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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Single-Step Conversion of Ethanol to n-Butene over Ag-ZrO2/SiO2 Catalysts

Ethanol is a promising platform molecule for production of a variety of fuels and chemicals. Of particular interest is producing middle distillate fuels (i.e., jet and diesel blendstock) from renewable ethanol feedstock. State-of-the-art alcohol-to-jet technology requires multiple process steps based on catalytic dehydration of ethanol to form ethylene, followed by sometimes a multi-step oligomerization, and then hydrotreatment and distillation. Here we report on a new catalytic route in which ethanol is directly converted to n-butene (1- and 2-butene mixtures) over Ag-ZrO2/SBA-16, thus offering the potential for a reduction in the number of required processing steps versus conventional alcohol-to-jet technology. This catalyst system provides the balanced metal and Lewis acid sites required to selectively facilitate a cascading sequence of reactions that includes dehydrogenation, aldol condensation, Meerwein–Ponndorf–Verley reduction, dehydration, and hydrogenation. High conversion and selectivity toward either n-butene or 1,3-butadiene is achieved by tuning the hydrogen feed partial pressure and other process/catalyst parameters. With sufficient hydrogen partial pressure 1,3-butadiene is completely and selectively hydrogenated to form n-butene. The reaction mechanism was elucidated through operando-nuclear magnetic resonance investigations coupled with reactivity measurements. Combined experimental-computational investigation reveals how changes in silver and zirconium composition and the silver oxidation state affects reactivity under controlled hydrogen partial pressures and after prolonged run times. Finally, catalyst effectiveness also was demonstrated when using wet ethanol feed, thus highlighting process flexibility in terms of feedstock purity requirements. This work was financially supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office, and was performed at the Pacific Northwest National Laboratory (PNNL) under Contract No. DE-AC05-76RL01830 and the National Renewable Energy Laboratory under Contract No. DE-AC36- 08GO28308. Part of the work conducted by S. A. Akhade was performed under the auspices of the U.S. DOE at Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344. This work was partly supported through the PNNL-WSU Distinguished Graduate Research Program for ADW. NMR and XPS experiments were performed using EMSL (grid.436923.9), a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research

Dagle, Vanessa↗
DOE OSTI2024

Simulation of Multiphase Flow and Poromechanical Effects Around Injection Wells in CO 2 Storage Sites

In geological CO 2 storage operations, wellbore deformations and leakage pathways formations can occur around injection and abandoned wells subjected to high rates and long-term CO 2 injection. To guide engineering design and prevent CO 2 leakage risks, a full understanding of the underlying physics and robust numerical models is necessary to evaluate the response of underground formations in the near wellbore region and in the reservoir. In this study, a multi-scale and multi-physics open-source simulator (GEOS) is used to simulate multiphase flow and poromechanical deformations over time in three dimensions. The governing equations for mechanical deformations of the rock body and multiphase compositional fluid flow within the rock matrix are solved with a fully coupled finite element and finite volume approach. The Drucker–Prager model with friction hardening is applied to simulate elastoplastic deformation and a multiphase fluid model with power-law correlations for relative permeability is used to model the migration of CO 2 plume, which are coupled with numerical implicit scheme. Simulation results are verified against multiple analytical solutions for multiphase flow and wellbore problems, thus demonstrating the accuracy of this advanced simulator. In two engineering applications, here we highlight the impact of elastoplastic deformation and coupled modeling for assessing induced displacements and stress perturbations, which are more pronounced in the near wellbore regions. This work focuses on short-term processes in the vicinity of injection wells where stress evolutions, rock deformations and multiphase compositional flow and transport are simulated jointly to ensure wellbore stability and prevent damage. This fully coupled geomechanical model can simulate multiphase flow and any associated poromechanical effects within the CO 2 storage site and in the surrounding formations. Such a large-scale, long-term, multi-physics simulation model is useful in many ways: it can guide operational decisions for CO 2 injection, assess the containment potential and risks of a site, and analyze the wellbore stability and integrity during and after CO 2 injection.

