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At least 91 records · Page 5

Image processing pipeline for AI-driven nanoparticle megalibrary characterization

Recent innovations have made it possible to produce megalibraries, millions of structurally and compositionally distinct nanoparticles on a chip. These megalibraries yield vast volumes of data that are impossible to analyze manually, necessitating the development of automated tools. In previous work, we created a binary classification machine learning model to select quality nanoparticle images for downstream analysis. In this work, we show that adding a custom image processing step before training can produce significantly higher-performing models in a fraction of the time and make them more robust to different image noise levels and microscope acquisition settings. The image processing pipeline proposed here effectively cleans raw nanoparticle images, enhances key features, and allows us to use much lower resolution images and simpler neural network model architectures. These features result in higher performance and significant cost savings. Experiments demonstrate superior performance relative to baseline, including an 18.2% improvement in recall and a 13.1% increase in accuracy. Given the high cost of downstream analysis, it is critical to minimize false positives, and our best-performing model reaches a precision of 95.9% and a weighted F-score of 95.1% on an unseen test set. Additionally, model training time is reduced from hours to less than a minute. We also show that, using this custom image processing pipeline, model performance is significantly improved at lower pixel resolutions compared to downsizing alone. We expect that adopting this pipeline for AI-driven automated nanoparticle characterization will allow researchers to rapidly and accurately analyze much greater volumes of data, thereby accelerating materials discovery.

77 NANOSCIENCE AND NANOTECHNOLOGY

Oxidation and recharge of reactive structural Fe( II ) in titanomagnetite (Fe 3− x Ti x O 4 ) nanoparticles

Mixed-valent iron oxide minerals, such as magnetite (Fe(II)(Fe(III)) 2 O 4 ), are an important source of solid-state ferrous iron (Fe(II)) that can impact the speciation and transport of electron accepting contaminants in the Earth’s subsurface, such as radioactive pertechnetate ( 99 Tc(VII)O 4 − ). However, when oxidizing conditions are encountered, structural Fe(II) at the mineral surface is consumed yielding a maghemite (γ-Fe(III) 2 O 3 )-like layer that limits further electron transfer. This oxidized surface layer can be recharged back to the original Fe(II)/(III) ratio by re-exposure to reducing conditions, i.e., aqueous solutions containing Fe 2+ . However, for substituted magnetite (Fe 3−x M x O 4 , M = transition metal cation), the extent of this redox recyclability is unclear. Here, we examine oxidation and recharge for titanomagnetite (Fe 3−x Ti x O 4 ) nanoparticles, where the Fe(II)/Fe(III) ratio varies by the amount of Fe(II) required to charge balance the titanium (Ti(IV)) substituted into the structure. The nanoparticles were synthesized by aqueous precipitation from a solution containing ferrous, ferric and titanium chloride at room temperature. Transmission electron microscopy combined with electron energy loss spectroscopy revealed that rapid precipitation formed core–shell-like nanoparticles consisting of a hyperstoichiometric magnetite core, with Ti(IV) and charge balancing Fe(II) enriched at the surface. This surface enrichment made Fe(II) more available for electron transfer reactions with redox active solution species. Examination of oxidation by H 2 O 2 followed by recharge with aqueous Fe 2+ indicates recyclability of reducing equivalents in the nanoparticles, yielding a core recrystallized to stoichiometric magnetite and a shell bearing excess Fe(II) to charge balance the substituted Ti(IV). The recharged particles are shown to have restored redox reactivity with 99 Tc(VII)O 4 − resulting in reduction to 99 Tc(IV)O 2 and oxidation of the structural Fe(II) to Fe(III).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

In situ transmission electron microscopy observations of CaCO 3 crystallization onto polysaccharide-coated nanoparticles

