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At least 757 records · Page 42

Role of emission controls in reducing the 2050 climate change penalty for PM2.5 in China

Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM2.5 to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM2.5 between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM2.5 climate change penalty of 1.43 µg m-3 in Eastern China, leading to an additional 35,000 PM2.5-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM2.5 climate change penalty weakens to 0.24 µg m-3 with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM2.5-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM2.5 decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM2.5 decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM2.5 and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions is key to attaining air quality targets and protecting human health in the context of future global climate change.

Liu, Song↗

Mechanistic insights into sulfate and phosphate-mediated hexavalent chromium removal by tea polyphenols wrapped nano-zero-valent iron

Nano zero-valent iron via green synthesis (g-nZVI) has great potential in removing toxic hexavalent Cr(VI) from industrial wastewater. Sulfate and phosphate in wastewater can influence Cr(VI) removal by g-nZVI. Here, in this study, the Cr(VI) removal kinetics by different g-nZVI materials were investigated with the existence of sulfate and/or phosphate, and the corresponding mechanisms were first revealed using multiple characterizations, including X-ray absorption near-edge spectra (XANES) and X-ray photoelectron spectroscopy (XPS). The results showed that Cr(OH) 3 was the dominant species initially formed on the surface of g-nZVI particles before transforming to Cr 2 O 3 during the reaction of g-nZVI with Cr(VI). Sulfate in wastewater can promote the reduction from Cr(VI) to Cr(OH) 3 by g-nZVI, because sulfate triggers the release of Fe(II) and tea polyphenols (from tea extracts) from the g-nZVI surface due to the corrosion of Fe 0 core, which is in line with an obvious increase in pseudo-second-order rate constant (k 2 ) and subtle change in Cr(VI) removal capacity (q e ). However, phosphate impedes the g-nZVI corrosion and inhibits q e because of the inner-sphere complexation of phosphate onto g-nZVI decreasing the released Fe(II) for Cr 2 O 3 production. When sulfate and phosphate coexisted in contaminated water, the inhibition effect of phosphate in Cr(VI) removal by g-nZVI was stronger than the promotion of sulfate. Accordingly, q e value of g-nZVI declined from 93.4 mg g –1 to 77.5 mg g –1 , while k 2 remained constant as the molar ratio of phosphate/sulfate increased from 0.1 to 10 in water. This study provides new insights into applying g-nZVI in efficient Cr(VI) removal from contaminated water with enrichment of sulphates and phosphates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of alkaline earth metal ion adsorption on goethite for various background electrolytes with the CD-MUSIC model

As water scarcity drives the use of more saline water sources, contaminant fate and transport models must capture the impact of high concentrations of alkaline earth metal ions (AEMs) and background electrolytes in these more complex waters. By utilizing macroscopic adsorption data from various electrolyte systems, a Charge Distribution – Multisite Complexation (CD-MUSIC) model, capable of incorporating electrolyte adsorption, was able to accurately simulate the adsorption behavior of alkaline earth metal ions onto goethite. The modeling effort was guided by previous spectroscopic and surface complexation modeling of alkaline earth metal adsorption and built on previous CD-MUSIC modeling that accounted for changes in crystal face contributions to the surface site density as a function of specific surface area. Further, the model was constrained to consider only two dominant surface complex species for each metal ion adsorption reaction. These two species were selected from 44 possible species through objective curve fitting of single-solute macroscopic adsorption data. While most of the alkaline earth metal surface complexes formed outer-sphere complexes at the goethite surface, an inner-sphere species was utilized for Mg 2+ . With the surface complex species and equilibrium constants obtained from this study, the calibrated model successfully predicted alkaline earth metal ion adsorption over a wide range of solution and surface conditions; the model predictions encompassed a wide range of pH (5–11), solute/solid ratio (1.37 × 10 -5 – 8.33 × 10 -4 mol -solute /g -solid ), ionic strengths (0.01 M – 0.7 M), and background electrolytes (Na + , Cs + , Rb + , Cl - , and NO 3 - ) using the same crystal face contribution methodology for site density, capacitance values, and surface acidity constants adopted for proton and cadmium adsorption in previous work (Han and Katz, 2019). Model simulations for a range of background water chemistries demonstrated the potential for Mg 2+ to reduce Cd 2+ adsorption to goethite in model seawater and oil- and gas-produced waters.

