Neural network enabled nanoplasmonic hydrogen sensors with 100 ppm limit of detection in humid air.

Environmental humidity variations are ubiquitous and high humidity characterizes fuel cell and electrolyzer operation conditions. Since hydrogen-air mixtures are highly flammable, humidity tolerant H2 sensors are important from safety and process monitoring perspectives. Here, we report an optical nanoplasmonic hydrogen sensor operated at elevated temperature that combined with Deep Dense Neural Network or Transformer data treatment involving the entire spectral response of the sensor enables a 100 ppm H2 limit of detection in synthetic air at 80% relative humidity. This significantly exceeds the <1000 ppm US Department of Energy performance target. Furthermore, the sensors pass the ISO 26142:2010 stability requirement in 80% relative humidity in air down to 0.06% H2 and show no signs of performance loss after 140 h continuous operation. Our results thus demonstrate the potential of plasmonic hydrogen sensors for use in high humidity and how neural-network-based data treatment can significantly boost their performance.

Electron Beam Induced Enhancement and Suppression of Oxidation in Cu Nanoparticles in Environmental Scanning Transmission Electron Microscopy.

We have investigated the effects of high-energy electron irradiation on the oxidation of copper nanoparticles in environmental scanning transmission electron microscopy (ESTEM). The hemispherically shaped particles were oxidized in 3 mbar of O2 in a temperature range 100-200 °C. The evolution of the particles was recorded with sub-nanometer spatial resolution in situ in ESTEM. The oxidation encompasses the formation of outer and inner oxide shells on the nanoparticles, arising from the concurrent diffusion of copper and oxygen out of and into the nanoparticles, respectively. Our results reveal that the electron beam actively influences the reaction and overall accelerates the oxidation of the nanoparticles when compared to particles oxidized without exposure to the electron beam. However, the extent of this electron beam-assisted acceleration of oxidation diminishes at higher temperatures. Moreover, we observe that while oxidation through the outward diffusion of Cu+ cations is enhanced, the electron beam appears to hinder oxidation through the inward diffusion of O2- anions. Our results suggest that the impact of the high-energy electrons in ESTEM oxidation of Cu nanoparticles is mostly related to kinetic energy transfer, charging, and ionization of the gas environment, and the beam can both enhance and suppress reaction rates.

Label-Free Imaging of Catalytic H2O2 Decomposition on Single Colloidal Pt Nanoparticles Using Nanofluidic Scattering Microscopy.

Single-particle catalysis aims at determining factors that dictate the nanoparticle activity and selectivity. Existing methods often use fluorescent model reactions at low reactant concentrations, operate at low pressures, or rely on plasmonic enhancement effects. Hence, methods to measure single-nanoparticle activity under technically relevant conditions and without fluorescence or other enhancement mechanisms are still lacking. Here, we introduce nanofluidic scattering microscopy of catalytic reactions on single colloidal nanoparticles trapped inside nanofluidic channels to fill this gap. By detecting minuscule refractive index changes in a liquid flushed trough a nanochannel, we demonstrate that local H2O2 concentration changes in water can be accurately measured. Applying this principle, we analyze the H2O2 concentration profiles adjacent to single colloidal Pt nanoparticles during catalytic H2O2 decomposition into O2 and H2O and derive the particles' individual turnover frequencies from the growth rate of the O2 gas bubbles formed in their respective nanochannel during reaction.

The Role of Grain Boundary Sites for the Oxidation of Copper Catalysts during the CO Oxidation Reaction.

The oxidation of transition metal surfaces is a process that takes place readily at ambient conditions and that, depending on the specific catalytic reaction at hand, can either boost or hamper activity and selectivity. Cu catalysts are no exception in this respect since they exhibit different oxidation states for which contradicting activities have been reported, as, for example, in the catalytic oxidation of CO. Here, we investigate the impact of low-coordination sites on nanofabricated Cu nanoparticles with engineered grain boundaries on the oxidation of the Cu surface under CO oxidation reaction conditions. Combining multiplexed in situ single particle plasmonic nanoimaging, ex situ transmission electron microscopy imaging, and density functional theory calculations reveals a distinct dependence of particle oxidation rate on grain boundary density. Additionally, we found that the oxide predominantly nucleates at grain boundary-surface intersections, which leads to nonuniform oxide growth that suppresses Kirkendall-void formation. The oxide nucleation rate on Cu metal catalysts was revealed to be an interplay of surface coordination and CO oxidation behavior, with low coordination favoring Cu oxidation and high coordination favoring CO oxidation. These findings explain the observed single particle-specific onset of Cu oxidation as being the consequence of the individual particle grain structure and provide an explanation for widely distributed activity states of particles in catalyst bed ensembles.