Polysaccharides and proteoglycans are widely associated with the organic matrix at sites of CaCO 3 biomineralization, and previous studies indicate that these macromolecules may confer greater roles in mineral nucleation than previously recognized. This investigation uses in situ liquid-phase transmission electron microscopy (LP-TEM) to observe CaCO 3 nucleation onto aminated silica (SiO 2 –NH 3 + ) nanoparticles treated with a layer of chitosan (near-neutral derivative of chitin) or heparin (a carboxylated and highly sulfated glycosaminoglycan). In the absence of polysaccharides, few CaCO 3 particles formed and exhibited mobility. However, the SiO 2 –NH 3 + nanoparticles were enveloped in a region of higher mass density relative to the bulk solution, suggesting the development of a local solute-rich environment that surrounds the charged NH 3 + groups. The heparin- or chitosan-coated silica particles also exhibited regions of higher mass density around the nanoparticles. In the presence of these polysaccharide coatings, we observed the nucleation of abundant CaCO 3 particles whereby the polyanionic heparin promoted more nucleation than the weakly cationic chitosan. Many crystallites appeared to form at the polysaccharide–TEM cell membrane–solution interface, further indicating interfacial and macromolecule-specific control on crystallization. The combined results demonstrate that chitosan and heparin have an appreciable effect on the timing, size, and location of CaCO 3 nucleation compared to the polysaccharide-free nanoparticles.

15 GEOTHERMAL ENERGY

Cross-reactive sarbecovirus antibodies induced by mosaic RBD nanoparticles

Broad immune responses are needed to mitigate viral evolution and escape. To induce antibodies against conserved receptor-binding domain (RBD) regions of SARS-like betacoronavirus (sarbecovirus) spike proteins that recognize SARS-CoV-2 variants of concern and zoonotic sarbecoviruses, we developed mosaic-8b RBD nanoparticles presenting eight sarbecovirus RBDs arranged randomly on a 60-mer nanoparticle. Mosaic-8b immunizations protected animals from challenges from viruses whose RBDs were matched or mismatched to those on nanoparticles. Here, we describe neutralizing mAbs isolated from mosaic-8b-immunized rabbits, some on par with Pemgarda, the only currently FDA-approved therapeutic mAb. Deep mutational scanning, in vitro selection of spike resistance mutations, and single-particle cryo-electron microscopy structures of spike–antibody complexes demonstrated targeting of conserved RBD epitopes. Rabbit mAbs included critical D-gene segment RBD-recognizing features in common with human anti-RBD mAbs, despite rabbit genomes lacking an equivalent human D-gene segment, thus demonstrating that the immune systems of humans and other mammals can utilize different antibody gene segments to arrive at similar modes of antigen recognition. These results suggest that animal models can be used to elicit anti-RBD mAbs with similar properties to those raised in humans, which can then be humanized for therapeutic use, and that mosaic RBD nanoparticle immunization coupled with multiplexed screening represents an efficient way to generate and select broadly cross-reactive therapeutic pan-sarbecovirus and pan-SARS-CoV-2 variant mAbs.

Science & Technology - Other Topics

Robust measurement of microbial reduction of graphene oxide nanoparticles using image analysis

ABSTRACT Shewanella oneidensis ( S. oneidensis ) has the capacity to reduce electron acceptors within a medium and is thus used frequently in microbial fuel generation, pollutant breakdown, and nanoparticle fabrication. Microbial fuel setups, however, often require costly or labor-intensive components, thus making optimization of their performance onerous. For rapid optimization of setup conditions, a model reduction assay can be employed to allow simultaneous, large-scale experiments at lower cost and effort. Since S. oneidensis uses different extracellular electron transfer pathways depending on the electron acceptor, it is essential to use a reduction assay that mirrors the pathways employed in the microbial fuel system. For microbial fuel setups that use nanoparticles to stimulate electron transfer, reduction of graphene oxide provides a more accurate model than other commonly used assays as it is a bulk material that forms flocculates in solutions with a large ionic component. However, graphene oxide flocculates can interfere with traditional absorbance-based measurement techniques. This study introduces a novel image analysis method for quantifying graphene oxide reduction, showing improved performance and statistical accuracy over traditional methods. A comparative analysis shows that the image analysis method produces smaller errors between replicates and reveals more statistically significant differences between samples than traditional plate reader measurements under conditions causing graphene oxide flocculation. Image analysis can also detect reduction activity at earlier time points due to its use of larger solution volumes, enhancing color detection. These improvements in accuracy make image analysis a promising method for optimizing microbial fuel cells that use nanoparticles or bulk substrates. IMPORTANCE Shewanella oneidensis ( S. oneidensis ) is widely used in reduction processes such as microbial fuel generation due to its capacity to reduce electron acceptors. Often, these setups are labor-intensive to operate and require days to produce results, so use of a model assay would reduce the time and expenses needed for optimization. Our research developed a novel digital analysis method for analysis of graphene oxide flocculates that may be utilized as a model assay for reduction platforms featuring nanoparticles. Use of this model reduction assay will enable rapid optimization and drive improvements in the microbial fuel generation sector.

