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Microwave Imaging Reflectometry for the study of Edge Harmonic Oscillations on DIII-D [Microwave Imaging Reflectometry (MIR) for the study of Edge Harmonic Oscillations (EHOs) on DIII-D]

Quiescent H-mode (QH) is an ELM free mode of operation in which edge-localized harmonic oscillations (EHOs) are believed to enhance particle transport, thereby stabilizing ELMs and preventing damage to the divertor and plasma facing components. Microwave Imaging Reflectometer (MIR) enabling direct comparison between the measured and simulated 2D images of density fluctuations near the edge can determine the 2D structure of density oscillation which can help to explain the physics behind EHO modes. MIR data sometimes indicates a counter-propagation between higher (n>1) and dominant (n=1) harmonics of coherent EHOs in the steep gradient regions of the pedestal. To preclude diagnostic artifacts, we have performed forward modeling that includes possible optical misalignments to show that offsets between transmitting and receiving antennas do not account for this feature. We have also simulated the non-uniform rotation of the EHO structure, which induces multiple harmonics that are properly characterized in the synthetic diagnostic. Excluding these possible explanations for the data, the counter-propagation observed in MIR data, which is not corroborated by external Mirnov coil array measurements, may be due to subtleties of the eigenmode structure, such as an inversion radius consistent with a magnetic island. Similar effects are observed in analysis of internal ECE-Imaging and BES data. Furthermore, the identification of a non-ideal structure motivates further exploration of nonlinear models of this instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An Open, Cloud-Based Platform for Whole-Building Fault Detection and Diagnostics

Small commercial buildings in the U.S. waste an estimated 300 Trillion BTU (approximately $6 billion in energy costs) annually due to faults, but lack cost-effective automated fault detection and diagnosis (AFDD) tools. NREL and GE Global Research are partnering to develop hybrid AFDD algorithms tailored to the unique needs of small commercial buildings (</=10,000 sq. ft.). The approach combines physics-based energy modeling tools with state-of-the-art machine learning algorithms to enable diagnostics using modeled input data. NREL, in partnership with Purdue University, has adapted DOE's physics-based modeling software EnergyPlus and OpenStudio to simulate common building faults. Cloud-based implementations of these physics-based models were used to generate data for multiple climate zones. The data were then used to train machine learning algorithms, such as those available in GE's Predix platform, to detect and diagnose building faults. Key features of the system including the automated, cloud-implementation of EnergyPlus, genetic algorithms for automated model feature selection, multiclass detection and diagnosis models, and anomaly detection algorithms will be presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

North Atlantic Simulations in Coordinated Ocean-Ice Reference Experiments Phase II (CORE-II). Part I: Mean States

Simulation characteristics from eighteen global ocean-sea-ice coupled models are presented with a focus on the mean Atlantic meridional overturning circulation (AMOC) and other related fields in the North Atlantic. These experiments use inter-annually varying atmospheric forcing data sets for the 60-year period from 1948 to 2007 and are performed as contributions to the second phase of the Coordinated Oceanice Reference Experiments (CORE-II). The protocol for conducting such CORE-II experiments is summarized. Despite using the same atmospheric forcing, the solutions show significant differences. As most models also differ from available observations, biases in the Labrador Sea region in upper-ocean potential temperature and salinity distributions, mixed layer depths, and sea-ice cover are identified as contributors to differences in AMOC. These differences in the solutions do not suggest an obvious grouping of the models based on their ocean model lineage, their vertical coordinate representations, or surface salinity restoring strengths. Thus, the solution differences among the models are attributed primarily to use of different subgrid scale parameterizations and parameter choices as well as to differences in vertical and horizontal grid resolutions in the ocean models. Use of a wide variety of sea-ice models with diverse snow and sea-ice albedo treatments also contributes to these differences. Based on the diagnostics considered, the majority of the models appear suitable for use in studies involving the North Atlantic, but some models require dedicated development effort. atmospheric forcing atmospheric temperatures

