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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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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Intercalative Redox Tuning for Cu/Li x Mn 2 O 4 -Catalyzed Oxidative Alkyne Coupling

Modulation of heterogeneous catalyst structure is ubiquitous within efforts to improve catalytic activity and selectivity at the molecular level. Herein, manganese oxide (MnO 2 ) is employed as a continuously tunable catalyst support through increasing extent of lithium intercalation and reduced surface potential. Oxidative grafting of an organocopper complex onto various lithium manganese oxides (Li x Mn 2 O 4 , x = 0-2.1) produced divalent and monovalent copper species on the partially reduced (0 ≤ x ≤ 1.2) and fully reduced (x = 2.1) surfaces, respectively, as determined by X-ray absorption fine structure (XAFS) analysis. In this study, the resultant materials are catalytically active for the oxidative coupling of terminal alkynes, with steady-state reaction rate data of oxidative propyne dimerization (200 °C, 0.6-2.4 kPa propyne, 2.4-9.9 kPa O 2 ) indicating that complete support lithiation (Li 2.1 Mn 2 O 4 ) provides increased catalytic performance and renders reoxidation steps less kinetically demanding compared to the unreduced parent material. Enacting a dual site (Cu and MnO x ) kinetic model can account for dimerization rates measured over Cu/Li 2.1 Mn 2 O 4 under various reactant concentrations, copper loadings, and surface coverages, providing supporting evidence for the synergistic role of the metal and support in facilitating the coupling reaction. Overall, results presented here provide an extension for general strategies of systematically controlling catalytic structure and function through lithium reduction of bulk oxides and subsequent electronic modulation of the metals supported thereon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Structural Uncertainty in the Sensitivity of Urban Temperatures to Anthropogenic Heat Flux

One key source of uncertainty for weather and climate models is structural uncertainty arising from the fact that these models must simplify or approximate complex physical, chemical, and biological processes that occur in the real world. However, structural uncertainty is rarely examined in the context of simulated effects of anthropogenic heat flux in cities. Using the Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model, it is found that the sensitivity of urban canopy air temperature to anthropogenic heat flux can differ by an order of magnitude depending on how anthropogenic heat flux is released to the urban environment. Moreover, varying model structures through changing the treatment of roof-air interaction and the parameterization of convective heat transfer between the canopy air and the atmosphere can affect the sensitivity of urban canopy air temperature by a factor of 4. Urban surface temperature and 2-m air temperature are less sensitive to the methods of anthropogenic heat flux release and the examined model structural variants than urban canopy air temperature, but their sensitivities to anthropogenic heat flux can still vary by as much as a factor of 4 for surface temperature and 2 for 2-m air temperature. Our study recommends using temperature sensitivity instead of temperature response to understand how various physical processes (and their representations in numerical models) modulate the simulated effects of anthropogenic heat flux.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

E-PVT: enhanced position-velocity-time scheduler for computer-controlled optical finishing with comprehensive considerations of dynamics constraints, continuity and efficiency

Deterministic computer-controlled optical finishing is an essential approach for achieving high-quality optical surfaces. Its determinism and convergence rely heavily on precise and smooth motion control to guide the machine tool over an optical surface to correct residual errors. One widely supported and smooth motion control model is position-velocity-time (PVT), which employs piecewise cubic polynomials to describe positions. Our prior research introduced a PVT-based velocity scheduling method, demonstrating sub-nanometer level convergence in ion beam figuring (IBF) processes. However, three challenges remained. Firstly, this method relies on quadratic programming, resulting in computational intensiveness for dense tool paths. Secondly, the dynamics constraints and velocity and acceleration continuities are not comprehensively considered, limiting the full potential of PVT-based control. Thirdly, no compensation mechanism existed when dynamics constraints are exceeded. In this study, in response to these challenges, we proposed the Enhanced PVT (E-PVT) method, reducing the time complexity from O ( n 3 ) to O ( n ) while fully addressing dynamics constraints and continuities. A novel compensation method utilizing particle swarm optimization was proposed to address situations where dynamics constraints might be exceeded while maintaining the overall processing efficiency. Validation through simulation and experimentation confirmed the improved performance of E-PVT.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Incorporating Full Elastodynamic Effects and Dipping Fault Geometries in Community Code Verification Exercises for Simulations of Earthquake Sequences and Aseismic Slip (SEAS)

