, C., Niegemann, J., Hafner, C. & Leuthold, J. Digital plasmonic absorption modulator exploiting epsilon-near-zero in transparent conducting oxides. IEEE Photonics J. 8, (2016).

68. Kuznetsov, A. I., Miroshnichenko, A. E., Brongersma, M. L., Kivshar, Y. S. & Luk’yanchuk, B. Optically resonant dielectric nanostructures. Science (80-. ). 354, (2016).

69. Grinblat, G., Li, Y., Nielsen, M. P., Oulton, R. F. & Maier, S. A. Enhanced third harmonic generation in single germanium nanodisks excited at the anapole mode. Nano Lett. 16, 4635–4640 (2016).

70. Flammer, P. D. et al. Hybrid plasmon/dielectric waveguide for integrated silicon-on-insulator optical elements. Opt. Express 18, 21013 (2010).

71. Chen, C. et al. Waveguide-Integrated Compact Plasmonic Resonators for On-Chip Mid-Infrared Laser Spectroscopy. Nano Lett. (2018). doi:10.1021/acs.nanolett.8b03156

72. Gurnett, D. A. & Bhattacharjee, A. Introduction to plasma physics with space and laboratory applications. (Cambridge University Press, 2005).

73. Anderson, A., Deryckx, K. S., Xu, X. G., Steinmeyer, G. & Raschke, M. B. Few-femtosecond plasmon dephasing of a single metallic nanostructure from optical response function reconstruction by interferometric frequency resolved optical gating. Nano Lett. 10, 2519–2524 (2010).

74. Khurgin, J. B. How to deal with the loss in plasmonics and metamaterials. Nature Nanotechnology 10, 2–6 (2015).

75. Brongersma, M. L., Halas, N. J. & Nordlander, P. Plasmon-induced hot carrier science and technology. Nat. Nanotechnol. 10, 25–34 (2015).

76. Tagliabue, G. et al. Quantifying the role of surface plasmon excitation and hot carrier transport in plasmonic devices. Nat. Commun. 9, 3394 (2018).

77. Zhang, Z. & Yates, J. T. Band bending in semiconductors: Chemical and physical consequences at surfaces and interfaces. Chem. Rev. 112, 5520–5551 (2012).

78. Chan, E. Y., Card, H. C. & Teich, M. C. Internal Photoemission Mechanisms at Interfaces Between Germanium and Thin Metal Films. IEEE J. Quantum Electron. 16, 373–381 (1980).

79. Mooney, J. M. & Silverman, J. The Theory of Hot-Electron Photoemission in Schottky-Barrier IR Detectors. IEEE Trans. Electron Devices 32, 33–39 (1985).

80. Kimukin, I. et al. High-speed GaAs-based resonant-cavity-enhanced 1.3 μm photodetector. Appl. Phys. Lett. 77, 3890 (2000).

81. Casalino, M., Sirleto, L., Moretti, L., Della Corte, F. & Rendina, I. Design of a silicon resonant cavity enhanced photodetector based on the internal photoemission effect at 1.55 νm. J. Opt. A Pure Appl. Opt. 8, 909–913 (2006).

82. Knight, M. W., Sobhani, H., Nordlander, P. & Halas, N. J. Photodetection with Active Optical Antennas. Science (80-. ). 332, 702–704 (2011).

83. Lee, H., Lee, Y. K., Hwang, E. & Park, J. Y. Enhanced Surface Plasmon Effect of Ag/TiO 2 Nanodiodes on Internal Photoemission. J. Phys. Chem. C 118, 5650–5656 (2014).

84. Desiatov, B. et al. Plasmonic enhanced silicon pyramids for internal photoemission Schottky detectors in the near-infrared regime. Optica 2, 335–338 (2015).

85. Goykhman, I., Desiatov, B., Khurgin, J., Shappir, J. & Levy, U. Waveguide based compact silicon Schottky photodetector with enhanced responsivity in the telecom spectral band. Opt. Express 20, 28594 (2012).

86. Li, W. & Valentine, J. Metamaterial perfect absorber based hot electron photodetection. Nano Lett. 14, 3510–3514 (2014).

87. Li, W. & Valentine, J. G. Harvesting the loss: Surface plasmon-based hot electron photodetection. Nanophotonics 6, 177–191 (2017).

