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DOE OSTI2024

Optical pulse-induced ultrafast antiferrodistortive transition in SrTiO 3

The ultrafast dynamics of the antiferrodistortive phase transition in perovskite SrTiO 3 is monitored via time-domain Brillouin scattering. Using femtosecond optical pulses, we initiate a thermally driven tetragonal-to-cubic structural transformation and detect the crystal phase through changes in the frequency of Brillouin oscillations (BO) induced by propagating acoustic phonons. Coupling the measured BO frequency with a spatiotemporal heat diffusion model, we demonstrate that, for a sample kept in the tetragonal phase, deposition of sufficient thermal energy induces a rapid transformation of the heat-affected region to the cubic phase. The initial phase change is followed by a slower reverse cubic-to-tetragonal phase transformation occurring on a timescale of hundreds of picoseconds. Here, we attribute this ultrafast phase transformation in the perovskite to a structural resemblance between atomic displacements of the R-point soft optic mode of the cubic phase and the tetragonal phase, both characterized by anti-phase rotation of oxygen octahedra. The structural relaxation time exhibits a strong temperature dependence consistent with the prediction of the equation of motion describing collective oxygen octahedra rotation based on the energy landscape of the phenomenological Landau theory of phase transitions. Evidence of such a fast structural transition in perovskites can open up new avenues in information processing and energy storage sectors.

36 MATERIALS SCIENCE↗

NASA NTRS2021

Ecosystem age-class dynamics and distribution in the LPJ-wsl v2.0 global ecosystem model

Forest ecosystem processes follow classic responses with age, peaking production around canopy closure and declining thereafter. Although age dynamics might be more dominant in certain regions over others, demographic effects on net primary production (NPP) and heterotrophic respiration (Rh) are bound to exist. Yet, explicit representation of ecosystem demography is notably absent in many global ecosystem models. This is concerning because the global community relies on these models to regularly update our collective understanding of the global carbon cycle. This paper aims to present the technical developments of a computationally efficient approach for representing age-class dynamics within a global ecosystem model, the Lund–Potsdam–Jena – Wald, Schnee, Landschaft version 2.0 (LPJ-wsl v2.0) dynamic global vegetation model and to determine if explicit representation of demography influenced ecosystem stocks and fluxes at global scales or at the level of a grid cell. The modeled age classes are initially created by simulated fire and prescribed wood harvesting or abandonment of managed land, otherwise aging naturally until an additional disturbance is simulated or prescribed. In this paper, we show that the age module can capture classic demographic patterns in stem density and tree height compared to inventory data, and that simulated patterns of ecosystem function follow classic responses with age. We also present two scientific applications of the model to assess the modeled age-class distribution over time and to determine the demographic effect on ecosystem fluxes relative to climate. Simulations show that, between 1860 and 2016, zonal age distribution on Earth was driven predominately by fire, causing a 45- to 60-year difference in ages between older boreal (50–90° N) and younger tropical (23° S–23° N) ecosystems. Between simulation years 1860 and 2016, land-use change and land management were responsible for a decrease in zonal age by −6 years in boreal and by −21 years in both temperate (23–50° N) and tropical latitudes, with the anthropogenic effect on zonal age distribution increasing over time. A statistical model helped to reduce LPJ-wsl v2.0 complexity by predicting per-grid-cell annual NPP and Rh fluxes by three terms: precipitation, temperature, and age class; at global scales, R2 was between 0.95 and 0.98. As determined by the statistical model, the demographic effect on ecosystem function was often less than 0.10 kg C/sq. myr but as high as 0.60 kg C/sq. myr where the effect was greatest. In the eastern forests of North America, the simulated demographic effect was of similar magnitude, or greater than, the effects of climate; simulated demographic effects were similarly important in large regions of every vegetated continent. Simulated spatial datasets are provided for global ecosystem ages and the estimated coefficients for effects of precipitation, temperature and demography on ecosystem function. The discussion focuses on our finding of an increasing role of demography in the global carbon cycle, the effect of demography on relaxation times (resilience) following a disturbance event and its implications at global scales, and a finding of a 40 Pg C increase in biomass turnover when including age dynamics at global scales. Whereas time is the only mechanism that increases ecosystem age, any additional disturbance not explicitly modeled will decrease age. The LPJ-wsl v2.0 age module represents another step forward towards understanding the role of demography in global ecosystems.

