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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23

Thermo-mechanical deterioration and molecular degradation of 3D-printed methacrylate-based polymer in various chemical environments

The advancement of additive manufacturing (AM) has accelerated the development of stereolithographic (SLA) photo-curable resins, particularly methacrylate-based polymers, due to the ability to their high-resolution, robust mechanical properties, and suitability. However, their long-term performance in chemical environments remains poorly understood. This study investigates the extent and mechanisms of degradation on an SLA-printed methacrylate-based polymer subjected to various chemicals, including polar and non-polar solvents, as well as strongly acidic aqueous solutions over a 12-week accelerated aging period. A comprehensive analytical approach incorporating swelling kinetics, surface morphology, tensile and dynamic mechanical analysis (DMA), Fourier-transform infrared (FTIR) spectroscopy, and mass spectrometry (MS) was employed to characterize chemical absorption, structural integrity, and leached products. Results reveal that degradation severity is governed by both the polarity and reactivity of the chemical environment. Notably, exposure to 6 mol L -1 HNO₃ induced the most severe deterioration, with over threefold higher swelling compared to other media, and significant reductions in tensile strength, tensile modulus, and glass transition temperature (T g ). In contrast, specimens aged in non-polar solvents (xylene and dodecane) exhibited negligible chemical interaction and retained mechanical performance. FTIR and MS analyses identified acid-catalyzed hydrolysis of ester groups as prominent degradation pathways in acidic media, while diffusion-controlled plasticization prevailed in polar solvents. Furthermore, this study provides valuable insights into the chemical stability of SLA-printed polymers and develops predictive degradation profiles that are crucial for designing durable polymer systems for advanced industrial use.

36 MATERIALS SCIENCE↗

Transforming E-Waste Into Strategic Resources: Techno-Economic Analysis of Gallium and By-products Recovery from LEDs via Bioleaching

The growing demand for gallium in optoelectronics and renewable energy applications raises concerns about supply security and production sustainability. This study evaluates the techno-economic feasibility of recovering gallium and by-products (copper and nickel) from waste GaN-based LEDs via bioleaching. A process flowsheet encompassing transportation, robotic disassembly, ball milling, bioleaching, solvent extraction/electrowinning, and refining was modeled. Based on mass balance analysis, more than 53 tons of LED waste are required annually to yield 1 kg of gallium alongside substantial copper and nickel co-products. Preliminary techno-economic analysis (TEA) shows an average total cost (ATC) of 6.84 USD/kg metal when costs are allocated by mass-weighted economic value (market price) fraction, corresponding to 6.75 USD/kg for copper, 15.91 USD/kg for nickel, and 470.95 USD/kg for gallium. For gallium, direct operational costs account for more than 70% of the cost. Monte Carlo simulations further quantify cost uncertainties under market price fluctuations. This work represents the first TEA of gallium recovery from GaN-based LEDs and highlights potential pathways for future cost reduction.

36 MATERIALS SCIENCE↗

Determination of the regeneration energy of direct air capture solvents/sorbents using calorimetric methods

Regeneration energy and recyclability are important parameters that dictate the viability of a CO 2 direct air capture (DAC) process. In this study, differential scanning calorimetry (DSC) is used in conjunction with thermogravimetric analysis (TGA) and Fourier Transform Infrared Spectroscopy (FTIR) to evaluate the regeneration energy required for CO 2 -loaded 3 M aqueous potassium sarcosinate (K-SAR) solvent and crystalline methyl-glyoxal-bisiminoguanidine (MGBIG) sorbent. Based on calorimetric measurements, for aqueous K-SAR, the sensible heat amounts to 1.5 GJ/tCO 2 and the enthalpy of desorption is estimated at 3.68 GJ/tCO 2 . The total energy of regeneration will also include the enthalpy of solvent vaporization, which will depend on the thermodynamic conditions and the level of regeneration. For MGBIG, the total regeneration energy required was measured at approximately 7.0 GJ/tCO 2 . Further, FTIR measurements were used to observe CO 2 and H 2 O release during the thermal regeneration process. For K-SAR, CO 2 release is seen to take place at temperatures greater than 80 °C and, for MGBIG, the CO 2 release takes place at temperatures greater than 100 °C. The moderate temperatures required for K-SAR and MGBIG regenerations compared to other DAC solvents/sorbents suggest that low-cost sources of heat, such as geothermal heat, could potentially be used for regeneration to drive down the cost of direct air capture.

