In Situ Plasmonic Sensing of Platinum Model Catalyst Sintering on Different Oxide Supports and in O₂ and NO₂ Atmospheres with Different Concentrations

Abstract

Improved understanding of thermal deactivation processes of supported nanoparticles via sintering is needed to increase the lifetime of catalysts. To monitor sintering processes under industrially relevant application conditions, in situ experimental methods compatible with elevated temperatures, high pressures, and harsh chemical environments are required. Here, we experimentally demonstrate the applicability of in situ indirect nanoplasmonic sensing (INPS) to investigate the sintering of Pt model catalysts on flat alumina and silica supports in O 2 and NO 2 atmospheres in real time and under operating conditions. Moreover, by means of finite-difference time-domain (FDTD) electrodynamics simulations, we establish a generic scaling approach to account for different inherent sensitivities of INPS sensor platforms featuring dielectric support layers with different refractive index. On the basis of these findings, we identify a universal, support-, and sintering-environment-independent correlation between INPS centroid shift signal and mean Pt particle size during the sintering process. As a first demonstration of the new possibilities offered by INPS and the obtained universal scaling to study sintering processes under different applied conditions, we investigate the dependence of the sintering rate of a SiO 2 -supported Pt model catalyst on the O 2 concentration in Ar carrier gas. We find a clear dependence of the sintering rate on the O 2 concentration in the 0.05−0.5% O 2 concentration range.

Effective Optical Properties of Inhomogeneously Distributed Nanoobjects in Strong Field Gradients of Nanoplasmonic Sensors

“…The distinction between the models is that the volume fraction is different in each sublayer and depends on the distance from the substrate as well as the distribution of particles in the layer. We base our initial analysis of nanoparticle layers on previously reported Pd particle distributions [10, 11], which are therein characterized by a mean and standard deviation. For convenience in calculations, we assume a Gaussian distribution of Pd nanospheres around a given mean radius μ r with corresponding standard deviations σ r , although in reality a spherical shape may not be adequate.…”

“…After this validation in simple planar systems, we employ the model to study LSPR measurements of sintering of Pd nanoparticles. We show the equivalence of averaging finite-difference time-domain (FDTD) simulation results for discrete nanoparticles and the gradient model, both of which reproduce the measured experimental evolution [10]. Finally, we apply the model to study the influence of microscopic variations in the size distributions of sintered nanoparticles and prove that the peak shift measured during this process is equally sensitive to not only the mean particle size, as demonstrated previously [10], but also to the particle dispersion and what complicates an unequivocal determination of state of the nanoparticles from a single measured value, i.e., the peak shift.…”

“…However, once disorder is present [4]—and it is a common feature of many bottom up fabrication techniques [5] as well as in sensors in which stochastic processes take place [6, 7]—accurate and efficient modeling becomes challenging. A good example of such a modeling problem is an indirect nanoplasmonic sensing (INPS) experiment [8] in which a metal nanoantenna, whose immediate vicinity is filled with smaller nanoparticles [9], interrogates their material and/or chemical changes of and reports them via a peak shift [10, 11]. The challenge lies in the fact that the nanoparticles, which constitute the sensed element, are random in both size, position, and shape [12] and in simulations; it is all but impossible to model even a small fraction of plasmonic sensors interrogated in an actual experiment.…”

“…In general, however, use of an effective medium is beneficial, as it enables rapid analysis of a large parameter space without tedious averaging of optical cross-sections. Hence, to accurately model structures, such as noble metal nanodisks randomly decorated with nanoparticles [8, 10, 34], we propose the gradient effective medium (GEM), in which the effective permittivity incorporates a gradient with a spatial dependence derived from the inhomogeneous distribution of nanoparticles.…”

Review on process-microstructure-performance relationship in ALD-engineered SOFCs

“…While oxide overlayers can be fabricated by using other techniques (sputtering [136][137][138], infiltration [139][140][141]), the conformal nature of the ALD process may further help to enhance the stability of metallic electrodes. The stabilization mechanism of metal nanoparticles by the oxide overlayer may include: (1) anchoring of metallic nanoparticles to the substrate, (2) stabilization of unstable metal surface atoms, which may impede the physical merging, and (3) Ostwald ripening of metallic nanoparticles [136,[142][143][144][145][146]. More interestingly, when ion conducting oxides, such as doped ZrO 2 or CeO 2, were applied, clear enhancement in ORR at the metal surface was observed, whose mechanism was recently proposed by Lee et al (figures 5(c), (d)) [26].…”