Accurate complex dielectric functions are critical to accelerate the development of rationally designed metal alloy systems for nanophotonic applications, and to thereby unlock the potential of alloying for tailoring nanostructure optical properties. To date, however, accurate alloy dielectric functions are widely lacking. Here, a time‐dependent density‐functional theory computational framework is employed to compute a comprehensive binary alloy dielectric function library for the late transition metals most commonly employed in plasmonics (Ag, Au, Cu, Pd, Pt). Excellent agreement is found between electrodynamic simulations based on these dielectric functions and selected alloy systems experimentally scrutinized in 10 at% composition intervals. Furthermore, it is demonstrated that the dielectric functions can vary in very non‐linear fashion with composition, which paves the way for non‐trivial optical response optimization by tailoring material composition. The presented dielectric function library is thus a key resource for the development of alloy nanomaterials for applications in nanophotonics, optical sensors, and photocatalysis.

In catalysis, nanoparticles enable chemical transformations and their structural and chemical fingerprints control activity. To develop understanding of such fingerprints, methods studying catalysts at realistic conditions have proven instrumental. Normally, these methods either probe the catalyst bed with low spatial resolution, thereby averaging out single particle characteristics, or probe an extremely small fraction only, thereby effectively ignoring most of the catalyst. Here, we bridge the gap between these two extremes by introducing highly multiplexed single particle plasmonic nanoimaging of model catalyst beds comprising 1000 nanoparticles, which are integrated in a nanoreactor platform that enables online mass spectroscopy activity measurements. Using the example of CO oxidation over Cu, we reveal how highly local spatial variations in catalyst state dynamics are responsible for contradicting information about catalyst active phase found in the literature, and identify that both surface and bulk oxidation state of a Cu nanoparticle catalyst dynamically mediate its activity.

In plasmon-mediated photocatalysis it is of critical importance to differentiate light-induced catalytic reaction rate enhancement channels, which include near-field effects, direct hot carrier injection, and photothermal catalyst heating. In particular, the discrimination of photothermal and hot electron channels is experimentally challenging, and their role is under keen debate. Here we demonstrate using the example of CO oxidation over nanofabricated neat Pd and Au 50 Pd 50 alloy catalysts, how photothermal rate enhancement differs by up to 3 orders of magnitude for the same photon flux, and how this effect is controlled solely by the position of catalyst operation along the light-off curve measured in the dark. This highlights that small fluctuations in reactor temperature or temperature gradients across a sample may dramatically impact global and local photothermal rate enhancement, respectively, and thus control both the balance between different rate enhancement mechanisms and the way strategies to efficiently distinguish between them should be devised.

Urban air pollution is a critical health problem in cities all around the world. Therefore, spatially highly resolved real-time monitoring of airborne pollutants, in general, and of nitrogen dioxide, NO 2 , in particular, is of utmost importance. However, highly accurate but fixed and bulky measurement stations or satellites are used for this purpose to date. This defines a need for miniaturized NO 2 sensor solutions with detection limits in the low parts per billion range to finally enable indicative air quality monitoring at low cost that facilitates detection of highly local emission peaks and enables the implementation of direct local actions like traffic control, to immediately reduce local emissions. To address this challenge, we present a nanoplasmonic NO 2 sensor based on arrays of Au nanoparticles coated with a thin layer of polycrystalline WO 3 , which displays a spectral redshift in the localized surface plasmon resonance in response to NO 2 . Sensor performance is characterized under (i) idealized laboratory conditions, (ii) conditions simulating humid urban air, and (iii) an outdoor field test in a miniaturized device benchmarked against a commercial NO 2 sensor approved according to European and American standards. The limit of detection of the plasmonic solution is below 10 ppb in all conditions. The observed plasmonic response is attributed to a combination of charge transfer between the WO 3 layer and the plasmonic Au nanoparticles, WO 3 layer volume expansion, and changes in WO 3 permittivity. The obtained results highlight the viability of nanoplasmonic gas sensors, in general, and their potential for practical application in indicative urban air monitoring, in particular.

