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At least 91 records · Page 5

Smart Monitoring and Diagnostic System (SMDS) for Packaged Air Conditioners and Heat Pumps for Small/Medium Commercial Buildings: Preparation for Commercialization: CRADA 478 [Abstract only]

This project will enable Pacific Northwest National Laboratory (PNNL) and industry partner, mCloud Technologies, to work collaboratively to ready the Smart Monitoring and Diagnostic System (SMDS) for commercial deployment and validate its performance under real-world conditions at field sites. This project will specifically focus on 1) implementing the SMDS algorithms in a scalable cloud-based software architecture, 2) designing new, innovative, complimentary commercial services based on the SMDS, 3) enhancing the SMDS energy and cost impact algorithms to reduce uncertainty in estimates, 4) determining the lower limits on SMDS performance degradation detection, 5) validating algorithm performance and default values of adjustable thresholds with existing data from controlled physical testing and from customer packaged air conditioners and heat pumps (commonly referred to as rooftop units or RTUs), 6) field testing to validate the system on multiple customer buildings in diverse environments, and 7) expanding field deployment to a larger set of mCloud’s customer buildings. Project results by validating, enhancing, and quantifying the performance of the SMDS will position mCloud, and potential future licensees, to implement the SMDS in commercial offerings that encourage and enable use of condition-based and predictive maintenance, leading to significant reductions in energy use and greenhouse gas emissions associated with space conditioning by RTUs. Furthermore, these enhancements will increase the value of the SMDS for users and increase the potential market for its use and impacts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Industry Facing PV Degradation Prediction Tool and Database to Enable a 50-Year Life Module

The Photovoltaic (PV) industry constantly aims for lower costs, higher-efficiency cells, and improved module designs. These trends lead to using new materials, designs, and manufacturing processes, resulting in a continually changing technological landscape. These changes can potentially introduce new, unknown degradation mechanisms and failure modes that are difficult to diagnose, analyze, test, and model. This introduces uncertainty into the expected lifetime of PV modules of 25 years. Furthermore, research efforts aim for up to 50 years of service life while keeping performance degradation at a minimum for decades of outdoor weathering - putting additional pressure on improving the accuracy of long-term durability and reliability assessments. Here there is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. Because the core of this type of analysis involves calculations that are complicated but ubiquitous for many degradation processes, an enhanced predictive modeling framework will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this work, we present an online tool that can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. A graphical user interface will aid in the understanding of the results. The prediction tool will be built modular and published as open source, enabling users to expand on the existing framework. We use an integration pipeline approach that allows us to leverage weather data from the National Solar Radiation Database to perform geospatial degradation analysis in the US and worldwide. Our repository will contain various degradation models and material parameters suitable for the reliability and durability assessment of materials and components deployed outdoors. We hope to become a repository that can be used for weathering and degradation analysis for various applications beyond the PV industry.

degradation↗

Operando Acoustic Monitoring of SEI Formation and Long-Term Cycling in NMC/SiGr Composite Pouch Cells

Stable long-term cycling and solid-electrolyte-interphase (SEI) formation are key challenges in the design of Si/graphite composites as Li-ion battery (LIB) anode materials. Typically, these long-term cycling properties are examined in flooded half-cell settings making use of a Li-metal counter electrode and a Si/graphite working electrode. This form factor has the advantage of offering an unlimited supply of Li-ions and electrolyte, thus isolating performance degradation to the passivation of the working electrode. However, half-cell studies are ineffective in revealing performance and degradation mechanisms of the Si/graphite composite in a more commercially realistic full cell setting. This paper outlines an operando acoustic technique that can offer insights on SEI formation and capacity degradation of Si/graphite composites in a full cell setting. Through a combination of electrochemical and chemical analyses, we show that increasing passivation of the silicon particles in the Si/graphite composite anode is correlated with an increase in the acoustic time-of-flight shift. We further show that temporary loss of the acoustic signal during the first cycle is associated with significant gassing of the cell. The operando acoustic technique outlined here is low-cost, simple to setup and has the potential for localized resolution, indicating usefulness in commercial-scale Si/graphite cell quality control and diagnosis.