58 GEOSCIENCES↗
DOE OSTI2023

Cationic Copper Species Stabilized by Zinc during the Electrocatalytic Reduction of CO 2 Revealed by In Situ X‐Ray Spectroscopy

Abstract Advanced in situ X‐ray absorption spectroscopy characterization of electrochemically co‐electrodeposited bi‐element copper alloy electrodes shows that zinc yields the formation of a stable cationic Cu species during the electroreduction of CO 2 at high cathodic polarization. In contrast, the formation/stabilization of cationic Cu species in copper oxides, or doping Cu with another element, like Ni, is not possible. It is found that the pure and mixed Cu:Zn electrodes behave similarly in term of electrocatalytic selectivity to multi‐carbon products. At higher Zn concentrations the electrode behaves like the pure Zn catalyst, which indicates that the Cu cationic species do not have a significant influence on the selectivity to multi‐carbon products. It is found that in the non‐monotonically distribution of products is dominated in term of surface energy in which copper prefers the surface. Otherwise, this work highlights the importance of in situ characterization to uncover the mechanisms mediating the catalytic reactions in contrast to ex situ or post mortem analysis, which can be a source of misinterpretation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ecological theory applied to environmental metabolomes reveals compositional divergence despite conserved molecular properties

Stream and river systems transport and process substantial amounts of dissolved organic matter (DOM) from terrestrial and aquatic sources to the ocean, with global biogeochemical implications. However, the underlying mechanisms affecting the spatiotemporal organization of DOM composition are under-investigated. To understand the principles governing DOM composition, we leverage the recently proposed synthesis of metacommunity ecology and metabolomics, termed ‘meta-metabolome ecology.’ Applying this novel approach to a freshwater ecosystem, we demonstrated that despite similar molecular properties across metabolomes, metabolite identity significantly diverged due to environmental filtering and variations in putative biochemical transformations. We refer to this phenomenon as ‘thermodynamic redundancy,’ which is analogous to the ecological concept of functional redundancy. We suggest that under thermodynamic redundancy, divergent metabolomes can support equivalent biogeochemical function just as divergent ecological communities can support equivalent ecosystem function. As these analyses are performed in additional ecosystems, potentially generalizable principles, like thermodynamic redundancy, can be revealed and provide insight into DOM dynamics.

Danczak, Robert E.↗
DOE OSTI2020

An analysis of carrier dynamics in methylammonium lead triiodide perovskite solar cells using cross correlation noise spectroscopy

Using cross correlation current noise spectroscopy, we have investigated carrier dynamics in methylammonium lead triiodide solar cells. This method provides space selectivity for devices with a planar multi-layered structure, effectively amplifying current noise contributions coming from the most resistive element of the stack. In the studied solar cells, we observe near full-scale shot noise, indicating the dominance of noise generation by a single source, likely the interface between the perovskite and the spiro-organic 2,2',7,7'-tetrakis(N,N-di-p-methoxyphenyl-amine)9,9'-spirobifluorene hole-transport layer. In this paper, we argue that the strong 1/f noise term has contributions from both the perovskite layer and interfaces. It displays a non-ideal dependence on photocurrent, S $\propto$ I 1.4 (instead of usual S $\propto$ I 2 ), which is likely due to current-induced halide migration. Finally, we observe generation–recombination noise. We argue that this contribution is due to bimolecular recombination in the perovskite bulk absorption layer. Extrapolating our results, we estimate that at standard 1 sun illumination, the electron–hole recombination time is 5 microseconds.

14 SOLAR ENERGY↗
DOE OSTI2021

Clock transitions guard against spin decoherence in singlet fission

Short coherence times present a primary obstacle in quantum computing and sensing applications. In atomic systems, clock transitions (CTs), formed from avoided crossings in an applied Zeeman field, can substantially increase coherence times. We show how CTs can dampen intrinsic and extrinsic sources of quantum noise in molecules. Conical intersections between two periodic potentials form CTs in electron paramagnetic resonance experiments of the spin-polarized singlet fission photoproduct. We report on a pair of CTs for a two-chromophore molecule in terms of the Zeeman field strength, molecular orientation relative to the field, and molecular geometry.

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

Uncertainty Quantification for Multiphase Computational Fluid Dynamics Closure Relations with a Physics-Informed Bayesian Approach

Multiphase Computational Fluid Dynamics (MCFD) based on the two-fluid model is considered a promising tool to model complex two-phase flow systems. MCFD simulation can predict local flow features without resolving interfacial information. As a result, the MCFD solver relies on closure relations to describe the interaction between the two phases. Those empirical or semi-mechanistic closure relations constitute a major source of uncertainty for MCFD predictions. In this paper, we leverage a physics-informed uncertainty quantification (UQ) approach to inversely quantify the closure relations’ model form uncertainty in a physically consistent manner. This proposed approach considers the model form uncertainty terms as stochastic fields that are additive to the closure relation outputs. Combining dimensionality reduction and Gaussian processes, the posterior distribution of the stochastic fields can be effectively quantified within the Bayesian framework with the support of experimental measurements. As this UQ approach is fully integrated into the MCFD solving process, the physical constraints of the system can be naturally preserved in the UQ results. Here, in a case study of adiabatic bubbly flow, we demonstrate that this UQ approach can quantify the model form uncertainty of the MCFD interfacial force closure relations, thus effectively improving the simulation results with relatively sparse data support.

