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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An Approach to Bayesian Optimization for Design Feasibility Check on Discontinuous Black-Box Functions

The paper presents a novel approach to applying Bayesian Optimization (BO) in predicting an unknown constraint boundary, also representing the discontinuity of an unknown function, for a feasibility check on the design space, thereby representing a classification tool to discern between a feasible and infeasible region. Bayesian optimization is a low-cost black-box global optimization tool in the Sequential Design Methods where one learns and updates knowledge from prior evaluated designs, and proceeds to the selection of new designs for future evaluation. However, BO is best suited to problems with the assumption of a continuous objective function and does not guarantee true convergence when having a discontinuous design space. This is because of the insufficient knowledge of the BO about the nature of the discontinuity of the unknown true function. In this paper, we have proposed to predict the location of the discontinuity using a BO algorithm on an artificially projected continuous design space from the original discontinuous design space. The proposed approach has been implemented in a thin tube design with the risk of creep-fatigue failure under constant loading of temperature and pressure. The stated risk depends on the location of the designs in terms of safe and unsafe regions, where the discontinuities lie at the transition between those regions; therefore, the discontinuity has also been treated as an unknown creep-fatigue failure constraint. The proposed BO algorithm has been trained to maximize sampling toward the unknown transition region, to act as a high accuracy classifier between safe and unsafe designs with minimal training cost. The converged solution has been validated for different design parameters with classification error rate and function evaluations at an average of <1% and ~150, respectively. Finally, the performance of our proposed approach in terms of training cost and classification accuracy of thin tube design is shown to be better than the existing machine learning (ML) algorithms such as Support Vector Machine (SVM), Random Forest (RF), and Boosting.

Engineering↗
DOE OSTI2025

EVs@Scale Next-Gen Profiles - EV Profile Capture 2024

As part of the U.S. DOE EVs@Scale consortium Next-Gen Profiles (NGP) project, the profile capture and analysis of production electric vehicles undergoing high power charging (HPC) is conducted over a wide range of conditions to explore variance and performance. Charge session parameters are collected from both the electric vehicle (EV) and electric vehicle supply equipment (EVSE) at a rate of 10Hz and entered into a time-series database for analysis. These charge profiles are captured under nominal and off-nominal conditions, exploring the impact of battery state of charge (SOC), battery temperature, vehicle condition, smart charge management (SCM), and EVSE limitations. Nominal conditions are defined to be ideal conditions that should transfer the maximum allowable energy in the minimum possible amount of time. Nominal condition profiles are compared across EVs to characterize state-of-the-art EV charging performance against one another. Off-nominal condition profiles are compared against its nominal condition profile counterpart to highlight the variance across less desirable starting conditions within a single EV. This EV Profile Capture 2024 report stands as an update from the EV Profile Capture 2023 report to include the additional EV & EVSE assets tested and analyzed in 2024. The major updates within this report include the addition of three next-generation electric vehicles, added test cases, and further analysis. This expansion of analysis includes power profiles, power distribution, quantifying SOC, energy and range performance, EVSE limitation impacts, boost converter performance, etc. Additionally, NGP time-series data has been used as input towards three national laboratory-led grid modelling efforts: ANL’s IEEE-37 HIL model, INL’s Caldera model, and NREL’s EVI-X model. A summary of these platforms and how NGP has worked to improve their effectiveness has also been added to this years’ report.

Thurston, Sam↗
DOE OSTI2022

A High-Voltage High-Reliability Scalable Architecture for Electric Vehicle Power Electronics (Final Report)

This project developed and demonstrated new composite converter technologies that lead to high power density (> 20 kW/L) at power levels of 10s of kW, 100s of kW, or possibly higher, with fundamental advances in converter efficiency and Q that lead to substantial increases in mean time to failure (MTTF). These advantages were realized through development of new composite converter topologies that perform buck, boost, or other conversion functions and that are scalable to higher voltage and power levels through sharing of voltage and current stresses among multiple dissimilar partial-power converter modules. The project led to experimental demonstration of a125 kW multifunction electric vehicle power conversion system having in-creased dc bus voltage (950 V nominal, 1200 V peak) that interfaces a 200 V to 400 V battery pack, and that includes integrated level 2 wired charging and wireless charging functions. The project incorporated SiC MOSFET modules having switching frequencies in excess of 100 kHz, planar magnetics, a hierarchical control architecture that enables scaling to higher voltages and powers with additional converter modules, and a high-power density in excess of 20 kW/L. The research demonstrated how a more complex converter approach can increase mean-time-to-failure, even though the number of elements is increased. This is achieved through significant reduction of temperature rise through fundamentally superior converter circuit topologies. The research also demonstrated new high power planar magnetics that increase power density. The technology is appropriate to a variety of applications including EV power trains, EV charging, PV inverters, battery storage, and similar areas. These systems potentially can be manufactured in the U.S.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Improving Proton Conductivity by Navigating Proton Trapping in High Scandium-Doped Barium Zirconate Electrolytes