Bennett, Danielle T. (ORCID:0009000188748827)

Science Driven Discovery of Nanoparticle Photocatalysts

Photocatalytic water splitting using suspensions of nanoparticle photocatalysts is a promising route to economically sustainable production of green hydrogen. The principal challenge is to develop photocatalysts with overall solar-to-hydrogen conversion efficiency that exceeds 10 percent. In this project we have developed a new platform for investigating candidate materials for photocatalytic water splitting. Our platform consists of patterned Au electrodes and a Ag/AgCl reference electrode on an insulating substrate onto which we disperse nanoparticle photocatalysts. We then cover the substrate with a thin layer of ionogel containing a protic ionic liquid that dissolves water from the ambient. Using this platform we have demonstrated photoelectrochemical activity mapping for single and small clusters of BiVO 4 nanoparticle photocatalysts and correlated these results to their Raman and photoluminescence spectra. The preliminary results suggest a strong correlation for low efficiency nanoparticles, followed by saturation for those with higher activities, indicating that interface reaction or electrolyte transport become the limiting factor. We anticipate that further application of this platform to investigation of candidate photocatalyst materials will provide useful insights into the mechanisms that limit their performance.

77 NANOSCIENCE AND NANOTECHNOLOGY

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Multiscale Modeling of Nanoparticle Precipitation in Oxide Dispersion-Strengthened Steels Produced by Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) enables the efficient production of near-net-shape oxide dispersion-strengthened (ODS) alloys, which possess superior mechanical properties due to oxide nanoparticles (e.g., yttrium oxide, Y-O, and yttrium-titanium oxide, Y-Ti-O) embedded in the alloy matrix. To better understand the precipitation mechanisms of the oxide nanoparticles and predict their size distribution under LPBF conditions, we developed an innovative physics-based multiscale modeling strategy that incorporates multiple computational approaches. These include a finite volume method model (Flow3D) to analyze the temperature field and cooling rate of the melt pool during the LPBF process, a density functional theory model to calculate the binding energy of Y-O particles and the temperature-dependent diffusivities of Y and O in molten 316L stainless steel (SS), and a cluster dynamics model to evaluate the kinetic evolution and size distribution of Y-O nanoparticles in as-fabricated 316L SS ODS alloys. The model-predicted particle sizes exhibit good agreement with experimental measurements across various LPBF process parameters, i.e., laser power (110–220 W) and scanning speed (150–900 mm/s), demonstrating the reliability and predictive power of the modeling approach. The multiscale approach can be used to guide the future design of experimental process parameters to control oxide nanoparticle characteristics in LPBF-manufactured ODS alloys. Additionally, our approach introduces a novel strategy for understanding and modeling the thermodynamics and kinetics of precipitation in high-temperature systems, particularly molten alloys.

Wang, Zhengming (ORCID:0000000241627112)

