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At least 1,333 records · Page 74

Revealing latent pole and zone line information in atom probe detector maps using crystallographically correlated metrics

Poles and zone lines observed within atom probe field evaporation images are useful for a range of atom probe crystallography studies, including calibration of the reconstruction and crystallographic characterisation of microstructural features such as grain boundaries. However, this information is not always readily apparent. Techniques for plotting crystallographically correlated metrics contained within atom probe data to enhance pole and zone line contrast across the detector space are developed. This includes consideration of the electric field, molecular ions, lattice structure retained within the reconstruction, specific elemental species, the number of pulses between detection events, and the lateral distance between sequential detection events. These approaches are then applied to experimental atom probe tomography datasets on technically pure Al, nanocrystalline Al, highly doped Si, and additively manufactured Inconel 738, Haynes 282, and Ti–6Al–4V. The results facilitate the extension of atom probe crystallography studies to a broader range of crystalline datasets where crystallographic information is not readily apparent from existing methods, as well as a deeper understanding of field evaporation behaviour during an atom probe experiment.

47 OTHER INSTRUMENTATION↗

Groundwater-native Fe(II) oxidation prior to aeration with H 2 O 2 to enhance As(III) removal

Groundwater contaminated with arsenic (As) must be treated prior to drinking, as human exposure to As at toxic levels can cause various diseases including cancer. Conventional aeration-filtration applied to anaerobic arsenite (As(III)) contaminated groundwater can remove As(III) by co-oxidizing native iron (Fe(II)) and As(III) with oxygen (O 2 ). However, the As(III) removal efficiency of conventional aeration can be low, in part, because of incomplete As(III) oxidation to readily-sorbed arsenate (As(V)). In this work, we investigated a new approach to enhance As(III) co-removal with native Fe(II) by the anaerobic addition of hydrogen peroxide (H 2 O 2 ) prior to aeration. Experiments were performed to co-oxidize Fe(II) and As(III) with H 2 O 2 (anaerobically), O 2 (aerobically), and by sequentially adding of H 2 O 2 and O 2 . Aqueous As(III) and As(V) measurements after the reaction were coupled with solid-phase speciation by Fe and As K-edge X-ray absorption spectroscopy (XAS). We found that complete anaerobic oxidation of 100 µM Fe(II) with 100 µM H 2 O 2 resulted in co-removal of 95% of 7 µM As(III) compared to 44% with 8.0-9.0 mg/L dissolved O 2 . Furthermore, we found that with 100 µM Fe(II), the initial Fe(II):H 2 O 2 ratio was a critical parameter to remove 7 µM As(III) to below the 10 µg/L (0.13 µM) WHO guideline, where ratios of 1:4 (mol:mol) Fe(II):H 2 O 2 led to As(III) removal matching that of 7 µM As(V). The improved As(III) removal with H 2 O 2 was found to occur partly because of the well-established enhanced efficiency of As(III) oxidation in Fe(II)+H 2 O 2 systems relatively to Fe(II)+O 2 systems. However, the XAS results unambiguously demonstrated that a large factor in the improved As(III) removal was also due to a systematic decrease in crystallinity, and thus increase in specific surface area, of the generated Fe(III) (oxyhydr)oxides from lepidocrocite in the Fe(II)+O 2 system to poorly-ordered Fe(III) precipitates in the Fe(II)+H 2 O 2 system. The combined roles of H 2 O 2 (enhanced As(III) oxidation and structural modification) can be easily overlooked when only aqueous species are measured, but this dual impact must be considered for accurate predictions of As removal in groundwater treatment.

54 ENVIRONMENTAL SCIENCES↗

Autonomous online optimization of a closed-circuit reverse osmosis system

As freshwater becomes increasingly scarce, many industrial and municipal water utilities look at premise-scale water treatment and reuse to meet water demand. Closed-circuit reverse osmosis (CCRO) has been proposed as a promising process design to do so. This sequencing batch process enables operation at higher brine salinity levels by means of a recycle flow. Optimal operation requires that the maximum salinity level at the membrane surface represents an optimal trade-off between brine disposal costs and energy efficiency. This maximum salinity level may change over time as the feed water composition changes and electricity markets fluctuate. In this article, we present the results of the experimental evaluation of an automatic technique for continuous online optimization, known as extremum seeking control. This technique has a long history in the process control community but has received little traction so far in the water industry. We modify this technique to enable its use for online optimization of CCRO, specifically to account for its sequential batch operation. We challenge the optimization schemes through several experimental tests and illustrate the advantages and drawbacks of extremum-seeking control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Drop-in sustainable aviation fuels enabled by feedstock-agnostic lignin deoxygenation

