Mesoporous Metal Sponges Produced by Explosive Decomposition.

The formation of mesoporous gold sponges by explosive decomposition of 'knallgold' (also known as 'fulminating' gold) is studied. Proof-of-principle experiments are conducted and then the phenomena are further investigated using 'toy physics' molecular dynamics simulations. The simulations invoked various ratios of a volatile Lennard-Jones element G and a noble metal element N. In both experiment and simulation the morphology of the resulting sponge is found to depend on the stoichiometry of the starting material. As the mole fraction of G (χG) is increased from 0.5 to close to 1.0 in the simulations, the morphology of the sponges changes from closed to open, with a corresponding increase in the average mean curvature from 0 to +0.12 inverse Lennard-Jones length (L) units. The average Gaussian curvature of the simulated sponges is always negative, with the minimum value of 0.05 L-2 being found for χG ≈0.65. In broad agreement with experiment, sponge formation in the simulations is bounded by stoichiometry; no sponges form if χG is <0.52, for χG between 0.52 and 0.70 the sponge is characterized by vermicular cavities whereas classic bicontinuous fibrous sponges form for 0.70< χG < 0.85 and, finally, discrete particles result if χG >0.85.

Computation via Neuron-like Spiking in Percolating Networks of Nanoparticles.

The biological brain is a highly efficient computational system in which information processing is performed via electrical spikes. Neuromorphic computing systems that work on similar principles could support the development of the next generation of artificial intelligence and, in particular, enable low-power edge computing. Percolating networks of nanoparticles (PNNs) have previously been shown to exhibit critical spiking behavior, with promise for highly efficient natural computation. Here we employ a rate coding scheme to show that PNNs can perform Boolean operations and image classification. Near perfect accuracy is achieved in both tasks by manipulating the spiking activity using certain control voltages. We demonstrate that the key to successful computation is that nanoscale tunnel gaps within the percolating networks transform input data through a powerful modulus-like nonlinearity. These results provide a basis for implementation of further computational schemes that exploit the brain-like criticality of these networks.

Noise and pulse dynamics in backward stimulated Brillouin scattering.

We theoretically and numerically study the effects of thermal noise on pulses in backwards stimulated Brillouin scattering (SBS). Using a combination of stochastic calculus and numerical methods, we derive a theoretical model that can be used to quantitatively predict noise measurements. We study how the optical pulse configuration, including the input powers of the pump and Stokes fields, pulse durations and interaction time, affects the noise in the output Stokes field. We investigate the effects on the noise of the optical loss and waveguide length, and we find that the signal-to-noise ratio can be significantly improved, or reduced, for specific combinations of waveguide properties and pulse parameters.

Noise in Brillouin based information storage.

We theoretically and numerically study the efficiency of Brillouin-based opto-acoustic data storage in a photonic waveguide in the presence of thermal noise and laser phase noise. We compare the physics of the noise processes and how they affect different storage techniques, examining both amplitude and phase storage schemes. We investigate the effects of storage time and pulse properties on the quality of the retrieved signal and find that phase storage is less sensitive to thermal noise than amplitude storage.

Atomic Scale Dynamics Drive Brain-like Avalanches in Percolating Nanostructured Networks.

Self-assembled networks of nanoparticles and nanowires have recently emerged as promising systems for brain-like computation. Here, we focus on percolating networks of nanoparticles which exhibit brain-like dynamics. We use a combination of experiments and simulations to show that the brain-like network dynamics emerge from atomic-scale switching dynamics inside tunnel gaps that are distributed throughout the network. The atomic-scale dynamics emulate leaky integrate and fire (LIF) mechanisms in biological neurons, leading to the generation of critical avalanches of signals. These avalanches are quantitatively the same as those observed in cortical tissue and are signatures of the correlations that are required for computation. We show that the avalanches are associated with dynamical restructuring of the networks which self-tune to balanced states consistent with self-organized criticality. Our simulations allow visualization of the network states and detailed mechanisms of signal propagation.

Extending the applicability of the four-flux radiative transfer method.