A Microshutter for the Nanofabrication of Plasmonic Metal Alloys with Single Nanoparticle Composition Control.

Alloying offers an increasingly important handle in nanomaterials design in addition to the already widely explored size and geometry of nanostructures of interest. As the key trait, the mixing of elements at the atomic level enables nanomaterials with physical or chemical properties that cannot be obtained by a single element alone, and subtle compositional variations can significantly impact these properties. Alongside the great potential of alloying, the experimental scrutiny of its impact on nanomaterial function is a challenge because the parameter space that encompasses nanostructure size, geometry, chemical composition, and structural atomic-level differences among individuals is vast and requires unrealistically large sample sets if statistically relevant and systematic data are to be obtained. To address this challenge, we have developed a microshutter device for spatially highly resolved physical vapor deposition in the lithography-based fabrication of nanostructured surfaces. As we demonstrate, it enables establishing compositional gradients across a surface with single nanostructure resolution in terms of alloy composition, which subsequently can be probed in a single experiment. As a showcase, we have nanofabricated arrays of AuAg, AuPd, and AgPd alloy nanoparticles with compositions systematically controlled at the level of single particle rows, as verified by energy dispersive X-ray and single particle plasmonic nanospectroscopy measurements, which we also compared to finite-difference time-domain simulations. Finally, motivated by their application in state-of-the-art plasmonic hydrogen sensors, we investigated PdAu alloy gradient arrays for their hydrogen sorption properties. We found distinctly composition-dependent kinetics and hysteresis and revealed a composition-dependent contribution of a single nanoparticle response to the ensemble average, which highlights the importance of alloy composition screening in single experiments with single nanoparticle resolution, as offered by the microshutter nanofabrication approach.

Bulk-Processed Plasmonic Plastic Nanocomposite Materials for Optical Hydrogen Detection.

ConspectusSensors are ubiquitous, and their importance is only going to increase across many areas of modern technology. In this respect, hydrogen gas (H2) sensors are no exception since they allow mitigation of the inherent safety risks associated with mixtures of H2 and air. The deployment of H2 technologies is rapidly accelerating in emerging energy, transport, and green steel-making sectors, where not only safety but also process monitoring sensors are in high demand. To meet this demand, cost-effective and scalable routes for mass production of sensing materials are required. Here, the state-of-the-art often resorts to processes derived from the microelectronics industry where surface-based micro- and nanofabrication are the methods of choice and where (H2) sensor manufacturing is no exception.In this Account, we discuss how our recent efforts to develop sensors based on plasmonic plastics may complement the current state-of-the-art. We explore a new H2 sensor paradigm, established through a series of recent publications, that combines (i) the plasmonic optical H2 detection principle and (ii) bulk-processed nanocomposite materials. In particular, plasmonic plastic nanocomposite sensing materials are described that comprise plasmonic H2-sensitive colloidally synthesized nanoparticles dispersed in a polymer matrix and enable the additive manufacturing of H2 sensors in a cost-effective and scalable way. We first discuss the concept of plasmonic plastic nanocomposite materials for the additive manufacturing of an active plasmonic sensing material on the basis of the three key components that require individual and concerted optimization: (i) the plasmonic sensing metal nanoparticles, (ii) the surfactant/stabilizer molecules on the nanoparticle surface from colloidal synthesis, and (iii) the polymer matrix. We then introduce the working principle of plasmonic H2 detection, which relies on the selective absorption of H species into hydride-forming metal nanoparticles that, in turn, induces distinct changes in their optical plasmonic signature in proportion to the H2 concentration in the local atmosphere. Subsequently, we assess the roles of the key components of a plasmonic plastic for H2 sensing, where we have established that (i) alloying Pd with Au and Cu eliminates hysteresis and introduces intrinsic deactivation resistance at ambient conditions, (ii) surfactant/stabilizer molecules can significantly accelerate and decelerate H2 sorption and thus sensor response, and (iii) polymer coatings accelerate sensor response, reduce the limit of detection (LoD), and enable molecular filtering for sensor operation in chemically challenging environments. Based on these insights, we discuss the rational development and detailed characterization of bulk-processed plasmonic plastics based on glassy and fluorinated matrix polymers and on tailored flow-chemistry-based synthesis of Pd and PdAu alloy colloidal nanoparticles with optimized stabilizer molecules. In their champion implementation, they enable highly stable H2 sensors with response times in the 2 s range and an LoD of few 10 ppm of H2. To put plasmonic plastics in a wider perspective, we also report their implementation using different polymer matrix materials that can be used for 3D printing and (an)isotropic Au nanoparticles that enable the manufacturing of macroscopic plasmonic objects with, if required, dichroic optical properties and in amounts that can be readily upscaled. We advertise that melt processing of plasmonic plastic nanocomposites is a viable route toward the realization of plasmonic objects and sensors, produced by scalable colloidal synthesis and additive manufacturing techniques.