42 ENGINEERING↗

Migration of inclusions in a matrix due to a spatially varying interface energy

An interfacial energy can be a function of a bulk field such as temperature or electric field. Here we find that in a system with a gradient in temperature or electric potential, the resulting variation in interfacial energy can induce a particle to migrate by either surface or bulk diffusion. For a circular particle under a constant unidirectional gradient in the bulk field, the field dependence of the interfacial energy induces a circular particle to move as a circle at a constant velocity along the direction from higher to lower interfacial energy. A linear stability analysis of this steady state migration suggests that perturbations will damp out as time evolves, and thus under these conditions a migrating circular particle is morphologically stable. Other spatial distributions of interface energy can lead to the distortion of an initially circular shaped particle during migration. A phase field model is developed that captures these distortions and verifies the theoretical results mentioned above.

36 MATERIALS SCIENCE↗

Effect of hydrophobic ionic liquids aqueous solubility on metal extraction from hydrochloric acid media: Mathematical modelling and trivalent thallium behavior

A mathematical model to explain cations’ solubility of both protic and aprotic ionic liquids in a wide range of hydrochloric acid solutions has been developed. The concept of this model is based on an assumption of the mineral acid extraction into the organic phase, formation of a salt there between an ionic liquid cation and chloride-anion due to ions recombination and partial salt back-extraction. The proposed approach allows estimating corresponding extraction constants. Comparison of calculated and experimentally measured solubility product constants shows that they are in good agreement. It has been determined also that the more the hydrophilicity of the ionic liquids’ cation the more hydrochloric acid is extracted. Furthermore, this model has been utilized to facilitate analysis of thallium transfer into hydrophobic ionic liquids providing insights into the mechanism of metal extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydroxypyridinone-based stabilization of Np(IV) enabling efficient U/Np/Pu separations in the Adapted PUREX process

The classical process to recover uranium (U) and plutonium (Pu) from used nuclear fuel using tributyl phosphate (TBP), namely the Plutonium Uranium Redox EXtraction (PUREX) process, is complicated by the persistent presence of neptunium (Np) and thus requires extra purification steps. The concept of Adapted PUREX seeks to achieve Np recovery by adjusting the valence of the metal more effectively, thereby controlling its behavior more precisely. This study introduces the use of an aqueous hydroxypyridinone chelator, 3,4,3-LI(1,2-HOPO) (abbreviated as HOPO), to dictate the behavior of Np for recovery and meanwhile simplify cumbersome reprocessing steps. The interactions between Np and HOPO were probed mechanistically by way of absorption spectrophotometry, in conjunction with cyclic voltammetry. UV–Vis-NIR spectra illustrated the reduction of NpO 2 2+ to Np 4+ , with a fast reaction rate. Cyclic voltammetry revealed quasi-reversible processes between the oxidized and reduced forms of the ligand and its Np complexes. The corresponding heterogeneous rate constants (k 0 ) were estimated from the peak-to-peak separation potentials (ΔE p ), at ~ 4 – 35 μm/s for both HOPO and NpHOPO, with scan rates of 0.01 – 0.4 V/s. Meanwhile, the electromotive force (E MF ) as well as the change of Gibbs free energy (ΔG) were assessed from the half-wave potential (E 1/2 ), demonstrating the completeness of NpO 2 2+ reduction to Np 4+ by HOPO. The cumulative formation constant of the resulting NpHOPO complex (logβ 101 ) was determined by metal competition titration to be 42.0 ± 0.6, corroborating the extraordinarily high affinity of HOPO to tetravalent metal ions. Here, the prowess of valence control by HOPO and the high stability of the formed complex resulted in enhanced separations of Np from U and of Pu from U, with a maximum separation factor of ~7000 for both, nearly 90- and 10300-fold higher, respectively, than the values obtained using conventional PUREX formulae.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

The Cell Utilized Partitioning Model as a Predictive Tool for Optimizing Counter-Current Chromatography Processes