Current sustainable aviation fuels (SAFs) require blending with petroleum-derived fuels due to incomplete hydrocarbon distributions, most notably a lack of aromatics. Lignin, the most abundant renewable source of aromatics, is a promising feedstock for addressing this limitation. Here, we demonstrate a sequential reductive catalytic fractionation and continuous hydrodeoxygenation process that converts multiple woody feedstocks into aromatic hydrocarbons at up to 93% of the theoretical carbon yield. Blending these products with commercial SAFs produces drop-in compatible fuels with elastomer swell performances equivalent to conventional aviation fuels. The process is adaptable across multiple biomass sources, yielding aromatic hydrocarbons with consistent enthalpic efficiencies and fuel properties. These findings establish a scalable route to 100% drop-in SAFs, leveraging lignin-derived aromatics within the existing biofuels infrastructure.

09 BIOMASS FUELS↗

Describing the Influence of Ball-milling on the Amorphization of Flubendazole Using the PDF and RMC Methods with X-ray Powder Diffraction Data

Flubendazole (FBZ) is a poorly water-soluble drug, and different methodologies have been proposed to improve its oral bioavailability. Obtaining the amorphous drug phase is an alternative to improve its water solubility. Several techniques for drug amorphization, such as spray drying, lyophilization, melt quenching, solvent-evaporation, and ball milling, can yield various types of structural disorder and possibly render variations in physicochemical properties. Herein, we focus on evaluating the influence of the ball-milling process on the amorphization of FBZ. The characterization of the average global and local structures before, during, and after the milling process is described by sequential Rietveld refinements, pair distribution function analysis, and the Reverse Monte Carlo method. In conclusion, we show that preserving the local structure (nearest molecules) can be responsible for avoiding the fast structure recrystallization commonly observed when using the solvent-evaporation process for the studied drug.

60 APPLIED LIFE SCIENCES↗

Long noncoding RNAs: A potential target in sepsis-induced cellular disorder

Sepsis, an inflammation-related clinical syndrome, is characterized by disrupted immune homeostasis accompanied by infection and multiple organ dysfunction as determined by the Sequential Organ Failure Assessment (SOFA). Substantial evidence has recently suggested that lncRNAs orchestrate various biological processes in diseases, and lncRNAs play special roles in the diagnosis and management of sepsis. To date, very few reviews have provided clear and comprehensive clues to demonstrate the roles of lncRNAs in the pathogenesis of sepsis. Based on previously published studies, in this review, we summarize the different functions of lncRNAs in sepsis-induced cellular disorders and sepsis-induced organ failure to show the potential roles of lncRNAs in the diagnosis and management of sepsis. We further depict the function of some lncRNAs known to be pivotal regulators in the pathogenesis of sepsis to discuss the underlying molecular events. Additionally, we list and discuss several hotspots in research on lncRNAs, which may be conducive to future lncRNA-targeted therapeutic approaches for sepsis treatment.

60 APPLIED LIFE SCIENCES↗

Benefits and pathologies associated with the inflammatory response

Adult skeletal muscle regenerates completely after a damage, thanks to the satellite cells, or muscle stem cells (MuSCs), that implement the adult myogenic program. This program is sustained by both robust intrinsic mechanisms and extrinsic cues coming from the close neighborhood of MuSCs during muscle regeneration. Among the various cell types present in the regenerating muscle, immune cells, and particularly macrophages, exert numerous functions and provide sequential transient niches to support the myogenic program. The adequate orchestration of the delivery of these cues ensures efficient muscle regeneration and full functional recovery. The situation is very different in muscular dystrophies where asynchronous and permanent microinjuries occur, triggering contradictory regenerating cues at the same time in a specific area, that lead to chronic inflammation and fibrogenesis. Here we review the beneficial effects that leukocytes, and particularly macrophages, exert on their neighboring cells during skeletal muscle regeneration after an acute injury. Then, the more complicated (and less beneficial) roles of leukocytes during muscular dystrophies are presented. Finally, we discuss how the inflammatory compartment may be a target to improve muscle regeneration in both acute muscle injury and muscle diseases.

