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Catalytic site ensembles: A context to reexamine the Langmuir-Hinshelwood kinetic description

The Langmuir-Hinshelwood formalism describes catalytic reactions of Langmuirian surface species under the assumption that all adsorbates are randomly-distributed – enabling adjacency of surface-bound intermediates to be determined solely by coverages of single-site occupants. We demonstrate herein that this approximation is inappropriate even for simple catalytic reactions (e.g. A + A → A 2 ) and manifestly neglects islanding of slowly-consumed species and partitioning of highly-reactive species inherently engendered by ≥ two-site elementary steps (e.g. A*–A* → A 2(g) + *–*). Rigorous description of kinetically-consequential islanding/partitioning phenomena requires explicit description of the coverage and chemical dynamics of all multi-site ensembles. Higher-order, ensemble-specific rate terms identify the particular microscopic events relevant to each ensemble, and, in doing so, reveal that each elementary step (e.g. A (g) adsorption) describes not one event (e.g. A (g) + * → A*) , but a sum over all ensemble-specific paths (e.g. A (g) + *–* → A*–* and A (g) + A*–* → A*–A*). De-convoluting each elementary step into its constituent multi-site paths proffers kinetic detail otherwise inaccessible – enabling (i) identification of rate- and selectivity-determining site ensembles, (ii) calculation of rates and degrees of rate control of ensemble-specific elementary steps, (iii) incorporation of adsorbate surface diffusion, (iv) incorporation of lateral adsorbate interactions, and (v) quantitative description of catalysis of multi-site-occupying intermediates (e.g. *C n H m * species in hydrocarbon (de-)hydrogenation and C-C bond coupling/cleavage reactions) which we demonstrate here is inaccessible to the Langmuir-Hinshelwood formalism even if adsorbate surface diffusion is infinitely-fast.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurements of Turbulence Attenuation by a Dilute Dispersion of Solid Particles in Homogeneous Isotropic Turbulence

This research addresses turbulent gas flows laden with fine solid particles at sufficiently large mass loading that strong two-way coupling occurs. By two-way coupling we mean that the particle motion is governed largely by the flow, while the particles affect the gas-phase mean flow and the turbulence properties. Our main interest is in understanding how the particles affect the turbulence. Computational techniques have been developed which can accurately predict flows carrying particles that are much smaller than the smallest scales of turbulence. Also, advanced computational techniques and burgeoning computer resources make it feasible to fully resolve very large particles moving through turbulent flows. However, flows with particle diameters of the same order as the Kolmogorov scale of the turbulence are notoriously difficult to predict. Some simple flows show strong turbulence attenuation with reductions in the turbulent kinetic energy by up to a factor of five. On the other hand, some seemingly similar flows show almost no modification. No model has been proposed that allows prediction of when the strong attenuation will occur. Unfortunately, many technological and natural two-phase flows fall into this regime, so there is a strong need for new physical understanding and modeling capability. Our objective is to study the simplest possible turbulent particle-laden flow, namely homogeneous, isotropic turbulence with a uniform dispersion of monodisperse particles. We chose such a simple flow for two reasons. First, the simplicity allows us to probe the interaction in more detail and offers analytical simplicity in interpreting the results. Secondly, this flow can be addressed by numerical simulation, and many research groups are already working on calculating the flow. Our detailed data can help guide some of these efforts. By using microgravity, we can further simplify the flow to the case of no mean velocity for either the turbulence or the particles. In fact the addition of gravity as a variable parameter may help us to better understand the physics of turbulence attenuation. The experiments are conducted in a turbulence chamber capable of producing stationary or decaying isotropic turbulence with nearly zero mean flow and Taylor microscale Reynolds numbers up to nearly 500. The chamber is a 410 mm cubic box with the corners cut off to make it approximately spherical. Synthetic jet turbulence generators are mounted in each of the eight corners of the box. Each generator consists of a loudspeaker forcing a plenum and producing a pulsed jet through a 20 mm diameter orifice. These synthetic jets are directed into ejector tubes pointing towards the chamber center. The ejector tubes increase the jet mass flow and decrease the velocity. The jets then pass through a turbulence grid. Each of the eight loudspeakers is forced with a random phase and frequency. The resulting turbulence is highly Isotropic and matches typical behavior of grid turbulence. Measurements of both phases are acquired using particle image velocimetry (PIV). The gas is seeded with approximately 1 micron diameter seeding particles while the solid phase is typically 150 micron diameter spherical glass particles. A double-pulsed YAG laser and a Kodak ES-1.0 10-bit PIV camera provide the PIV images. Custom software is used to separate the images into individual images containing either gas-phase tracers or large particles. Modern high-resolution PIV algorithms are then used to calculate the velocity field. A large set of image pairs are acquired for each case, then the results are averaged both spatially and over the ensemble of acquired images. The entire apparatus is mounted in two racks which are carried aboard NASA's KC-135 Flying Microgravity Laboratory. The rack containing the turbulence chamber, the laser head, and the camera floats freely in the airplane cabin (constrained by competent NASA personnel) to minimize g-jitter.