ocean model comparisons↗

Interface diagnostics platform for thin-film solid-state batteries

Understanding the impedances of battery materials and their interfaces remains a major challenge, usually addressed by electrochemical impedance spectroscopy (EIS) where frequency-dependent complex impedance of full battery cells is measured and then modeled by a network of connected electrical elements. As conventionally applied, this approach produces ambiguity in that (1) multiple different network configurations may fit the data convincingly and (2) the method offers no direct association of the electrical elements with physical features of the battery. Here we present a new methodology that resolves both sources of ambiguity, enabled by expanding the experimental scope to directly inform the configuration of elements and their parameters in the network model. We demonstrate this methodology using thin film fabrication of solid state battery devices patterned by shadow masked sputter deposition, so that diagnostic devices corresponding to individual interface and material components can be fabricated simultaneously with full cell batteries. EIS models for the diagnostic devices can then be connected to form full cell networks whose topology matches the well-known physical configuration of the battery. When connected in this way, the full network model – made from connecting the diagnostic device EIS models – fits the full cell EIS data. For the case of a thin film solid state battery composed of amorphous silicon anode, lithium phosphorus oxynitride (LiPON) solid electrolyte, and lithium vanadium oxide (Li x V 2 O 5 ) cathode, we show that the approach allows us to identify ionic impedance/conductivity of the cathode/electrolyte as a limiting impedance and the anode/electrolyte interface cycling instability as a primary degradation factor.

25 ENERGY STORAGE↗

Cardiopulmonary Resuscitation in Microgravity: Efficacy in the Swine During Parabolic Flight

INTRODUCTION: The International Space Station will need to be as capable as possible in providing Advanced Cardiac Life Support (ACLS) and cardiopulmonary resuscitation (CPR). Previous studies with manikins in parabolic microgravity (0 G) have shown that delivering CPR in microgravity is difficult. End tidal carbon dioxide (PetCO2) has been previously shown to be an effective non-invasive tool for estimating cardiac output during cardiopulmonary resuscitation. Animal models have shown that this diagnostic adjunct can be used as a predictor of survival when PetCO2 values are maintained above 25% of pre-arrest values. METHODS: Eleven anesthetized Yorkshire swine were flown in microgravity during parabolic flight. Physiologic parameters, including PetCO2, were monitored. Standard ACLS protocols were used to resuscitate these models after chemical induction of cardiac arrest. Chest compressions were administered using conventional body positioning with waist restraint and unconventional vertical-inverted body positioning. RESULTS: PetCO2 values were maintained above 25% of both 1-G and O-G pre-arrest values in the microgravity environment (33% +/- 3 and 41 +/- 3). No significant difference between 1-G CPR and O-G CPR was found in these animal models. Effective CPR was delivered in both body positions although conventional body positioning was found to be quickly fatiguing as compared with the vertical-inverted. CONCLUSIONS: Cardiopulmonary resuscitation can be effectively administered in microgravity (0 G). Validation of this model has demonstrated that PetCO2 levels were maintained above a level previously reported to be predictive of survival. The unconventional vertical-inverted position provided effective CPR and was less fatiguing as compared with the conventional body position with waist restraints.

Weightlessness↗

Lyman-alpha rocket spectra and models of the quiet and active solar chromosphere based on partial redistribution diagnostics

Absolute intensity Lyman-alpha profiles with a spatial resolution of 0.8 min and a spectral resolution of 50 mA were obtained for network and cell regions in the quiet sun, umbral and penumbral areas of a sunspot, two plages, and a quiescent prominence of the limb. Weak limb brightening shown by the Lyman-alpha cores and wings are consistent with predictions derived from partial redistribution line transfer calculations. Through use of a comoving two-level partial redistribution code which conserves mass flux, unequal red and blue Lyman-alpha peak intensities may be interpreted as flow velocities near 20,000 K. Outflows in the plages and downflows in the network are also noted. A model of a mean quiet sun chromosphere consistent with the Lyman-alpha integrated intensity, the Lyman continuum slope, and the millimeter continuum is presented.