42 ENGINEERING↗
DOE OSTI2021

A selection function toolbox for subsets of astronomical catalogues

ABSTRACT Large catalogues are ubiquitous throughout astronomy, but most scientific analyses are carried out on smaller samples selected from these catalogues by chosen cuts on catalogued quantities. The selection function of that scientific sample – the probability that a star in the catalogue will satisfy these cuts and so make it into the sample – is thus unique to each scientific analysis. We have created a general framework that can flexibly estimate the selection function of a sample drawn from a catalogue in terms of position, magnitude and colour. Our method is unique in using the binomial likelihood and accounting for correlations in the selection function across position, magnitude, and colour using Gaussian processes and spherical harmonics. We have created a new open-source python package selectionfunctiontoolbox that implements this framework and used it to make three different estimates of the APOGEE DR16 red giant sample selection function, as a subset of 2MASS, with each estimate using an increasing amount of technical knowledge of the APOGEE targeting. In a companion paper, we applied our methodology to derive estimates of the astrometric and spectroscopic selection functions of Gaia EDR3. Our framework will make it trivial for astrophysicists to estimate the selection function that they should be using with the custom sample of stars that they have chosen to answer their scientific question.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Denial of Service Attack Detection via Differential Analysis of Generalized Entropy Progressions

Denial-of-Service (DoS) attacks are one the most common and consequential cyber attacks in computer networks. While existing research offers a plethora of detection methods, the issue of achieving scalability, a low false positive rate, and high detection accuracy remains open. In this work, we address this problem by developing a differential method based on generalized entropy progression. In this method, named as DoDGE, we continuously fit the line of best fit to the entropy progression of destination addresses and check if the derivative, that is, the slope of this line is less than the negative of the dynamically computed standard deviation of the derivatives. Furthermore, to distinguish from flash events, we leverage the symmetry that when a flash event occurs, the derivative of the entropy progression of source addresses is positive. With this design, we omit the usage of the thresholds and the results with five real-world network traffic datasets confirm that DoDGE outperforms threshold-based DoS attack detection by two orders of magnitude in terms of false positives on average. When compared to ten machine learning (ML) models, DoDGE achieves a balanced accuracy of 99%, while the average balanced accuracy for the ML models is 52%. Moreover, the results show that DoDGE successfully differentiates between a flash event and a DoS attack. Furthermore, since the main computation cost of DoDGE is the entropy computation, which is linear in the volume of the unit-time network flow, uses integer only operations, and works on a small fraction of the total flow, it is lightweight and scalable.

Cybersecurity, wireless communication↗
DOE OSTI2022

Concealed Cathode Degradation in Lithium-Ion Cells with a Ni-Rich Oxide

Difficulties with sourcing cobalt and the interest in increasing cell energy have motivated the development of Ni-rich oxide materials for lithium-ion battery cathodes. Despite the intense research on the topic, there is limited information available on the long-term performance of novel cathode formulations. Here, we evaluate the stability of LiNi 0.9 Mn 0.05 Co 0.05 O 2 in full-cells tested for over five months, assessing how cycling, voltage and electrolyte additives impact cathode aging. We use differential voltage analysis to extract insights about the cathode from the full-cell data and identify the isolation of cathode particles in the delithiated (charged) state as a relevant mode of aging. Importantly, this particular mechanism of cathode aging does not cause immediate cell capacity fade, causing the simple analysis of cell capacity retention to overestimate the cathode stability under the investigated conditions. So, our observations serve as cautionary tale indicating that careful analysis of data from extended testing may be required for assessing the performance of Ni-rich cathodes and for evaluating how these materials are affected by electrolyte additives.