Eaton, John↗

ESR Dipole Power Supply Current Ripple and Noise Specifications

This note presents key findings for the ESR main magnet dipole power supplies (PS), where we find the current ripple specification to be close to or beyond the state-of-the-art. These specifications originate from beam-beam considerations, with the requirement to limit the ripple-induced hadron emittance growth to below 10%/hour. Beam dynamics that drive this PS ripple specification arise from the beam motions at the Interaction Point (IP). The frequency of the motions can be separated into "low", compared to the betatron frequency, and "high", i.e. around the betatron frequency and harmonics. In terms of the driving frequency, "low" implies ƒ<<ƒ 0 v x,y and "fast" means ƒ≈{ƒ 0 v x,y , ƒ 0 (1- v x,y , etc.}, where ƒ 0 =1/ T 0 =78.2 kHz is the revolution frequency, and v x,y are the fractional parts of the betatron tunes. Frequencies higher than ƒ 0 /2 will be folded back due to the particles sampling the field once per turn. To provide flexibility for future lattice adjustments and working point variations, we do not consider the tunes as fixed. Instead, we assume a certain margin and allow them to potentially fall within the range of 0.1< v x,y <0.5. In other words, the high-frequency region spans approximately from 8kHz to 40 kHz. Consequently,, we definte the dipole PS ripple in two distinct frequency ranges: the low-frequency range of [1-8000] Hz and the high-frequency range of [8-40] kHz. For the physics effects we analyzed in this note, there is no distinction between the ripple (which can be approximately reproduced in the frequency domain) and the random noise if both have some power within the frequency bandwidth of interest. Therefore, while we will use the term "ripple" for short, it should always be understood that we are referring to "ripple plus noise." Except for the lower end of the low-frequency range, the impact of the rippling PS current on the beam will be considerably reduced due to the eddy currents induced in the walls of the vacuum chamber. We will account for this effect in the PS ripple specifications to follow. The remaining sections of this note are structure as follows: Section II outlines the beam-beam physics requirements for the positional stability of the beam at the IP. Section III describes the anticipated shielding effect of the eddy currents induced in the vacuum chamber. Section IV derives the ripple requirement for the low-frequency range by propagating the closed orbit ripple resulting from the rippling dipoles to the IP (relevant lattice simulation results are summarized in the Appendix). In Section V, we present the analytical criterion for the ripple in the high-frequency range by considering resonant oscillations of the electron beam around a stable closed orbit near the betatron frequency. Finally, Section VI provides a summary of our findings and discusses related work.

43 PARTICLE ACCELERATORS↗

Quantification of uncertainties in thermoelectric properties of materials from a first-principles prediction method: An approach based on Gaussian process regression

We present the electron-phonon averaged via Gaussian process regression (EPA-GPR) method, in which the electron-phonon coupling matrix is represented as a function of two energies and is in turn modeled as a Gaussian process. The EPA-GPR method can be used as an efficient method to estimate thermoelectric properties of materials for fast-screening applications, comparable to the original electron-phonon averaged (EPA) method and the electron-phonon averaged via moving-least-squares (EPA-MLS) method. The EPA-GPR method does not require specification of any open parameter, unlike the other EPA-related methods, since all the hyperparameters in the model can be unambiguously estimated within the type II maximum likelihood (ML-II) approximation. Thus, the EPA-GPR method is a parameter-free estimation method. Additionally, the concept of Gaussian processes in the EPA-GPR method allows us to quantify the uncertainty in estimated properties of thermoelectric materials. One can randomly realize the electron-phonon coupling coefficients from the identified Gaussian process, and those realized samples can be further analyzed in the solution process of the semiclassical Boltzmann transport equation for charge carriers. The results of the semiclassical Boltzmann transport equation provide the statistical properties of the thermoelectric properties of interest. The means, standard deviations, histograms, and confidence intervals of the Seebeck coefficient, the electrical conductivity, and the power factor can be constructed and analyzed. Furthermore the proposed EPA-GPR method is applied to a p-type half-Heusler compound, i.e., HfCoSb, as a case example, the results of which clearly present the advantages of the method.