60 APPLIED LIFE SCIENCES↗

Development and experimental verification of an active noise cancellation (ANC) method for non-invasive sensing

Ultrasonic wave propagation may be used in non-invasive sensing to identify the properties of a fluid in a container. An ultrasonic excitation can be coupled into the liquid or the gas through the walls of the container and detected by a receiver on the other side. However, in addition to this fluid path, another signal will also propagate through the structure and is referred as noise in this study. For most materials, this structural noise will be of higher amplitude compared to the fluid signal due to the large acoustic impedance difference between the solid container and the fluid. In this paper, an active noise cancellation (ANC) method is developed and demonstrated on an experimental setup. It was shown that this method cancels more than 90% of the noise signal in a given time window of interest. A sequential version of this cancellation method is also proposed, and it was shown that its performance improves as the number of canceling excitations is increased. The performance was found to be independent of the location of canceling transducers and position of the silence window but dependent on the width of the silence window. As an example, the ANC method was applied to noise cancellation of a signal travelling through water in a stainless-steel container. The signal-to-noise ratio (SNR) of the water signal in the window of interest was increased by 148% from 13.98 dB to 34.68 dB by using the proposed ANC method.

42 ENGINEERING↗

Toward data assimilation of ship-induced aerosol–cloud interactions

Satellite imagery can detect temporary cloud trails or ship tracks formed from aerosols emitted from large ships traversing our oceans, a phenomenon that global climate models cannot directly reproduce. Ship tracks are observable examples of marine cloud brightening, a potential solar climate intervention that shows promise in helping combat climate change. In this paper, we demonstrate a simulation-based approach in learning the behavior of ship tracks based upon a novel stochastic emulation mechanism. Our method uses wind fields to determine the movement of aerosol–cloud tracks and uses a stochastic partial differential equation (SPDE) to model their persistence behavior. This SPDE incorporates both a drift and diffusion term which describes the movement of aerosol particles via wind and their diffusivity through the atmosphere, respectively. We first present our proposed approach with examples using simulated wind fields and ship paths. We then successfully demonstrate our tool by applying the approximate Bayesian computation method-sequential Monte Carlo for data assimilation.

54 ENVIRONMENTAL SCIENCES↗

Automated control and optimization of laser-driven ion acceleration

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.

47 OTHER INSTRUMENTATION↗

How does ion temperature gradient turbulence depend on magnetic geometry? Insights from data and machine learning

Magnetic geometry has a significant effect on the level of turbulent transport in fusion plasmas. Here, we model and analyse this dependence using multiple machine learning methods and a dataset of >200 000 nonlinear gyrokinetic simulations of ion-temperature-gradient turbulence in diverse non-axisymmetric geometries. The dataset is generated using a large collection of both optimised and randomly generated stellarator equilibria. At fixed gradients and other input parameters, the turbulent heat flux varies between geometries by several orders of magnitude. Trends are apparent among the configurations with particularly high or particularly low heat flux. Regression and classification techniques from machine learning are then applied to extract patterns in the dataset. Due to a symmetry of the gyrokinetic equation, the heat flux and regressions thereof should be invariant to translations of the raw features in the parallel coordinate, similar to translation invariance in computer vision applications. Multiple regression models including convolutional neural networks (CNNs) and decision trees can achieve reasonable predictive power for the heat flux in held-out test configurations, with highest accuracy for the CNNs. Using Spearman correlation, sequential feature selection and Shapley values to measure feature importance, it is consistently found that the most important geometric lever on the heat flux is the flux surface compression in regions of bad curvature. The second most important geometric feature relates to the magnitude of geodesic curvature. These two features align remarkably with surrogates that have been proposed based on theory, while the methods here allow a natural extension to more features for increased accuracy. The dataset, released with this publication, may also be used to test other proposed surrogates, and we find that many previously published proxies do correlate well with both the heat flux and stability boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimal experimental design: Formulations and computations