25 ENERGY STORAGE↗
DOE OSTI2022

Operating Lifetime Study of Ultraviolet (UV) Light-Emitting Diode (LED) Products

Light-emitting diodes (LEDs) can emit radiation that spans the range from near infrared (IR) to all three bands of ultraviolet (UV) radiation: UV-A, UV-B, and UV-C. This report focuses on LEDs that emit in one of the three UV bands because they have the potential to displace lowpressure mercury vapor (LPMV) lamps in a variety of industrial processes, including ink and adhesive curing, medical procedures, and germicidal disinfection. However, before emerging UV LED technologies can displace LPMV lamps, the efficiency and reliability of these sources must meet the user’s expectations in each application. An earlier report focused on the construction and initial performance of commercial UV LED products in radiometric and current-voltage (IV) tests [1]. This report focuses on the long-term performance and reliability of the same set of commercial products. The intent of this report is to provide to the lighting industry a benchmark of the state of UV LEDs as of mid-2021 when these products were purchased. Understanding the failure modes and failure rates of UV LEDs is important in improving UV product reliability at the LED, lamp, and luminaire level and is critical to developing products with higher efficiency, lower carbon footprint, and significantly reduced environmental impact than LPMV lamps.

42 ENGINEERING↗
DOE OSTI2022

Opportunities for Utilization of Low-Cost Algae Resources: Techno-Economic Analysis Screening for Near-Term Deployment (Parts 1 and 2)

This report presents a comprehensive techno-economic analysis (TEA) for the production, collection, or procurement of several low-cost algae resources that may otherwise be considered "waste" biomass materials today, as well as the utilization of these materials through exemplary conversion processes to produce renewable fuels and chemicals. In contrast to conventional TEA models attributed to large-scale algae "farming" approaches, which may be able to produce substantially more biomass and thus fuels/products at a national scale in the future, this assessment focuses on understanding opportunities and costs for such "waste" algal biomass resources as may be available at considerably lower cost today. Economics for base case assumptions and a range of sensitivity scenarios are presented, employing conversion technologies that are simple and well understood, and thus may be deployed at smaller community scale in the near term, as a means to support and expand a nascent algae industry on the way to employing a larger commercial algae farm approach for commodity-scale production. Specifically, three algal biomass resources are considered in this assessment, as may be sourced from (1) municipal wastewater treatment (WWT) utilizing algae in place of more conventional technologies for nitrogen/phosphorus removal, (2) collection and removal of harmful algal bloom (HAB) biomass as proliferates in certain inland water bodies, and (3) procurement of residual biomass following commercial lipid extraction (EXT) operations performed at smaller scale by industry today focused on higher-value nutraceutical applications. These three resources are evaluated through two conversion pathways: (1) combined algal biomass processing (CAP) through a simple/low-complexity configuration, and (2) anaerobic digestion (AD). The CAP pathway produces liquid fuels and chemical coproducts (polymer for off-site upgrading to bioplastics), whereas the AD pathway produces biogas (specifically renewable natural gas [RNG]) and crop fertilizer coproducts. To streamline the discussion, this report is broken into two sections: Part 1 focuses on WWT-derived biomass, and Part 2 on HAB and EXT biomass.

09 BIOMASS FUELS↗
DOE OSTI2023

Application of Particle Accelerators to Mitigate Energy and Climate Change Problems Facing America

Reliable CO 2 -free baseload power is needed to address ever-increasing demands for electricity while minimizing adverse climate change. Diversified power supply provided by solar, wind, geothermal, and nuclear reactors can displace the use of fossil fuels. The United States (U.S.) is taking a new look at nuclear power as a source of electrical energy and the nuclear industry is proposing new approaches which may minimize capital costs. However, nuclear power comes with a variety of technical problems. Chief among those is managing the used fuel from nuclear reactors. No long-term, practicable solution to this problem is available. The lack of progress on a comprehensive waste management strategy restricts growth in the nuclear power industry and minimizes the role that nuclear energy may serve as part of a zero-carbon future (Bahr, 2021). According to the Nuclear Waste Policy Act of 1982, as amended, the U.S. Government has possession of the used reactor fuel and incurs large annual storage fees paid to utilities to store and safeguard the accumulated used fuel. In effect, short term on-site storage of nuclear waste is the current waste management plan. The amount of used reactor fuel in the U.S. is approximately 80,000 metric tons. While no geologic repository exists within the U.S., the potential site at Yucca Mountain, NV would accommodate 70,000 metric tons, which fails to meet current and future needs. Given the technical and political challenges associated with establishing a single geological storage site, it is necessary for the U.S. to implement technologies that improve the suitability of geological storage by reducing the volume and radiotoxicity of stored material. No extant technology meets this need. Accelerator driven waste burners have been proposed as a scalable method to process used nuclear fuel, however considerable technical challenges remain which impede commercialization. Innovations in design require investigation of novel materials, development of accurate models and simulations, and a comprehensive assessment of safety and performance. This proposal elaborates how LANL is uniquely positioned to make key contributions to this area of research.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Modifications to Solar Titan-130 Combustion Systems for Efficient, High Turndown Operation