42 ENGINEERING↗

Performance enhancement and degradation mechanism identification of a single-atom Co–N–C catalyst for proton exchange membrane fuel cells

Development of platinum group metal (PGM)-free catalysts for oxygen reduction reaction (ORR) has been a strategic research topic for proton exchange membrane (PEM) fuel cells. Present state-of-art PGM-free ORR catalysts are Fe, N co-doped carbon (Fe-N-C) catalysts, which unfortunately exhibit instability concerns. Herein, we report a stable atomically dispersed Co, N co-doped carbon (Co-N-C) catalyst with high Co content of 1.0 at% and the active site, i.e., the coordination of Co, is CoN2+2 in nature. The Co-N-C catalyst demonstrated high ORR activity comparable to, and high stability over 3 times better than, that of the Fe-N-C catalyst. It also achieved a high activity of 22 mA cm2 at 0.9 ViR-free and a power density of 0.61 W cm-2 under 1.0 bar H2/O2. Further, we identify two main degradation mechanisms of the PGM-free catalysts: catalyst oxidation by H2O2/radicals and demetalation. The improved stability of Co-N-C relative to Fe-N-C is attributed to less Fenton-reactive nature of Co and significantly enhanced resistance to demetalation of Co-N-C.

Xie, Xiaohong↗

Hydrogen-induced degradation dynamics in silicon heterojunction solar cells via machine learning

Abstract Among silicon-based solar cells, heterojunction cells hold the world efficiency record. However, their market acceptance is hindered by an initial 0.5% per year degradation of their open circuit voltage which doubles the overall cell degradation rate. Here, we study the performance degradation of crystalline-Si/amorphous-Si:H heterojunction stacks. First, we experimentally measure the interface defect density over a year, the primary driver of the degradation. Second, we develop SolDeg, a multiscale, hierarchical simulator to analyze this degradation by combining Machine Learning, Molecular Dynamics, Density Functional Theory, and Nudged Elastic Band methods with analytical modeling. We discover that the chemical potential for mobile hydrogen develops a gradient, forcing the hydrogen to drift from the interface, leaving behind recombination-active defects. We find quantitative correspondence between the calculated and experimentally determined defect generation dynamics. Finally, we propose a reversed Si-density gradient architecture for the amorphous-Si:H layer that promises to reduce the initial open circuit voltage degradation from 0.5% per year to 0.1% per year.

14 SOLAR ENERGY↗

Irradiation Assessment of a Lightweight Industrial Robot - Towards Faster, Safer and Sooner Waste Decommissioning - 20317

Robotic systems have been successfully applied in the nuclear industry for several decades as a safe approach to minimize the exposure dose of human operators. As nuclear waste management and decommissioning gathers pace, there is an emerging interest integrating modern off-the-shelf industrial robots in nuclear robotic systems which make use of complex electronics and software to improve functionality over traditional machines. The use of the industrial robots will significantly increase the pace of development of automated waste management systems at a reduced cost, and although these off-the-shelf robots are proven robust in typical industrial environments, performance in radioactive environments is less clear. This paper investigates the performance degradation of a lightweight industrial robot (KUKA iiwa 7 LBR 800) in a controlled radiation field, aiming to simulate conditions in highly radioactive nuclear waste handling facilities. The degradation of the industrial robot's performance is identified while measuring the air kerma dose-tolerance of sensitive components, via a systematic experimental methodology. The experience from this experiment has demonstrated the significant capabilities of industrial robots, which tolerated a large gamma dose of 164 Gy before a system failure. Future tests are planned, aiming to enable faster, safer and sooner waste management and decommissioning using complex robotic systems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Lithium-ion battery physics and statistics-based state of health model