A generalized four-flux method capable of modeling and tuning the spectral reflectance of a diverse range of complex composite coatings is presented. An example application is exploring and maximizing the visible and near-infrared (IR) spectral reflectance available from the diverse structures arising from combinations of the many practical paint ingredients that are available or can be made when applied to different substrates. This requires consideration of scatterers that can differ in composition, particle size, size distribution, and fill factor, and are held in place by a variety of organic binders, which typically partially absorb in the near IR. This extended model is further enhanced by an explicit matrix algorithm that allows analysis of diverse multilayer stacks. This is applied to a multilayer and is designed to model useful changes that result from varying the pigment fill factor as a function of depth within a layer. What we believe is a novel feature is the way the scattering affects matrix absorptance. The model includes contributions to total absorptance from the scattering pigments and from the paint binder that can arise in different bands or simultaneously at the same wavelengths. Model accuracy is demonstrated by example results when compared to experimental data on dried single layer paint profiles using imaged cross sections. The model input covering the actual pigment and binder properties used are material, shape, size, and size distributions, mass added, and the measured optical constants from 400 nm to 2,500 nm of the undoped binder resin layer. One interesting result is the comparison of a two-layered stack, with bigger particles in the first layer and smaller ones in the second, to one with the opposite depth profile.

Multipolar and dark-mode plasmon resonances on drilled silver nano-triangles.

Dark-mode plasmon resonances can be excited by positioning a suitable nano-antenna above a nanostructure to couple a planar incident wave-front into a virtual point source. We explore this phenomenon using a prototypical nanostructure consisting of a silver nanotriangle into which a hole has been drilled and a rod-like nano-antenna of variable aspect ratio. Using numerical simulations, we establish the behavior of the basic drilled nanotriangle under plane wave illumination and electron beam irradiation to provide a baseline, and then add the nano-antenna to investigate the stimulation of additional dark-mode plasmon resonances. The introduction of a suitably tuned nano-antenna provides a new and general means of exciting dark-mode resonances using plane wave light. The resulting system exhibits a very rich variety of radiant and sub-radiant resonance modes.

Multimode resonances in silver nanocuboids.

A rich variety of dipolar and higher order plasmon resonances have been predicted for nanoscale cubes and parallopipeds of silver, in contrast to the simple dipolar modes found on silver nanospheres or nanorods. However, in general, these multimode resonances are not readily detected in experimental colloidal ensembles, due primarily to the usual variation of size and shape of the particles obscuring or blending the individual extinction peaks. Recently, methods have been found to prepare silver parallopipeds with unprecedented shape control by nucleating the silver onto a tightly controlled suspension of gold nanorods (Okuno, Y.; Nishioka, K.; Kiya, A.; Nakashima, N.; Ishibashi, A.; Niidome, Y. Uniform and Controllable Preparation of Au-Ag Core-Shell Nanorods Using Anisotropic Silver Shell Formation on Gold Nanorods. Nanoscale 2010, 2, 1489-1493). The optical extinction spectra of suspensions of such monodisperse particles are found to contain multiple extinction peaks, which we show here to be due to the multimode resonances predicted by theoretical studies. Control of the radius of the nanoparticle edges is found to be an effective way to turn some of these modes on or off. These nanoparticles provide a flexible platform for the excitation, manipulation, and exploration of higher order plasmon resonances.

Stochastic Spiking Behavior in Neuromorphic Networks Enables True Random Number Generation.

There is currently a great deal of interest in the use of nanoscale devices to emulate the behaviors of neurons and synapses and to facilitate brain-inspired computation. Here, it is shown that percolating networks of nanoparticles exhibit stochastic spiking behavior that is strikingly similar to that observed in biological neurons. The spiking rate can be controlled by the input stimulus, similar to "rate coding" in biology, and the distributions of times between events are log-normal, providing insights into the atomic-scale spiking mechanism. The stochasticity of the spiking behavior is then used for true random number generation, and the high quality of the generated random bit-streams is demonstrated, opening up promising routes toward integration of neuromorphic computing with secure information processing.

Universal scaling of local plasmons in chains of metal spheres.