Proton-conducting oxides are used in intermediate-temperature (300 °C < T < 700 °C) applications of fuel cells, electrolyzers, membrane reactors, hydrogen pumps, and sensors. The proton conductivity of doped ABO 3 perovskites is partly dependent on the proton concentration and hence on the level of material hydration. However, how the material hydration ability is affected by differences in doping is not fully understood. Here, we show the prospect of proton trapping and detrapping that influences material hydration and dehydration. The proton-trapping influence is significant for Sc-doped BaZrO 3 compared to Y-doped BaZrO 3 . Here, our work offers a perspective to understand how defect interaction/associations influence the hydration ability of proton-conducting oxides. Furthermore, positron annihilation lifetime spectroscopy was revealed to be a valuable technique for studying the proton-trapping phenomena and the defect chemistry of dense proton conductors. Density functional theory calculations also showed that a high hydration level in Sc-doped BaZrO 3 boosts proton migration. In contrast, the effect of boosting the proton migration due to increased hydration is limited for Y-doped BaZrO 3 . This effect, in turn, might explain the trend of conductivity with dopant concentration in doped BaZrO 3 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Active analog tuning of the phase of light in the visible regime by bismuth-based metamaterials

The active and analog tuning of the phase of light by metamaterials is needed to boost the switching performance of photonic devices. However, demonstrations of this type of tuning in the pivotal visible spectral region are still scarce. Herein, we report the active analog tuning of the phase of visible light reflected by a bismuth (Bi)-based metamaterial, enabled by a reversible solid-liquid transition. This metamaterial, fabricated by following a lithography-free approach, consists of twodimensional assemblies of polydisperse plasmonic Bi nanostructures embedded in a refractory and transparent aluminum oxide matrix. The analog tuning of the phase is achieved by the controlled heating of the metamaterial to melt a fraction of the nanostructures. A maximum tuning of 320° (1.8 π) is observed upon the complete melting of the nanostructures at 230°C. This tuning is reversible by cooling to 25°C. In addition, it presents a wide hysteretic character due to liquid Bi undercooling. This enables the phase achieved by this analog approach to remain stable over a broad temperature range upon cooling and until resolidification occurs around 100°C. Therefore, Bi-based metamaterials are endowed with analog optical memory capabilities, which are appealing for a wide range of applications, including optical data storage with enhanced information density or bistable photonic switching with a tunable “on” state.

36 MATERIALS SCIENCE↗
DOE OSTI2020

THE EFFECT OF FUEL REACTIVITY AND EXHAUST GAS RECIRCULATION ON KNOCK PROPENSITY OF NATURAL GAS

The development of high efficiency, spark ignited natural gas engines is currently limited by engine knock at high compression ratio/elevated boost pressures and misfire at lean conditions/high exhaust gas recirculation (EGR) levels. The knock and misfire limits are further confounded by the wide variety in fuel reactivity observed in “pipeline quality” natural gas. In this study, a rapid compression machine was used to characterize the effects of EGR and variation in natural gas fuel reactivity on the homogeneous ignition delay, flame propagation rate, and end- gas autoignition propensity for stoichiometric natural gas/oxidizer/EGR blends. A reduced chemical kinetic mechanism was also developed to accurately model the homogeneous ignition delays measured in the Colorado State University rapid compression machine (CSU RCM). Pipeline quality natural gas with a range of chemical reactivity (68 < Methane Number < 95) was simulated using mixtures of CH4, C2H6, and C3H8. Exhaust gas recirculation gases were simulated with mixtures of Ar, CO2, CO, and NO at substitution rates of 0 to 30 mass percent. Ignition delay period under homogeneous autoignition conditions was measured at compressed pressures of 30.2 to 34.0 bar and compressed temperatures of 667 to 980 K. End-gas autoignition fraction and flame propagation rate were measured by initiating a laser spark in the center of the combustion chamber, after compression, at pressures of 30.7 to 32.7 bar and temperatures of 751 to 795 K. The results indicate that both fuel reactivity and the presence of reactive species (NO and CO) in the exhaust gas recirculation have a strong impact on end-gas autoignition fraction. A chemical kinetic mechanism was developed to predict homogeneous ignition delays for pipeline quality natural gas in a pressure and temperature range of 1-100 bar and 500-1000 K respectively. This mechanism accurately predicted measured homogeneous ignition delay in the RCM with a total average relative error of 11.0%.