26

88. Duchene, J. S., Tagliabue, G., Welch, A. J., Cheng, W. H. & Atwater, H. A. Hot Hole Collection and Photoelectrochemical CO2Reduction with Plasmonic Au/p-GaN Photocathodes. Nano Lett. 18, 2545–2550 (2018).

89. Blandre, E., Jalas, D., Petrov, A. Y. & Eich, M. Limit of efficiency of generation of hot electrons in metals and their injection inside a semiconductor using a semi-classical approach. ACS Photonics (2018). doi:10.1021/acsphotonics.8b00473

90. Mehbod, M., Thijs, W. & Bruynseraede, Y. Electron tunneling through semiconducting barriers. Phys. Status Solidi 32, 203–211 (1975).

91. Foerster, B. et al. Chemical Interface Damping Depends on Electrons Reaching the Surface. ACS Nano 11, 2886–2893 (2017).

92. Liu, Y. et al. Investigation of the TiN gate electrode with tunable work function and its application for FinFET fabrication. IEEE Trans. Nanotechnol. 5, 723–728 (2006).

93. Bard, A. J. & Fox, M. A. Artificial Photosynthesis: Solar Splitting of Water to Hydrogen and Oxygen. Acc. Chem. Res. 28, 141–145 (1995).

94. Linic, S., Christopher, P. & Ingram, D. B. Plasmonic-metal nanostructures for efficient conversion of solar to chemical energy. Nat. Mater. 10, 911–921 (2011).

95. Zhang, Q. et al. Recent advancements in plasmon-enhanced visible light-driven water splitting. J. Mater. 3, 33–50 (2017).

96. Mubeen, S. et al. An autonomous photosynthetic device in which all charge carriers derive from surface plasmons. Nat. Nanotechnol. 8, 247–251 (2013).

97. Oldenburg, S. J., Jackson, J. B., Westcott, S. L. & Halas, N. J. Infrared extinction properties of gold nanoshells. Appl. Phys. Lett. 75, 2897–2899 (1999).

98. Wang, T., Nguyen, V. H., Buchenauer, A., Schnakenberg, U. & Taubner, T. Surface enhanced infrared spectroscopy with gold strip gratings. Opt. Express 21, 9005 (2013).

99. Carabe, J. & Gandia, J. J. Thin-film-silicon solar cells. Opto-Electronics Rev. 12, 1–6 (2004).100. Jang, Y. H. et al. Plasmonic Solar Cells: From Rational Design to Mechanism Overview. Chem. Rev.

116, 14982–15034 (2016).101. Mandal, P. & Sharma, S. Progress in plasmonic solar cell efficiency improvement: A status review.

Renew. Sustain. Energy Rev. 65, 537–552 (2016).102. Zhou, N. et al. Plasmon-enhanced light harvesting: applications in enhanced photocatalysis,

photodynamic therapy and photovoltaics. RSC Adv. 5, 29076–29097 (2015).103. Ding, H., Lv, J., Wu, H., Chai, G. & Liu, A. Enhanced light-harvesting by plasmonic hollow gold

nanospheres for photovoltaic performance. R. Soc. Open Sci. 5, (2018).104. Sandén, S. et al. Plasmon-enhanced polymer-sensitized solar cells. J. Phys. Chem. C 119, 5570–5576

(2015).105. Tan, H., Santbergen, R., Smets, A. H. M. & Zeman, M. Plasmonic light trapping in thin-film silicon

solar cells with improved self-assembled silver nanoparticles. Nano Lett. 12, 4070–4076 (2012).106. Atwater, H. A. & Polman, A. Plasmonics for improved photovoltaic devices. Nat. Mater. 9, 205–213

(2010).107. Derkacs, D., Lim, S. H., Matheu, P., Mar, W. & Yu, E. T. Improved performance of amorphous silicon

solar cells via scattering from surface plasmon polaritons in nearby metallic nanoparticles. Appl. Phys. Lett. 89, 1–4 (2006).

108. Hylton, N. P. et al. Loss mitigation in plasmonic solar cells: Aluminium nanoparticles for broadband photocurrent enhancements in gaas photodiodes. Sci. Rep. 3, 1–6 (2013).

109. Fales, A. M., Vogt, W. C., Pfefer, J. & Ilev, I. K. Quantitative Evaluation of Nanosecond Pulsed Laser-Induced Photomodification of Plasmonic Gold Nanoparticles. Sci. Rep. 7, 1–11 (2017).