30 DIRECT ENERGY CONVERSION↗

Surface Reconstruction in Hydrated Amphiphilic Block Copolymer Thin Films Probed by Fluid Cell Atomic Force Microscopy

In many thin film materials, nuanced interplays of interfacial energies control the surface morphology and rearrangement. This work evaluates polymer−solvent interactions and solvent-driven surface reconstructions via ex situ and in situ fluid cell Atomic Force Microscopy (fc-AFM) analysis of amphiphilic block copolymer (BCP) thin films upon exposure to deionized (DI) water. We examine the differences in surface morphology, whole-film swelling, and force response in thin films of polystyrene-block-poly(ethylene oxide) (PS-b-PEO) and polystyrene- block-poly[(allyl glycidyl ether)-co-(ethylene oxide)] (PS-b- P[AGE-co-EO]) processed into standing-up cylinder morphologies perpendicular to a silicon substrate (⊥C). Using Amplitude Modulation AFM (AM-AFM) and Amplitude-Phase Distance (APD) force spectroscopy, this work probes the mechanoresponsive nature of the dynamic surface layers of these films, unveiling surface layer stratification and surface chain rearrangement via minimal tip−sample stimulation. To help rationalize the observed reconfigurations, the energetic driving forces were estimated using the harmonic mean approximations of interfacial energies. Given the nonionizable nature of the minority P(AGE-co-EO) block and the energetic driving forces for chain mobility, this work shows how the elimination of unfavorable PS−water interfaces drives chain rearrangement and coverage of the PS surface by chains of the hydrophilic block. This work highlights considerations for increasing the heterogeneity and complexity of BCP thin films via random blocks and how those changes to local interfacial energies may drive larger scale film morphology reconstructions, with broader implications for tuning interface hydrophilicity.

Copolymers↗

Deployment of neural-network-based neutron microscopic cross sections in the Griffin reactor physics application

The capability to utilize neural networks to predict macroscopic and microscopic cross section parametric spaces has been developed for the Griffin reactor physics application. The LibTorch interface enables Griffin's MOOSE-based materials to interact with LibTorch-trained models, allowing for the evaluation of complex macroscopic or microscopic cross section spaces, which are then used to evaluate the neutronic properties of the Griffin finite element model. This study benchmarks traditional ISOXML-formatted tabulation libraries against neural network-based models for 279 nuclides on 20,160 grid points for zero-dimensional and two-dimensional reactor models. Benchmark metrics include the fundamental mode eigenvalue, fission and absorption rates, and various temperature coefficients of reactivity (isothermal, fuel, and moderator). From the perspective of storage space, the complete set of LibTorch models uses 11 MB on disk, compared to the 10 GB for the ISOXML multigroup library that covers the same grid space. For the two-dimensional performance case considered in Griffin, the Torch model uses 97% less RAM than the reference ISOXML dataset while runtime increases by a factor of 3 when using the LibTorch model compared to the ISOXML dataset with multi-linear interpolation. The LibTorch model consistently yields errors within 0.01% for most analyzed quantities except for the temperature coefficients of reactivity where the maximum discrepancies are up to 0.3 $\frac{pcm}{K}$. Due to the neural network attempting to best predict quantities with no regard for a positive or negative bias for any given quantity, predictions may experience random fluctuations, resulting in both positive and negative errors. Future work will entail both depletion and coupled transient analysis to determine the predictive capabilities of Griffin with neural network-based cross sections.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Sub-pilot-scale Production of High-Value Products from U.S. Coals