The project team of Southwest Research Institute® (SwRI®), Solar Turbines Incorporated (Solar), the Electric Power Research Institute (EPRI), the University of California, Irvine (UCI), and the Georgia Institute of Technology (Georgia Tech) investigated methods to allow higher efficiency part-load operation of a Solar Titan 130 gas turbine. The objective was to develop a low-emission combustion system capable of sustaining combustion and avoiding lean blowout during high turndown operation, which would allow the gas turbine to operate as efficiently as possible at part load. Currently, electric utility markets are beginning to experience substantial increases in renewable energy generation. Some of these renewable energy sources have highly variable output in an uncontrolled manner. In order to maintain grid stability, there is a need for power plants to ramp up power to the grid rapidly to make up for drops in renewable generation. This is often termed spinning reserve, but the size of this reserve may need to increase as renewable penetration into the electric utility market increases. Small combined heat and power (CHP) power plants provide a promising option for meeting this spinning reserve requirement. In order to operate in spinning reserve while still meeting the heat requirements for the CHP, the gas turbine needs to operate efficiently at very low loads. Efficient, high turndown operations in this engine are limited by the lean flammability limit of the premixed combustion system. This project sought enhance the lean operability range of the Titan 130 combustor. First, the project team participated in a brainstorming activity and ultimately selected two concepts to explore: fuel augmentation with hydrogen (H2) to improve the stability at lean operating conditions and modifications to the fuel nozzle to improve the emissions performance at lean operating conditions. Analytical and laboratory investigations were accomplished by UCI to investigate the efficacy of H2 addition at improving lean blow out (LBO) limits and the resulting emissions. These investigations used a variety of chemical reactor network (CRN) and CFD models, validated against laboratory data, to model the impact of H 2 and inform the experimental efforts accomplished by SwRI and Solar. Ultimately, both the CRN and CFD models yielded generally good agreement with the experimental data below a particular temperature threshold. Atmospheric tests of a full-scale T130 annular combustor were performed at SwRI facilities in San Antonio, Texas, to investigate the use of H 2 addition. For these tests, the T130 combustion system remained largely unchanged; minor modifications were performed to the fuel ducting to allow for the safe use of H 2 . The test ultimately demonstrated that the addition of H 2 to the fuel mixture significantly increased the AFR ratio at which the combustor could operate. This improvement to the LBO limit should allow for less use of compressor bleed and less throttling needed by the inlet guide vanes (IGV). This in turn could result in more efficient operation of the gas turbine at lower load points. The second modification explored in this work was a direct modification to the T130 injector. The project team hypothesized that modifications to the pilot of the T130 injector could provide lower emissions at high turn-down operations. These modifications were manufactured and explored by the team at Solar. High pressure rig tests, originally slated to occur at SwRI, were ultimately accomplished by Solar to maintain overall project budget and mitigate cost growth attributable to supply chain issues and inflation. The pressurized rig tests ultimately showed that the SwRI Project No. 18.24153 - DE-EE0008415 Page 2 Final Technical Report January 24, 2024 modifications did not significantly alter the performance of the combustion system at the high turn-down conditions; both the modified injectors and the baseline configuration exhibited elevated emissions comparted to the full-load operating condition. A final set of studies performed by EPRI investigated the benefit-cost of flexible CHP as well as a grid interconnection study for the California Independent System Operator (CAISO) grid. These studies considered: traditional CHP with no spinning reserve available for on-demand grid support, 50% flexible CHP where 50% of the machine’s capacity is consumed by on-site baseload operations while providing an additional 50% capacity for on-demand grid support, and 70% flexible CHP where 70% of capacity is consumed on-site by baseload operations and 30% is available for on-demand grid support. In all cases, the analyses showed a benefit-to-cost ratio greater than unity implying a positive net present value for all configurations. However, the traditional CHP showed the most economic benefit. These results are sensitive to several factors, many of which are not fully known and may vary over time. Thus site owners must be convinced that taking up the increased costs and risks from flexible CHP would be worth implementing. As the grid in California and across the country transition to incorporate larger renewable energy generation, flexible CHP can provide much needed operating reserves and dispatchability. Alternative fuel options, such as hydrogen blending and biofuels, may also lower carbon intensities of CHP. Flexible CHP should be examined in the evolving market to understand innovative business models, changes market rules and services, and new technologies.