Monte Carlo Simulation of Nanoparticle Encapsulation in Flames

Gas-phase combustion (flame) synthesis has been an essential industrial process for producing large quantities of powder materials such as carbon black, titanium dioxide, and silicon dioxide. Flames typically produce simple oxides, with carbon black being the noted exception because the oxides of carbon are gaseous and are easily separated from the particulate matter that is formed during fuel pyrolysis. Furthermore, the powders produced in flames are usually agglomerated, nanometer-sized particles (nanoparticles). This composition and morphology is acceptable for many applications. However, the present interest in nanoparticles for advanced materials application has led to efforts to employ flames for the synthesis of unagglomerated nanoparticles (2 to 100 nm) of metals and non-oxide ceramics. Sodium-halide chemistry has proven to be viable for producing metals and non-oxide ceramics in flames. Materials that have been produced to date include Si (Calcote and Felder, 1993), TiN, TiB2, TiC, TiSi2, SiC, B4C (Glassman et al, 1993) Al, W, Ti, TiB2, AlN, and W-Ti and Al-AlN composites (DuFaux and Axelbaum, 1995, Axelbaum et al 1996,1997). Many more materials are possible. The main challenge that faces application of flame synthesis for advanced materials is overcoming formation of agglomerates in flames (Brezinsky, 1997). The high temperatures and high number densities in the flame environment favor the formation of agglomerates. Agglomerates must be avoided for many reasons. For example, when nanopowders are consolidated, agglomerates have a deleterious effect on compaction density, leading to voids in the final part. Efforts to avoid agglomeration in flames without substantially reducing particle number density and, consequently, production rate, have had limited success. Another critical challenge that faces all synthesis routes for nanopowders is ensuring that the powders are high purity and that the process is scaleable. Though the containerless, high temperature environment of a flame is excellent for producing high-purity simple compounds, ultrafine metals and non-oxide ceramic powders are inherently reactive in the presence of oxygen and/or moisture. Thus, the handling of these powders after synthesis poses a challenging problem. Impurities acquired during handling of nanoparticles have plagued the advancement of nanostructured materials technology.

Sun, Z.

Polymer Crosslinked 3-D Assemblies of Nanoparticles: Mechanically Strong Lightweight Porous Materials

In analogy to supramolecular assemblies, which are pursued because of properties above and beyond those of the individual molecules, self-standing monolithic three-dimensional assemblies of nanoparticles also have unique properties attributed to their structure. For example, ultra low-density 3-D assemblies of silica nanoparticles, known as silica aerogels, are characterized by large internal void space, high surface area and very low thermal conductivity. Aerogels, however, are also extremely fragile materials, limiting their application to a few specialized environments, e.g., in nuclear reactors as Cerenkov radiation detectors, in space (refer to NASA's Stardust Program) and aboard certain planetary vehicles (thermal insulators on Mars Rovers in 1997 and 2004). The fragility problem is traced to well-defined weak points in the aerogel skeletal framework, the interparticle necks. Using the surface functionality of the nanoparticle building blocks as a focal point, we have directed attachment of a conformal polymer coating over the entire framework, rendering all necks wider. Thus, although the bulk density may increase only by 3x, the mesoporosity (pores in the range 2-50 nm) remains unchanged, while the strength of the material increases by up to 300... Having addressed the fragility problem, aerogels are now robust materials, and a variety of applications, ranging from thermal/acoustic insulators to catalyst supports, to platform for sensors, and dielectrics are all within reach. Our approach employs molecular science to manipulate nanoscopic matter for achieving useful macroscopic properties, and in our view it resides at the core of what defines nanotechnology. In that spirit, this technology is expandable in three directions. Thus, we have already crosslinked successfully amine-modified silica, and we anticipate that more rich chemistry will be realized by been creative with the nanoparticle surface modifiers. On the other hand, although we do not expect orders-of-magnitude increase in strength, nevertheless, by varying the polymer we expect to impart other properties such as hydrophobicity, thermal stability and perhaps electrical conductivity. Besides polymers, crosslinkers will include metals and ceramics (e.g., through POSS precursors). Finally, network morphology directs load dissipation, and of approximately 30 different crosslinked oxide aerogels, vanadia, whose structure is fibrous rather than particulate, yields a much stronger (by 4..) material than silica of the same density. It seems imperative to implement control of network morphology, even through templating.

