Resolving Nonequilibrium Shape Variations among Millions of Gold Nanoparticles.

Nanoparticles, exhibiting functionally relevant structural heterogeneity, are at the forefront of cutting-edge research. Now, high-throughput single-particle imaging (SPI) with X-ray free-electron lasers (XFELs) creates opportunities for recovering the shape distributions of millions of particles that exhibit functionally relevant structural heterogeneity. To realize this potential, three challenges have to be overcome: (1) simultaneous parametrization of structural variability in real and reciprocal spaces; (2) efficiently inferring the latent parameters of each SPI measurement; (3) scaling up comparisons between 105 structural models and 106 XFEL-SPI measurements. Here, we describe how we overcame these three challenges to resolve the nonequilibrium shape distributions within millions of gold nanoparticles imaged at the European XFEL. These shape distributions allowed us to quantify the degree of asymmetry in these particles, discover a relatively stable "shape envelope" among nanoparticles, discern finite-size effects related to shape-controlling surfactants, and extrapolate nanoparticles' shapes to their idealized thermodynamic limit. Ultimately, these demonstrations show that XFEL SPI can help transform nanoparticle shape characterization from anecdotally interesting to statistically meaningful.

Electron Donor-Specific Surface Interactions Promote the Photocatalytic Activity of Metal-Semiconductor Nanohybrids.

In the past two decades, the application of colloidal semiconductor-metal nanoparticles (NPs) as photocatalysts for the hydrogen generation from water has been extensively studied. The present body of literature studies agrees that the photocatalytic yield strongly depends on the electron donating agent (EDA) added for scavenging the photogenerated holes. The highest reported hydrogen production rates are obtained in the presence of ionic EDAs and at high pH. The large hydrogen production rates are attributed to fast hole transfer from the NP onto the EDAs. However, the present discussions do not treat the influence of EDA-specific surface interactions. This systematic study focuses on that aspect by combining steady-state hydrogen production measurements with time-resolved and static optical spectroscopy, employing 11-mercaptoundecanoic acid-capped, Pt-tipped CdSe/CdS dot-in-rods in the presence of a large set of EDAs. Based on the experimental results, two distinct EDA groups are identified: surface-active and diffusion-limited EDAs. The largest photocatalytic efficiencies are obtained in the presence of surface-active EDAs that induce an agglomeration of the NPs. This demonstrates that the introduction of surface-active EDAs can significantly enhance the photocatalytic activity of the NPs, despite reducing their colloidal stability and inducing the formation of NP networks.

Far-Field Petahertz Sampling of Plasmonic Fields.

The response of metal nanostructures to optical excitation leads to localized surface plasmon (LSP) generation with nanoscale field confinement driving applications in, for example, quantum optics and nanophotonics. Field sampling in the terahertz domain has had a tremendous impact on the ability to trace such collective excitations. Here, we extend such capabilities and introduce direct sampling of LSPs in a more relevant petahertz domain. The method allows to measure the LSP field in arbitrary nanostructures with subcycle precision. We demonstrate the technique for colloidal nanoparticles and compare the results to finite-difference time-domain calculations, which show that the build-up and dephasing of the plasmonic excitation can be resolved. Furthermore, we observe a reshaping of the spectral phase of the few-cycle pulse, and we demonstrate ad-hoc pulse shaping by tailoring the plasmonic sample. The methodology can be extended to single nanosystems and applied in exploring subcycle, attosecond phenomena.

Time-Resolved Single-Particle X-ray Scattering Reveals Electron-Density Gradients As Coherent Plasmonic-Nanoparticle-Oscillation Source.

Dynamics of optically excited plasmonic nanoparticles are presently understood as a series of scattering events involving the initiation of nanoparticle breathing oscillations. According to established models, these are caused by statistical heat transfer from thermalized electrons to the lattice. An additional contribution by hot-electron pressure accounts for phase mismatches between theory and experimental observations. However, direct experimental studies resolving the breathing-oscillation excitation are still missing. We used optical transient-absorption spectroscopy and time-resolved single-particle X-ray diffractive imaging to access the electron system and lattice. The time-resolved single-particle imaging data provided structural information directly on the onset of the breathing oscillation and confirmed the need for an additional excitation mechanism for thermal expansion. We developed a new model that reproduces all of our experimental observations. We identified optically induced electron density gradients as the initial driving source.

Theory of radial oscillations in metal nanoparticles driven by optically induced electron density gradients.