42 ENGINEERING↗

Design, Synthesis, and Characterization of Polymer Precursors to Li x PON and Li x SiPON Glasses: Materials That Enable All-Solid-State Batteries (ASBs)

LiPON-like glasses that form lithium dendrite impenetrable interfaces between lithium battery components are enabling materials that may replace liquid electrolytes permitting production of all-solid-state batteries (ASBs). Unfortunately, to date, such materials are introduced only via gas-phase deposition. Furthermore, we demonstrate the design and synthesis of easily scaled, lowtemperature, low-cost, solution-processable inorganic polymers containing LiPON/LiSiPON elements. OPCl 3 and hexachlorophosphazene [Cl 2 P=N] 3 provide starting points for elaboration using MNH 2 (M = Li/Na) or (Me 3 Si)NH followed by reaction with controlled amounts of LiNH 2 to produce oligomers/polymers with molecular weights (MWs) ≈1–2 kDa characterized by multinuclear NMR, gel permeation chromatography (GPC), thermogravimetric analysis (TGA), Fourier-transform infrared (FTIR), X-ray powder diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and matrix-assisted laser desorption/ ionization (MALDI)-time-of-flight (ToF) offering stabilities to 150–200 °C and ceramic yields (800 °C) of 50–60%. 7 Li NMR suggests that precursor-bound Li + dissociates easily, beneficial for electrochemical applications. XPS shows higher N/P ratios (1–3) than via gas-phase methods (<1) correlating N/P ratios, 7 Li shifts, and Li + conductivities. Li 2 SiPHN offers the highest ambient conductivity of 3 × 10 –1 mS cm –1 at 400 °C/2 h/N 2 .

36 MATERIALS SCIENCE↗

Kinetic Study of Polyvinyl Chloride Pyrolysis with Characterization of Dehydrochlorinated PVC

In this paper, we study the kinetics of polyvinyl chloride (PVC) decomposition using a combination of experimental and computational approaches. Here, we develop a simplified kinetic model that contains only two steps: dehydrochlorination of PVC and further decomposition of the PVC residue. The model is consistent with density functional theory (DFT) calculations and experimental data. Dehydrochlorination is an autocatalytic reaction that starts with a tertiary chloride (Cl) and generates hydrogen chloride (HCl) and benzene as the main products. Benzene and HCl formation rates showed similar trends, indicating that HCl likely catalyzes a homolytic carbon-carbon (C-C) bond cleavage, which gives rise to benzene and an aliphatic fragment. We characterized the structure of dehydrochlorinated PVC (PVC residue) by using thermal gravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), and nuclear magnetic resonance spectroscopy (NMR). FTIR and NMR results indicate that the PVC residue contains 20% quaternary carbon content, indicating a high concentration of cross-linked molecules. We predict that the most probable structure in the cross-linked centers of the PVC residue is cyclohexadiene, which is supported by DFT calculations, FTIR, and NMR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Quantitative Examination of Catalyst Component Impacts on Hydrogen Adsorption and Spillover

Hydrogen spillover is a widely recognized but poorly understood surface phenomenon. We coupled volumetric chemisorption with Fourier transform infrared spectroscopy, thermogravimetric analysis, and acid–base titrations to quantify the roles of metal (Pt, Au) and support chemistry (anatase, rutile, P25 titania) on spillover. We show that metal identity has little to no impact on the amount of spillover hydrogen. Spillover pressure dependence is essentially the same on Au/TiO 2 and Pt/TiO 2 , indicating H 2 adsorption is equilibrated across both the metal and support. Conversely, spillover is highly sensitive to support surface chemistry, as rutile TiO 2 stabilizes ∼5× more surface hydrogen than anatase TiO 2 . This change is due to a combination of factors, including the rutile surface’s higher proton affinity, stabilized surface electronic states, and larger surface entropy. This work highlights the utility of Au/MO x catalysts as control materials for spillover, as they enable quantitative evaluation of H 2 adsorption on active metals and spillover onto the support.