Counter-current chromatography (CCC) is capable of unique elution modes that isolate analytes using the movement of the stationary phase in addition to moving the mobile phase. These modes include elution-extrusion CCC (EECCC) and dual-mode CCC (DM CCC) that are not possible in traditional solid-liquid chromatography systems. Although EECCC and DM CCC are widely used to recover highly retained components, to our knowledge, optimizing the elution process in these modes with predictive models has not been reported. To address this gap, we developed a predictive model for CCC dubbed the Cell Utilized Partitioning (CUP) model. The CUP model accurately predicts the effluents of multicomponent separations in EECCC and DM CCC modes when compared to experimental data. Furthermore, CUP model simulations were extended to investigate the influence of operating and intrinsic parameters on the yield and productivity, and to compare the separation performances of EECCC and DM CCC in various conditions. The results demonstrate that low distribution constants, usually a KD less than 1, and a selectivity > 1.3, under specific flowrate ranges, increase both productivity and yield. From these results, generalized optimization and scaleup guidelines are proposed that can apply to research settings and to industrial processes to maximize preparative CCC performance.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗

A heat flux sensor leveraging the transverse Seebeck effect in elemental antimony

Certain configurations of anisotropic single crystal materials can generate a thermoelectric voltage orthogonal to an induced temperature gradient. This phenomenon is known as the Transverse Seebeck Effect (TSE) and can be leveraged to fabricate simple and robust heat flux sensors. Only a small number of materials have been considered as TSE-based transducers and, among these, few have been developed into sensors with ruggedization against chemical and mechanical degradation. Here, we report on the fabrication and characterization of a rugged TSE-based heat flux sensor using prismatic antimony single crystals. The heat flux sensor was tested under static and dynamic heating scenarios. The sensor has a linear responsivity of 16.8 µV/(W/cm2) to heat fluxes spanning more than two orders of magnitude and a time constant of 4.4 s. The sensor’s response to localized heating, probed with a laser scanning technique, validated that the transduction mechanism is primarily the TSE by ruling out a sizable contribution from the conventional Seebeck effect. Finite element analysis corroborated that components used in the sensor package are the primary determinants of the time constant and the decrement of the responsivity from its theoretical maximum. Design principles that may be applied to elicit a faster transient response or higher responsivity are proposed. Furthermore, the results establish single crystal antimony as a promising transducer material for heat flux measurement systems and demonstrate potential effects of ruggedization on sensor performance.

36 MATERIALS SCIENCE↗

Investigation of post-injection strategies for diesel engine Catalyst Heating Operation using a vapor-liquid-equilibrium-based spray model

Most multidimensional engine simulations spend much time solving for non-equilibrium spray dynamics (atomization, collision, vaporization). However, their accuracy is limited by significant grid dependency, and the need for extensive calibration. This is critical for modeling cold-start diesel fuel post injections, which occur at low temperatures and pressures, far from typical model validation ranges. At the same time, resolving micron-scale spray phenomena would render full Eulerian multiphase calculations prohibitive. In this study, an improved phase equilibrium based approach was implemented and assessed for simulating diesel catalyst heating operation strategies. A phase equilibrium solver based on the model by Yue and Reitz [1] was implemented: a fully multiphase CFD solver is employed with an engineering-size engine grid, and fuel injection is modeled using the standard Lagrangian parcels approach. Mass and energy from the liquid parcels are released to the Eulerian multiphase mixture according to an equilibrium-based liquid jet model. An improved phase equilibrium solver was developed to handle large real-gas mixtures such as those from accurate chemical kinetics mechanisms. The liquid-jet model was improved such that momentum transfer to the Eulerian solver better reproduces the physical spray jet structure. Validation of liquid/vapor penetration predictions showed that the model yields accurate results with very limited tuning and low sensitivity to the few calibration constants. In-cylinder simulations of diesel catalyst heating operation strategies showed that capturing spray structure is paramount when short, transient injection pulses and low temperatures are present. Furthermore, the EP model provides improved predictions of post-injection spray structure and ignitability, while conventional spray modeling does not capture the increase of liquid penetration during the expansion stroke. Finally, the only important EP model calibration constant, Cliq, does not affect momentum transfer, but it changes the local charge cooling distribution through the local energy transfer, which makes it candidate to additional research. The results confirm that non-equilibrium spray processes do not need to be resolved in engineering simulations of high-pressure diesel sprays.