We provide a microscopic approach to describe the onset of radial oscillation of a silver nanoparticle. Using the Heisenberg equation of motion framework, we find that the coupled ultrafast dynamics of coherently excited electron occupation and the coherent phonon amplitude initiate periodic size oscillations of the nanoparticle. Compared to the established interpretation of experiments, our results show a more direct coupling mechanism between the field intensity and coherent phonons. This interaction triggers a size oscillation via an optically induced electron density gradient occurring directly with the optical excitation. This source is more efficient than the incoherent heating process currently discussed in the literature and well-describes the early onset of the oscillations in recent experiments.

Full-Spectrum InP-Based Quantum Dots with Near-Unity Photoluminescence Quantum Efficiency.

Photoluminescent color conversion by quantum dots (QDs) makes possible the formation of spectrum-on-demand light sources by combining blue LEDs with the light generated by a specific blend of QDs. Such applications, however, require a near-unity photoluminescence quantum efficiency since self-absorption magnifies disproportionally the impact of photon losses on the overall conversion efficiency. Here, we present a synthesis protocol for forming InP-based QDs with +90% quantum efficiency across the full visible spectrum from blue/cyan to red. The central features of our approach are as follows: (1) the formation of InP core QDs through one-batch-one-size reactions based on aminophosphine as the phosphorus precursor, (2) the introduction of a core/shell/shell InP/Zn(Se,S)/ZnS structure, and (3) the use of specific interfacial treatments, most notably the saturation of the ZnSe surface with zinc acetate prior to ZnS shell growth. Moreover, we adapted the composition of the Zn(Se,S) inner shell to attain the intended emission color while minimizing line broadening induced by the InP/ZnS lattice mismatch. The protocol is established by analysis of the QD composition and structure using multiple techniques, including solid-state nuclear magnetic resonance spectroscopy and Raman spectroscopy, and verified for reproducibility by having different researchers execute the same protocol. The realization of full-spectrum, +90% quantum efficiency will strongly facilitate research into light-matter interaction in general and luminescent color conversion in particular through InP-based QDs.

Unsupervised learning approaches to characterizing heterogeneous samples using X-ray single-particle imaging.

One of the outstanding analytical problems in X-ray single-particle imaging (SPI) is the classification of structural heterogeneity, which is especially difficult given the low signal-to-noise ratios of individual patterns and the fact that even identical objects can yield patterns that vary greatly when orientation is taken into consideration. Proposed here are two methods which explicitly account for this orientation-induced variation and can robustly determine the structural landscape of a sample ensemble. The first, termed common-line principal component analysis (PCA), provides a rough classification which is essentially parameter free and can be run automatically on any SPI dataset. The second method, utilizing variation auto-encoders (VAEs), can generate 3D structures of the objects at any point in the structural landscape. Both these methods are implemented in combination with the noise-tolerant expand-maximize-compress (EMC) algorithm and its utility is demonstrated by applying it to an experimental dataset from gold nanoparticles with only a few thousand photons per pattern. Both discrete structural classes and continuous deformations are recovered. These developments diverge from previous approaches of extracting reproducible subsets of patterns from a dataset and open up the possibility of moving beyond the study of homogeneous sample sets to addressing open questions on topics such as nanocrystal growth and dynamics, as well as phase transitions which have not been externally triggered.

Carrier localization in zero-dimensional and one-dimensional CdSe-CdS heterostructures.

Mobile charge carriers in heterostructured nanoparticles are relevant for applications requiring charge separation and extraction. We investigate the benchmark systems CdSe-CdS core-shell quantum dots and quantum dots in quantum rods by optical and THz pump-probe spectroscopy. We relate photoconductivity and carrier location and observe that only shell-located electrons in quantum rods contribute to an observable photoconductivity. Despite the shallow electron confinement in the quasi-type II heterostructures, core-located carriers are bound into immobile excitons that respond on external electrical fields by polarization.

Surface-Enhanced Raman Scattering and Surface-Enhanced Infrared Absorption by Plasmon Polaritons in Three-Dimensional Nanoparticle Supercrystals.