A pseudo-2d model using COMSOL Multiphysics® software is developed to simulate performance and performance degradation of Li-ion batteries consisting of layered and olivine cathodes with graphite anode when subjected to peak shaving grid service. Multiple degradation pathways are considered, including solid electrolyte interphase (SEI) formation and breakdown at the anode, cathode dissolution and its synergistic effect on SEI formation at the anode. The model is validated by simulating commercial cylindrical cell performance. A global model is developed to simulate performance across all chemistries, along with individual chemistry models using global model parameters as initial values. There is good agreement between these models for various optimization parameters such as SEI equilibrium potential, cathode dissolution exchange current density, solvent diffusivity in the SEI and SEI ionic conductivity. To circumvent time constraints related to the COMSOL model, a 0d global model is developed which fits data well and provides more clarity on differences in cathode dissolution exchange current density. Again, good agreement for various optimization parameters is obtained among the COMSOL global & individual chemistry models and the 0-d model. The lessons learned from the physics-based model is used to develop a top down statistics-based model using current, voltage and anode volumetric change per mole lithium intercalated, along with their interactions as degradation predictors. This model predicts out of sample degradation for multiple grid services and electric vehicle drive cycle with high accuracy and provides the pathway to develop an efficient battery management system combining machine learning and findings from physics-based computationally intensive algorithms.

Crawford, Aladsair J.↗

Mitigating Inter-Job Interference via Process-Level Quality-of-Service

Jobs on most high-performance computing (HPC) systems share the network with other concurrently executing jobs. Network sharing leads to contention that can severely degrade performance. Here we investigate the use of Quality of Service (QoS) mechanisms to reduce the negative impacts of network contention. QoS allows users to manage resource sharing between network flows and to provide bandwidth guarantees to specific flows. Our results show that careful use of QoS reduces the impact of network contention for specific jobs, resulting in up to a 40% performance improvement. In some cases, it completely eliminates the impact of contention. It achieves these improvements with limited negative impact to other jobs; any job that experiences performance loss typically degrades less than 5%, and often much less. Our approach can help ensure that HPC machines maintain high levels of throughput as per-node compute power continues to increase faster than network bandwidth.

97 MATHEMATICS AND COMPUTING↗

A physics-based parametric regression approach for feedwater pump system diagnosis

Here in this paper, we assessed the performance of a model-based approach for fault diagnosis of a nuclear power plant feedwater pump system. Physics-based models were constructed to monitor the performance of the system components. Plant data were used for the calibration of the models and subsequently in the diagnosis of abnormal events. We considered two real-time events representing scenarios of a pump fault and component performance degradation. The two events were correctly diagnosed, and the results demonstrated the high detection sensitivity of the physics-based models. Various sensor fault scenarios were simulated to show the capability of the approach to detect and uniquely identify sensor faults. Results for a scenario in which the plant operated in flexible power mode also showed that the diagnostic approach is insensitive to changes of operating conditions, which is one of the advantages of the model-based approach using physics-based models over purely data-driven approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Combined Cr and S poisoning behaviors of La 1-x Sr x MnO 3±δ and La 1-x Sr x Co 1-y FeyO 3-δ cathodes in solid oxide fuel cells

Although the individual effects of airborne Cr and S contaminants on SOFC cathode performance degradation have been extensively studied, the combined effects of Cr and S contaminants remain largely unexplored. Under the real SOFC operating condition where the Cr and S species coexist, their effects may compete, affecting the poisoning behavior. Here, our investigation reveals that the combined Cr and S poisoning behavior of LSCF remains different from those of individual Cr and S poisonings, while the combined poisoning mechanism of LSM is equivalent to the sum of those of individual Cr and S effects. For LSCF electrode, gaseous Cr species are deposited mainly at the LSCF/GDC interface by electrochemical reduction, rather than forming SrCrO 4 on LSCF surfaces (as in the case of Cr-only poisoning), indicating no reaction between Cr vapors and SrO on the LSCF surface. Thermodynamic analysis demonstrates that the SrO on LSCF surface absorbs SO 2 (g) and thereby loses the Cr-gettering effect, allowing Cr vapors to flow through LSCF and to reach the LSCF/GDC interface where the Cr deposition occurs. Unlike LSCF, LSM electrode shows cumulative effects of Cr and S, as Cr accumulation occurs at the triple-phase boundary and S absorption takes place at localized Sr-rich regions.

36 MATERIALS SCIENCE↗

New Radiation Tolerant LGAD for High Energy Physics

Low Gain Avalanche Detectors (LGADS) have recently been studied for applications in high energy physics. However, radiation hardness remains a problem. Here, we propose new LGAD process flow that allows for the creation of a very steep born profile in the multiapplication region, reducing the fractional acceptor removal and resulting performance degradation.