Alloying is an increasingly important handle to engineer the optical properties of metal nanoparticles that find applications in, for example, optical metamaterials, nanosensors, and plasmon-enhanced catalysis. One advantage of alloying over traditionally used particle size and shape engineering is that it, in principle, enables tuning of optical properties without a spectral shift of the localized surface plasmon resonance, which is important for applications where a specific spectral band is targeted. A second advantage is that alloying simultaneously enables adjustment of nanoparticle electronic, chemical, mechanical, and light absorption properties. However, a systematic survey of the impact of alloying on light absorption in metal nanoparticles does not exist, despite its key role in applications that include photothermal therapy, plasmonic heat generation, and plasmon catalysis. Therefore, we present here the systematic screening of the light absorption properties of binary late transition-metal alloys composed of Au, Ag, Cu, Pd, and Pt in the visible spectral range, based on a combination of experiments and finite-difference time-domain simulations, and discuss in detail the underlying physics. By studying these 10 alloy systems for 14 different nanoparticle sizes, we find that most nanoparticles experience a maximal absorption efficiency at around 80 nm particle diameter, and that most alloy systems outperform their neat constituents, with integrated absorption enhancement factors of up to 200%. This highlights the untapped potential of alloying for the engineering of light absorption in nanoparticles, and the presented material screening constitutes a resource for the rational selection of alloy systems with tailored absorption properties.

Gold nanorods stabilized with mesoporous silica shells are characterized and used as the catalyst for a model CO oxidation reaction to counter the costly sintering phenomena found in many industrial nanoparticle catalysts.

Cationic surfactants are widely used in the colloidal synthesis of noble metal nanoparticles in general, and of Pd nanoparticles in particular, to stabilize them toward aggregate formation in solution and to promote shape-specific particle growth. Despite the benefits at the synthesis stage, these surfactants can be problematic once the nanoparticles are to be applied as they may both geometrically block and electronically alter surface sites that are important for surface chemical reactions. This is particularly relevant in applications like bio- and chemosensors where analyte-nanoparticle surface interactions constitute the actual sensing event. Here, H2 sensors based on Pd and its alloys are no exception since the dissociation of H2 on the particle surface is the first step toward hydride formation and thus hydrogen detection, and it has been demonstrated that the presence of surfactant molecules detrimentally affects the hydrogen sorption rate. Here, we therefore develop a scheme to remove cationic surfactants from Pd nanoparticle surfaces by means of subsequent O2 and H2 plasma treatment, whose effectiveness we verify by X-ray photoelectron spectroscopy. Furthermore, we find that the plasma treatment both alters the surface structure of the Pd nanoparticles at the atomic level and leads to surface contamination by so-called H2 plasma swift chemical sputtering of Al, Si and F species present in the plasma chamber, which in combination significantly reduce hydrogen sorption rates and increase apparent activation energies, as revealed by plasmonic hydrogen sorption kinetic measurements. Finally, we show that both these effects can be reversed by mild thermal annealing and that after the complete plasma cleaning–thermal annealing sequence hydrogen sorption rates essentially identical to the ones of neat Pd particles never exposed to cationic surfactants can be achieved. This advertises tailored plasma cleaning and mild heat treatments as an effective recipe for the removal of surfactant molecules from nanoparticle surfaces.

The temperature of nanoparticles is a critical parameter in applications that range from biology, to sensors, to photocatalysis. Yet, accurately determining the absolute temperature of nanoparticles is intrinsically difficult because traditional temperature probes likely deliver inaccurate results due to their large thermal mass compared to the nanoparticles. Here we present a hydrogen nanothermometry method that enables a noninvasive and direct measurement of absolute Pd nanoparticle temperature via the temperature dependence of the first-order phase transformation during Pd hydride formation. We apply it to accurately measure light-absorption-induced Pd nanoparticle heating at different irradiated powers with 1 °C resolution and to unravel the impact of nanoparticle density in an array on the obtained temperature. In a wider perspective, this work reports a noninvasive method for accurate temperature measurements at the nanoscale, which we predict will find application in, for example, nano-optics, nanolithography, and plasmon-mediated catalysis to distinguish thermal from electronic effects.