Surface-enhanced vibrational spectroscopy strongly increases the cross section of Raman scattering and infrared absorption, overcoming the limited sensitivity and resolution of these two powerful analytic tools. While surface-enhanced setups with maximum enhancement have been studied widely in recent years, substrates with reproducible, uniform enhancement have received less attention although they are required in many applications. Here, we show that plasmonic supercrystals are an excellent platform for enhanced spectroscopy because they possess a high density of hotspots in the electric field. We describe the near field inside the supercrystal within the framework of plasmon polaritons that form due to strong light-matter interaction. From the polariton resonances we predict resonances in the far-field enhancement for Raman scattering and infrared absorption. We verify our predictions by measuring the vibrations of polystyrene molecules embedded in supercrystals of gold nanoparticles. The intensity of surface-enhanced Raman scattering is uniform within 10% across the crystal with a peak integrated enhancement of up to 300 and a peak hotspot enhancement of 105. The supercrystal polaritons induce pairs of incoming and outgoing resonances in the enhanced cross section as we demonstrate experimentally by measuring surface-enhanced Raman scattering with multiple laser wavelengths across the polariton resonance. The infrared absorption of polystyrene is likewise enhanced inside the supercrystals with a maximum enhancement of 400%. We show with a coupled oscillator model that the increase originates from the combined effects of hotspot formation and the excitation of standing polariton waves. Our work clearly relates the structural and optical properties of plasmonic supercrystals and shows that such crystals are excellent hosts and substrates for the uniform and predictable enhancement of vibrational spectra.

Inter-individual variability in spring phenology of temperate deciduous trees depends on species, tree size and previous year autumn phenology.

We explored the inter-individual variability in bud-burst and its potential drivers, in homogeneous mature stands of temperate deciduous trees. Phenological observations of leaves and wood formation were performed weekly from summer 2017 to summer 2018 for pedunculate oak, European beech and silver birch in Belgium. The variability of bud-burst was correlated to previous' year autumn phenology (i.e. the onset of leaf senescence and the cessation of wood formation) and tree size but with important differences among species. In fact, variability of bud-burst was primarily related to onset of leaf senescence, cessation of wood formation and tree height for oak, beech and birch, respectively. The inter-individual variability of onset of leaf senescence was not related to the tree characteristics considered and was much larger than the inter-individual variability in bud-burst. Multi-species multivariate models could explain up to 66% of the bud-burst variability. These findings represent an important advance in our fundamental understanding and modelling of phenology and tree functioning of deciduous tree species.

Structural order in plasmonic superlattices.

The assembly of plasmonic nanoparticles into ordered 2D- and 3D-superlattices could pave the way towards new tailored materials for plasmonic sensing, photocatalysis and manipulation of light on the nanoscale. The properties of such materials strongly depend on their geometry, and accordingly straightforward protocols to obtain precise plasmonic superlattices are highly desirable. Here, we synthesize large areas of crystalline mono-, bi- and multilayers of gold nanoparticles >20 nm with a small number of defects. The superlattices can be described as hexagonal crystals with standard deviations of the lattice parameter below 1%. The periodic arrangement within the superlattices leads to new well-defined collective plasmon-polariton modes. The general level of achieved superlattice quality will be of benefit for a broad range of applications, ranging from fundamental studies of light-matter interaction to optical metamaterials and substrates for surface-enhanced spectroscopies.

Deep strong light-matter coupling in plasmonic nanoparticle crystals.

In the regime of deep strong light-matter coupling, the coupling strength exceeds the transition energies of the material1-3, fundamentally changing its properties4,5; for example, the ground state of the system contains virtual photons and the internal electromagnetic field gets redistributed by photon self-interaction1,6. So far, no electronic excitation of a material has shown such strong coupling to free-space photons. Here we show that three-dimensional crystals of plasmonic nanoparticles can realize deep strong coupling under ambient conditions, if the particles are ten times larger than the interparticle gaps. The experimental Rabi frequencies (1.9 to 3.3 electronvolts) of face-centred cubic crystals of gold nanoparticles with diameters between 25 and 60 nanometres exceed their plasmon energy by up to 180 per cent. We show that the continuum of photons and plasmons hybridizes into polaritons that violate the rotating-wave approximation. The coupling leads to a breakdown of the Purcell effect-the increase of radiative damping through light-matter coupling-and increases the radiative polariton lifetime. The results indicate that metallic and semiconducting nanoparticles can be used as building blocks for an entire class of materials with extreme light-matter interaction, which will find application in nonlinear optics, the search for cooperative effects and ground states, polariton chemistry and quantum technology4,5.

Timeline of autumn phenology in temperate deciduous trees.