Investigators from the University of Utah, University of Wyoming and Marshall University pursued a program to study the conversion of raw coal to high-value products of carbon fiber and silicon carbide. Team members also developed an initial framework for a data portal that can incorporate laboratory data on coal processing and product quality, and also work with tools for machine learning for data analysis, data visualization and economic assessment. Experimental R&D efforts focused on the conversion of raw coal to coal tar and other byproducts, and the resulting tar intermediates were upgraded to form anisotropic and isotropic pitch materials. These pitch materials were produced from coal using both thermal (pyrolysis) and chemical (mild solvolysis liquefaction) decomposition of raw coal. Four different coals were studied: Utah bituminous coal (Sufco), Wyoming PRB coal (Black Thunder), Illinois bituminous coal (Illinois #6), and West Virginia bituminous coal (Flying Eagle). Both metallurgical-grade coking coals and lower-grade steam coals were investigated, and controlled secondary gas-phase reactions were used during a two-stage pyrolysis process to induce cracking and condensation reactions among the pyrolytic tar species. This approach successfully improved the performance of the lower grade coals for yielding pitch materials, with properties more consistent with a commercial-grade pitch that had previously demonstrated success for quality carbon fiber production. The use of waste plastic materials was also studied, to help improve physical and chemical characteristics of the intermediate tars and final pitch product; in particular, for lowering the pitch softening point to an acceptable level for melt spinning carbon fiber. Mild solvolysis liquefaction was also used as a method for producing pitch for carbon fiber production. As expected, significantly higher pitch yields were obtained using this approach, and waste plastic materials were also successfully used to reduce pitch softening point to an acceptable level. The plastic materials were also utilized to create a solvent for the mild solvolysis process, and this plastic-derived solvent was shown to provide results consistent with more expensive commercial chemical solvents, and could thus avoid the need for costly recovery and recycle of a liquefaction solvent. Additional experimental R&D focused on the production of silicon carbide (β-SiC) from the residual char byproduct from pitch production, and also on the production of carbon fiber from the anisotropic pitch. SiC was successfully synthesized using a mixture of residual char and sandstone at a ratio of 1:1. Reaction temperature and residence time were optimized and yielded a product purity of 81%. For carbon fiber production, the most successful pitch samples were obtained from the mild solvolysis liquefaction approach, combined with the use of a plastic (HDPE)-derived solvent. Fiber properties improved over time as laboratory fiber production methodologies improved, and final yields of carbon fiber were obtained with a diameter of 12.14 ± 1.10 um, Modulus of 173.73 ± 15.25 GPa, and Tensile Strength of 1.04 ± 0.10 GPa. A proof-of-concept Modern Community Research Data Portal (MCRDP) was developed and deployed for coal and coal-derived pitch characterization, with the full support of (i) remote web-based access, (ii) distributed analysis, (iii) interactive visualization and exploration, (iv) shared and long-term data access, (v) advanced query capabilities and (vi) real-time collaboration. The Coal to Products Data Portal “coaltoproducts.org” provides researchers with space to store and share data within a project, tools for analyzing and understanding data for scientific investigation, and the ability to publish data to the broader community for reproducibility. The portal leverages the Material Commons 2.0 (MC) platform developed by the Center for PRedictive Integrated Structural Materials Science (PRISMS) of the University of Michigan, to achieve long-term longevity of data collections and, more importantly, collaborative science. A number of data visualization tools were also assessed and implemented for interrogating the experimental and modeling data. The machine learning portion of this project analyzed datasets from two different coal conversion processes performed on a diverse set of coal samples from both the coal pyrolysis experiments and the solvent liquefaction experiments. The work was initiated by exploring standard regression models on the pyrolysis data, aiming to understand the impact of sample characteristics and processing conditions on key product metrics. Over the course of the project, the focus expanded to include a variety of machine learning tools, delving into both supervised and unsupervised learning methods. Models tested on the pyrolysis data included linear, ridge, lasso, elastic-net, Gaussian process, random forest regression, and AutoSklearn, and the approach was continually refined to enhance predictive accuracy and model interpretability. Similar techniques were applied to the liquefaction data with an additional focus on feature engineering. Along with mesophase content, additional outputs of interest were the pitch yield, softening point, and QI content. Insights derived from these analyses are crucial in determining the factors influencing the quality and yield of coal-derived products. As the work progressed, the research evolved from foundational model comparisons to analyses of random forests, decision paths, and feature importance scores. A thorough market analysis was performed to examine the prospects of coal-based carbon fibers. The best opportunities for coal come from its lower and more stable price relative to petroleum, particularly for subbituminous coals, which is the primary advantage that a coal refinery may have over a petroleum refinery. Before a commercial CTP production facility can be modeled, however, several things need to be understood regarding the nature of the would-be coal refinery. These include the technology to be deployed, the size of facility, the volume(s) of co-product(s), and the waste and emissions profile of the plant. The volume of co-products and waste may be substantial and will require separate market analysis to ensure viability. In the near-term, the importance of coal tar pitch, in the form of carbon pitch, to the aluminum and steel industries is likely to overshadow the alternative use of this material as an input for carbon fiber. The importance of steel and aluminum in building materials, and the need for carbon materials in their manufacturing, will ensure that demand for these products remains for the long run. In addition, carbon fiber may also be the best substitute for steel and aluminum well into the future. While society will eventually be able to shift production of much of its electricity needs to renewables, it will not be able to shift away from fossil fuels for production of high-strength construction and vehicular materials. Demand for carbon fiber is expected to increase quickly, but the volume of carbon fiber and the amount of coal that would be needed to produce even a sizeable share of this market may still be relatively small compared to current coal production. Thus, other coal-based products like graphene, graphite, carbon foams, resins, and carbon-based building products will play important roles in sustaining coal production as coal-fired power generation continues to decline.