Basri, G. S.↗

The Role of Deep Convection and Large-scale Circulation in Driving Model Spread in Low Cloud Feedback and Equilibrium Climate Sensitivity

This project aims to advance the understanding of the processes that drive the large uncertainties in climate change projections, use observations to constrain model physics and reduce the inter-model spread in equilibrium climate sensitivity (ECS). There are three major goals: 1) Characterize the representation of the physical pathways that link deep convection, large-scale circulation and low cloud feedback in CMIP6 model simulations and determine the relative contribution of each pathway to the CMIP6 model spread in low cloud feedback and ECS; 2) Use process-oriented diagnostics and multiple observations to evaluate CMIP6 model performance in capturing the observed cloud-circulation relation and deep convection characteristics including convective transition statistics and the bulk properties of mesoscale convective systems (MCSs). Error decomposition in CMIP6 models will be performed. 3) Conduct E3SM short-range hindcasts following the DOE Cloud-Associated Parameterizations Testbed (CAPT) protocol to pinpoint specific model parameters/processes that are crucial to the representation of deep convection, circulation, clouds and the pathways that connect them. We will modify convective parameters in E3SM and analyze the perturbed physics experiments (PPEs) to isolate model parameters that are critical to the uncertainty of ECS.

54 ENVIRONMENTAL SCIENCES↗

Contributions of Satellite Observations to Understanding Climate Change

One of the challenges facing atmospheric scientists is to interpret trends in multi-decadal data records. Although data records from satellite instruments are not as long as some ground-based records, global coverage and resolved vertical profiles provide unique information for identifying signatures of climate change. For example, the Halogen Occultation Experiment (HALOE) on the Upper Atmosphere Research Satellite provided profiles of O3, H2O, HC1, HF, CH4 from October 1991 until November 2005. There are also multi-annual ground based measurements of the column HCl. Middle latitude ground-based measurements show a seasonal cycle, and the HALOE profiles show that this is driven by the seasonal change in the composition and mass of the region between the tropopause and 380K surface (the lowermost stratosphere). Understanding the processes that produce the seasonal cycle makes it possible to interpret a future change in the seasonal cycle as a marker of a change in the stratospheric residual circulation. Satellite observations have also provided key information for improving the physical basis of models used to predict future composition and climate circulation. An example is the "tape recorder" signature in tropical stratospheric water vapor, i.e., the slow ascent of high and low water vapor anomalies roughly corresponding to the tropopause temperature at the time air entered the stratosphere. This signature has become a key diagnostic of performance for climate models.

Douglass, Anne R.↗

Forward Modeling of Gamma Reaction History Signatures From Anticipated Deuterium-Tritium Filled MagLIF Implosions on Sandia’s Z-Machine

Nuclear reaction history measurements provide a bang time and burn width of Inertial Confinement Fusion (ICF) implosions and are essential for understanding implosion performance to constrain ICF capsule design. When fusion fuel contains Deuterium (D) and Tritium (T) gas, reaction history is informed by measuring the 16.75 MeV gamma rays generated from the D(T,γ) 5 He reaction. Such DT based reaction history measurements have not been made on the Magnetized Laser Inertial Fusion (MagLIF) platform on Sandia’s Z-Machine due to the lack of Tritium being used. The recent development of ICF implosions with tritiated fuel will open the possibility of measuring the gamma reaction history on the Z-Machine. A forward model of the Gamma Reaction History diagnostic on Z (GRH-Z) has been developed using the MCNP6.3 (Monte-Carlo N-Particle) radiation transport code. The model included the Z-Machine geometry of interest to characterize the impact of neutron induced gamma rays on the DT reaction history measurements. In addition, the impulse response functions of the GRH-Z diagnostic to understand the temporal response of the detector, and the minimum yields required to make a reaction history measurement were calculated. This approach also predicted that with T 2 gas doping of MagLIF implosions a reaction history may be made for high performance shots >8e12-2.4e13 depending on the chosen threshold for the detector, with a maximum signal to background ratio of 25%. It was found that for long duration ICF implosions that additional collimation will be needed to prevent the neutron induced gamma rays from modifying the shape of the measured DT reaction history curve.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis

Hybrid Diagnosis Engine (HyDE) is a general framework for stochastic and hybrid model-based diagnosis that offers flexibility to the diagnosis application designer. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. Several alternative algorithms are available for the various steps in diagnostic reasoning. This approach is extensible, with support for the addition of new modeling paradigms as well as diagnostic reasoning algorithms for existing or new modeling paradigms. HyDE is a general framework for stochastic hybrid model-based diagnosis of discrete faults; that is, spontaneous changes in operating modes of components. HyDE combines ideas from consistency-based and stochastic approaches to model- based diagnosis using discrete and continuous models to create a flexible and extensible architecture for stochastic and hybrid diagnosis. HyDE supports the use of multiple paradigms and is extensible to support new paradigms. HyDE generates candidate diagnoses and checks them for consistency with the observations. It uses hybrid models built by the users and sensor data from the system to deduce the state of the system over time, including changes in state indicative of faults. At each time step when observations are available, HyDE checks each existing candidate for continued consistency with the new observations. If the candidate is consistent, it continues to remain in the candidate set. If it is not consistent, then the information about the inconsistency is used to generate successor candidates while discarding the candidate that was inconsistent. The models used by HyDE are similar to simulation models. They describe the expected behavior of the system under nominal and fault conditions. The model can be constructed in modular and hierarchical fashion by building component/subsystem models (which may themselves contain component/ subsystem models) and linking them through shared variables/parameters. The component model is expressed as operating modes of the component and conditions for transitions between these various modes. Faults are modeled as transitions whose conditions for transitions are unknown (and have to be inferred through the reasoning process). Finally, the behavior of the components is expressed as a set of variables/ parameters and relations governing the interaction between the variables. The hybrid nature of the systems being modeled is captured by a combination of the above transitional model and behavioral model. Stochasticity is captured as probabilities associated with transitions (indicating the likelihood of that transition being taken), as well as noise on the sensed variables.

Narasimhan, Sriram↗

Observation of D 2 molecule line emission after massive D 2 injection into runaway electron plateaus in DIII-D

Molecular deuterium line emission is observed in both the visible and ultraviolet (UV) wavelength ranges after massive (> 100 Torr-L) injection of D 2 gas into post-disruption runaway electron (RE) dominated plasmas in the DIII-D tokamak. D 2 UV line emission is found to be the dominant source of radiated power, surpassing D Lyα. Interpretive modeling with a collisional-radiative model (CRM) indicates that D 2 radiation surpasses D radiation because Lyα is strongly trapped, while D 2 UV lines are mostly untrapped. The CRM also indicates that the D 2 line emission is completely dominated by RE impact (rather than thermal electron impact), so the D 2 line emission can serve as a good diagnostic for the spatial localization of REs. Analysis of D 2 visible lines indicates that the D 2 molecules in the plasma are thermally equilibrated with the background plasma, with vibrational, rotational, and kinetic temperatures all near 0.3 eV. D 2 spectroscopy therefore serves as a convenient diagnostic of background plasma temperature. As a result, measurement of D 2 radiated power also appears to serve as a useful diagnostic for constraining neutral transport modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles

Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected to a low-dimensional subspace for accelerating convergence of the solution algorithm and consequently reducing the number of transient simulations. The proposed approach was demonstrated via two case studies associated with different VCC applications where 10 parameters were calibrated in each case using laboratory measurements. The reduced-dimension BO framework only required 1 / 8 th of the iterations associated with a standard BO method that deals with high-dimensional calibration parameters for converged solutions and yielded comparable accuracy. Furthermore, both calibrated models revealed significant accuracy improvements compared to uncalibrated models.