ABSTRACT Numerical modeling of earthquake dynamics and derived insight for seismic hazard relies on credible, reproducible model results. The sequences of earthquakes and aseismic slip (SEAS) initiative has set out to facilitate community code comparisons, and verify and advance the next generation of physics-based earthquake models that reproduce all phases of the seismic cycle. With the goal of advancing SEAS models to robustly incorporate physical and geometrical complexities, here we present code comparison results from two new benchmark problems: BP1-FD considers full elastodynamic effects, and BP3-QD considers dipping fault geometries. Seven and eight modeling groups participated in BP1-FD and BP3-QD, respectively, allowing us to explore these physical ingredients across multiple codes and better understand associated numerical considerations. With new comparison metrics, we find that numerical resolution and computational domain size are critical parameters to obtain matching results. Codes for BP1-FD implement different criteria for switching between quasi-static and dynamic solvers, which require tuning to obtain matching results. In BP3-QD, proper remote boundary conditions consistent with specified rigid body translation are required to obtain matching surface displacements. With these numerical and mathematical issues resolved, we obtain excellent quantitative agreements among codes in earthquake interevent times, event moments, and coseismic slip, with reasonable agreements made in peak slip rates and rupture arrival time. We find that including full inertial effects generates events with larger slip rates and rupture speeds compared to the quasi-dynamic counterpart. For BP3-QD, both dip angle and sense of motion (thrust versus normal faulting) alter ground motion on the hanging and foot walls, and influence event patterns, with some sequences exhibiting similar-size characteristic earthquakes, and others exhibiting different-size events. These findings underscore the importance of considering full elastodynamics and nonvertical dip angles in SEAS models, as both influence short- and long-term earthquake behavior and are relevant to seismic hazard.

Geochemistry & Geophysics↗
DOE OSTI2021

Powder spreading, densification, and part deformation in binder jetting additive manufacturing

Binder jetting additive manufacturing (AM) can print complex structures in economical and scalable manner. Binder jetting AM comprises of deposition and weak binding of particles, known as green part, at room temperature and subsequent binder removal and sintering densification at high temperatures. However, during the densification (i.e., sintering), the part significantly deforms due to volume shrinkage. The deformation during sintering is difficult to predict, which prevents the widespread application of this technology. In this research, powder spreading simulation using discrete element method (DEM) was performed first to capture local variations in powder bed configuration. Second, finite element method (FEM) with a phenomenological continuum constitutive model was used to predict part shrinkage during the sintering process. DEM simulation showed variations in packing density, particle segregation, formation of uneven powder bed surface, and shift in particle size distribution (PSD). The sintering simulation modeled part deformation with a reasonable accuracy of 3% for solid-state sintering and intermediate liquid phase sintering. A demonstration case with non-uniform initial packing density showed that inhomogeneous green part density and PSD should be accounted for prediction of part deformation in binder jetting AM.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Derivation of physical equations for high-speed laser welding using large language models

It is challenging to formulate complex physical phenomena that occur in a manufacturing process, particularly when the available data are limited, rendering conventional data-driven approaches ineffective. This study aims to predict humping onset in high-speed laser welding by introducing a novel framework, namely text-to-equations generative pre-trained transformer (T2EGPT). This method leverages the capabilities of large language models (LLMs), in combination with sparse experimental data and enriched literature data, to derive an interpretable and generalizable equation for predicting humping initiation. By capturing key correlations among physical parameters, T2EGPT generates a compact and dimensionless expression that accurately predicts hump formation. The equation reveals that humping arises from the interplay between inertia-driven backward melt flow and capillary-driven surface stabilization, where inertial forces drive molten metal backward and capillary forces resist surface deformation. Furthermore, compared to traditional data-driven models, T2EGPT demonstrates enhanced predictive accuracy and cross-material transferability. More broadly, this study highlights the potential of LLMs to integrate textual information with data-driven discovery, enabling the extraction of physical laws in data-scarce scientific domains.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Proliferated Resilient Economical Half-Meter Aperture Space Telescopes (PREEMPT)