LPJ-wsl↗

DOE OSTI2021

Ultrafast all-optical diffraction switching using semiconductor metasurfaces

Ultrafast all-optical switching using Mie resonant metasurfaces requires both on-demand tunability of the wavefront of the light and ultrafast time response. However, devising a switching mechanism that has a high contrast between its “on” and “off” states without compromising speed is challenging. Here, we report the design of a tunable Mie resonant metasurface that achieves this behavior. Our approach utilizes a diffractive array of semiconductor resonators that support both dipolar and quadrupolar Mie resonances. By balancing the strengths of the dipole and quadrupole resonances, we can suppress radiation into the first diffraction order, thus creating a clearly delineated “off”-state at the operating wavelength. Then, we use optical injection of free- carriers to spectrally shift the multipoles and rebalance the multipole strengths, thereby enabling radiation into the diffraction order—all on an ultrafast timescale. We demonstrate ultrafast off-to-on switching with I on /I off ≈ 5 modulation of the diffracted intensity and ultrafast on-to-off switching with Ion/Ioff ≈ 9 modulation. Furthermore, both switches exhibit a fast τ tr ≈ 2.7 ps relaxation time at 215 μJ cm -2 pump fluence. Further, we show that for higher fluences, the temporal response of the metasurface is governed by thermo-optic effects. This combination of multipole engineering with lattice diffraction opens design pathways for tunable metasurface-based integrated devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1995

Noninvasive analysis of human neck muscle function

STUDY DESIGN. Muscle use evoked by exercise was determined by quantifying shifts in signal relaxation times of T2-weighted magnetic resonance images. Images were collected at rest and after exercise at each of two intensities (moderate and intense) for each of four head movements: 1) extension, 2) flexion, 3) rotation, and 4) lateral flexion. OBJECTIVE. This study examined the intensity and pattern of neck muscle use evoked by various movements of the head. The results will help elucidate the pathophysiology, and thus methods for treating disorders of the cervical musculoskeletal system. SUMMARY OF BACKGROUND DATA. Exercise-induced contrast shifts in T2 has been shown to indicate muscle use during the activity. The noninvasive nature of magnetic resonance imaging appears to make it an ideal approach for studying the function of the complex neuromuscular system of the neck. METHODS. The extent of T2 increase was examined to gauge how intensely nine different neck muscles or muscle pairs were used in seven subjects. The absolute and relative cross-sectional area of muscle showing a shift in signal relaxation was assessed to infer the pattern of use among and within individual neck muscles or muscle pairs. RESULTS. Signal relaxation increased with exercise intensity for each head movement. The absolute and relative cross-sectional area of muscle showing a shift in signal relaxation also increased with exercise load. Neck muscles or muscle pairs extensively used to perform each head movement were: extension--semispinalis capitis and cervicis and splenius capitis; flexion--sternocleidomastoid and longus capitis and colli; rotation--splenius capitis, levator scapulae, scalenus, semispinalis capitis ipsilateral to the rotation, and sternocleidomastoid contralateral; and lateral flexion--sternocleidomastoid CONCLUSION. The results of this study, in part, agree with the purported functions of neck muscles derived from anatomic location. This also was true for the few selected muscles that have been examined in human electromyographic studies. Neck muscle function and morphology can be studied at a detailed level using exercise-induced shifts in magnetic resonance images.

NASA Program Space Physiology and Countermeasures↗

DOE OSTI2020

Single-ion magnetism in the extended solid-state: insights from X-ray absorption and emission spectroscopy