Roadmap on Deep Learning for Microscopy.

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.

Inverse designed plasmonic metasurface with parts per billion optical hydrogen detection.

Plasmonic sensors rely on optical resonances in metal nanoparticles and are typically limited by their broad spectral features. This constraint is particularly taxing for optical hydrogen sensors, in which hydrogen is absorbed inside optically-lossy Pd nanostructures and for which state-of-the-art detection limits are only at the low parts-per-million (ppm) range. Here, we overcome this limitation by inversely designing a plasmonic metasurface based on a periodic array of Pd nanoparticles. Guided by a particle swarm optimization algorithm, we numerically identify and experimentally demonstrate a sensor with an optimal balance between a narrow spectral linewidth and a large field enhancement inside the nanoparticles, enabling a measured hydrogen detection limit of 250 parts-per-billion (ppb). Our work significantly improves current plasmonic hydrogen sensor capabilities and, in a broader context, highlights the power of inverse design of plasmonic metasurfaces for ultrasensitive optical (gas) detection.

Time-Resolved Thickness and Shape-Change Quantification using a Dual-Band Nanoplasmonic Ruler with Sub-Nanometer Resolution.

Time-resolved measurements of changes in the size and shape of nanobiological objects and layers are crucial to understand their properties and optimize their performance. Optical sensing is particularly attractive with high throughput and sensitivity, and label-free operation. However, most state-of-the-art solutions require intricate modeling or multiparameter measurements to disentangle conformational or thickness changes of biomolecular layers from complex interfacial refractive index variations. Here, we present a dual-band nanoplasmonic ruler comprising mixed arrays of plasmonic nanoparticles with spectrally separated resonance peaks. As electrodynamic simulations and model experiments show, the ruler enables real-time simultaneous measurements of thickness and refractive index variations in uniform and heterogeneous layers with sub-nanometer resolution. Additionally, nanostructure shape changes can be tracked, as demonstrated by quantifying the degree of lipid vesicle deformation at the critical coverage prior to rupture and supported lipid bilayer formation. In a broader context, the presented nanofabrication approach constitutes a generic route for multimodal nanoplasmonic optical sensing.

Nanofluidic Trapping of Faceted Colloidal Nanocrystals for Parallel Single-Particle Catalysis.

Catalyst activity can depend distinctly on nanoparticle size and shape. Therefore, understanding the structure sensitivity of catalytic reactions is of fundamental and technical importance. Experiments with single-particle resolution, where ensemble-averaging is eliminated, are required to study it. Here, we implement the selective trapping of individual spherical, cubic, and octahedral colloidal Au nanocrystals in 100 parallel nanofluidic channels to determine their activity for fluorescein reduction by sodium borohydride using fluorescence microscopy. As the main result, we identify distinct structure sensitivity of the rate-limiting borohydride oxidation step originating from different edge site abundance on the three particle types, as confirmed by first-principles calculations. This advertises nanofluidic reactors for the study of structure-function correlations in catalysis and identifies nanoparticle shape as a key factor in borohydride-mediated catalytic reactions.

Label-free nanofluidic scattering microscopy of size and mass of single diffusing molecules and nanoparticles.