The PREEMPT LDRD was motivated by a major national need for better space-based imaging systems that are both high performing and affordable for the US Government. Current optical payloads for intelligence, surveillance and reconnaissance (ISR) and space domain awareness (SDA) missions can cost hundreds of millions of dollars and take years to develop, which makes it difficult to build the large constellations required for persistent, world-wide coverage. To address this, the team aimed to advance a different kind of large-aperture (>25 cm) telescope, called a monolithic telescope, in which key optical surfaces are built into a single piece of fused silica. This design greatly reduces payload and spacecraft complexity, the need for precision focus actuators, improves mechanical and thermal robustness, and lowers cost when compared with traditional Cassegrain telescopes that rely on many precisely aligned components. The project focused on five primary thrusts. The first thrust was to advance the concept of a V10, 25 cm, monolithic telescope forward from optical design to flight-ready stage. This was accomplished in partnership with Optimax, who delivered the first test unit in the early stages of the LDRD. The team developed several technologies necessary for this optic to be integrated into a flight demonstration. These include carbon fiber housings, highly detailed structural and thermal models and stress-reducing elastic averaging Hirth groove designs. These technologies resulted in a successful maturation of the optic, which is now slated to fly in late 2026/early 2027 for a demonstration mission. The second thrust was to advance the manufacturability of these optics. In collaboration with NIF’s optical manufacturing shop, we reduced polishing time from 480 hours to 65 hours through the implementation of optimized processes and new tools. The NIF team utilized a conceptual V8 (18 cm) optic to demonstrate this optimization, though it can be applied to the rest of the monolithic optic portfolio. Third, the team developed the first conceptual V20 (50 cm) payload, which is slated to be the next generation of LLNL optical payload systems. A set of structural, dynamic and thermal simulations were performed to identify potential challenges in the future development of this payload. Early-stage simulations suggest the payload is feasible, though thermal management will be the key focus area to maintain optimal performance. Fourth, a non-linear model of Viton was developed, to further enhance the reliability of our structural and dynamic models for future payloads. Viton acts as the primary interface material between the optic and its housing. Lastly, the team focused on successfully displaying the feasibility of using additively manufactured metal composites for optical space payloads. The team successfully demonstrated layer by layer deposition of Al-SiC composites, which have highly tunable structural and coefficient of thermal expansion (CTE) properties. These are crucial for optical payloads because CTE mismatch is one of the causes for degraded optical performance for telescopes in orbit. Overall, the work showed that monolithic telescopes could become a practical, lower-cost path to high-resolution space imaging for both national security and scientific missions.

42 ENGINEERING↗
DOE OSTI2021

Gas hydrate deposit formation in transient flowloop tests and mitigation with a surface treatment

Thermodynamic and thermal mitigation strategies are traditionally utilized to prevent gas hydrate formation but may be rendered ineffective for certain unplanned, extended shut-in scenarios. Unfortunately, the current knowledge regarding transient gas hydrate formation has been extremely limited to only a few studies and unable to address this complex issue adequately. This work, conducted in a lab-scale flowloop, aims to add to the understanding of this area by delving into the implications of transient conditions on gas hydrate formation mechanisms, while also exploring a possible mitigation strategy of a surface treatment. Specifically, the effects of phase separation on gas hydrate formation locations, transportability, and plugging are presented for an oil-dominated system. An omniphobic surface treatment is shown to affect initial gas hydrate deposition and its wall adherence strength, as well as the overall plugging outcome. Overall, this work combines observational information with process data measurements to provide a better understanding of phase separated gas hydrate systems and passive deposition mitigation strategies. This can further aid advanced gas hydrate modeling efforts, which currently do not adequately address transient flow effects on phase separation/dispersion. Here, it offers representative gas hydrate testing for coatings, which have exclusively been limited to non-flowing and/or bench-scale analysis, to give confidence in their potential application as advanced deposition prevention tools.

03 NATURAL GAS↗
DOE OSTI2021

Defect-Driven Oxide Transformations and the Electrochemical Interphase

The redox reaction pathway is crucial to the sustainable production of the fuels and chemicals required for a carbon-neutral society. Our society is becoming increasingly dependent on devices using batteries and electrolyzers, all of which rely on a series of redox reactions. The overall properties of oxide materials make them very well suited for such electrochemical and catalytic applications due to their associated cationic redox properties and the static site-adsorbate interactions. As these technologies have matured, it has become apparent that defect-driven redox reactions, defect-coupled diffusion, and structural transformations that are both time- and rate-dependent are also critical materials processes. This change in focus, considering not only redox properties but also more complex, dynamic behaviors, represents a new research frontier in the molecular sciences as they are strongly linked to device operation and degradation and lie at the heart of various phenomena that take place at electrochemical interfaces. Fundamental studies of the structural, electronic, and chemical transformation mechanisms are key to the advancement of materials and technological innovations that could be implemented in various electrochemical systems. In this Account, we focus on recent studies and advances in characterizing and understanding the dynamic redox evolution and structural transformations that take place in model perovskites and layered oxides under reactive conditions and correlate them with degradation mechanisms and operations in electrolyzers and batteries. We show that the dynamic evolution of oxygen vacancies and cationic migration in the surface or bulk occurs at the solid-liquid interface, using a combination of different synchrotron-based Xray spectroscopies and scattering probes. Detailed redox-structure-reactivity correlation studies show how defects and diffusion processes can be tailored to drive various physical and chemical transformations in electrolyzers and batteries. We also highlight a strong correlation between oxygen redox reactivity and structural reorganization in both model thin films and particles, helping to bridge the gap between fundamental studies of the reaction mechanism and device applications. Finally, on the basis of these findings, we discuss strategies to probe and tune the redox reactivity and structural stability of the redox-active oxide interphase toward devising efficient pathways for energy and chemical harvesting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Aqueous Interfaces in Chemical Separations