Large single-ion magnetic anisotropy is observed in lithium nitride doped with iron. The iron sites are two-coordinate, putting iron doped lithium nitride amongst a growing number of two coordinate transition metal single-ion magnets (SIMs). Uniquely, the relaxation times to magnetisation reversal are over two orders of magnitude longer in iron doped lithium nitride than other 3d-metal SIMs, and comparable with high-performance lanthanide-based SIMs. To understand the origin of these enhanced magnetic properties a detailed characterisation of electronic structure is presented. Access to dopant electronic structure calls for atomic specific techniques, hence a combination of detailed single-crystal X-ray absorption and emission spectroscopies are applied. Together K-edge, L 2,3 -edge and Kβ X-ray spectroscopies probe local geometry and electronic structure, identifying iron doped lithium nitride to be a prototype, solid-state SIM, clean of stoichiometric vacancies where Fe lattice sites are geometrically equivalent. Extended X-ray absorption fine structure and angular dependent single-crystal X-ray absorption near edge spectroscopy measurements determine Fe I dopant ions to be linearly coordinated, occupying a D 6h symmetry pocket. The dopant engages in strong 3dπ-bonding, resulting in an exceptionally short Fe–N bond length (1.873(7) Å) and rigorous linearity. It is proposed that this structure protects dopant sites from Renner–Teller vibronic coupling and pseudo Jahn–Teller distortions, enhancing magnetic properties with respect to molecular-based linear complexes. The Fe ligand field is quantified by L 2,3 -edge XAS from which the energy reduction of 3d z 2 due to strong 4s mixing is deduced. Quantification of magnetic anisotropy barriers in low concentration dopant sites is inhibited by many established methods, including far-infrared and neutron scattering. We deduce variable temperature L 3 -edge XAS can be applied to quantify the J = 7/2 magnetic anisotropy barrier, 34.80 meV (~280 cm –1 ), that corresponds with Orbach relaxation via the first excited, M J = ±5/2 doublet. The results demonstrate that dopant sites within solid-state host lattices could offer a viable alternative to rare-earth bulk magnets and high-performance SIMs, where the host matrix can be tailored to impose high symmetry and control lattice induced relaxation effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Dendrite Suppression by a Polymer Coating: A Coarse‐Grained Molecular Study

Abstract A major hurdle to the successful deployment of high‐energy‐density lithium metal based batteries is dendrite growth during battery cycling, which raises safety and cycle life concerns. Coating the Li metal anode with a soft polymer layer has been previously shown to be effective in suppressing dendrite growth, leading to uniform lithium deposition even at high current densities. A 3D coarse‐grained molecular model to study the mechanism of dendrite suppression is presented. It is found that the most effective coatings delay or even prevent dendrites from penetrating the polymer layer during deposition. The optimal deposition can be achieved by jointly tuning the polymer stiffness and relaxation time. Higher polymer dielectric permittivity and coating thickness are also effective, but the deposition rate and, therefore, the charging current density is reduced. These findings provide the basis for rational design of soft polymer coatings for stable lithium deposition.

Kong, Xian↗

DOE OSTI2020

Microengineering Pressure Sensor Active Layers for Improved Performance

Abstract Pressure sensors play an integral role in a wide range of applications, such as soft robotics and health monitoring. In order to meet this demand, many groups microengineer the active layer—the layer that deforms under pressure and dictates changes in the output signal—of capacitive, resistive/piezoresistive, piezoelectric, and triboelectric pressure sensors in order to improve sensor performance. Geometric microengineering of the active layer has been shown to improve performance parameters such as sensitivity, dynamic range, limit of detection, and response and relaxation times. There are a wide range of implemented designs, including microdomes, micropyramids, lines or microridges, papillae, microspheres, micropores, and microcylinders, each offering different advantages for a particular application. It is important to compare the techniques by which the microengineered active layers are designed and fabricated as they may provide additional insights on compatibility and sensing range limits. To evaluate each fabrication method, it is critical to take into account the active layer uniformity, ease of fabrication, shape and size versatility and tunability, and scalability of both the device and the fabrication process. By better understanding how microengineering techniques and design compares, pressure sensors can be targetedly designed and implemented.

Ruth, Sara Rachel Arussy↗

DOE OSTI2021

Strain Effects on Rashba Spin–Orbit Coupling of 2D Hole Gases in GeSn/Ge Heterostructures

A demonstration of 2D hole gases in GeSn/Ge heterostructures with a mobility as high as 20 000 cm 2 V –1 s –1 is given. Both the Shubnikov–de Haas oscillations and integer quantum Hall effect are observed, indicating high sample quality. The Rashba spin-orbit coupling (SOC) is investigated via magneto-transport. Further, a transition from weak localization to weak anti-localization is observed, which shows the tunability of the SOC strength by gating. The magneto-transport data are fitted to the Hikami–Larkin–Nagaoka formula. The phase-coherence and spin-relaxation times, as well as spin-splitting energy and Rashba coefficient of the k-cubic term, are extracted. Furthermore, the analysis reveals that the effects of strain and confinement potential at a high fraction of Sn suppress the Rashba SOC caused by the GeSn/Ge heterostructures.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Panoramic Mapping of Phonon Transport from Ultrafast Electron Diffraction and Scientific Machine Learning