Label-free characterization of single biomolecules aims to complement fluorescence microscopy in situations where labeling compromises data interpretation, is technically challenging or even impossible. However, existing methods require the investigated species to bind to a surface to be visible, thereby leaving a large fraction of analytes undetected. Here, we present nanofluidic scattering microscopy (NSM), which overcomes these limitations by enabling label-free, real-time imaging of single biomolecules diffusing inside a nanofluidic channel. NSM facilitates accurate determination of molecular weight from the measured optical contrast and of the hydrodynamic radius from the measured diffusivity, from which information about the conformational state can be inferred. Furthermore, we demonstrate its applicability to the analysis of a complex biofluid, using conditioned cell culture medium containing extracellular vesicles as an example. We foresee the application of NSM to monitor conformational changes, aggregation and interactions of single biomolecules, and to analyze single-cell secretomes.

Competing oxidation mechanisms in Cu nanoparticles and their plasmonic signatures.

Chemical reactions involving nanoparticles often follow complex processes. In this respect, real-time probing of single nanoparticles under reactive conditions is crucial for uncovering the mechanisms driving the reaction pathway. Here, we have captured in situ the oxidation of single Cu nanoparticles to unravel a sequential competitive activation of different mechanisms at temperatures 50-200 °C. Using environmental scanning transmission electron microscopy, we monitor the evolution of oxide formation with sub-nanometre spatial resolution, and show how the prevalence of oxide island nucleation, Cabrera-Mott, Valensi-Carter and Kirkendall mechanisms under different conditions determines the morphology of the particles. Moreover, using in situ electron energy-loss spectroscopy, we probe the localised surface plasmons of individual particles during oxidation, and with the aid of finite-difference time-domain electrodynamic simulations investigate the signature of each mechanism in their plasmonic response. Our results shed light on the rich and intricate processes involved in the oxidation of nanoparticles, and provide in-depth insight into how these processes govern their morphology and optical response, beneficial for applications in catalysis, sensing, nanomedicine and plasmonics.

Unraveling Molecular Fingerprints of Catalytic Sulfur Poisoning at the Nanometer Scale with Near-Field Infrared Spectroscopy.

Fundamental understanding of catalytic deactivation phenomena such as sulfur poisoning occurring on metal/metal-oxide interfaces is essential for the development of high-performance heterogeneous catalysts with extended lifetimes. Unambiguous identification of catalytic poisoning species requires experimental methods simultaneously delivering accurate information regarding adsorption sites and adsorption geometries of adsorbates with nanometer-scale spatial resolution, as well as their detailed chemical structure and surface functional groups. However, to date, it has not been possible to study catalytic sulfur poisoning of metal/metal-oxide interfaces at the nanometer scale without sacrificing chemical definition. Here, we demonstrate that near-field nano-infrared spectroscopy can effectively identify the chemical nature, adsorption sites, and adsorption geometries of sulfur-based catalytic poisons on a Pd(nanodisk)/Al2O3 (thin-film) planar model catalyst surface at the nanometer scale. The current results reveal striking variations in the nature of sulfate species from one nanoparticle to another, vast alterations of sulfur poisoning on a single Pd nanoparticle as well as at the assortment of sulfate species at the active metal-metal-oxide support interfacial sites. These findings provide critical molecular-level insights crucial for the development of long-lifetime precious metal catalysts resistant toward deactivation by sulfur.

Optical Hydrogen Nanothermometry of Plasmonic Nanoparticles under Illumination.

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.

Nanoplasmonic NO2 Sensor with a Sub-10 Parts per Billion Limit of Detection in Urban Air.

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, NO2, 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 NO2 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 NO2 sensor based on arrays of Au nanoparticles coated with a thin layer of polycrystalline WO3, which displays a spectral redshift in the localized surface plasmon resonance in response to NO2. 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 NO2 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 WO3 layer and the plasmonic Au nanoparticles, WO3 layer volume expansion, and changes in WO3 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.

Robust Colloidal Synthesis of Palladium-Gold Alloy Nanoparticles for Hydrogen Sensing.