Chemical separations play a vital role in refinery and reprocessing of critical materials, such as platinum group metals, rare earths, and actinides. The choice of separation system─whether it is liquid–liquid extraction (LLE), sorbents, or membranes─depends on specific needs and applications. In almost all separation processes, the desired metal ions adsorb or transfer across an aqueous interface, such as the solid/liquid interface in sorbents or oil/water interfaces in LLE. Despite these separation technologies being extensively used for decades, our understanding of the molecular-scale mechanisms governing ion adsorption and transport at interfaces remains limited. This knowledge gap presents a significant challenge in meeting the increasing demands for these critical materials due to their growing use in advanced technologies. Fortunately, recent advancements in surface-specific experimental and computational techniques offer promising avenues to bridge this gap and facilitate the development of next-generation separation systems. Interestingly, unanswered questions regarding interfacial phenomena in chemical separations hold great relevance to various fields, including energy storage, geochemistry, and atmospheric chemistry. Therefore, the model interfacial systems developed for studying chemical separations, such as amphiphilic molecules assembled at a solid/water, air/water, or oil/water interface, may have far-reaching implications, extending beyond separations and opening doors to addressing a wide range of scientific inquiries. This perspective discusses recent interfacial studies elucidating amphiphile–ion interactions in chemical separations of metal ions. Finally, these studies provide direct, molecular-scale information about solute and solvent behavior at aqueous interfaces, including multivalent and complex ions in highly concentrated solutions, which play key roles in LLE of critical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Direct Structural Evidence for Interfacial Gradients in Asymmetric Polymer Nanocomposite Blends

Understanding the complex structure of polymer blends filled with nanoparticles (NPs) is key to design their macroscopic properties. In this work, the spatial distribution of hydrogenated (H) and deuterated (D) polymer chains asymmetric in mass is studied by small-angle neutron scattering. Depending on the chain mass, a qualitatively new large-scale organization of poly(vinyl acetate) chains beyond the random-phase approximation is evidenced in nanocomposites with attractive polymer–silica interactions. The silica is found to systematically induce bulk segregation. Only with long H-chains, a strong scattering signature is observed in the q range of the NP size: it is the sign of interfacial isotopic enrichment, that is, of contrasted polymer shells close to the NP surface. A quantitative model describing both the bulk segregation and the interfacial gradient (over ca. 10–20 nm depending on the NP size) is developed, showing that both are of comparable strength. In all cases, NP surfaces trap the polymer blend in a non-equilibrium state, with preferential adsorption around NPs only if the chain length and isotopic preference toward the surface combine their entropic and enthalpic driving forces. This structural evidence for interfacial polymer gradients will open the road for quantitative understanding of the dynamics of many-chain nanocomposite systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Investigating the Relative Roles of INPs and CCN in a Simulated Thunderstorm Using a New Immersion Freezing Algorithm

Microphysical processes in deep convective clouds are sensitive to the number concentrations of cloud condensation nuclei (CCN) and ice nucleating particles (INPs), but the effects of INPs are less studied. Modeling studies investigating the effects of INPs and/or CCN on deep convection typically retain a volume‐dependent raindrop freezing relation. The resulting neglect of aerosol accumulation in raindrops via drop collisions has likely produced unrealistic storm responses to INPs in past studies. To address this deficiency, a new immersion freezing algorithm was developed and embedded in a bulk microphysics scheme that freezes both cloud drops and raindrops using the same immersion freezing INP (IF‐INP) activity spectrum based on measurements. Multiple idealized simulations of a single case of deep convection observed during the Clouds, Aerosols, and Complex Terrain Interactions (CACTI) field campaign were conducted, with microphysical differences produced by independently altering IF‐INP temperature dependencies and CCN number concentrations from their observed values. Surface precipitation in all simulations resulted almost exclusively from riming graupel that melted upon descending to the surface. Rainfall and cold pools were substantially and systematically weakened with increased CCN due to decreased graupel riming rates but were relatively insensitive to variations in the magnitude and slope of IF‐INP spectra due to compensating depletion of supercooled liquid water. These compensating processes were a consequence of the accumulation of IF‐INPs in raindrops, encouraging caution in studying IF‐INP effects upon thunderstorms using traditional volume‐dependent drop freezing relationships.