01 COAL, LIGNITE, AND PEAT↗

Simulating sticky particles: A Monte Carlo method to sample a stratification

Many problems in materials science and biology involve particles interacting with strong, short-ranged bonds that can break and form on experimental timescales. Treating such bonds as constraints can significantly speed up sampling their equilibrium distribution, and there are several methods to sample probability distributions subject to fixed constraints. We introduce a Monte Carlo method to handle the case when constraints can break and form. More generally, the method samples a probability distribution on a stratification: a collection of manifolds of different dimensions, where the lower-dimensional manifolds lie on the boundaries of the higher-dimensional manifolds. We show several applications of the method in polymer physics, self-assembly of colloids, and volume calculation in high dimensions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interplay between disorder and collective coherent response: Superradiance and spectral motional narrowing in the time domain

The interplay between static and dynamic disorder and collective optical response in molecular ensembles is an important characteristic of nanoplasmonic and nanophotonic molecular systems. Here we investigate the cooperative superradiant response of a molecular ensemble of quantum emitters under the influence of environmental disorder, including inhomogeneous broadening (as induced by a static random distribution of the molecular transition frequencies) and motional narrowing (as induced by stochastic modulation of these excitation energies). The effect of inhomogeneous broadening is to destroy the coherence of the collective molecular excitation and suppress superradiant emission. However, fast stochastic modulation of the molecular excitation energy can effectively restore the coherence of the quantum emitters and lead to a recovery of superradiant emission, which is an unexpected manifestation of motional narrowing. For a light-scattering process as induced by an off-resonant incident pulse, stochastic modulation leads to inelastic fluorescence emission at the average excitation energy at long times and suggests that dynamic disorder effects can actually lead to collective excitation of the molecular ensemble.

74 ATOMIC AND MOLECULAR PHYSICS↗

Mars 2020 Perseverance Rover SHERLOC Instrument Isolation System

The NASA Jet Propulsion Laboratory (JPL) successfully landed the Mars 2020 Perseverance Rover at Jezero Crater on the Martian surface. Perseverance’s main mission objective is to cache Martian rock and regolith samples in hermetically sealed tubes to be brought back to Earth by future missions. To achieve this goal the rover is equipped with a 2-meter-long Robotic Arm (RA) which manipulates the Turret to interact with the surface. The Turret is comprised of science instruments and tools that enable surface sampling and science. The backbone of the Turret hardware is the Rotary Percussive Coring Drill. The science instruments, which are directly mounted to the structural housing of this drill, must be able to withstand not only the launch and entry, descent and landing (EDL) loads of the vehicle but also the dynamic percussive environment, induced by the drill throughout surface operations. This paper discusses the technical hardware design, development and testing of a vibration isolation system to protect the Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) Instrument from these dynamic environments. The hardware design aspect of this problem was limited by both size and mass constraints. The Turret is tightly configured and the physical space in which hardware can reside is restricted due to multiple axes of surface interaction points. Another driving requirement is the extreme range of thermal non-operational environment from -135C to +90C. This, in addition to SHERLOC being a heavier instrument than previously integrated on a turret, made the use of isolation systems employed on previous rover missions problematic. The final design incorporates custom wire mesh springs preloaded within titanium hexapod struts equipped with flexure ends. Custom versions of commercially available wire mesh springs were designed and tested. These custom springs differed in dimension, density and stiffness from the off the shelf options. The newly designed springs went through various stages of flight acceptance testing. Detailed physics-based modeling to understand what loads the isolation system would experience was used to define the test conditions for the springs and entire isolation subsystem. The testing program developed around this was extensive to fully characterize the isolation performance over cleanliness levels, temperature and life. Another major aspect of this work was developing a method of replicating the drill’s percussive environment for performance and life testing of Turret mounted hardware. Attaching the instrument to an operating drill for testing was not a viable option. A method of using a Highly Accelerated Life Test (HALT) table was developed and applied across the project as the most representative and tunable option to physically simulate this new environment. This method, along with launch environment random vibration testing, was used to build an entire dynamic qualification and flight hardware test program. The results of the design, modeling, testing and analysis of the SHERLOC Isolation System is described throughout the following paper.

Krafchak, Todd↗

Si content in methacrylamide-containing A- b -(B- r -C) block copolymers and its impact on reactive ion etching properties

Block copolymers (BCPs) of an A-block-(B-random-C) architecture have been explored as materials for nanolithography because the composition and chemistry of the random block enables modification of thermodynamic and wetting properties to meet manufacturing criteria. Here, in this study, A-b-(B-r-C) BCPs created by an amidation reaction of polystyrene-block-poly(pentafluorophenyl methacrylate) (PS-b-PPFMA) with controlled amounts of Si add insight to previous conclusions about the dual contributions of BCP chemistry and reactive ion etch (RIE) gas chemistry on etch properties. We focus on two RIE etch characteristics: organosilicon etch resistance in H 2 /N 2 plasma etching and enhanced removal of non-styrenic structures in an Ar/O 2 etch. Consistent with previous studies, higher amounts of Si result in greater etch resistance under H 2 /N 2 RIE, where at least ∼10 wt. % Si is necessary to exhibit sufficient etch resistance. By contrast, Ar/O 2 etching resulted in etch rates independent of Si content. We observe previously unreported surface roughening aligned with morphological domains during the H 2 /N 2 etch of modified PS-b-PPFMA BCPs. Limited in the amount of allowable Si to attain equal surface energy between blocks, these BCPs are further disqualified in forming a Si-containing mask. However, in an Ar/O 2 etch, the same BCPs exhibit suitable etch contrast and smooth domain structures, forming a uniform PS mask. Ultimately, this study uses the chemical flexibility of these materials to demonstrate the mechanisms of interactions between BCP and etch chemistry that must be considered to design effective materials for pattern transfer applications.