Adsorption↗

Chemolithoautotroph distributions across the subsurface of a convergent margin

Subducting oceanic crusts release fluids rich in biologically relevant compounds into the overriding plate, fueling subsurface chemolithoautotrophic ecosystems. To understand the impact of subsurface geochemistry on microbial communities, we collected fluid and sediments from 14 natural springs across a ~200 km transect across the Costa Rican convergent margin and performed shotgun metagenomics. The resulting 404 metagenome-assembled genomes (MAGs) cluster into geologically distinct regions based on MAG abundance patterns: outer forearc-only (25% of total relative abundance), forearc/arc-only (38% of total relative abundance), and delocalized (37% of total relative abundance) clusters. In the outer forearc, Thermodesulfovibrionia, Candidatus Bipolaricaulia, and Firmicutes have hydrogenotrophic sulfate reduction and Wood-Ljungdahl (WL) carbon fixation pathways. In the forearc/arc, Anaerolineae, Ca. Bipolaricaulia, and Thermodesulfovibrionia have sulfur oxidation, nitrogen cycling, microaerophilic respiration, and WL, while Aquificae have aerobic sulfur oxidation and reverse tricarboxylic acid carbon fixation pathway. Transformation-based canonical correspondence analysis shows that MAG distribution corresponds to concentrations of aluminum, iron, nickel, dissolved inorganic carbon, and phosphate. While delocalized MAGs appear surface-derived, the subsurface chemolithoautotrophic, metabolic, and taxonomic landscape varies by the availability of minerals/metals and volcanically derived inorganic carbon. Furthermore, the WL pathway persists across all samples, suggesting that this versatile, energy-efficient carbon fixation pathway helps shape convergent margin subsurface ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Windowed Fourier transform and cross-correlation algorithms for molecular tagging velocimetry

In this study, simulated and experimental molecular tagging velocimetry (MTV) images have been analyzed with a technique commonly used to process grid images on surfaces, the windowed Fourier transform with local spectrum analysis (WFT-LSA). A systematic synthetic image study of the modulation transfer function (MTF) and error tendencies of the WFT-LSA was performed and compared with a PIV-style cross-correlation algorithm to see if advanced strategies such as iterative image deformation can improve analysis of gridded images with high noise levels. Testing of single-pass algorithms showed that in typical MTV images, the WFT-LSA yields significantly lower bias errors than cross-correlation (CC) at displacements greater than 1 pixel but slightly higher random error at all displacements and image conditions. Analysis of the MTF shows that CC provided better resolution of spatial fluctuations than the WFT-LSA in many combinations of grid size and interrogation window. Tests of image deformation algorithms showed that the gap in performance between CC and WFT-LSA is maintained even as both methods improve. Additionally, WFT-LSA and CC methods are applied to real MTV experiments in high-speed gas jet flows. A preliminary analysis of phosphorescence lifetime provided by acetone vapor excited at 266 nm is used for assessing the required gas speeds for making MTV application feasible. The application of WFT-LSA to real MTV images demonstrates the ability of the algorithm to handle further real-world effects that could not be considered in the synthetic image analysis, like reduced signal-to-noise ratio and non-uniform intensity of the tagging grid across the image introduced by the actual laser beam energy distribution. With experimental images, CC is more accurate with shear flows but less robust to high noise levels than WFT-LSA, as predicted by the synthetic image analysis.

42 ENGINEERING↗

Discovery and adaptation of microbes that degrade oxidized low-density polyethylene films

There is a growing interest in developing a methodology for effectively cleaving carbon–carbon (C–C) bonds in polymer backbones through bioconversion processes that utilize microorganisms and their enzymes. This upsurge of interest is driven by the goal of achieving a circular economy. Polyolefin post-consumer plastics are a substantial source of carbon, but the recycling potential is severely limited. Upcycling routes are needed for converting polyolefin post-consumer plastics into value-added products while concurrently mitigating adverse environmental effects. These materials contain carbon-based chemicals that can, in principle, serve as the feedstock for microbial metabolism. Some microbes have been reported to grow on polyolefin plastics, but the rate of biodegradation is insufficient for industrial processes. In this study, low-density polyethylene (LDPE) films were subjected to two mild ozone-based oxidation treatments, which facilitated biodegradation. The degree of oxidation was determined by Fourier transform infrared spectroscopy via analysis of the carbonyl index (1,710/1,460 cm −1 ), which ranged from 0.3 to 2.0, and also via analysis of the carboxylic acid content. Following oxidation of the films, studies were conducted to investigate the ability of a panel of polyvinyl alcohol-degrading microbes to degrade the oxidized films. A defined minimal medium was used to cultivate and assess microbial growth on the oxidized films. Following 45 days of cultivation, the most effective strains were further cultivated up to three additional generations on the oxidized film substrates to improve their ability to degrade the oxidized LDPE films. After these enrichments, we identified a strain from the third generation of Pseudomonas sp. Rh926 that exhibited significant cell growth and reduced the oxidized LDPE film mass by 25% in 30 days, demonstrating an enhanced capacity for degrading the oxidized LDPE films.