47 OTHER INSTRUMENTATION↗

A low temperature unitized regenerative fuel cell realizing 60% round trip efficiency and 10 000 cycles of durability for energy storage applications

Unitized regenerative fuel cells (URFC) convert electrical energy to and from chemical bonds in hydrogen. URFCs have the potential to provide economical means for efficient long-term, seasonal, energy storage and on-demand conversion back to electrical energy. We first optimize the catalyst layer for discrete electrolyzer and fuel cell and then configure the URFC. The goal is to identify a cost competitive configuration for URFCs, and demonstrate it in terms of upper limit of round trip efficiencies (RTEs). Two possible configurations of URFCs are compared via experiments and techno-economic analysis (TEA), which emphasize the advantages of the unconventional constant-electrode (CE) URFC over the traditional constant-gas (CG) configuration. We also study the stability via accelerated stress tests (ASTs) and demonstrate steady state operation in a daily cycle for day to night energy shifting. From the investigations, the optimum composition of the URFC anode catalyst layer is 90 at% Ir-black balanced by Pt-black for both CE and CG configurations. At 80 °C and 1 A cm -2 , the optimized CE URFC achieves 57% and 60% RTE with air and O 2 as the reductant gases, respectively. We then evaluated the differences in durability using an AST over 10k charge–discharge cycles; the results reveal that the wider potential window at the anode in CE (0.05–1.55 V) has minimal effect on catalyst layer stability compared to CG (0.55–1.55 V). Furthermore, there was no degradation up to the range of 2k–5k cycles; beyond that the fuel cell (discharge) performance degraded while the electrolyzer (charge) performance was still stable. Finally, the observations here indicate substantial potential to employ URFCs as efficient and cost-effective bidirectional energy-conversion devices within energy storage and utilization systems after appropriate technological and operational optimizations.

25 ENERGY STORAGE↗

Copper Outdiffusion from Copper-Plated Solar Cell Contacts during Damp Heat Exposure

Plated copper (Cu) contacts for silicon (Si) solar cells are an attractive alternative material to conventional screenprinted silver, but there are unresolved questions on the long-term integrity of plated contact structures. Here, in this work, we perform characterization on plated Cu contacts from encapsulated cells that were degraded during extended exposure to damp heat (DH) stress. First, using energy-dispersive X-ray spectroscopy, we find evidence of Cu outdiffusion upward through capping layers made of both tin and silver applied with light-induced plating, resulting in a layer of Cu on the outer contact surface. We hypothesize that if Cu is mobile in the module, it may eventually find some route by which to enter the Si cells where it can degrade performance. Subsequently, in several types of Cu-plated, DH-degraded cells, secondary ion mass spectrometry detects elevated levels of Cu at the Si surface and in the Si cell bulk, which suggests that Cu can indeed migrate from contacts into Si over the course of DH stress.

14 SOLAR ENERGY↗

Failure Modes of Platinized pn+-GaInP Photocathodes for Solar-Driven H2 Evolution

The long-term stability for the hydrogen-evolution reaction (HER) of homojunction pn+-Ga0.52In0.48P photocathodes (band gap = 1.8 eV) with an electrodeposited Pt catalyst (pn+-GaInP/Pt) has been systematically evaluated in both acidic and alkaline electrolytes. Electrode dissolution during chronoamperometry was correlated with changes over time in the current density-potential (J-E) behavior to reveal the underlying failure mechanism. Pristine pn+-GaInP/Pt photocathodes yielded an open-circuit photopotential (Eoc) as positive as >1.0 V vs the potential of the reversible hydrogen electrode (RHE) and a light-limited current density (Jph) of >12 mA cm-2 (1-sun illumination). However, Eoc and Jph gradually degraded at either pH 0 or pH 14. The performance degradation was attributed to three different failure modes: (1) gradual thinning of the n+-emitter layer due to GaInP dissolution in acid; (2) active corrosion of the underlying GaAs substrate at positive potentials causing delamination of the upper GaInP epilayers; and (3) direct GaAs/electrolyte contact compromising the operational stability of the device. This work reveals the importance of both substrate stability and structural integrity of integrated photoelectrodes toward stable solar fuel generation.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,S↗