Ma, Jiacheng↗

A Representation Fusion Framework for Decoupling Diagnostic Information in Multimodal Learning

Modern medicine increasingly relies on multimodal data, ranging from clinical notes to imaging and genomics, to guide diagnosis and treatment. However, integrating these heterogeneous data sources in a principled and interpretable manner remains a major challenge. We present MODES (Multi-mOdal Disentangled Embedding Space), a representation fusion framework that explicitly separates shared and modality-specific factors of variation, offering a structured latent space for multimodal information that improves both prediction and interpretability. By leveraging pre-trained unimodal foundation models, MODES mitigates the dependency on extensive paired datasets, crucial in data-scarce clinical settings. We introduce a masking strategy that optimizes representation dimensionality by eliminating low-information dimensions, to achieve compact, information-rich representations. Our framework demonstrates superior performance in predicting diagnoses and phenotypes compared to unimodal and conventional fusion models. MODES also enables robust diagnostic inference in missing data scenarios, offering an opportunity toward interpretable and efficient multimodal diagnostics in personalized healthcare.

60 APPLIED LIFE SCIENCES↗

Detachment scalings derived from 1D scrape-off-layer simulations

Fusion power plants will require detachment to mitigate sputtering and keep divertor heat fluxes at tolerable levels. Controlling detachment on these devices may require the use of real-time scrape-off-layer modeling to complement the limited set of available diagnostics. In this work, we use the configurable Hermes-3 edge modeling framework to perform time-dependent, fixed-fraction-impurity 1D detachment simulations. Although currently far from real-time, these simulations are used to investigate time-dependent effects and the minimum physics set required for control-relevant modeling. We show that these simulations reproduce the expected rollover of the target ion flux — a typical characteristic of detachment onset. We also perform scans of the input heat flux and impurity concentration and show that the steady-state results closely match the scalings predicted by the 0D time-independent Lengyel–Goedheer model. This allows us to indirectly compare to SOLPS simulations, which find a similar scaling but a lower value for the impurity concentration required for detachment for given upstream conditions. We use this result to suggest a series of improvements for the Hermes simulations, and finally show simulations demonstrating the impact of time-dependence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Studying biomineralization pathways in a 3D culture model of breast cancer microcalcifications

Microcalcifications serve as diagnostic markers for breast cancer, yet their formation pathway(s) and role in cancer progression are debated due in part to a lack of relevant 3D culture models that allow studying the extent of cellular regulation over mineralization. Previous studies have suggested processes ranging from dystrophic mineralization associated with cell death to bone-like mineral deposition. In this paper, we evaluated microcalcification formation in 3D multicellular spheroids, generated from non-malignant, pre-cancer, and invasive cell lines from the MCF10A human breast tumor progression series. The spheroids with greater malignancy potential developed necrotic cores, thus recapitulating spatially distinct viable and non-viable areas known to regulate cellular behavior in tumors in vivo. The spatial distribution of the microcalcifications, as well as their compositions, were characterized using nanoCT, electron-microscopy, and X-ray spectroscopy. Apatite microcalcifications were primarily detected within the viable cell regions and their number and size increased with malignancy potential of the spheroids. Levels of alkaline phosphatase decreased with malignancy potential, whereas levels of osteopontin increased. Finally, these findings support a mineralization pathway in which cancer cells induce mineralization in a manner that is linked to their malignancy potential, but that is distinct from physiological osteogenic mineralization.

60 APPLIED LIFE SCIENCES↗

Electromagnetic Analysis of ITER Electron Cyclotron Emission Model

The ITER electron cyclotron emission (ECE) diagnostic system is located at diagnostics shielding module 2 (DSM2), equatorial port 9 (EP9), to measure electron temperature profile and electron temperature fluctuations, and also assess nonthermal electron distributions via the oblique view. Therefore, ECE has both radial and oblique views with two hot sources for calibration and two couples of mirrors for two different optical views. It shall receive that the large electromagnetic (EM) loads up to 100-MN/m3 force density due to the eddy currents on the copper mirrors generated by the short transient plasma disruption. The simplified EM analysis model using magnetic field ( B ) data and flux variations (dB/dt) method based on the worst case of plasma disruption, MD_DW_EXP16MS_CATIII, has been developed to calculate the force and moments for each ECE component and support structure for EP9 DSM2 Bay2 and Bay3. The B and dB/dt methods use the constant B and dB/dt assumed for each local bay space, but the real B and dB/dt are basically varied along the radial direction of each bay. The complex global model with the local ECE components and support structure using Maxwell transient has been developed to do EM analysis to compare the results of the B and dB/dt models. The volumetric EM force density of the whole ECE components and support structure can be used for the subsequent structural analysis. In conclusion, combined with the thermal and nuclear loads and seismic and initial loads, the ECE integration analysis can be finalized for the operation case.