Adaptation↗

Transformer Health Monitoring via Synchrophasors

Traditional transformer protection schemes such as differential protection operate once the transformer is in a critical state. Proactive means of transformer health evaluation such as Sweep Frequency Response Analysis, can only be performed periodically with the transformer out-of-service. This work presents a framework where the health and structural integrity of transformers is monitored via synchrophasors in real-time. Synchrophasors and subspace estimation techniques are used to build reduced-order models which are then analyzed across multiple domains. A diagnostics algorithm is developed and tested via Matlab simulations. Test results are promising, opening up new prospects in transformer protection research.

cyber-physical security↗

Planar Transformer With Asymmetric Integrated Leakage Inductance Using Horizontal Air Gap

This article presents a novel planar-based transformer winding and core structure with controllable leakage inductance generation for integrated magnetics applications. As a result of limitations in integrated magnetics from the literature, a new approach is proposed utilizing semi-interleaved windings and controllable leakage via a leakage flux core leg featuring a horizontal air gap. Here, the proposed transformer design is analyzed via detailed reluctance modeling to determine closed-form equations for the magnetizing and asymmetrically distributed leakage inductances. Next, a genetic-algorithm-based multiobjective design optimization problem is developed, seeking to minimize the core and winding losses of the proposed transformer subject to a set of parametric and geometric constraints in a dc-ac dual-active-bridge topology for microinverter applications. The optimization was extended to include other integrated magnetic structures from the literature, where it is determined that the proposed transformer is superior from the perspectives of efficiency, footprint area, and parasitic capacitance. Based on the results of the optimization analysis, two designs with theoretical transformer California Energy Commission (CEC) efficiency drops (i.e., CEC efficiency reduction specifically due to the transformer loss mechanisms) of 1.19% and 0.83% were fabricated and evaluated for electrical and thermal performance in the proposed 40 V, 400 W microinverter.

42 ENGINEERING↗

Voltage Calculations in Secondary Distribution Networks via Physics-Inspired Neural Network Using Smart Meter Data

The increasing penetration of distributed energy resources (DERs) leads to voltage issues across distribution networks, necessitating voltage calculations by utilities. Electric model-free voltage calculation offers an enticing solution. However, most researches mainly focus on primary distribution networks ignoring secondary distribution networks and commonly overlook extreme voltage case calculations, which require the model’s extrapolation abilities. Here, in addressing the gaps, this paper presents a customized physics-inspired neural network (PINN) model, the structure of which is inspired by the derived coupled power flow model of primary-secondary distribution networks. To ensure precision and rapid convergence, a crafted training framework for the PINN model is proposed. The PINN’s “structure-mimetic” design enables superior extrapolation for unseen scenarios and enhances physical information awareness. We demonstrate this through two applications: hosting capacity analysis and customer-transformer connectivity. The effectiveness and advantages of the proposed PINN model are validated on two public testing systems and one utility distribution feeder model.

Distribution network↗

Reimagining Disassembly Interfaces With Visualization: Combining Instruction Tracing and Control Flow With DisViz

In applications where efficiency is critical, developers may examine their compiled binaries, seeking to understand how the compiler transformed their source code and what performance implications that transformation may have. This analysis is challenging due to the vast number of disassembled binary instructions and the many-to-many mappings between them and the source code. These problems are exacerbated as source code size increases, giving the compiler more freedom to map and disperse binary instructions across the disassembly space. Interfaces for disassembly typically display instructions as an unstructured listing or sacrifice the order of execution. Here, we design a new visual interface for disassembly code that combines execution order with control flow structure, enabling analysts to both trace through code and identify familiar aspects of the computation. Central to our approach is a novel layout of instructions grouped into basic blocks that displays a looping structure in an intuitive way. We add to this disassembly representation a unique block-based mini-map that leverages our layout and shows context across thousands of disassembly instructions. Finally, we embed our disassembly visualization in a web-based tool, DisViz, which adds dynamic linking with source code across the entire application. DizViz was developed in collaboration with program analysis experts following design study methodology and was validated through evaluation sessions with ten participants from four institutions. Participants successfully completed the evaluation tasks, hypothesized about compiler optimizations, and noted the utility of our new disassembly view. Our evaluation suggests that our new integrated view helps application developers in understanding and navigating disassembly code.