110. Vázquez-Vázquez, C. et al. Nanoreactors for simultaneous remote thermal activation and optical monitoring of chemical reactions. J. Am. Chem. Soc. 135, 13616–13619 (2013).

111. Vologodskii, A. & Frank-Kamenetskii, M. D. DNA melting and energetics of the double helix. Phys. Life Rev. 1, 1–21 (2017).

112. Huang, X. & El-Sayed, M. A. Plasmonic photo-thermal therapy (PPTT). Alexandria J. Med. 47, 1–9 (2011).

113. Pustovalov, V. K., Smetannikov, A. S. & Zharov, V. P. Photothermal and accompanied phenomena of selective nanophotothermolysis with gold nanoparticles and laser pulses. Laser Phys. Lett. 5, 775–792 (2008).

114. Zharov, V. P., Mercer, K. E., Galitovskaya, E. N. & Smeltzer, M. S. Photothermal nanotherapeutics and nanodiagnostics for selective killing of bacteria targeted with gold nanoparticles. Biophys. J. 90, 619–627 (2006).

115. Osinkina, L. et al. Tuning DNA binding kinetics in an optical trap by plasmonic nanoparticle heating. Nano Lett. 13, 3140–3144 (2013).

27

116. Khan, V. R. & Brown, I. R. The effect of hyperthermia on the induction of cell death in brain, testis, and thymus of the adult and developing rat. Cell Stress Chaperones 7, 73–90 (2002).

117. de Andrade Mello, P. et al. Hyperthermia and associated changes in membrane fluidity potentiate P2X7 activation to promote tumor cell death. Oncotarget 8, 67254–67268 (2017).

118. Sapsford, K. E. et al. Functionalizing nanoparticles with biological molecules: Developing chemistries that facilitate nanotechnology. Chem. Rev. 113, 1904–2074 (2013).

119. Lowery, A. R., Gobin, A. M., Day, E. S., Halas, N. J. & West, J. L. Immunonanoshells for targeted photothermal ablation of tumor cells. Int. J. Nanomedicine 1, 149–154 (2006).

120. Krol, S. et al. Therapeutic benefits from nanoparticles: The potential significance of nanoscience in diseases with compromise to the blood brain barrier. Chem. Rev. 113, 1877–1903 (2013).

121. Pérez-Hernández, M. et al. Dissecting the molecular mechanism of apoptosis during photothermal therapy using gold nanoprisms. ACS Nano 9, 52–61 (2015).

122. Singh, R. & W., L. J. Nanoparticle-based targeted drug delivery. Exp. Mol .Pathol. 86, 215–223 (2009).123. Sandell, J. L. & Zhu, T. C. A review of in-vivo optical properties of human tissues and its impact on

PDT. J. Biophotonics 4, 773–787 (2011).124. Spyratou, E., Makropoulou, M., Efstathopoulos, E. P., Georgakilas, A. G. & Sihver, L. Recent advances

in cancer therapy based on dual mode gold nanoparticles. Cancers (Basel). 9, 1–19 (2017).125. Longmire, M., Choyke, P. L. & Kobayashi, H. Clearance Properties of Nano-sized Particles and

Molecules as Nanomedicine. Nanomedicine 3, 703–717 (2012).126. Khlebtsov, B. N., Khanadeev, V. A., Maksimova, I. L., Terentyuk, G. S. & Khlebtsov, N. G. Silver

nanocubes and gold nanocages: Fabrication and optical and photothermal properties. Nanotechnologies Russ. 5, 454–468 (2010).

127. Wang, Y. et al. Comparison study of gold nanohexapods, nanorods, and nanocages for photothermal cancer treatment. ACS Nano 7, 2068–2077 (2013).

128. Geetha, C. S., Sabareeswaran, A. & Mohanan, P. V. Pre-clinical evaluation of titanium nitride coated titanium material. Toxicol. Mech. Methods 22, 144–150 (2012).

129. Baffou, G. & Quidant, R. Thermo-plasmonics: Using metallic nanostructures as nano-sources of heat. Laser Photonics Rev. 7, 171–187 (2013).

130. Baffou, G. & Rigneault, H. Femtosecond-pulsed optical heating of gold nanoparticles. Phys. Rev. B - Condens. Matter Mater. Phys. 84, 1–13 (2011).

131. Baffou, G. et al. Photoinduced heating of nanoparticle arrays. ACS Nano 7, 6478–6488 (2013).132. Baffou, G., Quidant, R. & Girard, C. Thermoplasmonics modeling: A green’s function approach. Phys.