Abstract One central challenge in understanding phonon thermal transport is a lack of experimental tools to investigate frequency‐resolved phonon transport. Although recent advances in computation lead to frequency‐resolved information, it is hindered by unknown defects in bulk regions and at interfaces. Here, a framework that can uncover microscopic phonon transport information in heterostructures is presented, integrating state‐of‐the‐art ultrafast electron diffraction (UED) with advanced scientific machine learning (SciML). Taking advantage of the dual temporal and reciprocal‐space resolution in UED, and the ability of SciML to solve inverse problems involving coupled Boltzmann transport equations, the frequency‐dependent interfacial transmittance and frequency‐dependent relaxation times of the heterostructure from the diffraction patterns are reliably recovered. The framework is applied to experimental Au/Si UED data, and a transport pattern beyond the diffuse mismatch model is revealed, which further enables a direct reconstruction of real‐space, real‐time, frequency‐resolved phonon dynamics across the interface. The work provides a new pathway to probe interfacial phonon transport mechanisms with unprecedented details.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Optical Response of MoTe 2 and WTe 2 Weyl Semimetals: Distinguishing between Bulk and Surface Contributions

A first-principles investigation of the optical response of the Weyl Semimetals MoTe 2 and WTe 2 is presented. The approach, based on combining two formulations, allows to both separate the intraband and interband parts of the optical conductivity and to distinguish between the bulk and surface contributions to the optical response. It is found that the response is truly anisotropic, with peaks that can be associated with interband transitions involving either bulk or surface states. The role of the relaxation time, and the relation of the calculated results with available experimental measurements, are also discussed. Furthermore, the approach reported is transferable to any system, topologically trivial or non-trivial, thus addressing the long-standing need for comprehensive characterization of the optical response.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Frequency‐Scanning Considerations in Axionlike Dark Matter Spin‐Precession Experiments

Abstract Galactic dark matter may consist of axionlike particles (ALPs) that can be described as an “ultralight bosonic field” oscillating at the ALP Compton frequency. The ALP field can be searched for using nuclear magnetic resonance (NMR), where resonant precession of spins of a polarized sample can be sensitively detected. The ALP mass to which the experiment is sensitive is scanned by sweeping the bias magnetic field. The scanning either results in detection of ALP dark matter or rules out ALP dark matter with sufficiently strong couplings to nuclear spins over the range of ALP masses corresponding to the covered span of Larmor frequencies. In this work, scanning strategies are analyzed with the goal of optimizing the parameter‐space coverage via a proper choice of experimental parameters (e.g., the effective transverse relaxation time).

Zhang, Yuzhe (ORCID:0009000660829066)↗

DOE OSTI2021

Clustering Nuclear Magnetic Resonance: Machine learning assistive rapid two‐dimensional relaxometry mapping

Abstract Low‐field nuclear magnetic resonance (NMR) relaxometry is an attractive approach from point‐of‐care testing medical diagnosis to in situ oil‐gas exploration. One of the problems, however, is the inherently long relaxation time of the (liquid) samples, (and hence low signal‐to‐noise ratio) which causes unnecessarily long repetition time. In this work, a new class of methodology is presented for rapid and accurate object classification using NMR relaxometry with the aid of machine learning. It is demonstrated that the sensitivity and specificity of the classification is substantially improved with higher order of (pseudo)‐dimensionality (e.g., 2D‐ or multi‐dimensional). This new methodology (termed as ‘Clustering NMR’) may be extremely useful for rapid and accurate object classification (in less than a minute) using low‐field NMR.