Eom, Christopher J. [University of Chicago, IL (Un↗

Validity and Reliability of Dynamic Visual Acuity (DVA) Measurement During Walking

DVA is primarily subserved by the vestibulo‐ocular reflex mechanism. Individuals with vestibular hypofunction commonly experience highly debilitating illusory movement or blurring of visual images during daily activities possibly, due to impaired DVA. Even without pathologies, gradual age‐related morphological deterioration is evident in all components of the vestibular system. We examined the construct validity to detect age‐related differences and test‐retest reliability of DVA measurements performed during walking. METHODS: Healthy adults were recruited into 3 groups: 1. young (20‐39years, n=18), 2. middle‐aged (40‐59years, n=14), and 3. older adults (60‐80years, n=15). Randomly selected seven participants from each group (n=21) participated in retesting. Participants were excluded if they had a history of vestibular or neuromuscular pathologies, dizziness/vertigo or >1 falls in the past year. Older persons with MMSE scores <29/30 were excluded to minimize cognitive errors. Participants' age, height, weight and normal walking speed were recorded. The binocular DVA was measured while walking on a treadmill at 0.8 m/s, 1.0 m/s and 1.2 m/s speeds. The walking speeds chosen represent a range of slow to moderate walking speeds for adult life span in participants who have no current mobility problems. The monitor that displayed Landolt 'C' optotypes was placed at 50 cm from the eyes for nearDVA (primary compensation by otolith organs) and at 3.0 m for farDVA (primary compensation by semicircular canals). A mixed factor ANOVA (age group x speed) was performed separately for the Near and FarDVA for detecting group differences. Intraclass correlation coefficients (ICCs) were calculated for each condition to determine test‐retest reliability. RESULTS: The three age groups were not different in their height, weight and normal walking speed (p>0.05). The post hoc analyses for DVA measurements demonstrated that each group was significantly different from the other two groups for Near as well as FarDVA (p<0.001‐p=0.031). The effect of speed was significant for both NearDVA (p=0.012) and FarDVA (p=0.014), however, there was no age group x speed interaction (FarDVA p=0.607, NearDVA p=0.343). The ICCs for Near and FarDVA ranged between 0.85‐ 0.88 and 0.71‐0.87, respectively. CONCLUSIONS: Differences in DVA between the three age groups were detected by using both Near and FarDVA protocols irrespective of the walking speed. Therefore, age group‐specific reference values should be used for detecting malfunction. Further, consistency in walking speed is critical for comparing between studies. NearDVA at all walking speeds and FarDVA at the speed of 1.2 m/s demonstrated excellent testretest reliability. FarDVA at 0.8 m/s and 1.0 m/s demonstrated good test‐retest reliability (ICCs 0.71 and 0.77, respectively).

Deshpande, Nandini↗

A modified electrolyte non-random two-liquid model with analytical expression for excess enthalpy: Application to the MEA-H 2 O-CO 2 system

We report accurate thermodynamic properties of electrolyte systems are critical for the design and operation of many chemical processes. A comprehensive description of the thermodynamic framework for multi-electrolyte mixed solvent systems is presented, where the parameter structure of the symmetric electrolyte-Non-Random Two Liquid (e-NRTL) model is reformulated and a thermodynamically consistent and analytically derived formulation for the excess enthalpy is developed from the e-NRTL model. The refined parameter structure of the e-NRTL model avoids numerical singularities of the analytical formulation for the excess enthalpy in the absence of ionic species and extends the derived excess enthalpy formulation to non-electrolyte systems. The thermodynamic framework is demonstrated for the MEA-H 2 O-CO 2 case study using experimental data on thermodynamic quantities for the binary MEA-H 2 O system and the ternary MEA-H 2 O-CO 2 system. The model is implemented in Pyomo and will be available for release in the Institute for the Design of Advanced Energy Systems (IDAES) computational platform.