Rev. B - Condens. Matter Mater. Phys. 82, 1–11 (2010).133. Sidambe, A. T. Biocompatibility of advanced manufactured titanium implants-A review. Materials

(Basel). 7, 8168–8188 (2014).134. Csaki, A. et al. A parallel approach for subwavelength molecular surgery using gene-specific positioned

metal nanoparticles as laser light antennas. Nano Lett. 7, 247–253 (2007).135. Lee, K., Drachev, V. P. & Irudayaraj, J. DNA-gold nanoparticle reversible networks grown on cell

surface marker sites: Application in diagnostics. ACS Nano 5, 2109–2117 (2011).136. Kogan, M. J. et al. Nanoparticle-mediated local and remote manipulation of protein aggregation. Nano

Lett. 6, 110–115 (2006).137. Reismann, M., Bretschneider, J. C., Von Plessen, G. & Simon, U. Reversible photothermal melting of

DNA in DNA-gold-nanoparticle networks. Small 4, 607–610 (2008).138. Khosravi Khorashad, L., Besteiro, L. V., Wang, Z., Valentine, J. & Govorov, A. O. Localization of

Excess Temperature Using Plasmonic Hot Spots in Metal Nanostructures: Combining Nano-Optical Antennas with the Fano Effect. J. Phys. Chem. C 120, 13215–13226 (2016).

139. Raimondi, S. Fluorescence in situ hybridization: Molecular probes for diagnosis of pediatric neoplastic diseases. Cancer Invest 18, 135–147 (2000).

140. Jain, P. K., Huang, W. & El-Sayed, M. A. On the universal scaling behavior of the distance decay of plasmon coupling in metal nanoparticle pairs: A plasmon ruler equation. Nano Lett. 7, 2080–2088 (2007).

141. Behera, S. & Joseph, J. Plasmonic metamaterial based unified broadband absorber/near infrared emitter for thermophotovoltaic system based on hexagonally packed tungsten doughnuts. J. Appl. Phys. 122, (2017).

142. Zhang, W., Li, Q. & Qiu, M. A plasmon ruled based on nanoscale photothermal effect. Opt. Express 21, 172 (2013).

143. Heinz, H. et al. Nanoparticle decoration with surfactants: Molecular interactions, assembly, and applications. Surf. Sci. Rep. 72, 1–58 (2017).

144. Song, Y. et al. AC Electroosmosis-Enhanced Nanoplasmofluidic Detection of Ultralow-Concentration Cytokine. Nano Lett. 17, 2374–2380 (2017).

28

145. Hammond, J. L., Bhalla, N., Rafiee, S. D. & Estrela, P. Localized surface plasmon resonance as a biosensing platform for developing countries. Biosensors 4, 172–188 (2014).

146. Sun, G., Khurgin, J. B. & Soref, R. A. Plasmonic light-emission enhancement with isolated metal nanoparticles and their coupled arrays. J. Opt. Soc. Am. B 25, 1748 (2008).

147. de Silva, A. P. et al. Signaling Recognition Events with Fluorescent Sensors and Switches. Chem. Rev. 97, 1515–1566 (1997).

148. Nelson, R. W. Biosensor chip mass spectrometry: A chip-based proteomics approach. Electrophoresis 21, 1155–1163 (2000).

149. Toseland, C. P. Fluorescent labeling and modification of proteins. J. Chem. Biol. 6, 85–95 (2013).150. Dahlin, A. et al. Localised surface plasmon resonance sensing of lipid-membrane-mediated

biorecognition events. J. Am. Chem. Soc. 127, 5043–5048 (2005).151. Bhagawati, M., You, C. & Piehler, J. Quantitative real-time imaging of protein-protein interactions by

LSPR detection with micropatterned gold nanoparticles. Anal. Chem. 85, 9564–9571 (2013).152. Zhao, Q. et al. A reusable localized surface plasmon resonance biosensor for quantitative detection of

serum squamous cell carcinoma antigen in cervical cancer patients based on silver nanoparticles array. Int. J. Nanomedicine 9, 1097–1104 (2014).