42 ENGINEERING↗

Verification of stability and unraveling the electronic and physical properties of bulk and (001)-surfaces of newly synthesized Ti 2 ZnX (X = C, N) MAX phases

MAX phase family has been extended by the addition of late transition metals at the A-site with the expectation of diverse functional properties. Here, we present our systematic density functional investigation on the thermodynamic and phonon stabilities, elastic properties, including elastic constants, elastic moduli and elastic anisotropy of newly synthesized Ti 2 ZnX (X = C, N) phases in comparison with conventional Ti 2 AlX (X = C, N). Due to the smaller size of N as compared to C, the unit cell dimension is reduced when C atoms are replaced by N atoms at the X-site. Furthermore, the Ti 2 ZnC and Ti 2 ZnN are stable at the equilibrium volume of 110.84 Å 3 and 105.70 Å 3 . The thermodynamic, mechanical and dynamical stabilities are validated by estimating the formation energies, elastic constants and phonon dispersions, respectively. The elastic properties of Ti 2 ZnN are less anisotropic as compared to those of Ti 2 ZnC. To understand the thin-film characteristics in Ti 2 ZnX, the surface properties with (001)-terminated slabs are investigated. Both Ti 2 ZnX bulk and (001)-surfaces exhibit metal-like electronic structures. There is a strong covalent bonding between Ti-X and Ti-Zn atoms confirmed by the charge density map and Mulliken population analysis. Additional states are generated at the Fermi level (EF) due to the unusual d-p states hybridization between Ti and Zn atoms. The anisotropy in chemical bonding is confirmed by the cleavage energy difference between Ti-X and Ti-Zn. Here, Ti(X)-001 and Zn-001 terminations are stable surfaces; however, in terms of chemical potentials, Zn-001 termination is the most favourable in Ti 2 ZnX.

36 MATERIALS SCIENCE↗

Methanol adsorption and dissociation on GaP(110) studied by ambient pressure X-ray photoelectron spectroscopy

Ambient pressure X-ray photoelectron spectroscopy (AP-XPS) was used to investigate methanol (CH 3 OH) adsorption and reaction on the GaP(110) surface. Exposure of CH 3 OH to GaP(110) at room temperature led to the formation of at least four different surface species as indicated by analysis of C 1s and O 1s XPS features. By combining AP-XPS data with density functional theory calculations, the surface species were identified as methoxy (CH 3 O*), formaldehyde (CH 2 O*), and paired methanol (p-CH 3 O*H) and methoxy (p-CH 3 O*) species, where “paired” means that they belong to a hydrogen-bonded methoxy-methanol complex. Asterisk * here indicates an adsite. The formation of CH 2 O* via the dehydrogenation of CH 3 O* was shown to be limited by the availability of vacant phosphorus (P) sites on GaP(110). With an increase in CH 3 OH pressure, the fractional coverage of CH 3 O* species reached 0.55, and the surface P sites were completely saturated with hydrogen. Under a constant CH 3 OH pressure of 0.5 Torr, the surface concentration of the paired species and of CH 2 O* remained constant until 400 K. At higher temperatures, thermally driven reactions led to a significant increase in the concentration of surface CH x * species, which suggests that C-O bond cleavage of the CH 3 O group is the dominant decomposition mechanism on GaP(110). In conclusion, based on the reactivity of GaP(110) toward CH 3 OH dehydrogenation, elevated temperatures and CH 3 OH pressures may be used to functionalize this surface.

36 MATERIALS SCIENCE↗

Implications of stop-and-go traffic on training learning-based car-following control

Learning-based car-following control (LCC) of connected and autonomous vehicles (CAVs) is gaining significant attention with the advancement of computing power and data accessibility. While the flexibility and large model capacity of model-free architecture enable LCC to potentially outperform the model-based car-following (CF) model in improving traffic efficiency and mitigating congestion, the generalizability of LCC for traffic conditions different from the training environment/dataset is not well-understood. Herein, this study seeks to explore the impact of stop-and-go traffic in the training dataset on the generalizability of LCC. It uses the characteristics of lead vehicle trajectories to describe stop-and-go traffic, and links the theory of identifiability (i.e., obtaining a unique parameter estimation result using sensor measurements) to the generalizability of behavior cloning (BC) and policy-based deep reinforcement learning (DRL). Correspondingly, the study shows theoretically that: (i) stop-and-go traffic can enable the property of identifiability and enhance the control performance of BC-based LCC in different traffic conditions; (ii) stop-and-go traffic is not necessary for DRL-based LCC to generalize to different traffic conditions; (iii) DRL-based LCC trained with only constant-speed lead vehicle trajectories (not sufficient to ensure identifiability) can be generalized to different traffic conditions; and (iv) stop-and-go traffic increases variance in the training dataset, which improves the convergence of parameter estimation while negatively impacting the convergence of DRL to the optimal control policy. Numerical experiments validate the above findings, illustrating that BC-based LCC entails comprehensive training datasets for generalizing to different traffic conditions, while DRL-based LCC can achieve generalization with simple free-flow traffic training environments. This further suggests DRL as a more promising and cost-effective LCC approach to reduce operational costs, mitigate traffic congestion, and enhance safety and mobility, which can accelerate the deployment and acceptance of CAVs.