Monoethanolamine↗

Interpretable machine learning study of the many-body localization transition in disordered quantum Ising spin chains

We apply support vector machine (SVM) to study the phase transition between many-body localized and thermal phases in a disordered quantum Ising chain in a transverse external field. The many-body eigenstate energy E is bounded by a bandwidth W = E max – E min . The transition takes place on a phase diagram spanned by the energy density ε = 2(E – E min )/W and the disorder strength δJ of the spin interaction uniformly distributed within [ – δJ, δJ], formally parallel to the mobility edge in Anderson localization. In our paper, we use the labeled probability density of eigenstate wave functions belonging to the deeply localized and thermal regimes at two different energy densities (ε's) as the training set, i.e., providing labeled data at four corners of the phase diagram. Then we employ the trained SVM to predict the whole phase diagram. The obtained phase boundary qualitatively agrees with previous work using entanglement entropy to characterize these two phases. We further analyze the decision function of the SVM to interpret its physical meaning and find that it is analogous to the inverse participation ratio in configuration space. Our findings demonstrate the ability of the SVM to capture potential quantities that may characterize the many-body localization phase transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Lattice QCD Calculation of Electroweak Box Contributions to Superallowed Nuclear and Neutron Beta Decays

We present the first lattice QCD calculation of the universal axial γ W -box contribution □ γ W V A to both superallowed nuclear and neutron beta decays. This contribution emerges as a significant component within the theoretical uncertainties surrounding the extraction of | V u d | from superallowed decays. Our calculation is conducted using two domain wall fermion ensembles at the physical pion mass. To construct the nucleon four-point correlation functions, we employ the random sparsening field technique. Furthermore, we incorporate long-distance contributions to the hadronic function using the infinite-volume reconstruction method. Upon performing the continuum extrapolation, we arrive at □ γ W V A = 3.65 ( 7 ) lat ( 1 ) PT × 10 − 3 . Consequently, this yields a slightly higher value of | V u d | = 0.973 86 ( 11 ) exp ( 9 ) RC ( 27 ) NS , reducing the previous 2.1 σ tension with the CKM unitarity to 1.8 σ . Additionally, we calculate the vector γ W -box contribution to the axial charge g A , denoted as □ γ W V V , and explore its potential implications. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Impact of particle loading and phase coupling on gas–solid flow dynamics: A case study of a two-phase, gas–solid flow in an annular pipe

The present study is devoted to a two-phase, gas–solid flow in an annular pipe (hollow cylinder) at an elevated pressure of 15 bars and moderate Reynolds number of circa 6000. The influence of the particle loading, the interaction between the phases, and turbulence dispersion on the flow dynamics is systematically studied by means of computational fluid dynamics simulations, employing the Ansys FLUENT commercial package. The cases with a particle volumetric fraction of 1.2% are referred to as “high particle loading,” and those with 0.13% are denoted as “low particle loading.” The following cases are investigated: (1) pure gas flow; (2) low particle loading two-phase flow with one-way coupling and with turbulence dispersion; (3) low particle loading two-phase flow with two-way coupling but without turbulence dispersion; (4) low particle loading two-phase flow with two-way coupling and with turbulence dispersion; (5) high particle loading two-phase flow with one-way coupling and with turbulence dispersion; (6) high particle loading two-phase flow with two-way coupling but without turbulence dispersion; and (7) high particle loading two-phase flow with two-way coupling and with turbulence dispersion. Additionally, the boundary layer is found to grow without fluctuations of the turbulent kinetic energy (TKE) for cases 1, 2, and 5. For case 4, the TKE fluctuations have been identified, although they appear to be less substantial than those in cases 6 and 7. The authors attribute the semi-chaotic nature of the TKE fluctuations to the particle loading and two-way coupling. In addition, the onset and development of the flow instability have been observed at a random axial distance in cases 4, 6, and 7. Such instability is also attributed to the two-way coupling with turbulence dispersion in the flow. It is concluded that the particle loading, one-way, or two-way coupling between the phases, and the turbulence dispersion models significantly influence the development of the flow dynamics with the same inlet and boundary conditions. Consequently, it is not a trivial question, which result a user should trust. The present computational results inspire to perform verification as well as experimental validation of the simulations, so the simulation results can subsequently be used with confidence for design analysis.

42 ENGINEERING↗

On-Demand Designing of Cathode Internal Surface Architecture for Dramatic Enhancement of SOFC Performance and Durability