Computer science↗

Three-dimensional super line-localization in low signal-to-noise microscope images via prior-apprised unsupervised learning (PAUL)

Biological processes such as processive enzyme turnover and intracellular cargo tracking involve the dynamic motion of a small "article" along a curvilinear biopolymer track. To understand these processes that occur across multiple length and time scales, one must acquire both the trajectory of the particle and the position of the track along which it moves, possibly by combining high-resolution single-particle tracking with conventional microscopy. Yet, usually there is a significant resolution mismatch between these modalities: while the tracked particle is localized with a precision of 10 nm, the image of the surroundings is limited by optical difraction, with 200 nm lateral and 500 nm axial resolutions. Compared to the particle's trajectory, the surrounding curvilinear structure appears as a blurred and noisy image. This disparity in the spatial resolutions of the particle trajectory and the surrounding curvilinear structure image makes data reconstruction, as well as interpretation, particularly challenging. Analysis is further complicated when the curvilinear structures are oriented arbitrarily in 3D space. Here, we present a prior-apprised unsupervised learning (PAUL) approach to extract information from 3D images where the underlying features resemble a curved line such as a filament or microtubule. This three-stage framework starts with a Hessian-based feature enhancement, which is followed by feature registration, where local line segments are detected on repetitively sampled subimage tiles. In the final stage, statistical learning, segments are clustered based on their geometric relationships. Principal curves are then approximated from each segment group via statistical tools including principal component analysis, bootstrap and kernel transformation. This procedure is characterized on simulated images, where sub-voxel medium deviations from true curves have been achieved. The 3D PAUL approach has also been implemented for successful line localization in experimental 3D images of gold nanowires obtained using a multifocal microscope. Lastly, this work not only bridges the resolution gap between two microscopy modalities, but also allows us to conduct 3D super line-localization imaging experiments, without using super-resolution techniques.

42 ENGINEERING↗

Biochar-compost-based controlled-release nitrogen fertilizer intended for an active microbial community

Nitrogen (N) fertilizers in agriculture suffer losses by volatilization of N to the air, surface runoff and leaching into the soil, resulting in low N use efficiency (NUE) (< 50%) and raising severe environmental pollutions. Controlled- release nitrogen fertilizers (CRNFs) can control the release of N nutrients to NUE in crop production. Different methods were used to develop new CRNFs. However, different CRNF technologies are still underdeveloped due to inadequate controlling on N releasing time and/or unsustainable diffusion. The study on the influences of CRNF processing parameters on microbial conditions are lacking when the CRNFs composed of various bio-ingredients such as biochar, composts, and biowaste. The complexity of processing methods, material biodegradability, and other physical properties make current CRNFs of questionable value in agricultural production. This research aims to develop a novel biochar-compost-based controlled-release urea fertilizer (BCRUF) to preserve microbial properties carried by the compost. The BCRUF was synthesized by pelletizing the 50:50 (dry, wt/wt) mixture of biochar and compost. BCRUF was loaded with urea and then spray-coated with polylactic acid (PLA). The releasing time of two types of BCRUFs, coated and uncoated with PLA, for 80% of N release in water was up to 6 h at three different temperatures (4, 23, and 40 °C), compared to conventional urea fertilizer and commercial environmentally smart N (ESN) fertilizer. The releasing time of coated BCRUF for 80% N release in soil was up to 192 h (8 days). Fourier-transform infrared spectroscopy (FTIR) analysis revealed that no new functional groups were found in the release solution, indicating no new chemical hazards generated. The differential scanning calorimetry (DSC) tests also verified that its thermal stability could be up to 160 °C. The microbe populations in the BCRUF pellets were reduced after the pelleting and drying processes in BCRUF fabrication, but a few bacteria can endure in the air-drying process. BCRUF pellets soaked in water for 4 days retained some bacteria. The BCRUF showed very promising characteristics to improve NUE and sustainability in agricultural production.