Leventis, Nicholas

An Additional Potential Factor for Kidney Stone Formation during Space Flights: Calcifying Nanoparticles (Nanobacteria): A Case Report

Spaceflight-induced microgravity appears to be a risk factor for the development of urinary calculi due to skeletal calcium liberation and other undefined factors, resulting in stone disease in crewmembers during and after spaceflight. Calcifying nanoparticles, or nanobacteria, reproduce at a more rapid rate in simulated microgravity conditions and create external shells of calcium phosphate in the form of apatite. The questions arises whether calcifying nanoparticles are niduses for calculi and contribute to the development of clinical stone disease in humans, who possess environmental factors predisposing to the development of urinary calculi and potentially impaired immunological defenses during spaceflight. A case of a urinary calculus passed from an astronaut post-flight with morphological characteristics of calcifying nanoparticles and staining positive for a calcifying nanoparticle unique antigen, is presented.

Jones, Jeffrey A.

Synthesis of Metal Nanoparticle-decorated Carbon Nanotubes under Ambient Conditions

This viewgraph presentation reviews the production of Metal Nanoparticle-decorated carbon Nanotubes. Multi-walled carbon nanotubes (MWCNTs) were efficiently decorated with metal nanoparticles (e.g. Ag, Pt, etc.) using the corresponding metal acetate in a simple mixing process without the need of chemical reagents or further processing. The conversion of acetate compounds to the corresponding metal reached over 90%, forming nanoparticles with average diameters less than 10 nm under certain conditions. The process was readily scalable allowing for the convenient preparation of multi-gram quantities of metal nanoparticle-decorated MWCNTs in a matter of a few minutes. These materials are under evaluation for a variety of electrical and catalytic applications. The preparation and characterization of these materials will be presented. The microscopic views of the processed MWCNTs are shown

Lin, Yi

Effects of Core-Shell Rubber (CSR) Nanoparticles on the Fracture Toughness of an Epoxy Resin at Cryogenic Temperatures

This study investigates the effects of core-shell rubber (CSR) nanoparticles on the fracture toughness of an epoxy resin at liquid nitrogen (LN2) temperatures. Varying amounts of Kane Ace (Registered TradeMark) MX130 toughening agent were added to a commercially available EPON 862/W epoxy resin. Resulting fracture toughness was evaluated by the use of Charpy impact tests conducted on an instrumented drop tower. The size and distribution of the CSR nanoparticles were characterized using Transmission Electric Microscopy (TEM) and Small Angle X-ray Scattering (SAXS). Up to nominal 4.6% addition of the CSR nanoparticles, resulted in a nearly 5 times increase in the measured breaking energy. However, further increases in the amount of CSR nanoparticles had no appreciable affect on the breaking energy.

Wang, J.

Effects of Core-Shell Rubber (CSR) Nanoparticles on the Cryogenic Fracture Toughness of CSR Modified Epoxy

This study investigated the effects of core-shell rubber (CSR) nanoparticles on the mechanical properties and fracture toughness of an epoxy resin at ambient and liquid nitrogen (LN2) temperatures. Varying amounts of Kane Ace(Registered TradeMark) MX130 and Kane Ace(Registered TradeMark) MX960 toughening agent were added to a commercially available EPON 862/Epikure W epoxy resin. Elastic modulus was calculated using quasi-static tensile data. Fracture toughness was evaluated by the resulting breaking energy measured in Charpy impact tests conducted on an instrumented drop tower. The size and distribution of the CSR nanoparticles were characterized using Transmission Electron Microscopy (TEM) and Small Angle X-ray Scattering (SAXS). Scanning Electron Microscopy (SEM) was used to study the fracture surface morphology. The addition of the CSR nanoparticles increased the breaking energy with negligible change in elastic modulus and ultimate tensile stress (UTS). At ambient temperature the breaking energy increased with increasing additions of the CSR nanoparticles up to 13.8wt%, while at LN2 temperatures, it reached a plateau at much lower CSR concentration.

Wang, Jun

Nanoparticle Filtration in a RTM Processed Epoxy/Carbon Fiber Composite

Several epoxy matrix composite panels were fabricated by resin transfer molding (RTM) E862/W resin onto a triaxially braided carbon fiber pre-form. Nanoparticles including carbon nanofiber, synthetic clay, and functionalized graphite were dispersed in the E862 matrix, and the extent of particle filtration during processing was characterized. Nanoparticle dispersion in the resin flashing on both the inlet and outlet edges of the panel was compared by TEM. Variation in physical properties such as Tg and moisture absorption throughout the panel were also characterized. All nanoparticle filled panels showed a decrease in Tg along the resin flow path across the panel, indicating nanoparticle filtration, however there was little change in moisture absorption. This works illustrates the need to obtain good nano-particle dispersion in the matrix resin to prevent particle agglomeration and hence particle filtration in the resultant polymer matrix composites (PMC).