The position, width, extinction, and electric field of localized plasmon modes in closely-coupled linear chains of small spheres are investigated. A dipole-like model is presented that separates the universal geometric factors from the specific metal permittivity. An electrostatic surface integral method is used to deduce universal parameters that are confirmed against results for different metals (bulk experimental Ag, Au, Al, K) calculated using retarded vector spherical harmonics and finite elements. The mode permittivity change decays to an asymptote with the number of particles in the chain, and changes dramatically from 1/f(3) to 1/f(1/2) as the gap fraction (ratio of gap between spheres to their diameter), f, gets smaller. Scattering increases significantly with closer coupling. The mode sharpness, strength and electric field for weakly retarded calculations are consistent with electrostatic predictions once the effect of radiative damping is accounted for.

The Quest for Zero Loss: Unconventional Materials for Plasmonics.

There has been an ongoing quest to optimize the materials used to build plasmonic devices: first the elements were investigated, then alloys and intermetallic compounds, later semiconductors were considered, and, most recently, there has been interest in using more exotic materials such as topological insulators and conducting oxides. The quality of the plasmon resonances in these materials is closely correlated with their structure and properties. In general gold and silver are the most commonly specified materials for these applications but they do have weaknesses. Here, it is shown how, in specific circumstances, the selection of certain other materials might be more useful. Candidate alternatives include Tix N, VO2 , Al, Cu, Al-doped ZnO, and Cu-Al alloys. The relative merits of these choices and the many pitfalls and subtle problems that arise are discussed, and a frank perspective on the field is provided.

Long-range temporal correlations in scale-free neuromorphic networks.

Biological neuronal networks are the computing engines of the mammalian brain. These networks exhibit structural characteristics such as hierarchical architectures, small-world attributes, and scale-free topologies, providing the basis for the emergence of rich temporal characteristics such as scale-free dynamics and long-range temporal correlations. Devices that have both the topological and the temporal features of a neuronal network would be a significant step toward constructing a neuromorphic system that can emulate the computational ability and energy efficiency of the human brain. Here we use numerical simulations to show that percolating networks of nanoparticles exhibit structural properties that are reminiscent of biological neuronal networks, and then show experimentally that stimulation of percolating networks by an external voltage stimulus produces temporal dynamics that are self-similar, follow power-law scaling, and exhibit long-range temporal correlations. These results are expected to have important implications for the development of neuromorphic devices, especially for those based on the concept of reservoir computing.

Optical performance and metallic absorption in nanoplasmonic systems.

Optical metrics relating to metallic absorption in representative plasmonic systems are surveyed, with a view to developing heuristics for optimizing performance over a range of applications. We use the real part of the permittivity as the independent variable; consider strengths of particle resonances, resolving power of planar lenses, and guiding lengths of planar waveguides; and compare nearly-free-electron metals including Al, Cu, Ag, Au, Li, Na, and K. Whilst the imaginary part of metal permittivity has a strong damping effect, field distribution is equally important and thus factors including geometry, real permittivity and frequency must be considered when selecting a metal. Al performs well at low permittivities (e.g. sphere resonances, superlenses) whereas Au & Ag only perform well at very negative permittivities (shell and rod resonances, LRSPP). The alkali metals perform well overall but present engineering challenges.

An improved transfer-matrix model for optical superlenses.

The use of transfer-matrix analyses for characterizing planar optical superlensing systems is studied here, and the simple model of the planar superlens as an isolated imaging element is shown to be defective in certain situations. These defects arise due to neglected interactions between the superlens and the spatially varying shadow masks that are normally used as scattering objects for imaging, and which are held in near-field proximity to the superlenses. An extended model is proposed that improves the accuracy of the transfer-matrix analysis, without adding significant complexity, by approximating the reflections from the shadow mask by those from a uniform metal layer. Results obtained using both forms of the transfer matrix model are compared to finite element models and two example superlenses, one with a silver monolayer and the other with three silver sublayers, are characterized. The modified transfer matrix model gives much better agreement in both cases.

Subwavelength optical imaging of evanescent fields using reflections from plasmonic slabs.