Fang, J. [Princeton Plasma Physics Laboratory (PPP↗

HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017) (and subsequently titled) Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020) (Final Technical Report)

This is the Final Technical Report for the DoE Measurement Innovation (previously Diagnostic Development) grant DE-SC0006077 titled HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017), and subsequently titled Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020). The grant was funded by the Office of Fusion Energy Sciences (FES) for the period 1 May 2011–17 July 2020. Work performed through the grant has resulted in diagnostic innovations and new measurement capabilities that will improve understanding of transport, magnetic equilibrium, and electric fields in magnetically confined plasmas. We have developed novel hardware and advanced techniques to expand beam-based diagnostic capabilities, and extend measurements to new operating regimes. Some have been realized using a Heavy Ion Beam Probe (HIBP) having traditional features, while other applications have joined our innovations with subsets of advantageous HIBP features. This work has established smaller, more economical detection systems and, in doing so, may enable substantial extension of scenarios in which beam-based diagnostics are deployed. Key Measurement Innovations include: Computer Models and Simulations of HIBP Applications-Computer modeling and simulating of HIBP applications is central to predicting interaction of beam particles with plasmas, designing diagnostic systems, and anticipating measurement characteristics. We have extended the capability and improved measurement fidelity of the HIBP diagnostic on the Madison Symmetric Torus (MST) reversed field pinch (RFP); simulated feasibility of HIBP operation in the Helically Symmetric eXperiment (HSX) optimized stellarator; and investigated the plausibility of HIBP measurements in the ASDEX Upgrade tokamak. We have also developed a new technique that uses ion optics to model a finite phase-space beam. It yields more realistic (than traditional method) estimates of sample volume characteristics, which influence measurement resolution and sensitivity. Extension of Diagnostic Capabilities and Measurements on the MST RFP-Capabilities have been extended using the first and only HIBP installation on an RFP. Challenges associated with operation of the diagnostic on MST include the three-dimensional nature of particle trajectories, temporal topology and amplitude changes in the plasma equilibrium, and strong particle and radiative emission from the plasma. We have addressed these challenges through development of detailed and higher precision diagnostic simulations, calibrated subtraction of noise to resolve secondary ion signals, and implementation of hardware that enables higher fidelity measurement of plasma fluctuations. Development of New Hardware and Measurement Techniques - We have advanced beam-based measurement capabilities via development of new detectors and techniques to determine the poloidal magnetic flux ψ in the plasma, and enable placement of detectors close to the plasma and thus allow a smaller and less expensive diagnostic. We have demonstrated measurement of ψ, an ability that was made possible by development of highly effective noise reduction techniques. We also modeled the effect of non-ideal and instrumentation effects by developing a virtual (simulated) diagnostic. Application of beam-based diagnostics on various devices and multiple magnetic configurations (e.g. stellarator, tokamak, and reversed field pinch) enables investigation of critical physics issues and measurements resulting in the broad parameter space data needed to test and validate theory & modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Development of a Simple and Rapid Diagnostic Method for Polymer-Electrolyte Fuel Cells

A simple and fast diagnostic tool has been developed for analyzing polymer-electrolyte fuel-cell degradation. The tool is based on analyzing changes in polarization curves of a cell over its lifetime. The shape of the polarization-change curve and its sensitivity to oxygen concentration are found to be unique for each degradation pathway based on analysis from a detailed 2-D numerical model of the cell. Using the polarization-change curve methodology, the primary mechanism for degradation (kinetic, ohmic, and/or transport related) can be identified. Here, the technique is applied to two sets of data to explain performance changes after two different cells undergo voltage-cycling accelerated stress test, where it is found that changes are kinetic and then ohmic or transport in nature depending on the cell type. The diagnostic tool provides a simple method for rapid determination of primary degradation mechanisms. Finally, areas for more detailed future investigations are also summarized.

08 HYDROGEN↗