Metal nanoparticles are currently used in a variety of applications, ranging from life sciences to nanoelectronic devices to gas sensors. In particular, the use of palladium nanoparticles is gaining increasing attention due to their ability to catalyze the rapid dissociation of hydrogen, which leads to an excellent response in hydrogen-sensing applications. However, current palladium-nanoparticle-based sensors are hindered by the presence of hysteresis upon hydride formation and decomposition, as this hysteresis limits sensor accuracy. Here, we present a robust colloidal synthesis for palladium-gold alloy nanoparticles and demonstrate their hysteresis-free response when used for hydrogen detection. The obtained colloidal particles, synthesized in an aqueous, room-temperature environment, can be tailored to a variety of applications through changing the size, ratio of metals, and surface stabilization. In particular, the variation of the viscosity of the mixture during synthesis resulted in a highly tunable size distribution and contributed to a significant improvement in size dispersity compared to the state-of-the-art methods.

Grain-growth mediated hydrogen sorption kinetics and compensation effect in single Pd nanoparticles.

Grains constitute the building blocks of polycrystalline materials and their boundaries determine bulk physical properties like electrical conductivity, diffusivity and ductility. However, the structure and evolution of grains in nanostructured materials and the role of grain boundaries in reaction or phase transformation kinetics are poorly understood, despite likely importance in catalysis, batteries and hydrogen energy technology applications. Here we report an investigation of the kinetics of (de)hydriding phase transformations in individual Pd nanoparticles. We find dramatic evolution of single particle grain morphology upon cyclic exposure to hydrogen, which we identify as the reason for the observed rapidly slowing sorption kinetics, and as the origin of the observed kinetic compensation effect. These results shed light on the impact of grain growth on kinetic processes occurring inside nanoparticles, and provide mechanistic insight in the observed kinetic compensation effect.

Light-Off in Plasmon-Mediated Photocatalysis.

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 Au50Pd50 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.

Highly Permeable Fluorinated Polymer Nanocomposites for Plasmonic Hydrogen Sensing.

Hydrogen (H2) sensors that can be produced en masse with cost-effective manufacturing tools are critical for enabling safety in the emerging hydrogen economy. The use of melt-processed nanocomposites in this context would allow the combination of the advantages of plasmonic hydrogen detection with polymer technology; an approach which is held back by the slow diffusion of H2 through the polymer matrix. Here, we show that the use of an amorphous fluorinated polymer, compounded with colloidal Pd nanoparticles prepared by highly scalable continuous flow synthesis, results in nanocomposites that display a high H2 diffusion coefficient in the order of 10-5 cm2 s-1. As a result, plasmonic optical hydrogen detection with melt-pressed fluorinated polymer nanocomposites is no longer limited by the diffusion of the H2 analyte to the Pd nanoparticle transducer elements, despite a thickness of up to 100 µm, thereby enabling response times as short as 2.5 s at 100 mbar (≡10 vol. %) H2. Evidently, plasmonic sensors with a fast response time can be fabricated with thick, melt-processed nanocomposites, which paves the way for a new generation of robust H2 sensors.

Shedding Light on CO Oxidation Surface Chemistry on Single Pt Catalyst Nanoparticles Inside a Nanofluidic Model Pore.

Investigating a catalyst under relevant application conditions is experimentally challenging and parameters like reaction conditions in terms of temperature, pressure, and reactant mixing ratios, as well as catalyst design, may significantly impact the obtained experimental results. For Pt catalysts widely used for the oxidation of carbon monoxide, there is keen debate on the oxidation state of the surface at high temperatures and at/above atmospheric pressure, as well as on the most active surface state under these conditions. Here, we employ a nanoreactor in combination with single-particle plasmonic nanospectroscopy to investigate individual Pt catalyst nanoparticles localized inside a nanofluidic model pore during carbon monoxide oxidation at 2 bar in the 450-550 K temperature range. As a main finding, we demonstrate that our single-particle measurements effectively resolve a kinetic phase transition during the reaction and that each individual particle has a unique response. Based on spatially resolved measurements, we furthermore observe how reactant concentration gradients formed due to conversion inside the model pore give rise to position-dependent kinetic phase transitions of the individual particles. Finally, employing extensive electrodynamics simulations, we unravel the surface chemistry of the individual Pt nanoparticles as a function of reactant composition and find strongly temperature-dependent Pt-oxide formation and oxygen spillover to the SiO2 support as the main processes. These results therefore support the existence of a Pt surface oxide in the regime of high catalyst activity and demonstrate the possibility to use plasmonic nanospectroscopy in combination with nanofluidics as a tool for in situ studies of individual catalyst particles.