Mohr, Jeffrey↗
DOE OSTI2023

Understanding the cold plasma synthesis of ammonia with model metal catalysts through plasma diagnostics (Final Report)

The industrial synthesis of ammonia, which amounts to over 200 million tons annually, is the most energy-intensive chemical process. Therefore, there is a critical need and increased interest in exploring less energetic routes to produce ammonia. Not only does ammonia have a direct impact on the food market, but also it has the potential as a fuel and hydrogen carrier. Recently, plasma catalysis has emerged as a promising alternative for synthesizing ammonia at mild (pressure, temperature and power) conditions. The key to this catalytic process is the synergy between the plasma and the catalyst, where the non-equilibrium plasma allows the generation of excited species, which recombine at the catalyst surface to form ammonia. However, our current understanding of this process is in its infancy. In this respect, model metals are ideal candidates for gaining a basic understanding of this reaction. Moreover, a major roadblock to rationally designing novel effective catalysts for plasma-assisted ammonia production is the need for fundamental aspects of this process. Through a comprehensive plan that integrates model metals as catalysts and world-class diagnostics, the proposed work aims to provide fundamental knowledge about the nature of reactive processes occurring during plasma-assisted catalysis and to demonstrate the selective production of ammonia, catalyzed by employing selected metals under non-thermal plasma conditions. Toward this goal, the central thrust of this proposal was to demonstrate that the synergy between plasma and rationally selected model metals will boost ammonia yields during plasma-assisted ammonia synthesis by delaying hydrogen recombination. Specifically, we aimed to (1) understand the formation and role of gas-phase active species such as NH, N 2 , N 2 + and Ha during the plasma-enhanced synthesis of ammonia through OES and FTIRAS using different reaction configurations: a) only plasma (non-packed DBD reactor) and b) packed DBD reactor with metal nanoparticles. This proposal was awarded/recommended with a run time on the PCRF facility FY20.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Thermal Image Processing for Feature Extraction from Encapsulated Phase Change Materials

Encapsulated inorganic particles with high melting points (>300 °C) are desired as high-temperature Phase Change Materials (PCMs) for next-generation Latent Heat Thermal Energy Storage (LHTES) systems. One of the many challenges during the development of PCMs is to achieve a high throughput that in turn depends on accurately modeling the relation between process parameters and geometric & thermal properties of the PCMs particle. During the production of the PCMs, a high-speed infrared camera is used to acquire images of the encapsulated material under controlled illumination conditions. This research article focuses on the development of image processing techniques for both geometric and thermal feature extraction during the development of the PCMs. A user-friendly GUI has been designed in MATLAB and preliminary experimental results have demonstrated that the method is fast, accurate and reliable for a high throughput production. The extracted features will be used to develop Machine Learning (ML) models to predict the geometric and thermal properties of the PCM based on the process parameter settings. The ML model will accelerate the search for the optimized process settings to boost the throughput of the production.

25 ENERGY STORAGE↗
DOE OSTI2025

Multimetallic Layered Composites (MMLCs) for Rapid, Economical Advanced Reactor Deployment (Final Report)

