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Results for “nanoparticle arrays”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Interplay between gain and loss in arrays of nonlinear plasmonic nanoparticles: toward parametric downconversion and amplification
With the help of a theoretical model and finite-difference time-domain (FDTD) simulations based on the hydrodynamic–Maxwell model, we examine the effect of difference-frequency generation (DFG) in an array of L-shaped metal nanoparticles (MNPs) characterized by intrinsic plasmonic nonlinearity. The outcomes of the calculations reveal the spectral interplay between gain and loss in the vicinity of the fundamental frequency of the localized surface plasmon resonances. Subsequently, we identify different array thicknesses and pumping regimes facilitating parametric amplification and spontaneous parametric downconversion. Our results suggest that the parametric amplification regime becomes feasible on a scale of hundreds of nanometers and spontaneous parametric downconversion on the scale of tens of nanometers, opening up new exciting opportunities for developing building blocks of photonic metasurfaces.
Method to synthesize nanoparticle supercrystals
Highly ordered arrays of 3D faceted nanoparticle supercrystals are formed by self-assembly with controlled nanoparticle packing and unique facet dependent optical property by using a binary solvent diffusion method. The binary diffusion results in supercrystals whose size and quality are determined by initial nanoparticle concentration and diffusion speed. The supercrystal solids display unique facet-dependent surface plasmonic and surface-enhanced Raman characteristics. The supercrystals have potential applications in areas such as optics, electronics, and sensor platforms.
Chiral Lattice Resonances in 2.5-Dimensional Periodic Arrays with Achiral Unit Cells
Not Available
Topology-controlled Polarized Photoluminescence from Rare-earth Doped Nanocrystals
We show topology-controlled polarization of photoluminescence from rare-earth doped nanocrystals using disorder-immune zigzag arrays of dielectric nanoparticles. Topological control is verified by comparing emission from nanocrystals deposited on trivial and nontrivial arrays of nanoparticles.
Conversion of Classical Light Emission from a Nanoparticle‐Strained WSe 2 Monolayer into Quantum Light Emission via Electron Beam Irradiation
Abstract Solid‐state single photon emitters (SPEs) within atomically thin transition metal dichalcogenides (TMDs) have recently attracted interest as scalable quantum light sources for quantum photonic technologies. Among TMDs, WSe 2 monolayers (MLs) are promising for the deterministic fabrication and engineering of SPEs using local strain fields. The ability to reliably produce isolatable SPEs in WSe 2 is currently impeded by the presence of numerous spectrally overlapping states that occur at strained locations. Here nanoparticle (NP) arrays with precisely defined positions and sizes are employed to deterministically create strain fields in WSe 2 MLs, thus enabling the systematic investigation and control of SPE formation. Using this platform, electron beam irradiation at NP‐strained locations transforms spectrally overlapped sub‐bandgap emission states into isolatable, anti‐bunched quantum emitters. The dependence of the emission spectra of WSe 2 MLs as a function of strain magnitude and exposure time to electron beam irradiation is quantified and provides insight into the mechanism for SPE production. Excitons selectively funnel through strongly coupled sub‐bandgap states introduced by electron beam irradiation, which suppresses spectrally overlapping emission pathways and leads to measurable anti‐bunched behavior. The findings provide a strategy to generate isolatable SPEs in 2D materials with a well‐defined energy range.
Separating Physically Distinct Mechanisms in Complex Infrared Plasmonic Nanostructures via Machine Learning Enhanced Electron Energy Loss Spectroscopy
Electron energy loss spectroscopy (EELS) enables direct exploration of plasmonic phenomena at the nanometer level. To isolate individual plasmon modes, linear unmixing methods can be used to separate different physical mechanisms, but in larger and more complex systems the interpretability of the components becomes uncertain. Here, infrared plasmonic resonances in self-assembled heterogeneous monolayer films of doped-semiconductor nanoparticles are examined beyond linear unmixing techniques, and both supervised and unsupervised machine-learning-based analyses of hyperspectral EELS datasets are demonstrated. Additionally, in the supervised approach, a human operator labels a small number of pixels in the hyperspectral dataset corresponding to features of interest which are then propagated across the entire dataset. In the unsupervised approach, non-linear autoencoders are used to create a highly-reduced latent-space representation of the dataset, within which insight into the relevant physics can be gleaned from straightforward distance metrics that do not depend on operator input and bias. The advantage of these approaches is that the labeling separates physical mechanisms without altering the data, enabling robust analyses of the influence of heterogeneities in mesoscale complex systems.