Peng, Weng Kung↗

DOE OSTI2022

Slip velocity boundary conditions for the lattice Boltzmann modeling of microchannel flows

Abstract Slip flows in ducts are important in numerous engineering applications, most notably in microchannel flows. Compared to the standard no‐slip Dirichlet condition, the case of slip formulates as a Robin‐type condition for the fluid tangential velocity. Such an increase in mathematical complexity is accompanied by a more challenging numerical transcription. The present work concerns with this topic, addressing the modeling of the slip velocity boundary condition in the lattice Boltzmann method (LBM) applied to steady slow viscous flows inside ducts of nontrivial shapes. As novelty, we extend the newly revised local second‐order boundary (LSOB) Dirichlet fluid flow method [ Philos. Trans. R. Soc. A 378, 20190404 (2020)] to implement the slip velocity condition within the two‐relaxation‐time (TRT) framework. The LSOB follows an in‐node philosophy where its operation principle seeks to explicitly reconstruct the unknown boundary populations in the form of a third‐order accurate Chapman–Enskog expansion, where the wall slip condition is built‐in as a normal Taylor‐type condition. The key point of this approach is that the required first‐ and second‐order momentum derivatives, rather than computed through nonlocal finite difference approximations, are locally determined through a simple local linear algebra procedure, whose formulation is particularly aided by the TRT symmetry argument. To express the obtained derivatives, two approaches are considered, called and , which operate with node and wall variables, respectively. These two formulations are developed to prescribe the physical slip condition over plane and curved walls, including the corners. Their consistency and accuracy characteristics are examined against alternative linkwise strategies to impose the wall slip velocity, such as the kinetic‐based diffusive bounce‐back scheme, the central linear interpolation slip scheme, and the multireflection slip scheme. The several slip schemes are tested over different 3D microchannel configurations, with walls not conforming with the LBM uniform mesh. Numerical tests confirm the advanced accuracy characteristics of the proposed LSOB slip boundary scheme, revealing the added challenge of the wall slip modeling, and that parabolic accuracy is a necessary requirement to reach second‐order accuracy within this problem class.

Silva, Goncalo↗

DOE OSTI2023

Effect of isopropanol cosolvent on the rheology and spinnability of aqueous polyacrylic acid solutions

Abstract We investigate the effect of alcohol fraction (isopropanol, IPA) in a binary water‐alcohol solvent mixture on the shear and extensional rheological properties, as well as the role of viscoelasticity on fiber formation of poly(acrylic acid) (PAA) in electrospinning. Comparison of the scaling of both specific viscosities η sp and extensional relaxation times λ E of PAA in water–IPA mixtures, showed stronger scaling compared to salt‐free aqueous polyelectrolyte solutions, except for the η sp in the unentangled regime displaying a polyelectrolyte‐like scaling η sp ~ c 0.5 for all IPA%. Such deviation suggested IPA induces association/aggregation of PAA. However, the trends between η sp and λ E magnitudes as a function of IPA% differ for concentrations compared in the entangled regime. The η sp as well as their elastic moduli exhibit a maximum, whereas λ E increases monotonically with IPA%, suggesting a complex interplay of various interactions are dictating their structure in water‐IPA mixtures, affecting their shear and extensional response differently. Electrospinning experiments showed increasing IPA% reduces the onset of both beaded and uniform fibers. Analysis using dimensionless numbers indicated the enhancement of their elasticity by IPA, and the consequent stabilizing effect on their jets/filaments against break‐up during electrospinning, plays a role in the improvement of their fiber formation.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Elucidating the Role of Hydrogen at c‐In 2 O 3 /a‐In 2 O 3− x Interface

Ab initio molecular dynamics simulations and hybrid functional electronic structure calculations are employed to determine the formation, the structural and electronic properties, and the dynamics of covalent (In—OH) and ionic (In—H—In) hydrogen defects at crystalline-In 2 O 3 /amorphous-In 2 O 3−x interface. This comprehensive computational study considers (i) various interstitial and substitutional hydrogen site locations within the crystalline, amorphous, and interfacial regions; (ii) several oxygen-to-hydrogen ratios; and (iii) possible defect charged states. The results reveal hydrogen's inability to fully passivate the undercoordinated under-shared in atoms in amorphous highly substoichiometric oxide, giving rise to the formation of deep electron traps even in net-charge neutral structures. These trap defects are found to be sensitive to photoexcitation, in contrast to In—OH with H's electronic states located below the valence band and to In—H—In, where H is found to maintain its charge state upon illumination. Nevertheless, H plays a critical role in photoinduced conductivity and its relaxation by promoting In—O coordination transformations at the interfacial region, including deterioration of the crystalline layer. Finally, the results help identify mobile H species and metastable H defect complexes (such as In—H—H—In, In—OH–H—In, and In—OH–O—In) that are responsible for long relaxation times of the conductivity decay.