This project focused on the development of multi-metallic layered composites (MMLCs) for advanced fission reactor technologies. There are many instances where one alloy or material simply cannot meet all the demands thrown at it by a reactor system, or cannot allow it to perform as strongly as one would like. Instead of focusing all our effort on developing one perfect alloy, we seek to leverage the design principle of “separation of functionality,” used in many other arenas in design, to boost performance beyond single alloys alone. One illustrative example shows the power of this approach for molten salt-cooled reactors: A three meter tall, three meter diameter reactor vessel made of Incoloy 800 was quoted at $\$$500k in 2018. A Hastelloy N vessel was quoted at $\$$5M. An MMLC vessel, in which a layer of Hastelloy N would be weld-overlaid onto Incoloy 800, was quoted at $\$$700k, and it would achieve the same performance. The potential economic gains of leveraging this approach are therefore substantial. At a minimum, each MMLC would contain one core structural layer and one coolant-facing corrosion-resistant layer. Sometimes, MMLCs required buffer layers, as the structural and corrosion-resistant layers were metallurgically incompatible. In other words, they didn’t always play nice, thus separating layers compatible with both functioned as intermediaries to keep the composite together. However, in doing so we inevitably produce new interfaces, where new issues can arise. Therefore, this project focused on what happens at these interfaces from a combination of high temperatures, irradiation, corrosion, and time. After all, a reactor makes money when it is operating, and outages of any kind erode its economic viability. First, we set out to experimentally prove that MMLCs for at least two advanced reactor systems can be made, today, in US domestic facilities. In this respect we were successful – one MMLC (a Ni-201/Incoloy 800H composite) was successfully made and drawn into two-inch coolant piping. Others were attempted, though new issues relating to cracking in vanadium layers for one and radiation damage performance of the corrosion-resistant layer in another prevented us from moving further in those specific arenas – these are engineering problems which deserve continued focus after this project. Additional experimental work focused on long-term corrosion testing of the outermost layers of the salt-cooled and liquid lead-cooled MMLC concepts, which would then be fed into predictions of how long the MMLCs could last. Next, computational (thermodynamics and atomistic) simulation studies studied how much we expect the interfaces to “blend,” due to the mixing action of neutron irradiation. This eats into both the margin for the structural layer of each MMLC, as dilution from the corrosion-resistant layer into the structural layer would decrease the total load-bearing capacity of an MMLC of finite size. On the other hand, dilution of the corrosion-resistant layer into the structural layer further reduced the margin of corrodible material, reducing the lifetime of the MMLC or necessitating extra thickness to be imparted to the MMLC to meet its functional requirements. Work here focused on irradiation-induced segregation to predict new phases which may embrittle the MMLCs, as well as quantifying irradiation-induced mixing at each interface. The results showed that mixing is expected, but it is both steady and therefore predictable, and not lifetime-limiting for most MMLC concepts – it simply has to be accounted for in calculations of reactor performance when utilizing an MMLC. Then, full-core simulations using the experimentally-derived corrosion data, the computationally discovered irradiation-induced mixing data (partially validated by experiment), and existing, benchmarked core designs for large and small sized reactor concepts (one salt-cooled, one lead-cooled) were conducted to quantify any expansion of reactor operating envelopes achieved by utilizing these MMLCs. This new framework, called REX (Reactor Envelope Expansion), incorporates a combination of core neutronics, thermal hydraulics, and the material performance data derived from this project to see how using an MMLC expands advanced fission reactor operating envelopes. It was discovered that in some cases, MMLC utilization does indeed increase the maximum operating temperatures and cycle lengths of reactor concepts, while in other cases it does not. Finally, our tech-to-market (T2M) strategy was not necessarily to create specific embodiments of MMLCs for immediate sale (because getting into the nuclear market is incredibly slow and laden with regulation, this is a long-term goal), but rather immediate stimulation of US industry using the design approach of MMLCs derived from this project. In this respect we were successful, as one of the PhD students funded on this project co-founded Allium Engineering, Inc., which created a stainless steel / low-alloy steel MMLC to function as chloride corrosion-resistant rebar for embedding into concrete structures. Allium Engineering continues to be successful, having recently opened their first factory as of this writing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Quantum Chemistry-Driven Machine Learning Approach for the Prediction of the Surface Tension and Speed of Sound in Ionic Liquids

Ionic liquids (ILs) have unique solvent properties and have thus garnered significant interest. However, exhaustive experimental determination of the physicochemical properties of ILs is unrealistic due to the large structural diversity of anions and cations, their high cost, the requirements of elevated temperature and pressure, and the time required. To circumvent these experimental costs, computational approaches to accurately calculate these properties have emerged. Here in the present study, we present a demonstration of two machine learning (ML) models for the prediction of two critical IL physical properties, the surface tension and the speed of sound, across a wide range of temperatures and pressures. The models make use of molecular descriptors derived from the COSMO-RS, a quantum chemical-based model. The ML models show excellent agreement with experimental observations, with an R2 value of 0.96–0.99 and RMSE of 1.71 mN/m and 16.12 m/s for the surface tension and speed of sound, respectively. This work paves the way for the development of COSMO-RS-informed ML models for the prediction of IL properties which can help to further optimize and accelerate technology development for ILs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Development of Nanocomposite Coatings for Future Large-Scale Time Projection Chambers