End-to-End Automated Segmentation Framework for Four-Dimensional Scanning Transmission Electron Microscopy Data
Four-dimensional scanning transmission electron microscopy (4D-STEM) is powerful for rapidly characterizing arrays of nanoparticles produced via high-throughput synthesis. However, such 4D-STEM datasets typically contain thousands of nanoparticles, each characterized by thousands of diffraction patterns spatially distributed across the nanoparticle, necessitating efficient and comprehensive analysis. We propose an end-to-end segmentation framework to automatically segment each nanoparticle into regions with distinct composition/orientation of crystal grains, using only the 4D-STEM data. Bragg disk information is extracted in a physics-informed manner from the diffraction patterns at each spatial location and combined with the real space coordinates to form feature vectors. These feature vectors are then used as inputs to a Gaussian mixture model (GMM) to segment the nanoparticle into distinct regions. We also develop two visualization tools based on the GMM outputs to infer the interface transition and the degree of superposition. Our framework comprehensively integrates machine learning tools and physics knowledge, and provides a basis for substantially compressing enormous 4D-STEM datasets, e.g., by replacing the full 4D-STEM dataset for each nanoparticle with only a single set of Bragg disk features for each distinct crystal grain identified in the nanoparticle. In this article, we demonstrate the power of our framework by presenting results for real, complex datasets.
Plasmon excitations in chemically heterogeneous nanoarrays
The capability of collective excitations, such as localized surface plasmon resonances, to produce a versatile spectrum of optical phenomena is governed by the interactions within the collective and single-particle responses in the finite system. In many practical instances, plasmonic metallic nanoparticles and arrays are either topologically or chemically heterogeneous, which affects both the constituent transitions and their interactions. Here, the formation of collective excitations in weakly Cu- and Pd-doped Au nanoarrays is described using time-dependent density functional theory. The additional impurity-induced modes in the optical response can be thought to result from intricate interactions between separated excitations or transitions. In this work, we investigate the heterogeneity at the impurity level, the symmetry aspects related to the impurity position, and the influence of the impurity position on the confinement phenomena. The chemically rich and symmetry-dependent quantum mechanical effects are analyzed with transition contribution maps demonstrating the possibility to develop nanostructures with more controlled collective properties.
Innovative nanopore sequencing technology including a self-assembled porous membrane
Methods and apparatus for long read, label-free, optical nanopore long chain molecule sequencing. In general, the present disclosure describes a novel sequencing technology based on the integration of nanochannels to deliver single long-chain molecules with widely spaced (>wavelength), ˜1-nm aperture “tortuous” nanopores that slow translocation sufficiently to provide massively parallel, single base resolution using optical techniques. A novel, directed self-assembly nanofabrication scheme using simple colloidal nanoparticles is used to form the nanopore arrays atop nanochannels that unfold the long chain molecules. At the surface of the nanoparticle array, strongly localized electromagnetic fields in engineered plasmonic/polaritonic structures allow for single base resolution using optical techniques.
Valence-free open nanoparticle superlattices
A cornerstone of advanced materials design is establishing a framework for assembling nanoparticle superstructures with tailored symmetries. A longstanding challenge has been assembling diamond-like superstructures for photonic devices. Traditionally, such open superstructures require functionalized nanoparticles with directional or anisotropic interactions, reminiscent of valence bonding in a diamond. Here, we present a robust strategy for assembling valence-free nanoparticles into a broad array of cubic superstructures. By grafting nanoparticles with oppositely charged, end-functionalized water-soluble polymers of adjustable molecular weight, we gain control over electrostatic interactions and conformational constraints. This unified approach yields lattices analogous to rock salt, CsCl, zinc-blende, diamond, and the rare simple cubic phase, with tunable lattice constants. Theoretical models and simulations elucidate the underlying interactions, providing a framework for engineering valence-free nanoparticle superlattices.
Modeling Structural Colors from Disordered One-Component Colloidal Nanoparticle-Based Supraballs Using Combined Experimental and Simulation Techniques
Bright, saturated structural colors in birds have inspired synthesis of self-assembled, disordered arrays of assembled nanoparticles with varied particle spacings and refractive indices. However, predicting colors of assembled nanoparticles, and thereby guiding their synthesis, remains challenging due to the effects of multiple scattering and strong absorption. In this work, we use a computational approach to first reconstruct the nanoparticles’ assembled structures from small-angle scattering measurements and then input the reconstructed structures to a finite-difference time-domain method to predict their color and reflectance. This computational approach is successfully validated by comparing its predictions against experimentally measured reflectance and provides a pathway for reverse engineering colloidal assemblies with desired optical and photothermal properties.
Sorting process of nanoparticles and applications of same
A sensing platform includes a substrate, an array of wells formed in the substrate, and sorted nanoparticles filling in the array of wells such that each well contains a single sorted nanoparticle, wherein the sorted nanoparticles are in a cluster state.