This project is aimed to design and modify the internal surfaces of porous composite cathode from currently commercially viable Solid Oxide Fuel Cells (SOFCs), using additive manufacturing process of Atomic Layer Deposition (ALD). The material systems being investigated are commercial composite electrodes complex three-dimensional topographies. In term of the chemistry of the ALD layer applied on the internal surface of the porous cathode, this project has employed commercially relevant electrolyte, electrocatalyst and noble metal materials set. Such materials are fully compatible with the commercial fuel cells, and this project has developed special nanostructure on the surface of the commercial composite cathodes. The formation of the designed nanoarchitecture on the surface of SOFC cathode has been achieved through precise control of ALD parameters and their effect on overall cell performance and resultant electrochemical reaction mechanism of cathodes has been investigated through full cell electrochemical performance testing and nanostructure characterization by transmission electron microscopy (TEM). Under the support of this award, following has been achieved: (1). For cathode materials in solid oxide fuel cells (SOFCs), such as perovskite mixed conductor La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3-x (LSCF), cation surface segregation and consequently losing conductivity and active sites for the oxygen reduction reaction (ORR) are problematic. To mitigate the cation segregation and enhance SOFC durability, further decorating the internal backbone surface using the desired electrocatalysts could be a promoting approach. Commonly, the cation segregation such as Sr is very volatile, so the effective surface decoration is ideally conformal. Nevertheless, the conformal surface coating would inevitably alter the ORR pathways that initially take place on the surface of the backbone. To reveal the impact of the conformal coating on both the catalytic activity and the conductivity of the cathode, the unary electrocatalyst of Pt or CoO x , was applied to the LSCF/SDC composite electrode of inherently functional SOFCs, respectively. Both ALD coating layers evolve strong interaction with the LSCF composite cathode. Upon operations, the Pt coating layer remains conformal on LSCF grain surfaces but turns into discrete particles on SDC grain surfaces. Meanwhile, CoO x conformal coating grows to be the discrete nanograins on both the LSCF and SDC grains. ALD coating of the cathode alone reduces the ohmic resistance up to 28 % for the entire cells. The increased conductivity induced by the ALD coating of Pt or CoO x is ascribed to different mechanisms. For the inherent functional SOFCs, the present study presents a novel and feasible approach to apply a conformal, dense coating layer on the surface of a mixed conductor, simultaneously increasing the conductivity and durability of the SOFC cathode. (2). High resistance of the oxygen electrode still significantly hinders the state-of-the-art Solid Oxide Fuel Cells (SOFCs). In particular, for an oxygen electrode consisting of mixed electronic and ionic conductors, such as perovskite lanthanum strontium cobalt ferrite (LSCF), it deteriorates due to its low chemical stability of the grain surface. Such degradation is often associated with the segregation of cations. To prevent the cation surface segregation and its resultant perovskite phase decomposition, we demonstrate a conformal ultra-thin (7-10 nm) surface heterogeneous coating layer consisting of subjacent discrete Pt nanoparticles capped with a superjacent fully dense conformal CoO x layer. The performance studies indicate the ALD coating reduces the cell series resistance by up to 40 %. The conformal CoO x layer consists of randomly orientated but single-layered nanograins, with high-density intergranular and surface grain boundaries serving as the electrochemical reaction sites and facilitating mass transport. The conformal coating layer appears to have successfully suppressed the Sr outward diffusion and confined the Sr enriched layer to a ~ 2 nm interface perovskite phase between the coating layer and the LSCF grain surface. Moreover, this ultra-thin Sr enriched perovskite layer presumably possesses high oxygen vacancy and high ionic conductivity and further imposes tensile strain to the LSCF grain surfaces. With the combination of a conformal CoO x nanoionics, Sr enriched layer, and its strained interface, the ALD coating induced surface layer is estimated to have a conductivity of ~ 1.27x10 4 S/cm, which is over two orders magnitude of that from LSCF at 750 ºC.

30 DIRECT ENERGY CONVERSION↗

Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights

Rapid expansion of wind energy development across the world has highlighted the need to better understand turbine-caused avian mortality. The risk to golden eagles (Aquila chrysaetos) is of particular concern due to their small population size and conservation status. Golden eagles subsidize their flight in part by soaring in orographic updrafts, which can place them in conflict with wind turbines utilizing the same low-altitude wind resource. Understanding the behavior of soaring raptors in varying atmospheric conditions can therefore be relevant to predicting and mitigating their risk of collision. We present a predictive movement model that simulates individual paths of golden eagles during directional flight (such as migration) that is subsidized by orographic updraft. We modeled eagles in a 50 km by 50 km study area in Wyoming containing three wind power plants with documented golden eagle collisions with turbines. The movement model is applicable to any region where ground elevation is known at turbine scale (50 m) and wind conditions are known at facility scale (3 km). For a given set of atmospheric conditions, the model simulates movements of thousands of orographic soaring eagles to produce a density map quantifying the relative probability of eagle presence. We validated the simulated tracks with GPS telemetry data showing four directional tracks made by golden eagles transiting through the area in 2019 and 2020. For each eagle track, validation was performed using the ratio of the model-simulated eagle presence likelihood with uniform eagle presence and the presence computed using directed random-walk movements. We found that the predictive performance of the model was significantly better (likelihood ratio 1) for low-altitude movements than high-altitude movements that can involve thermal-soaring. We employed the model to produce seasonal presence maps for migrating golden eagles. We found significant turbine-level variations in eagle presence between northerly and southerly migration routes through the study area. Overall, the proposed model offers a generalizable, probabilistic, and predictive tool to assist wind energy developers, ecologists, wildlife managers, and industry consultants in estimating the potential for conflict between soaring birds and wind turbines, thereby reducing the need for site-specific data on golden eagle movements.

17 WIND ENERGY↗