Cessation of xylem formation or wood growth (CWG) and onset of foliar senescence (OFS) are key autumn phenological events in temperate deciduous trees. Their timing is fundamental for the development and survival of trees, ecosystem nutrient cycling and the seasonal exchange of matter and energy between the biosphere and atmosphere, and affects the impact and feedback of forests to global change. A large-scale experimental effort and improved observational methods have allowed us to compare the timing of CWG and OFS for different deciduous tree species in Western Europe, particularly in silver birch, a pioneer species, and European beech, a late-succession species, at stands of different latitudes, of different levels of site fertility, for 2 years with contrasting meteorological and drought conditions, i.e., the low moderately dry 2017 and the extremely dry 2018. Specifically, we tested whether foliar senescence started before, after or concurrently with CWG. Onset of foliar senescence and CWG occurred generally between late September and early November, with larger differences across species and sites for OFS. Foliar senescence started concurrently with CWG in most cases, except for the drier 2018 and, for beech, at the coldest site, where OFS occurred significantly later than CWG. The behavior of beech in Spain, the southern edge of its European distribution, was unclear, with no CWG, but very low wood growth at the time of OFS. Our study suggests that OFS is generally triggered by the same drivers of CWG or when wood growth decreases in late summer, indicating an overarching mechanism of sink limitation as a possible regulator of the timing of foliar senescence.

Dark plasmon modes for efficient hot electron generation in multilayers of gold nanoparticles.

The excitation of dark plasmons, i.e., coupled plasmon modes with a vanishing net dipole, is expected to favor Landau damping over radiative damping. Dark plasmon excitation might, therefore, lead to an increased absorption of energy within gold nanoparticles, resulting in a strong generation of hot electrons compared to the generation via bright plasmons. We performed transient-absorption spectroscopy on gold nanoparticle films to assess the initial electronic temperature before thermalization. We observe a significant increase in the electron-phonon coupling time when dark plasmon modes are excited in these films. The results indicate an efficient energy absorption due to the suppressed radiative decay of dark plasmon modes and a subsequent energy transformation into hot electrons.

Strain in InP/ZnSe, S core/shell quantum dots from lattice mismatch and shell thickness-Material stiffness influence.

We investigate the buildup of strain in InP quantum dots with the addition of shells of the lower-lattice constant materials ZnSe and ZnS by Raman spectroscopy. Both materials induce compressive strain in the core, which increases with increasing shell volume. We observe a difference in the shell behavior between the two materials: the thickness-dependence points toward an influence of the material stiffness. ZnS has a larger Young's modulus and requires less material to develop stress on the InP lattice at the interface, while ZnSe requires several layers to form a stress-inducing lattice at the interface. This hints at the material stiffness being an additional parameter of relevance for designing strained core/shell quantum dots.

Kinetics of pressure-induced nanocrystal superlattice formation.

Colloidal nanocrystals (NC) are known to self-organize into superlattices that promise many applications ranging from medicine to optoelectronics. Recently, the formation of high-quality PEGylated gold NC was reported at high hydrostatic pressure and high salt concentrations. Here, we study the formation kinetics of these superlattices after pressure jumps beyond their crystallisation pressure by means of small-angle X-ray scattering with few ms experimental resolution. The timescale of NC formation was found to be reduced the larger the width of the pressure jump. This is connected to an increase of crystal quality, i.e., the faster the NC superlattice forms, the better the crystal quality. In contrast to the formation kinetics, the melting of the NC superlattice is approximately one order of magnitude slower and shows linear kinetics.

Direct optical excitation of dark plasmons for hot electron generation.

An ideal plasmonic system for hot-electron generation allows the optical excitation of plasmons, limits radiation losses, exhibits strong non-radiative electron damping, and is made from scalable and cost-effective materials. Here we demonstrate the optical excitation of dark interlayer plasmons in bilayers of colloidal gold nanoparticles. This excitation is created by an antiparallel orientation of the dipole moments in the nanoparticle layers; it is expected to exhibit strongly reduced radiative damping. Despite the vanishing dipole moment, an incoming electromagnetic wave that is propagating normal to the surface will excite the dark mode due to field retardation. We observe a strong peak in the absorption spectrum of a colloidal gold bilayer (nanoparticle diameter = 46 nm); this peak is absent for a nanoparticle monolayer. The full width at half maximum of the dark mode is 230 meV for an ideal nanoparticle crystal and 320 meV for the structure produced by self-assembly out of solution. The position and width of the dark plasmon are efficiently tailored by the interparticle distance within the layer, nanoparticle size and layer number. We present time-resolved pump and probe experiments of hot-electron generation by bright and dark bilayer nanoparticle modes.

Validation of a Muscle-Specific Tissue Image Analysis Tool for Quantitative Assessment of Dystrophin Staining in Frozen Muscle Biopsies.