153. Halkare, P., Punjabi, N., Wangchuk, J., Kondabagil, K. & Mukherji, S. LSPR based fiber optic sensor for detection of E. coli using bacteriophage T4. 2015 Work. Recent Adv. Photonics 1–4 (2015). doi:10.1109/WRAP.2015.7805945

154. Jung, L. S., Campbell, C. T., Chinowsky, T. M., Mar, M. N. & Yee, S. S. Quantitative Interpretation of the Response of Surface Plasmon Resonance Sensors to Adsorbed Films. Langmuir 14, 5636–5648 (1998).

155. Kim, T. H. et al. Full-colour quantum dot displays fabricated by transfer printing. Nat. Photonics 5, 176–182 (2011).

156. Lozano, G., Rodriguez, S. R. K., Verschuuren, M. A. & Rivas, J. G. Metallic nanostructures for efficient LED lighting. Light Sci. Appl. 5, 1–10 (2016).

157. Guo, K., Lozano, G., Verschuuren, M. A. & Gómez Rivas, J. Control of the external photoluminescent quantum yield of emitters coupled to nanoantenna phased arrays. J. Appl. Phys. 118, (2015).

158. Khurgin, J. B., Sun, G. & Soref, R. A. Electroluminescence efficiency enhancement using metal nanoparticles. Appl. Phys. Lett. 93, (2008).

159. Khurgin, J. B., Sun, G. & Soref, R. A. Enhancement of luminescence efficiency using surface plasmon polaritons: figures of merit. J. Opt. Soc. Am. B 24, 1968 (2007).

160. Sun, G., Khurgin, J. B. & Soref, R. A. Practicable enhancement of spontaneous emission using surface plasmons. Appl. Phys. Lett. 90, 2005–2008 (2007).

161. Cambiasso, J., König, M., Cortés, E., Schlücker, S. & Maier, S. A. Surface-Enhanced Spectroscopies of a Molecular Monolayer in an All-Dielectric Nanoantenna. ACS Photonics 5, 1546–1557 (2018).

162. Bharadwaj, P. & Novotny, L. Spectral dependence of single molecule fluorescence enhancement. Opt. Express 15, 14266 (2007).

163. Schmidt, M. K. et al. Dielectric antennas - a suitable platform for controlling magnetic dipolar emission. Opt. Express 20, 13636 (2012).

164. Okamoto, K. et al. Surface-plasmon-enhanced light emitters based on InGaN quantum wells. Nat. Mater. 3, 601–605 (2004).

165. Qi, Z. et al. Au nanoparticle-decorated silicon pyramids for plasmon-enhanced hot electron near-infrared photodetection. Nanotechnology 28, (2017).

166. ALavirad, M., Olivieri, A., Roy, L. & Berini, P. High-responsivity sub-bandgap hot-hole plasmonic Schottky detectors. Opt. Express 24, 22544–22554 (2016).

167. Reineck, P., Brick, D., Mulvaney, P. & Bach, U. Plasmonic Hot Electron Solar Cells: The Effect of Nanoparticle Size on Quantum Efficiency. J. Phys. Chem. Lett. 7, 4137–4141 (2016).

168. Naldoni, A. et al. Broadband Hot-Electron Collection for Solar Water Splitting with Plasmonic Titanium Nitride. Adv. Opt. Mater. 5, 1–11 (2017).

169. Huang, X., El-Sayed, I. H., Qian, W. & El-Sayed, M. A. Cancer cell imaging and photothermal therapy in the near-infrared region by using gold nanorods. J. Am. Chem. Soc. 128, 2115–2120 (2006).

170. Miller, I. C., Castro, M. G., Maenza, J., Weis, J. P. & Kwong, G. A. Remote Control of Mammalian Cells with Heat-Triggered Gene Switches and Photothermal pulse Trains. ACS Synth Biol 7, 1167–1173 (2018).

171. McFarland, A. D. & Van Duyne, R. P. Single silver nanoparticles as real-time optical sensors with zeptomole sensitivity. Nano Lett. 3, 1057–1062 (2003).

172. Tanaka, T. et al. Enhanced red-light emission by local plasmon coupling of au nanorods in an organic light-emitting diode. Appl. Phys. Express 4, (2011).

173. Kim, N.-Y. et al. Localized surface plasmon-enhanced green quantum dot light-emitting diodes using

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gold nanoparticles. RSC Adv. 5, 19624–19629 (2015).174. Khadir, S., Diallo, A., Chakaroun, M. & Boudrioua, A. Exciton enhancement and exciplex quenching

by plasmonic effect of Aluminum nanoparticle arrays in a blue organic light emitting diode. Opt. Express 25, 9812 (2017).

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