CCN↗
DOE OSTI2021

Challenges for density functional theory: calculation of CO adsorption on electrocatalytically relevant metals

Density Functional Theory (DFT) is currently the most tractable choice of theoretical model used to understand the mechanistic pathways for electrocatalytic processes such as CO 2 or CO reduction. In this work, we assess the performance of two DFT functionals designed specifically to describe surface interactions, RTPSS and RPBE, as well as two popular meta-GGA functionals, SCAN and B97M-rV, that have not been a priori optimized for better interfacial properties. We assess all four functionals against available experimental data for prediction of bulk and bare surface properties on four electrocatalytically relevant metals, Au, Ag, Cu, and Pt, and for binding CO to surfaces of these metals. To partially mitigate issues such as thermal and anharmonic corrections associated with comparing computations with experiments, molecular benchmarks against high level quantum chemistry are reported for CO complexes with Au, Ag, Cu and Pt atoms, as well as the CO–water complex and the water dimer. Overall, we find that the surface modified RPBE functional performs reliably for many of the benchmarks examined here, and the meta-GGA functionals also show promising results. Specifically B97M-rV predicts the correct site preference for CO binding on Ag and Au (the only functional tested here to do so), while RTPSS performs well for surface relaxations and binding of CO on Pt and Cu.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Heat Exchanger Design for Waste Heat Recovery using Additive Manufacturing

With anticipated increases in global energy use and their associated emissions, there are many efforts to improve the emissions and efficiency of many industrial processes through waste heat recovery (WHR). To maximize improvements, the heat exchangers in WHR power cycles must be designed and optimized for a given heat source. Meanwhile, additive manufacturing (AM) is a single part manufacturing technique that provides the opportunity to develop unique and complex heat exchanger designs. Consequently, this work centers on the modeling, design, optimization, and testing of AM shell and tube heat exchangers for WHR. Specifically, a modified one-dimensional (1+1-D) and three-dimensional (3-D) heat exchanger models were developed and validated, with the 1+1-D model serving as the basis for design optimization. After modifications to the design to allow for AM, heat exchanger geometry optimizations were completed, targeting increased effectiveness across a range of physical parameters. Of the designs considered, nine were additively manufactured using Ti5553, and then tested using an external heat source and working fluid. Experimentally, the nineteen-tube, zero-baffle heat exchanger displayed the best overall performance, with the effects of dimensional accuracy, surface roughness, and baffles in the other designs also indicated. Next, the experimental results were used as inputs for the 1+1-D model. Although the original model was able to predict fluid outlet temperatures within 5% differences, larger variations in the heat exchanger performance parameters, temperature differences, and pressure drop necessitated optimizing the pressure drop and heat transfer calculations within the model. Thus, the resulting improved model was able to predict the heat transfer rates, heat source temperature difference, and effectiveness within 15% differences, while showing improvements in the pressure drops and working fluid temperature differences. The improved model serves as the foundation for future work to improve the design and performance of AM heat exchangers.

Spickler, Bailey Ann↗
DOE OSTI2022

$\mathrm{IH}$-$\mathrm{GAN}$: A conditional generative model for implicit surface-based inverse design of cellular structures

Variable-density cellular structures can overcome connectivity and manufacturability issues of topologically optimized structures, particularly those represented as discrete density maps. However, the optimization of such cellular structures is challenging due to the multiscale design problem. Past work addressing this problem generally either only optimizes the volume fraction of single-type unit cells but ignoring the effects of unit cell geometry on properties, or considers the geometry–property relation but builds this relation via heuristics. In contrast, we propose a simple yet more principled way to accurately model the property to geometry mapping using a conditional deep generative model, named Inverse Homogenization Generative Adversarial Network (IH-GAN). It learns the conditional distribution of unit cell geometries given properties and can realize the one-to-many mapping from properties to geometries. Here we further reduce the complexity of IH-GAN by using the implicit function parameterization to represent unit cell geometries. Results show that our method can 1) generate various unit cells that satisfy given material properties with high accuracy (R 2 -scores between target properties and properties of generated unit cells >98%) and 2) improve the optimized structural performance over the conventional variable-density single-type structure. In the minimum compliance example, our IH-GAN generated structure achieves a 79.7% reduction in concentrated stress and an extra 3.03% reduction in displacement. In the target deformation examples, our IH-GAN generated structure reduces the target matching error by 86.4% and 79.6% for two test cases, respectively. We also demonstrated that the connectivity issue for multi-type unit cells can be solved by transition layer blending.