H defects↗

DOE OSTI2025

Defect Engineering in Large‐Scale CVD‐Grown Hexagonal Boron Nitride: Formation, Spectroscopy, and Spin Relaxation Dynamics

Recently, numerous techniques have been reported for generating optically active defects in exfoliated hexagonal boron nitride (hBN), which hold transformative potential for quantum photonic devices. However, achieving on-demand generation of desirable defect types in scalable hBN films remains a significant challenge. Here, it is demonstrated that formation of negative boron vacancy defects, V B − , in suspended, large-area CVD-grown hBN is strongly dependent on the type of bombarding particles (ions, neutrons, and electrons) and irradiation conditions. In contrast to suspended hBN, defect formation in substrate-supported hBN is more complex due to the uncontrollable generation of secondary particles from the substrate, and the outcome strongly depends on the thickness of the hBN. Different defect types are identified by correlating spectroscopic and optically detected magnetic resonance features, distinguishing boron vacancies (formed by light ions and neutrons and emitting at 800 nm) from other optically active defects emitting at 650 nm assigned to anti-site nitrogen vacancy (N B V N ) and reveal the presence of additional “dark” paramagnetic defects that influence spin-lattice relaxation time (T 1 ) and zero-field splitting parameters, all of which strongly depend on the defect density. These results underscore the potential for precisely engineered defect formation in large-scale CVD-grown hBN, paving the way for the scalable fabrication of quantum photonic devices.

CVD↗

DOE OSTI2020

Prediction of gas hydrate saturation using machine learning and optimal set of well-logs

We report resistivity and acoustic logs are widely used to estimate gas hydrate saturation in various sedimentary systems using one of the two popular methods ((1) acoustic velocity and (2) electrical resistivity), but the limitations of these two methods are often overlooked, which include (i) well-specific calibration of empirical exponents in the electrical resistivity method, (ii) assumption of known pore morphology for gas hydrates in the acoustic velocity method, and (iii) presence of unknown mineralogy and bulk modulus terms in the acoustic velocity method. NMR-density porosity-derived gas hydrate saturation based on the analysis of the transverse magnetization relaxation time (T2) is considered the most precise method, but acquisition of NMR-based logs is limited at relatively recent drilled sites; additionally, its use in conventional oil and gas reservoirs is not that common due to higher cost and operational deployment limitations associated with acquiring NMR well-logs. This study proposes a new method that predicts gas hydrate saturation (S h ) for any well using porosity, bulk density, and compressional wave (P wave) velocity well-logs with neural network (or stochastic gradient descent regression) without any well-specific calibration and/or other aforementioned shortcomings of the existing methods. The method is developed by examining the underlying dependency between S h and different combinations of well-logs, chosen from 6 routine logs, with 12 different machine learning (ML) algorithms. The accuracy of the proposed method in predicting S h is ~ 84%, which is better than the accuracy of seismic and electrical resistivity methods (≤ 75%) per the results reported by three different studies. The robustness of the method in the specific case of permafrost-associated gas hydrates is demonstrated with well-log data from two wells drilled on the Alaska North Slope.

58 GEOSCIENCES↗

DOE OSTI2022

Quantifying the Relationship Between Microstructure and Performance in Gadolinium-Doped Ceria Infiltrated Ni/YSZ Symmetric Cells

Infiltration of mixed ionic/electronic conducting (MIEC) nanocatalysts into the anodes of solid oxide fuel cells (SOFCs) allow the hydrogen oxidation reaction (HOR) to occur at double-phase boundaries (DPBs), rather than being confined only to the triple phase boundaries (TPBs). In this research, we use a combination of cross-sectional scanning electron microscopy (SEM), three-dimensional (3-D) reconstruction, and electrochemical methods to characterize both baseline and gadolinium-doped ceria (GDC)-infiltrated symmetric cells, with the goal of establishing a comparison between the density of electrochemically active sites in uninfiltrated and GDC-infiltrated cells. Here, electrochemical impedance spectroscopy (EIS) and distribution of relaxation times (DRT) analysis showed GDC infiltration decreased the overall polarization of the anode by a factor of 8.78 X, and decreased the resistance associated with the reactions at the TPBs/DPBs by a factor of over 21 X. By quantifying expected GDC deposition morphology in the Ni/YSZ anode it is estimated that reactions occur in the baseline cell up to 84 nm from the active TPB lines.

36 MATERIALS SCIENCE↗