33 ADVANCED PROPULSION SYSTEMS↗

Implications of inertial subrange scaling for stably stratified mixing

In this work, we investigate the effects of the turbulent dynamic range on active scalar mixing in stably stratified turbulence by adapting the theoretical passive scalar modelling and demonstrating their usefulness through consideration of the results of direct numerical simulations of statistically stationary homogeneous stratified and sheared turbulence. By analysis of inertial and inertial–convective subrange scalings, we show that the relationship between the active scalar and turbulence time scales is predicted by the ratio of the Kolmogorov and Obukhov–Corrsin constants, provided mean flow parameters permit the two subrange scalings to be appropriate approximations. We use the resulting relationship between time scales to parameterise an appropriate turbulent mixing coefficient $\varGamma \equiv \chi /\epsilon$, defined here as the ratio of available potential energy ($E_p$) and turbulent kinetic energy ($E_k$) dissipation rates. With the analysis presented here, we show that $\varGamma$ can be estimated by $E_p,E_k$ and a universal constant provided an appropriate Reynolds number is sufficiently high. This large Reynolds number regime appears here to occur at $ {{Re_b}} \equiv \epsilon / \nu N^{2} \gtrapprox 300$ where $\nu$ is the kinematic viscosity and $N$ is the characteristic buoyancy frequency. We propose a model framework for irreversible diapycnal mixing with robust theoretical parametrisation and asymptotic behaviour in this high-$ {{Re_b}}$ limit.

42 ENGINEERING↗

Uniform momentum and temperature zones in unstably stratified turbulent flows

Wall-bounded turbulent flows exhibit a zonal arrangement, in which streamwise velocity organizes into uniform momentum zones (UMZs), separated by thin layers of elevated interfacial shear. While significant research efforts have focused on these structural features in neutrally stratified flows, the effects of unstable thermal stratification on UMZs and on analogous uniform temperature zones (UTZs) have not been considered previously. In this article, statistical properties of UMZs and UTZs are investigated using a suite of large eddy simulations of unstably stratified turbulent channel flow spanning weakly to highly convective conditions. When normalized by the friction velocity and stability-dependent mixing length, the mean velocity gradient based on UMZ interfacial velocity jumps and the vorticity thickness exhibits good collapse for all stabilities, establishing a link between UMZ properties and scaling predictions from Monin–Obukhov similarity theory. A similar relationship is found between UTZ properties and surface-layer scaling of the mean temperature gradient. In the mixed layer, mean UMZ depth is quasi-constant with wall-normal distance, while the deepest UTZs are found in the centre of the boundary layer. These instantaneous structures are found to be linked to the well-mixed velocity and temperature profiles in the convective mixed layer. Conditional averaging indicates that both UMZ and UTZ interfaces are associated with ejections of momentum and warm updrafts below the interface and sweeps of momentum and cool downdrafts above the interface. These results demonstrate a tangible connection between instantaneous structural features, mean properties and scaling laws in unstably stratified flows.