Self-Assembly of Virus Particle Based Materials for Hydrogen Catalysis
Viruses are sophisticated protein-based containers and their self-assembly from a small number of subunits into symmetrical, monodisperse architectures has inspired the work performed under this award. We have taken advantage of the robust self-assembly of the bacteriophage P22 for the encapsulation of enzymatic cargo materials and studied their activity in energy harvesting systems. The large internal cavity of the P22 is ideal for high-capacity loading of enzymes resulting in very high local catalyst concentrations. We have exploited the self-assembly properties of the bacteriophage P22 system for the packaging of a number of different enzymes, including a [NiFe] hydrogenase as well as enzymes capable of butanol biosynthesis, to create active and stable individual “nano-reactors”. Individual viral capsid-based nanoreactors are also ideal building blocks for the construction of higher order assemblies. We have demonstrated the construction of ordered 3-D arrays from active nanoparticle building blocks to form materials with collective behavior and properties beyond those of the individual particles and capable of catalyzing multi-step reactions. The successful implementation of the work performed under this DOE grant provides us with a great deal of knowledge about directed self-assembly at multiple lengthscales for the development of bioinspired catalytic materials for energy harvesting.
Diverse array of neutralizing antibodies elicited upon Spike Ferritin Nanoparticle vaccination in rhesus macaques
The repeat emergence of SARS-CoV-2 variants of concern (VoC) with decreased susceptibility to vaccine-elicited antibodies highlights the need to develop next-generation vaccine candidates that confer broad protection. Here we describe the antibody response induced by the SARS-CoV-2 Spike Ferritin Nanoparticle (SpFN) vaccine candidate adjuvanted with the Army Liposomal Formulation including QS21 (ALFQ) in non-human primates. By isolating and characterizing several monoclonal antibodies directed against the Spike Receptor Binding Domain (RBD), N-Terminal Domain (NTD), or the S2 Domain, we define the molecular recognition of vaccine-elicited cross-reactive monoclonal antibodies (mAbs) elicited by SpFN. We identify six neutralizing antibodies with broad sarbecovirus cross-reactivity that recapitulate serum polyclonal antibody responses. In particular, RBD mAb WRAIR-5001 binds to the conserved cryptic region with high affinity to sarbecovirus clades 1 and 2, including Omicron variants, while mAb WRAIR-5021 offers complete protection from B.1.617.2 (Delta) in a murine challenge study. Our data further highlight the ability of SpFN vaccination to stimulate cross-reactive B cells targeting conserved regions of the Spike with activity against SARS CoV-1 and SARS-CoV-2 variants.
Bioorthogonal catalytic patch
The toxicity and complicated administration procedures of transition metal catalysts have hampered the applications of bioorthogonal catalysis in vivo. Here the authors fill the needles of a microneedle array patch with palladium nanoparticles deposited on titanium nanosheets and show that the device, applied locally on the skin of mouse models bearing melanoma, promotes intratumoural conversion of systemically injected caged doxorubicin into the active drug, reducing its toxicity and side effects. Bioorthogonal catalysis mediated by transition metals has inspired a new subfield of artificial chemistry complementary to enzymatic reactions, enabling the selective labelling of biomolecules or in situ synthesis of bioactive agents via non-natural processes. However, the effective deployment of bioorthogonal catalysis in vivo remains challenging, mired by the safety concerns of metal toxicity or complicated procedures to administer catalysts. Here, we describe a bioorthogonal catalytic device comprising a microneedle array patch integrated with Pd nanoparticles deposited on TiO 2 nanosheets. This device is robust and removable, and can mediate the local conversion of caged substrates into their active states in high-level living systems. In particular, we show that such a patch can promote the activation of a prodrug at subcutaneous tumour sites, restoring its parent drug's therapeutic anticancer properties. Finally, this in situ applied device potentiates local treatment efficacy and eliminates off-target prodrug activation and dose-dependent side effects in healthy organs or distant tissues.
Topological nanophotonics for photoluminescence control
Rare-earth-doped nanocrystals are emerging light sources that can produce tunable emissions in colours and lifetimes, which has been typically achieved in chemistry and material science. However, one important optical challenge – polarization of photoluminescence – remains largely out of control by chemistry methods. Control over photoluminescence polarization can be gained via coupling of emitters to resonant nanostructures such as optical antennas and metasurfaces. However, the resulting polarization is typically sensitive to position disorder of emitters, which is difficult to mitigate. Recently, new classes of disorder-immune optical systems have been explored within the framework of topological photonics. Here we explore disorder-robust topological arrays of Mie-resonant nanoparticles for polarization control of photoluminescence of nanocrystals. We demonstrate polarized emission from rare-earth-doped nanocrystals governed by photonic topological edge states supported by zigzag arrays of dielectric resonators. We verify the topological origin of polarized photoluminescence by comparing emission from nanoparticles coupled to topologically trivial and nontrivial arrays of nanoresonators. We expect that our results may open a new direction in the study of topology-enable emission properties of topological edge states in many photonic systems.