Questions of ‘how best to acquire data’ are essential to modelling and prediction in the natural and social sciences, engineering applications, and beyond. Optimal experimental design (OED) formalizes these questions and creates computational methods to answer them. This article presents a systematic survey of modern OED, from its foundations in classical design theory to current research involving OED for complex models. We begin by reviewing criteria used to formulate an OED problem and thus to encode the goal of performing an experiment. We emphasize the flexibility of the Bayesian and decision-theoretic approach, which encompasses information-based criteria that are well-suited to nonlinear and non-Gaussian statistical models. We then discuss methods for estimating or bounding the values of these design criteria; this endeavour can be quite challenging due to strong nonlinearities, high parameter dimension, large per-sample costs, or settings where the model is implicit. A complementary set of computational issues involves optimization methods used to find a design; we discuss such methods in the discrete (combinatorial) setting of observation selection and in settings where an exact design can be continuously parametrized. Finally we present emerging methods for sequential OED that build non-myopic design policies, rather than explicit designs; these methods naturally adapt to the outcomes of past experiments in proposing new experiments, while seeking coordination among all experiments to be performed. Throughout, we highlight important open questions and challenges.

97 MATHEMATICS AND COMPUTING↗

Resolving atomic transport through iron oxide under irradiation using isotopic tracers

Structural materials in nuclear environments are exposed to complex and harsh conditions, including high temperatures, corrosive solutions, and irradiation. Material stability and likewise degradation are fundamentally controlled by atomic transport mechanisms. Here, we investigate the influence of radiation-induced, non-equilibrium point defect populations on mass transport within model oxide systems using isotopic tracers and atom probe tomography. An isotopically labelled hematite (a-Fe2O3) film was synthesized with 16O- and 18O-rich layers (>30nm and 10 nm, respectively) sequentially deposited via molecular beam epitaxy. One region of the film was proton irradiated to ~0.1 dpa at 450°C, and regions outside the beam spot provided a non-irradiated control of thermal annealing only. 3D APT was used to directly visualize the elemental and O-isotopic redistribution following both thermal and combined thermal and irradiation conditions. Complementary scanning transmission electron microscopy (STEM) was also employed to study the microstructural evolution. Error function fits of the 18O-concentration profiles enabled quantification of diffusion coefficients.

isotopic tracers, diffusion, proton irradiation, h↗

Multibeam Electron Diffraction

One of the primary uses for transmission electron microscopy (TEM) is to measure diffraction pattern images in order to determine a crystal structure and orientation. In nanobeam electron diffraction (NBED), we scan a moderately converged electron probe over the sample to acquire thousands or even millions of sequential diffraction images, a technique that is especially appropriate for polycrystalline samples. However, due to the large Ewald sphere of TEM, excitation of Bragg peaks can be extremely sensitive to sample tilt, varying strongly for even a few degrees of sample tilt for crystalline samples. In this paper, we present multibeam electron diffraction (MBED), where multiple probe-forming apertures are used to create multiple scanning transmission electron microscopy (STEM) probes, all of which interact with the sample simultaneously. We detail designs for MBED experiments, and a method for using a focused ion beam to produce MBED apertures. We show the efficacy of the MBED technique for crystalline orientation mapping using both simulations and proof-of-principle experiments. We also show how the angular information in MBED can be used to perform 3D tomographic reconstruction of samples without needing to tilt or scan the sample multiple times. Finally, we also discuss future opportunities for the MBED method.

47 OTHER INSTRUMENTATION↗

Mechanistic Understanding and Rational Design of Quantum Dot/Mediator Interfaces for Efficient Photon Upconversion