Reflection can significantly improve the quality of subwavelength near-field images, which is explained by appropriate interference between forward and reflected waves. Plasmonic slabs may form approximate super-mirrors. This paper develops general theory in both spectral and spatial representations that allows the reflector position and permittivity to be determined for optimum image uniformity. This elucidates previous observations and predicts behaviour for some other interesting regimes, including interferometric lithography.

Single-mode tuning of the plasmon resonance in high-density pillar arrays.

The Maxwell-Garnett (MG) effective medium model has a pure resonance controlled by volume fraction f, but is usually invalid at high density. I present special 2D structures that match quasistatic MG over the entire range 0 < f < 1, in several regular and semi-regular arrays, expanding the applicability of MG. Optimal contours depend on both lattice and fill-factor, transforming from circular at low f to nearly polygonal at high f. A key insight is the direct relationship between optimal surface polarization and surface position. Electrodynamic calculations underline the effect of constituent permittivity on spatial dispersion and required sizes for quasistatic response in various materials.

Effect of precursor stoichiometry on the morphology of nanoporous platinum sponges.

Nanoscale sponges formed by de-alloying suitable metallic alloys have a wide variety of potential applications due to their enhanced catalytic, optical, and electrochemical properties. In general, these materials have a bi-continuous, vermicular morphology of pores and ligaments with a fibrous appearance; however, other morphologies are sometimes reported. Here, we investigate how stoichiometry and process parameters control the characteristics of sponges formed from thin film precursors of AlxPt. Materials deposited at elevated temperatures and with mole fraction of Al between 0.65 and 0.90 produce the classic isotropic fibrous sponges with a morphology that varies systematically with precursor stoichiometry; however, de-alloying of material deposited at room temperature produced unusual isotropic foamy sponges. The evidence suggests that formation of a conventional fibrous sponge requires an equilibrated precursor whereas foamy morphologies will result if the precursor is metastable. Modeling was used to investigate the range of possible morphologies. As stoichiometry changed in the model system, the average mean and Gaussian curvature of the sponges systematically changed, too. The evolution of these shapes passed through certain special morphologies; for example, modelled structures with 0.80 Al had a zero average Gaussian curvature and might represent a structural optimum for some applications. These observations provide a means to control sponge morphology at the nanoscale.

Li-ion adsorption and diffusion on two-dimensional silicon with defects: a first principles study.

Using first principles calculations we investigate the binding and diffusion of Li on silicene and evaluate the prospects for application to Li-ion batteries. We find that the defect formation energy for silicene is half that of graphene, showing that silicene is more likely to contain defects. The overall lithium adsorption energy on silicene with defects is greater than the bulk cohesive energy of lithium giving stability for use in storage. Our results predict high mobility for lithium atoms on the surface of silicene with energy barriers in the range of 0.28-0.30 eV. Further, we find that the diffusion barrier through silicene is significantly lower than the diffusion barrier through graphene, with a value of 0.05 eV for the double vacancy and 0.88 eV for the single vacancy. The low diffusion barriers, both on the surface and through the hollow site, suggest a suitable material for use in Li-ion batteries.

Image fidelity for single-layer and multi-layer silver superlenses.

In response to increasing interest in the area of subdiffraction-limited near-field imaging, the performance of several different realizable and theoretical superresolving silver-based lenses is simulated for a variety of different input object profiles. A computationally-efficient T-matrix technique is used to model the lenses, which consist of layers of silver with total width of 40 nm sandwiched between layers of polymethyl methacrylate and silicon dioxide. The lenses are exposed to nonperiodic bright- and dark-slit input patterns, with feature size varied between 1 nm and 2.5 microm. The performance of the lenses is characterized in terms of transfer function, contrast profile, error profile, and input-to-output correlation. It is shown that increasing the number of layers in a lens increases the lens' transmission coefficients at high spatial frequencies; however, this does not always lead to better imaging performance. The main reasons for this are lens-specific resonances that distort features at certain spatial frequencies, and the increased attenuation of the DC component of transmitted images, which reduces image fidelity, particularly for dark-line features. This suggests that, to achieve optimum results, the design of the superresolving lens system should take into account the characteristics of the images that it is expected to transmit.