In the context of this award we tested the performance of thin high-resistivity coatings for their potential usage as field shaping systems in future large scale xenon Time Projection Chambers (TPC). A successful implementation of such thin coatings would likely simplify the design of potential future detectors, allowing to overcome some of the challenges observed with traditional systems constituted by massive discrete electrodes. We studied a wide range of materials and characterized their optical and electrical performances as functions of temperature and wavelength. The measurement campaign indicated that uniform coatings covering the full PTFE substrate (usually used as reflector in LXe TPCs) impact too severely on the light collection performance of such detectors when used with deep UV light. Despite tuning the composition and thicknesses of nanocomposite coatings, we were not able to identify a single coating, properly working at LXe temperature, that would simultaneously fulfill the resistance and optical requirements. Following the risk mitigation strategy identified in the proposal we moved the focus of the R&D to identify proper materials that, when coated with grid-like patterns on PTFE, would not alter meaningfully its optical properties (with respect to bare PTFE panels) but would still serve as effective field shaping systems, properly containing the drift field in TPC detectors. Among the various materials we identified germanium as the most promising one, providing a good adhesion to PTFE and the proper range of sheet resistivity. The Ge-patterned coating tested within a small scale LXe TPC showed good performance as a field shape system and, as desired, did not reduce the detector light yield. These results are encouraging and such technology should further be investigated as a potential alternative to more traditional field shaping electrodes. Incidentally, in the context of this R&D, we stumbled upon an unexpected behavior suggesting that some of the treatments performed on the PTFE panels, in preparation of the coatings, meaningfully boosted the PTFE reflectivity. The most probable candidate is the O2 plasma cleaning procedure. This hypothesis will be tested in the near future by operating the small scale TPC at UChicago first with regular PTFE panels and then with panels bombarded with O2 plasma (but no coatings). This finding, if confirmed, might open up the possibility of further boosting UV light collection in future large detectors by performing such a treatment on the PTFE surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Overcoming sparse datasets with multi-task learning as applied to high entropy alloys

Abstract The design of novel High Entropy Alloys for use in high-temperature applications is an area of active interest due to their potential to provide exceptional properties compared to conventional alloys. Since the increased popularity of machine learning, an important cog in the design process has been training surrogate models on alloy properties. However, these Single-Task models are trained on individual mechanical properties and do not take advantage of the relatedness between properties. Multi-Task models can capture the interdependencies between tasks, leading to potentially more accurate predictions for all tasks. In this paper, we investigate if Multi-Task models can show improvement over Single-Task models when used for predicting the mechanical properties of these alloys. To ensure fair evaluation between the models, we apply L 0 regularization and skip connections to the models, which allows them to adjust the number of model parameters and depth for optimal performance. We find that the Multi-Task models can leverage task relationships to perform better than Single-Task models, especially for high amounts of missing data in the tasks. Furthermore, adding simple auxiliary targets can boost Multi-Task performance even further despite not being effective as input descriptors to single-task models themselves. We anticipate that the proposed strategies can achieve more accurate predictions and consequently enable better design capabilities for such data-constrained domains without incurring much additional computational cost.