The semiconductor-nanocrystal-sensitized, three-component upconversion system has made great strides over the past 5 years. The three components (i.e., triplet photosensitizer, mediator, and emitter) each play critical roles in determining the input and output photon energy and overall quantum efficiency (QE). The nanocrystal photosensitizer converts the absorbed photon into singlet excitons and then triplet excitons via intersystem crossing. The mediator accepts the triplet exciton via either direct Dexter-type triplet energy transfer (TET) or sequential charge transfer (CT) while extending the exciton lifetime. Through a second triplet energy-transfer step from the mediator to the emitter, the latter is populated in its lowest excited triplet state. Triplet–triplet annihilation (TTA) between two triplet emitters generates the emitter in its bright singlet state, which then emits the upconverted photon. Quantum dots (QD) have a tunable band gap, large extinction coefficient, and small singlet–triplet energy losses compared to metal–ligand charge-transfer complexes. This high triplet exciton yield makes QDs good candidates for photosensitizers. In terms of driving triplet energy transfer, the triplet energy of the mediator should be slightly lower than the triplet exciton energy of the QD sensitizer for a downhill energy landscape with minimal energy loss. The same energy cascade is also required for the transfer from the mediator to the emitter. Lastly, the triplet energy of the emitter must be slightly larger than one-half of its singlet energy to ensure that TTA is exothermic. Optimization of the sensitizer, mediator, and emitter will lead to an increase in the anti-Stokes shift and the total quantum efficiency. Evaluating each individual step’s efficiency and kinetics is necessary for the understanding of the limiting factors in existing systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthetic and Mechanistic Implications of Chlorine Photoelimination in Nickel/Photoredox C(sp 3 )–H Cross-Coupling

In recent years, the development of light-driven reactions has contributed numerous advances in synthetic organic chemistry. A particularly active research area combines photoredox catalysis with nickel catalysis to accomplish otherwise inaccessible cross-coupling reactions. In these reactions, the photoredox catalyst absorbs light to generate an electronically excited charge-transfer state that can engage in electron or energy transfer with a substrate and the nickel catalyst. Our group questioned whether photoinduced activation of the nickel catalyst itself could also contribute new approaches to cross-coupling. Over the past 5 years, we have sought to advance this hypothesis for the development of a suite of mild and site-selective C(sp 3 )–H cross-coupling reactions with chloride-containing coupling partners via photoelimination of a Ni–Cl bond. On the basis of a report from the Nocera laboratory, we reasoned that photolysis of a Ni(III) aryl chloride species, generated by single-electron oxidation of a typical Ni(II) intermediate in cross-coupling, might allow for the catalytic generation of chlorine atoms. Combining this with the ability of Ni(II) to accept alkyl radicals, we hypothesized that photocatalytically generated chlorine atoms could mediate hydrogen atom transfer (HAT) with C(sp 3 )–H bonds to generate a substrate-derived alkyl radical that is captured by the Ni center in cross-coupling. A photoredox catalyst was envisioned to promote the necessary single-electron oxidation and reduction of the Ni catalyst to facilitate an overall redox-neutral process. Overall, this strategy would offer a visible-light-driven mechanism for chlorine radical formation enabled by the sequential capture of two photons. As an initial demonstration, we developed a Ni/photoredox-catalyzed α-oxy C(sp 3 )–H arylation of cyclic and acyclic ethers. This method was extended to a mild formylation of abundant and complex aryl chlorides through selective 2-functionalization of 1,3-dioxolane. Seeking to develop a suite of reactions that introduce carbon at all different oxidation states, we explored C(sp 3 )–H cross-coupling with trimethyl orthoformate, a common laboratory solvent. We found that trimethyl orthoformate serves as a source of methyl radical for a methylation reaction via β-scission from a tertiary radical generated upon chlorine-mediated HAT. Since chlorine radical is capable of abstracting unactivated C(sp 3 )–H bonds, our efforts have also been directed at cross-coupling with a range of feedstock chemicals, such as alkanes and toluenes, along with late-stage intermediates, using chloroformates as coupling partners. Overall, this platform enables access to valuable synthetic transformations with (hetero)aryl chlorides, which despite being the most ubiquitous and inexpensive aryl halide coupling partners, are rarely reactive in Ni/photoredox catalysis. Little is known about the photophysics and photochemistry of organometallic Ni complexes relevant to cross-coupling. We have conducted mechanistic investigations, including computational, spectroscopic, emission quenching, and stoichiometric oxidation studies, of Ni(II) aryl halide complexes common to Ni/photoredox reactions. These studies indicate that chlorine radical generation from excited Ni(III) is operative in the described C(sp 3 )–H functionalization methods. More generally, the studies illustrate that the photochemistry of cross-coupling catalysts cannot be ignored in metallaphotoredox reactions. We anticipate that further mechanistic understanding should facilitate catalyst design and lead to the development of new synthetic methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ab Initio Direct Dynamics