20 FOSSIL-FUELED POWER PLANTS↗
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 OSTI2023

Multi-Source Data Aggregation and Real-Time Anomaly Classification and Localization in Power Distribution Systems

This paper proposes a real-time anomaly location and classification framework for power distribution systems to simultaneously determine the type of anomaly (i.e., short-circuit fault, cyber attack, DER switching) and its location. The proposed framework employs the data aggregation module to collect the measurement data from multiple field devices operating at different sampling rates, such as protection relays and D-PMUs. The output of the data aggregation is then fed into a multi-task learning-based long-based short-term memory (MTL-LSTM) to classify the type of anomaly and the location in two separate tasks. The proposed MTL-LSTM approach can be utilized in real-time operation in order to distinguish between normal and several anomalous operations and locate the anomaly. The proposed framework is tested on a modified IEEE 33-bus test feeder benchmark that integrates solar generation and energy storage. Furthermore, the results show that the proposed framework can locate and classify anomalies for several operation conditions with more than 96% accuracy. Further experiments highlight the impact of aggregating multiple sources of data on the performance of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Evaluating Probability of Containment Effectiveness at a GCS Sites using integrated assessment modeling approach with Bayesian decision Networks

Improved scientific and engineering understanding of the behavior of geologic CO2 storage together with established regulatory framework and incentive structures raise the prospects for accelerated, large-scale deployment of this greenhouse gas emissions reduction approach. Incentive structures call for the establishment of appropriate verification and accounting approaches to support claims of the integrity of a geologic storage complex and to justify taking credit for long-term storage. In this study, we present a framework for assessing the probability of containment effectiveness over the lifetime of a geologic carbon storage site (e.g., after 70 years of injection and post-injection site performance) using forward stochastic model realizations based on site characterization data and using a monitoring-informed Bayesian network based on hypothetical detectability from surface seismic surveys over the site injection and post-injection phases. The National Risk Assessment Partnership’s open-source Integrated Assessment Model (NRAP-Open-IAM) was utilized to develop an ensemble of 10,000 a priori stochastic forecasts of CO2 containment. Those simulations were used to train the Bayesian network model to estimate the prior probabilities of the CO2 leakage mass into overlying, monitorable aquifers considering the uncertainties in the reservoir properties, permeability of potentially leaky wells and the overlying aquifers. The conditional probabilities in the Bayesian network were either learned from the NRAP-Open-IAM simulations or derived from the predefined detection thresholds for the monitoring method. Observations obtained from monitoring, over time during the site operation phases were then used to generate updated posterior probabilities of containment (and any loss from containment) in the Bayesian network by propagating the prior probabilities through the conditional probabilities. We demonstrate how to construct and use the Bayesian network for verifying the long-term storage complex effectiveness informed by monitoring based on the NRAP-Open-IAM simulations previously developed for the FutureGen 2.0 site. This approach may have relevance for stake holders to demonstrate secure geologic storage, provide a defensible, probabilistic approach to claim credit for geologic storage, and to estimate the likelihood that any fraction of the claimed credit may need to be refunded to the creditor based on available monitoring information.

Bayesian network, Risk assessment, Monitoring, car↗
DOE OSTI2023

A multi-MeV alpha particle source via proton-boron fusion driven by a 10-GW tabletop laser

Nuclear fusion between protons and boron-11 nuclei has undergone a revival of interest thanks to the rapid progress in pulsed laser technology. Potential applications of such reaction range from controlled nuclear fusion to radiobiology and cancer therapy. A laser-driven fusion approach consists in the interaction of high-power, high-intensity pulses with H- and B-rich targets. We report on an experiment exploiting proton-boron fusion in CN-BN targets to obtain high-energy alpha particle beams (up to 5 MeV) using a very compact approach and a tabletop laser system with a peak power of ~10 GW, which can operate at high-repetition rate (up to 1 kHz). The secondary resonance in the cross section of proton-boron fusion (~150 keV in the center-of-mass frame) is exploited using a laser-based approach. The generated alpha particles are characterized in terms of energy, flux, and angular distribution using solid-state nuclear-track detectors, demonstrating a flux of ~10 5 particles per second at 10 Hz, and ~10 6 per second at 1 kHz. Hydrodynamic and particle-in-cell numerical simulations support our experimental findings. Potential impact of our approach on future spread of ultra-compact, multi-MeV alpha particle sources driven by moderate intensity (10 16 -10 17 W/cm 2 ) laser pulses is anticipated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