Mechanics↗

Zonally dominated dynamics and Dimits threshold in curvature-driven ITG turbulence

The saturated state of turbulence driven by the ion-temperature-gradient instability is investigated using a two-dimensional long-wavelength fluid model that describes the perturbed electrostatic potential and perturbed ion temperature in a magnetic field with constant curvature (a $Z$ -pinch) and an equilibrium temperature gradient. Numerical simulations reveal a well-defined transition between a finite-amplitude saturated state dominated by strong zonal-flow and zonal temperature perturbations, and a blow-up state that fails to saturate on a box-independent scale. We argue that this transition is equivalent to the Dimits transition from a low-transport to a high-transport state seen in gyrokinetic numerical simulations (Dimits et al. , Phys. Plasmas , vol. 7, 2000, 969). A quasi-static staircase-like structure of the temperature gradient intertwined with zonal flows, which have patch-wise constant shear, emerges near the Dimits threshold. The turbulent heat flux in the low-collisionality near-marginal state is dominated by turbulent bursts, triggered by coherent long-lived structures closely resembling those found in gyrokinetic simulations with imposed equilibrium flow shear (van Wyk et al. , J. Plasma Phys. , vol. 82, 2016, 905820609). The breakup of the low-transport Dimits regime is linked to a competition between the two different sources of poloidal momentum in the system – the Reynolds stress and the advection of the diamagnetic flow by the $\boldsymbol {E}\times \boldsymbol {B}$ flow. By analysing the linear ion-temperature-gradient modes, we obtain a semi-analytic model for the Dimits threshold at large collisionality.

Physics↗

Magnetic nulls in interacting dipolar fields

The prominence of nulls in reconnection theory is due to the expected singular current density and the indeterminacy of field lines at a magnetic null. Electron inertia changes the implications of both features. Magnetic field lines are distinguishable only when their distance of closest approach exceeds a distance Δ d . Electron inertia ensures Δ d ≳ c/ω pe . The lines that lie within a magnetic flux tube of radius Δ d at the place where the field strength B is strongest are fundamentally indistinguishable. If the tube, somewhere along its length, encloses a point where B = 0 vanishes, then distinguishable lines come no closer to the null than ≈ (a 2 c/ω pe ) 1/3 , where a is a characteristic spatial scale of the magnetic field. Here, the behaviour of the magnetic field lines in the presence of nulls is studied for a dipole embedded in a spatially constant magnetic field. In addition to the implications of distinguishability, a constraint on the current density at a null is obtained, and the time required for thin current sheets to arise is derived.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Learning and meta-learning of stochastic advection–diffusion–reaction systems from sparse measurements

Physics-informed neural networks (PINNs) were recently proposed in [18] as an alternative way to solve partial differential equations (PDEs). A neural network (NN) represents the solution, while a PDE-induced NN is coupled to the solution NN, and all differential operators are treated using automatic differentiation. Here, we first employ the standard PINN and a stochastic version, sPINN, to solve forward and inverse problems governed by a non-linear advection–diffusion–reaction (ADR) equation, assuming we have some sparse measurements of the concentration field at random or pre-selected locations. Subsequently, we attempt to optimise the hyper-parameters of sPINN by using the Bayesian optimisation method (meta-learning) and compare the results with the empirically selected hyper-parameters of sPINN. In particular, for the first part in solving the inverse deterministic ADR, we assume that we only have a few high-fidelity measurements, whereas the rest of the data is of lower fidelity. Hence, the PINN is trained using a composite multi-fidelity network, first introduced in [12], that learns the correlations between the multi-fidelity data and predicts the unknown values of diffusivity, transport velocity and two reaction constants as well as the concentration field. For the stochastic ADR, we employ a Karhunen–Loève (KL) expansion to represent the stochastic diffusivity, and arbitrary polynomial chaos (aPC) to represent the stochastic solution. Correspondingly, we design multiple NNs to represent the mean of the solution and learn each aPC mode separately, whereas we employ a separate NN to represent the mean of diffusivity and another NN to learn all modes of the KL expansion. For the inverse problem, in addition to stochastic diffusivity and concentration fields, we also aim to obtain the (unknown) deterministic values of transport velocity and reaction constants. The available data correspond to 7spatial points for the diffusivity and 20 space–time points for the solution, both sampled 2000 times. We obtain good accuracy for the deterministic parameters of the order of 1–2% and excellent accuracy for the mean and variance of the stochastic fields, better than three digits of accuracy. In the second part, we consider the previous stochastic inverse problem, and we use Bayesian optimisation to find five hyper-parameters of sPINN, namely the width, depth and learning rate of two NNs for learning the modes. Here, we obtain much deeper and wider optimal NNs compared to the manual tuning, leading to even better accuracy, i.e., errors less than 1% for the deterministic values, and about an order of magnitude less for the stochastic fields.

97 MATHEMATICS AND COMPUTING↗

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↗