Debnath, Arindam (ORCID:0000000194274499)↗
DOE OSTI2022

Scalable High-H 2 Flux, Robust Thin Film Solid Oxide Electrolyzer

This project was aimed at the development of proton-conducting SOEC (P-SOEC) technology that has the potential to meet key DOE H 2 production targets. A decreased proton resistance of the electrolyte and Faradaic efficiency improvements were sought to increase the fraction of consumed electrolysis power that is used to actually generate H 2 , while simultaneously decreasing cost dramatically. Moreover, the development project was intended to yield maximum durability through the use of a steam protective layer. Furthermore, sputtering was used to overcome processing challenges that have hampered P-SOEC development, while the low-temperature operation goal of 500 °C was expected to aid in mitigating thermally activated long-term degradation. The approach to high-performance, lower-temperature SOECs leveraged our existing SOFC Ni-cermet anode support and extensive thin-film sputtering layer-deposition experience. Rather than an all-in-one, reversible fuel cell approach which has many unacceptable tradeoffs, we focused on the many benefits to hydrogen generating SOECs, including the existence of synergies for reduced manufacturing costs (e.g., SOECs and SOFCs share supporting layers and overall manufacturing processing). The end result of this project was expected to increase current performance at 500 °C from approximately 0.8 A/cm 2 (at 60% Faradaic efficiency) at 1.4 V to > 1 A/cm 2 (at > 95% Faradaic efficiency) with a > 40% reduction in system cost and to enable operation of P-SOECs in steam contents >> 20% for a goal of a > 40,000 hours lifetime. To enable 500 °C operation in a very high steam atmosphere (> 20%), we proposed the use of a sputtered dense thin film (~0.1-1 µm thick) of high-stability Ba(Zr,Y)O 3 (BZY) to protect the Ba(Ce,Zr,Y,Yb)O 3 (BCZYYb) electrolyte. The BZCYYb, in turn, blocks the hole conductivity of the BZY to boost Faradaic efficiency. As FE increases, more of the consumed electricity is used in electrolysis to generate H 2 , rather than being shunted. Additionally, as cell resistance decreases, the voltage required to maintain current decreases, as well as the power required to generate the same amount of H 2 . With the proposed enhancements, these two factors result in the final 46% decrease in power needed to run the system. Likewise, a production rate of 50,000 kg H 2 /day will require 55% less active area, such that a system will need only 650 cells for an 80 cm 2 active area instead of ~1,440. Taking the 2016 DOE projected current cost and modifying the electricity cost and linearly scaling the other costs (except thermal feedstock) based on the cell area improvement, results in a 44% decrease in lifetime system cost, or a decrease from $\$$4.95/kg H 2 to $\$$2.75/kg H 2 . This is well below the 2018 DOE target of $\$$4/kg H 2 . The results from this project showed that we can create a P-SOEC with enhanced steam stability using two different electrolytes (i.e., one on top of the other) and achieve sufficiently low area specific resistance (ASR) to achieve the target performance. Unfortunately, due to extended delays at the beginning of the project and related supply chain and equipment access issues, we were not able to completely show increased Faradaic efficiency for the P-SOEC and therefore were unable to demonstrate the full proof of concept within the first budget period budget. While there are still challenges that remain to be solved, significant progress was made during this project and the concept still has merit that warrants further development.

08 HYDROGEN↗
DOE OSTI2023

Intermediate Temperature Proton‐Conducting Solid Oxide Electrolysis Cells with Improved Performance and Durability

Technical understanding: A high-performance and stable intermediate temperature proton-conducting solid oxide electrolysis cell (PCEC) will add significantly to the hydrogen roadmap of EERE. However, the low electrocatalytic activity of the air electrode and the instability of the electrolyte are technical barriers. In this research, we utilized computational fluid dynamic modeling and materials/microstructure engineering to investigate the complex reaction chain and to improve the performance and reliability of the protonic ceramic electrochemical cells. An active and stable Pr 1.8 Ba 0.2 NiO 4+δ -BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3-δ (BZCYYb) scaffold conformal coating electrode was rationally designed where the robust Pr 1.8 Ba 0.2 NiO 4+δ functions both as a catalytic active and a protective layer. The PCECs with porosity-optimized scaffold conformal coating electrodes demonstrate 1.46 Acm -2 under 1.3 V at 600°C, which is among the highest in recent years. The final optimization by computational fluid dynamic modeling and conformal coating technique was applied to evolve the PCEC air electrode from Pr 2 NiO 4+δ to Pr 1.8 Ba 0.2 NiO 4+δ -BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3-δ scaffold conformal coating. The electrolysis current was boosted from 0.445A/cm 2 to 1.46A/cm 2 at 600°C and 1.3V. A superior low degradation rate of 1mV/kh was achieved in a 5000-hour of operation. Technical effectiveness and economic feasibility: The effectiveness of this TCO conformal coating on electrolyte backbone as air electrode has been proven by long-term demonstration. Based on the highly conductive BZCYYb electrolyte and the TCO steam electrode PNO, this project rationally took advantage of the existent materials to structure a PCEC device with high TRL and low risk. The solution infiltration method used to structure the conformal coating is a standard method used by the solid oxide cell community. Very minimal adoption is needed in the current SOC fabrication process. It is a cost-effective, scalable method for manufacturing, and brings up remarkable impact on the current technical status of PCEC. Benefit to the public: The findings in the research showed the industry that the severe challenge in PCEC can be overcome in a practical way. A various energy-hydrogen ecosystem is not beyond reach. The success of this technology provides sustainable and affordable H 2 to society. It will stimulate investment from the governmental and private sectors in response to the device manufacture and deployment, and the related infrastructure construction. It will generate high-pay domestic jobs and environmental benefits to the general public in the United States.