CONTEXT.­: Duchenne muscular dystrophy is a rare, progressive, and fatal neuromuscular disease caused by dystrophin protein loss. Common investigational treatment approaches aim at increasing dystrophin expression in diseased muscle. Some clinical trials include assessments of novel dystrophin production as a surrogate biomarker of efficacy, which may predict a clinical benefit from treatment. OBJECTIVES.­: To establish an immunofluorescent scanning and digital image analysis workflow that provides an objective approach for staining intensity assessment of the immunofluorescence dystrophin labeling and determination of the percentage of biomarker-positive fibers in muscle cryosections. DESIGN.­: Optimal and repeatable digital image capture was achieved by a rigorously qualified fluorescent scanning process. After scanning qualification, the MuscleMap (Flagship Biosciences, Westminster, Colorado) algorithm was validated by comparing high-power microscopic field total and dystrophin-positive fiber counts obtained by trained pathologists to data derived by MuscleMap. Next, the algorithm was tested on whole-slide images of immunofluorescent-labeled muscle sections from Duchenne muscular dystrophy, Becker muscular dystrophy, and control patients. RESULTS.­: When used under the guidance of a trained pathologist, the digital image analysis tool met predefined validation criteria and demonstrated functional and statistical equivalence with manual assessment. This work is the first, to our knowledge, to qualify and validate immunofluorescent scanning and digital tissue image-analysis workflow, respectively, with the rigor required to support the clinical trial environments. CONCLUSIONS.­: MuscleMap enables analysis of all fibers within an entire muscle biopsy section and provides data on a fiber-by-fiber basis. This will allow future clinical trials to objectively investigate myofibers' dystrophin expression at a greater level of consistency and detail.

Resonant Energy Transfer can Trigger Multiexciton Recombination in Dense Quantum Dot Ensembles.

Core/shell quantum dots/quantum rods are nanocrystals with typical application scenarios as ensembles. Resonance energy transfer is a possible process between adjacent nanocrystals. Highly excited nanocrystals can also relax energy by multiexciton recombination, competing against the energy transfer. The two processes have different dependencies and can be convolved, resulting in collective properties different from the superposition of the individual nanocrystals. A platform to study the interplay of energy transfer and multiexciton recombination is presented. CdSe/CdS quantum dot/quantum rods encapsulated in amphiphilic micelles with an interparticle distance control by spacer ligands are used for time-resolved photoluminescence and transient absorption experiments. At exciton populations around one, the ensemble starts to be in a state where energy transfer can trigger multiexciton Auger recombination, altering the collective dynamics.

Nonlinear dynamics of river runoff elucidated by horizontal visibility graphs.

Horizontal Visibility Graphs (HVGs) are a recently developed method to construct networks from time series. The values of the time series are considered as the nodes of the network and are linked to each other if there is no larger value between them, such as they can "see" each other. The network properties reflect the nonlinear dynamics of the time series. For some classes of stochastic processes and for periodic time series, analytical results can be obtained for network-derived quantities such as the degree distribution, the local clustering coefficient distribution, the mean path length, and others. HVGs have the potential to discern between deterministic-chaotic and correlated-stochastic time series. Here, we investigate the sensitivity of the HVG methodology to properties and pre-processing of real-world data, i.e., time series length, the presence of ties, and deseasonalization, using a set of around 150 runoff time series from managed rivers at daily resolution from Brazil with an average length of 65 years. We show that an application of HVGs on real-world time series requires a careful consideration of data pre-processing steps and analysis methodology before robust results and interpretations can be obtained. For example, one recent analysis of the degree distribution of runoff records reported pronounced sub-exponential "long-tailed" behavior of North American rivers, whereas another study of South American rivers showed hyper-exponential "short-tailed" behavior resembling correlated noise. We demonstrate, using the dataset of Brazilian rivers, that these apparently contradictory results can be reconciled by minor differences in data-preprocessing (here: small differences in subtracting the seasonal cycle). Hence, data-preprocessing that is conventional in hydrology ("deseasonalization") changes long-term correlations and the overall runoff dynamics substantially, and we present empirical consequences and extensive simulations to investigate these issues from a HVG methodological perspective. After carefully accounting for these methodological aspects, the HVG analysis reveals that the river runoff dataset shows indeed complex behavior that appears to stem from a superposition of short-term correlated noise and "long-tailed behaviour," i.e., highly connected nodes. Moreover, the construction of a dam along a river tends to increase short-term correlations in runoff series. In summary, the present study illustrates the (often substantial) effects of methodological and data-preprocessing choices for the interpretation of river runoff dynamics in the HVG framework and its general applicability for real-world time series.