Miller, Sandi G.

Synthesis of Solid-Solution Mn x Zn 1– x O Nanoparticles and their Electrochemical Oxidation of Furfural

Electrochemical valorization of biomass-derived substrates has become a prominent area of research due to its potential to produce value-added products from renewable feedstocks in a more sustainable way. First-row transition metal electrodes are compelling candidates for these conversions due to their stability, abundance, and cost-effectiveness. Herein, we report on the colloidal synthesis of Mn x Zn 1– x O (x = 0.3-0.7) nanoparticles and their electrocatalytic activity towards furfural oxidation. We find that the hindrance of a MnO impurity can be achieved by leveraging the oxidation state of the Mn precursor. The Mn x Zn 1– x O composition closely follows the ratio of precursors, with all the nanoparticles having a wurtzite structure as determined by ICP-MS and PXRD, respectively. XANES and XPS revealed the presence of Mn in different oxidation states with the ratio of these varying based on the composition. When comparing the electrocatalytic activity of the monometallic and bimetallic oxides for furfural oxidation, a decrease in current density was observed with increasing Zn content. We find the Mn x Zn 1– x O nanoparticles favor the formation of the 6 e - oxidation product 5-hydroxy-2(5H)-furanone, while both monometallic oxides primarily yield CO 2 and other deeply oxidized products as the majority pathway. Furthermore, these findings can contribute towards the design and synthesis of more active and selective electrocatalyst.

Aldehydes

Volumetric Shaping of Nanoparticle-DNA Crystals by Light-Induced Milling

DNA-programmable self-assembly enables the formation of nanoparticle crystals with controlled lattice symmetry. While this approach offers the formation of complexly ordered nanostructures for optical, mechanical, and biological applications, a mesoscale control over such nanomaterials is limited. Directing the material formation process through the assembly pathway or external fields allows for modulating crystal morphology, but achieving arbitrary morphology remains challenging. Here, we present a photothermal method for shaping 3D DNA-programmable crystals of gold nanoparticles. Through local heating of nanoparticles due to plasmonic light absorption, we induce targeted volumetric dissolution of specifically defined crystal areas with micron-scale accuracy. This technique effectively prescribes crystal shaping and creates arbitrarily shaped voids within crystals. We further investigate both computationally and experimentally the key factors governing volumetric material subtraction. The developed automated light-milling platform enables the fabrication of nanomaterials exhibiting both DNA-programmable nanoscale order and custom-designed mesoscale architecture.

36 MATERIALS SCIENCE

Plasmonic Hybridization and Near-Field Localization in Gold “Dog Bone” Nanoparticles

Gold nanoparticles with complex anisotropic geometries offer unique opportunities for tailoring plasmonic near-fields beyond the limits of conventional nanorods. Here we combine photon-induced near-field electron microscopy (PINEM) and full-wave simulations to resolve plasmon hybridization and near-field localization in gold dog-bone nanoparticles and their dimers with and without conformal SiO 2 shells. We demonstrate that the dog-bone geometry drives unconventional polarization-dependent field confinement, including pronounced tip-localized near-fields under both longitudinal and transverse excitation. Conformal SiO 2 shells red-shift the plasmon resonances through dielectric screening and prevent charge-transfer coupling in adjacent dimers. Depending on the dimer orientation and excitation polarization, coupled structures exhibit distinct bonding- and antibonding-like hybridized modes as well as interparticle near-field channels. However, weakly interacting dimers retain largely independent particle responses with geometry-governed asymmetries. The close agreement between PINEM measurements and simulations establishes a direct picture of how shape, dielectric environment, and nanoscale coupling together define plasmonic modes in complex anisotropic nanoparticles. These findings provide design principles for engineering localized optical fields in plasmonic nanoscale structures.

hybridization