08 HYDROGEN↗
DOE OSTI2021

Signatures of deconfined quark phases in binary neutron star mergers

We investigate the quark deconfinement phase transition in the context of binary neutron star (BNS) mergers. We employ a new finite-temperature composition-dependent equation of state (EOS) with a first order phase transition between hadrons and deconfined quarks to perform numerical relativity simulations of BNS mergers. Here, the softening of the EOS due to the phase transition causes the merger remnants to be more compact and to collapse to a black hole (BH) at earlier times. The phase transition is imprinted on the postmerger gravitational wave (GW) signal duration, amplitude, and peak frequency. However, this imprint is only detectable for binaries with sufficiently long-lived remnants. Moreover, the phase transition does not result in significant deviations from quasi-universal relations for the postmerger GW peak frequency. We also study the impact of the phase transition on dynamical ejecta, remnant accretion disk masses, r-process nucleosynthetic yields and associated electromagnetic (EM) counterparts. While there are differences in the EM counterparts and nucleosynthesis yields between the purely hadronic models and the models with phase transitions, these can be primarily ascribed to the difference in remnant collapse time between the two. An exception is the non-thermal afterglow caused by the interaction of the fastest component of the dynamical ejecta and the interstellar medium, which is systematically boosted in the binaries with phase transition as a consequence of the more violent merger they experience.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

High current density electroreduction of CO 2 into formate with tin oxide nanospheres

In this study, we demonstrate three-dimensional (3D) hollow nanosphere electrocatalysts for CO 2 conversion into formate with excellent H-Cell performance and industrially-relevant current density in a 25 cm 2 membrane electrode assembly electrolyzer device. Varying calcination temperature maximized formate production via optimizing the crystallinity and particle size of the constituent SnO 2 nanoparticles. The best performing SnO 2 nanosphere catalysts contained ~ 7.5 nm nanocrystals and produced 71–81% formate Faradaic efficiency (FE) between -0.9 V and -1.3 V vs. the reversible hydrogen electrode (RHE) at a maximum formate partial current density of 73 ± 2 mA cm geo -2 at -1.3 V vs. RHE. The higher performance of nanosphere catalysts over SnO 2 nanoparticles and commercially-available catalyst could be ascribed to their initial structure providing higher electrochemical surface area and preventing extensive nanocrystal growth during CO 2 reduction. Our results are among the highest performance reported for SnO 2 electrocatalysts in aqueous H-cells. We observed an average 68 ± 8% FE over 35 h of operation with multiple on/off cycles. In situ Raman and time-dependent X-ray diffraction measurements identified metallic Sn as electrocatalytic active sites during long-term operation. Further evaluation in a 25 cm 2 electrolyzer cell demonstrated impressive performance with a sustained current density of 500 mA cm geo -2 and an average 75 ± 6% formate FE over 24 h of operation. Our results provide additional design concepts for boosting the performance of formate-producing catalysts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Solid State Quantum Refrigeration Superconducting, Absorption and Measurement Based (Final Technical Report)