The reactivity and dynamics of molecular systems can be explored computationally by classical trajectory calculations. The traditional approach involves fitting a functional form of a potential energy surface (PES) to the energies from a large number of electronic structure calculations and then integrating numerous trajectories on this fitted PES to model the molecular dynamics. The ever-decreasing cost of computing and continuing advances in computational chemistry software have made it possible to use electronic structure calculations directly in molecular dynamics simulations without first having to construct a fitted PES. In this “on-the-fly” approach, every time the energy and its derivatives are needed for the integration of the equations of motion, they are obtained directly from quantum chemical calculations. This approach started to become practical in the mid-1990s as a result of increased availability of inexpensive computer resources and improved computational chemistry software. The application of direct dynamics calculations has grown rapidly over the last 25 years and would require a lengthy review article. The present Account is limited to some of our contributions to methods development and various applications. To improve the efficiency of direct dynamics calculations, we developed a Hessian-based predictor-corrector algorithm for integrating classical trajectories. Hessian updating made this even more efficient. Furthermore, this approach was also used to improve algorithms for following the steepest descent reaction paths. For larger molecular systems, we developed an extended Lagrangian approach in which the electronic structure is propagated along with the molecular structure. Strong field chemistry is a rapidly growing area, and to improve the accuracy of molecular dynamics in intense laser fields, we included the time-varying electric field in a novel predictor-corrector trajectory integration algorithm. Since intense laser fields can excite and ionize molecules, we extended our studies to include electron dynamics. Specifically, we developed code for time-dependent configuration interaction electron dynamics to simulate strong field ionization by intense laser pulses. Our initial application of ab initio direct dynamics in 1994 was to CH 2 O → H 2 + CO; the calculated vibrational distributions in the products were in very good agreement with experiment. In the intervening years, we have used direct dynamics to explore energy partitioning in various dissociation reactions, unimolecular dissociations yielding three fragments, reactions with branching after the transition state, nonstatistical dynamics of chemically activated molecules, dynamics of molecular fragmentation by intense infrared laser pulses, selective activation of specific dissociation channels by aligned intense infrared laser fields, angular dependence of strong field ionization, and simulation of sequential double ionization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Influence of Nonlocal Metal–Dielectric Environments on Physical and Chemical Processes

Plasmonic nanolayers and laminar metallic/dielectric multilayers were originally developed for optical cloaking applications and lensing applications that could potentially image objects whose size was below the diffraction limit. These assemblies were initially formed from gold or silver nanorods grown within an alumina mesh. However, more recently, assemblies with similar properties have also been prepared by sequential thin-layer deposition of alternating layers of gold and magnesium fluoride (MgF 2 ). These metal/dielectric composite materials enable control of the dielectric constant in the directions perpendicular to the layers and balance the real and imaginary dielectric constants of the assembly such that the speed and the amplitude of the waves traveling through the assembly are not attenuated. In this Account, we will also focus on a few of the applications ranging from surface wetting to fluorescence quenching to enhancement of photochemical reactions. First, we will share an introduction to processes used to create these materials, which are combinations of low refractive index metals and transparent higher index materials arranged in a scalable repeating fashion. Two fabrication methods were employed: an electrochemical deposition of Ag nanorods into an anodized alumina matrix which produced materials with an anisotropic negative refractive index material within the plane of the film and lamellar metal/dielectric layers in which the negative index perpendicular to the growth direction. These alternating layers of plasmonic metals and dielectric materials were ultimately chosen to prepare films for further testing, because of their relative ease of fabrication. We will continue with a discussion of a few of the applications of both of these nonlocal dielectric composite materials including more specialized plasmonic, composite, and hyperbolic metamaterials including fluorescence quenching, photochemical reactions, and surface wetting. In each of these applications, the unique response caused by the enhancement of the electric field and the interface between hyperbolic materials and plasmonic materials as they interact photophysically with their near neighbors is presented. In each of the applications, the enhanced electric field extends from the composite substrate layer to interact with its near neighbors and beyond. Furthermore, the presence of this extended interaction can be observed in the form of decreased emission lifetime, enhancement of photochemical reaction rates, and changes in the surface energies measured by contact angle goniometry. In this Account, all of these situations will be addressed. Finally, we will conclude with a summary and vision for the future as well as a discussion of the unique challenges and opportunities available as research active faculty at an HBCU.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