Investigating performance and variability of NIF ICF experiments with deep learning

The parameter space involved in designing an inertial confinement fusion shot at the National Ignition Facility (NIF) is massively multi-dimensional and the cost of a single shot makes a comprehensive set of sensitivity studies in the laboratory impractical. The use of machine learning to overcome these challenges has gained popularity and has had several successful applications by the scientific community. We extend on these efforts by training a neural network (NN) on information about the experimental design, engineering elements, and drive asymmetry to predict with uncertainty the neutron yield of an experiment. We find the measured and model predicted values are in good agreement, with an R 2 value of 0.91 for a randomly selected test dataset. Almost all the predicted 95% credible intervals contain the corresponding measured value for both training and test datasets. We identify correlations picked up by the NN between the shot design, yield, and variability and use them to motivate shot sensitivity studies. The first shot to exceed the Lawson-like ignition criteria (N210808) was conducted at the NIF and subsequent shots studied the design’s robustness. In a follow-up shot to N210808, our model predicts capsule quality to be the main performance degradation mechanism that prevented the shot from repeating previous performance levels. Shot N221204 was the first shot to exceed a target energy gain of 1. Our model predicts increased yield with reduced coast time for a N221204 study and greater variability for designs with lower peak powers at constant yield. The model’s fast prediction speed and uncertainty prediction are useful for identifying interesting design paths that could warrant further investigation with conventional simulations to search for robust high yield designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding Recoverable vs Unrecoverable Voltage Losses and Long-Term Degradation Mechanisms in Anion Exchange Membrane Fuel Cells

Anion exchange membrane fuel cells (AEMFCs) have recently shown excellent progress in terms of their performance – e.g., achievable power and current density. However, very few AEMFCs have been demonstrated with the ability to operate for a long duration (>1000 h). In addition, it is unknown whether performance losses observed during operation are reversible, irreversible, or a combination of the two. In this study, a high-performance AEMFC operated continuously at 600 mA/cm 2 for 3600 h (150 days) at 80 °C with H 2 /O 2 reacting gases was demonstrated. Throughout testing, the electrochemical properties of the AEMFC were probed to provide information about performance degradation pathways and their degree of reversibility. It was found that a portion of the performance loss that occurs during AEMFC operation was due to suboptimal reaction conditions and can be recovered. At the end of the experiment, the cell was disassembled, and its structure and composition were evaluated at the nanoscale by aberration-corrected scanning transmission electron microscopy and energy-dispersive X-ray spectroscopy. The structure and composition of the electrode were compared to cells at the beginning of their operational life. It was found that the primary mechanism for long-term AEMFC performance loss was catalyst agglomeration. During the operational time, there was no evidence of significant polymer degradation, likely due to the high hydration state of the cell. By documenting the long-term changes in high-performing AEMFCs, this work provides important information for the systematic design of cell components and demonstrates the importance of controlling cell operation, which can aid in the commercialization and widespread deployment of low-cost, long-life AEMFCs.

30 DIRECT ENERGY CONVERSION↗

Exploring the Effectiveness of Carbon Cloth Electrodes for All-Vanadium Redox Flow Batteries

Vanadium redox flow batteries (VRFBs) have shown to be a promising technology for integrating intermittent renewable energy sources into the existing electrical grid. Incorporation of carbon cloth electrodes into VRFB is an area of interest for their enhanced electrochemical performance, however, issues with performance degradation throughout the duration of the experiment persist. This study investigates the performance evolution of carbon cloth electrodes during VRFB cycling to build a hypothesis on possible reasons for the declining performance. Electrochemical impedance spectroscopy and polarization curve measurements are used in conjunction to monitor the electrode degradation and shed light on the effectiveness of carbon cloth electrodes during extended cycling experiments. A detailed investigation into the structure of the carbon cloth electrodes before and after cycling, via several material characterization tests, provides insight needed to determine an explanation for the increasing resistance. The structural integrity and surface morphology of the carbon cloth electrodes are evaluated to compare the electrode before and after cycling, displaying any changes to the electrode due to cycling. Durability of hydrophilicity during RFB cycling is found to be a key feature for future carbon cloth electrode design efforts.

25 ENERGY STORAGE↗