58 GEOSCIENCES↗

Combinatorial Evaluation of Physical Feature Engineering, Classical Machine Learning, and Deep Learning Models for Synchrophasor Data at Scale

A major objective of the project was to train and evaluate the effectiveness of multiple event and anomaly detection, identification and classification deep temporal learning models for processing of real-time phasor measurement unit (PMU) data streams. A vast dataset, consisting of two years of phasor measurements from all three U.S. Interconnections, was curated and released by the Department of Energy (DOE) through Pacific Northwest National Laboratory (PNNL). The dataset also included an event log that provided event times and types (e.g. generator trips, line trips, planned service events, transformer operations, etc.). Our analysis of this dataset addressed six (6) of the eleven (11) research priorities identified in Funding Opportunity Announcement (FOA) DE-FOA-0001861 “Big Data Analysis of Synchrophasor Data” (FOA 1861). Rather than being limited to pre-determined specific algorithms, this project relied on the uniquely structured, highly performant underlying time series database capabilities of the PredictiveGrid platform to assess the vast dataset utilizing a wide variety of algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Universality of Collective Density Fluctuations in Liquids at and away from Equilibrium – An Integrated Neutron Scattering, Theoretical, and Computational Study (Final Technical Report)

Liquids, ubiquitous on earth, are prototypical disordered condensed matter. As the mediate phase between non-structured gases and ordered solids, liquids p ossess intriguing complexities that are absent on either extreme counter phase, especially when they are driven away from equilibrium. Despite decades of studies, the physics of liquids still keeps surprising us and challenges our understanding of condensed matter, emergent phenomena, and complex systems. Among the many interesting properties, the nature of collective dynamics in liquids remains elusive because of both the presence of strong interactions and the absence of translational invariance. This project studied the universal features of collective density fluctuations (or collective modes), which include both phonon-like excitations and collective relaxations, in the Q-dependent generalized hydrodynamic regime in liquids and liquid-like matter both at and away from equilibrium. We performed systematic studies of the fast collective dynamics (including both phonon-like excitations and collective relaxations) of four classes of liquids characterized by different fragilities and interactions using synergistically integrated coherent neutron scattering experiments (Inelastic Neutron Scattering (INS), Quasi-Elastic Neutron Scattering (QENS), and Neutron Spin Echo (NSE)), a ViscoElastic Hydrodynamics theory we have been developing, andMolecular Dynamics (MD) simulations and our analysis package LiquidLib. The transformative knowledge of the collective dynamics in liquids is important to understand and ultimately control the transport of mass, energy, and charge in liquids, both at and away from thermal equilibrium, which may will likely impact a wide range of disciplines.

36 MATERIALS SCIENCE↗

A Highly Efficient and Affordable Hybrid System for Hydrogen and Electricity Production (Final Project)

The pursuit of clean, secure, and sustainable energy has sparked significant interest in fuel cells for power generation and electrolyzer cells for hydrogen production. Among all types of fuel and electrolyzer cells, solid oxide cells (SOCs) have emerged as promising candidates due to their high efficiency and versatility. However, conventional oxygen-ion conductive SOCs face several challenges related to their performance and durability associated with their high-temperature operation (≥ 800 ºC). This has led to a growing interest in intermediate-temperature (≤ 650 ºC) proton-conducting solid oxide cells (p-SOCs) as potential alternatives. In collaboration between Phillips 66 and Georgia Tech, this project aims to achieve a 1 kW p-SOCs system to demonstrate the commercial viability of efficient SOC systems. This report addresses four primary areas and key challenges we overcame: (1) development of efficient and durable proton-conducting electrolyte (e.g., BaHf 0.1 Ce 0.7 Yb 0.2 O 3-δ ) and electrode/catalyst materials, (2) large area cell fabrication (10 x 10 cm 2 ), (3) scalable stack design and building (250 W and 1 kW), and (4) demonstration of a 1 kW prototype system. Notably, significant challenges faced during the large area cell fabrication process were addressed by achieving cell flatness, improving fabrication yield, and ensuring electrode/electrolyte interfacial adhesion. Stack designs were also developed, focusing on reducing contact resistance and optimizing stack components (e.g., sealants). These efforts resulted in the achievement of high performance and durability with promising outputs of 250 W and 1 kW. Furthermore, the integration of these stacks into a fuel-powered system was explored, with refinements made to heat management, as well as to pressure and heating conditions. The results demonstrated the potential applicability of our p-SOC technology in commercial energy storage and power generation systems. Additionally, the report discusses techno-economic analysis and a market transformation plan, aiming to evaluate and advance the commercial feasibility of this technology.

25 ENERGY STORAGE↗