During this DOE grant, DE-SC0017890, in place for the past six years, all proposed research was carried out and published in peer-reviewed papers, as well as other projects that emerged during the research. In that effort the research team accomplished all proposed research, as well as many closely related research projects discovered and conceived of during the grant. These works included “Efficient Quantum Measurement Engines”, a work published in Physical Review Letters, giving a theory of quantum measurement-based engines, which uses quantum measurement as a resource. These engines are designed to efficiently convert energy from the stochastic quantum measurement process into useful work. Further publications include “Experimental Realization of a Quantum Dot Energy Harvester”, a joint theory and experimental work in collaboration with the group of Charles Smith in Cambridge, UK, as well as long time theoretical collaborators, Rafael Sánchez and Björn Sothmann. This work, featured as an Editor’s Suggestion in Physical Review Letters, realized an earlier theoretical proposal of ours, whereby two resonant tunneling quantum dots are connected to a central electronic cavity that is heated by a hot energy source. We also published “Superconducting Quantum Refrigerator: Breaking and Rejoining Cooper Pairs with Magnetic Field Cycles” a work done in collaboration with experimentalist Francesco Giazotto from ENS Pisa, Italy, which also resulted in a patent. This paper, published in Phys. Rev. Applied, advanced the concept of a cyclic fridge based on the normal/superconducting phase transition together with layered materials separated by tunnel junctions. We also completed the proposed research on a heat transistor, publishing “Thermal transistor and thermometer based on Coulomb-coupled conductors”, carried out as a collaboration between my group and theorists Splettstoesser (Lund U., Sweden), Sothmann (U. Duisburg-Essen, Germany), and Sánchez (U. Autónoma de Madrid, Spain). We carried out an analysis of a quantum coupled to a quantum point contact as a sensitive thermometer and heat transistor. We found the optimal statistical estimator for the temperature and compared it with experiments on the same type of devices. We also investigated autonomous quantum absorption refrigerators using quantum dots to cool by using a very hot thermal reservoir to drive heat between two other reservoirs. In the article “Quantifying the quantum heat contribution from a driven superconducting circuit”, we demonstrated that for a driven superconducting circuit, we showed heat flow provided by a hot source to the qubit can be switched on and off by varying external parameters, the frequency and the intensity of the driving. In the work “Stochastic thermodynamic cycles of a mesoscopic thermoelectric engine”, we reconsidered the autonomous thermoelectric heat engine in terms of underlying cycles. Rather than periodic behavior, the cycles were stochastic in nature. Nevertheless, by undertaking a graph theoretical analysis of the elementary transport processed, great quantitative and qualitative insight could be found. We also considered the quantum measurement process and showed that a quantum version of Maxwell’s demon could be related to the work extraction of a quantum system, closely related to arrow-of-time measures for quantum measurement, as described in our article “Thermodynamics of quantum measurement and Maxwell's demon's arrow of time”. This work was selected in Phys. Rev. A as an Editor’s Suggestion. A recent preprint titled “Cyclic Superconducting Quantum Refrigerators Using Guided Fluxon Propagation” accomplished an important piece of this grant: to propose a new kind of quantum refrigerator using the dynamics of fluxons in a type II superconductor. This invention envisioned a race-track type geometry where fluxons are confined. By applying a gradient of magnetic field together with electric current in a Corbino geometry, the circulating fluxons can actively cool a cold reservoir, realizing a new type of cyclic superconducting refrigerator. We also investigated the possibility of thermal control from different points of view. The application of quantum measurement to the system gives a new kind of control on the system of interest – we have pioneered this approach and shown that measurement can boost the thermal power of quantum engines as described in “Continuous measurement boosted adiabatic quantum thermal machines”. The ability to have heat flows on demand is an outstanding challenge, and we have provided new solutions to this problem in Thermal control across a chain of electronic nanocavities” for a chain of electron cavities using gating voltage control. The control methods using qubit/qubit coupling to create absorption fridges at their most fundamental level have also been developed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Numerical Analysis of Fuel Effects on Advanced Compression Ignition Using a Cooperative Fuel Research Engine Computational Fluid Dynamics Model

Growing environmental concerns and demand for a better fuel economy are driving forces that motivate the research for more advanced engines. Multi-mode combustion strategies have gained attention for their potential to provide high thermal efficiency and low emissions for light-duty applications. These strategies target optimizing the engine performance by correlating different combustion modes to load operating conditions. The extension from boosted spark ignition (SI) mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing the compression ratio and utilizing intake air heating. Further, in order to enable an accurate control of intake charge condition for ACI mode and rapid mode-switches, it is essential to gain fundamental insights into the autoignition process. Within the scope of ACI, homogeneous charge compression ignition (HCCI) mode is of significant interest. It is known for its potential benefits, operation at low fuel consumption, low NOx, and particulate matter (PM) emissions. In the present work, a virtual Cooperative Fuel Research (CFR) engine model is used to analyze fuel effects on ACI combustion. In particular, the effect of fuel octane sensitivity (S) (at constant Research Octane Number (RON)) on autoignition propensity is assessed under beyond-RON (BRON) and beyond-MON (BMON) ACI conditions. The three-dimensional CFR engine computational fluid dynamics (CFD) model employs a finite-rate chemistry approach with a multi-zone binning strategy to capture autoignition. Two binary blends with Research Octane Number (RON) of 90 are chosen for this study: primary reference fuel (PRF) with S = 0 and toluene–heptane (TH) blend with S = 10.8, representing paraffinic and aromatic gasoline surrogates. Reduced mechanisms for these blends are generated from a detailed gasoline surrogate kinetic mechanism. Simulation results with the reduced mechanisms are validated against experimental data from an in-house CFR engine, with respect to in-cylinder pressure, heat release rate, and combustion phasing. Thereafter, the sensitivity of combustion behavior to ACI operating condition (BRON versus BMON), air-fuel ratio (λ = 2 and 3), and engine speed (600 and 900 rpm) is analyzed for both fuels. It is shown that the sensitivity of a fuel’s autoignition characteristics to λ and engine speed significantly differs at BRON and BMON conditions. Moreover, this sensitivity is found to vary among fuels, despite the same RON. It is also observed that the presence of low-temperature heat release (LTHR) under BRON condition leads to more sequential autoignition and longer combustion duration than BMON condition. Finally, the study indicates that the octane index (OI) fails to capture the trend in the variation of autoignition propensity with S under the BMON condition.

33 ADVANCED PROPULSION SYSTEMS↗