42 ENGINEERING↗
DOE OSTI2023

Lightweight and effective tensor sensitivity for atomistic neural networks

Atomistic machine learning focuses on the creation of models that obey fundamental symmetries of atomistic configurations, such as permutation, translation, and rotation invariances. In many of these schemes, translation and rotation invariance are achieved by building on scalar invariants, e.g., distances between atom pairs. There is growing interest in molecular representations that work internally with higher rank rotational tensors, e.g., vector displacements between atoms, and tensor products thereof. Here, we present a framework for extending the Hierarchically Interacting Particle Neural Network (HIP-NN) with Tensor Sensitivity information (HIP-NN-TS) from each local atomic environment. Crucially, the method employs a weight tying strategy that allows direct incorporation of many-body information while adding very few model parameters. We show that HIP-NN-TS is more accurate than HIP-NN, with negligible increase in parameter count, for several datasets and network sizes. As the dataset becomes more complex, tensor sensitivities provide greater improvements to model accuracy. In particular, HIP-NN-TS achieves a record mean absolute error of 0.927 $\frac{\text{kcal}}{\text{mol}}$ for conformational energy variation on the challenging COMP6 benchmark, which includes a broad set of organic molecules. We also compare the computational performance of HIP-NN-TS to HIP-NN and other models in the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Probing plexciton emission from 2D materials on gold nanotrenches

Probing strongly coupled quasiparticle excitations at their intrinsic length scales offers unique insights into their properties and facilitates the design of devices with novel functionalities. In this work, we investigate the formation and emission characteristics of plexcitons, arising from the interaction between surface plasmons in narrow gold nanotrenches and excitons in monolayer WSe 2 . We study this strong plasmon–exciton coupling in both the far-field and the near-field. Specifically, we observe a Rabi splitting in the far-field reflection spectra of about 80 meV under ambient conditions, consistent with our theoretical modeling. Using a custom-designed near-field probe, we find that plexciton emission originates predominantly from the lower-frequency branch, which we can directly probe and map its local field distribution. We precisely determine the plexciton's spatial extension, similar to the trench width, with nanometric precision by collecting spectra at controlled probe locations. Our work opens exciting prospects for nanoscale mapping and engineering of plexcitons in complex nanostructures with potential applications in nanophotonic devices, optoelectronics, and quantum electrodynamics in nanoscale cavities.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Liquid ToF-SIMS revealing the oil, water, and surfactant interface evolution

Bilge water from ships is regarded as a major pollutant in the marine environment. Bilge water exists in a stable oil-in-water (O/W) emulsion form. However, little is known about the O/W liquid–liquid (l–l) interface. Traditional bulk characterization approaches are not capable of capturing the chemical changes at the O/W l–l interface. Although surfactants are deemed essential in droplet formation, their roles in bilge water stabilization have not been fully revealed. We have utilized novel in situ chemical imaging tools including in situ scanning electron microscopy (SEM) and in situ time-of-flight secondary ion mass spectrometry (ToF-SIMS) to study the evolving O/W interface using a NAVY bilge model for the first time. The droplet size distribution (DSD) does not change significantly without the addition of X-100 surfactants under static or rocking conditions. Both the oil components and the water clusters are shown to evolve over time at the O/W droplet interface by in situ liquid SIMS imaging. Of particular interest to droplet stabilization, the contribution of surfactants to the aged bilge droplets becomes more significant as the droplet size increases. The higher mass surfactant component does not appear on the droplet surface immediately while many lower mass surfactants are solvated inside the droplet. We have provided the first three-dimensional images of the evolving O/W interface and demonstrated that in situ surface chemical mapping is powerful enough to reveal the complex and dynamic l–l interface in the liquid state. Our observational insights suggest that surfactants are important in mediating droplet growth and facilitating effective separation of bilge water emulsion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