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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 OSTI2022

Exploring the benefits of utilizing small modular device for sustainable and flexible shale gas water management

Growing shale gas extraction in recent years has triggered wide discussions on the associated freshwater requirement and wastewater management. Many optimization approaches have been developed for shale gas water management; however, most of the studies assumed permanent utilization of wastewater treatment facilities with fixed capacities. Considering the rapidly declining characteristics of shale gas wastewater production, these treatment facilities could remain largely underutilized after the first few months/years of production, making them less economically attractive. To maximize the capacity utilization of treatment facilities and further improve the economic performance of shale gas development, this study develops a systematic optimization framework, where the capacity strategy of conventional treatment facilities and utilization of the recent concept of modular manufacturing are both considered for flexible shale gas water management. The proposed mixed-integer linear programming (MILP) model simultaneously optimizes the design and planning of integrated shale gas and water supply chain, with a focus on capacity planning for both large-scale conventional treatment facilities and small-scale modular devices. A series of Marcellus-based case studies are performed to illustrate the applicability of the proposed model and provide general insights into the trade-offs between the multiple types of treatment facilities. The optimization results reveal that the combinatorial utilization of conventional facilities and modular devices for wastewater treatment (66% by conventional facilities and 34% by modular devices) brings 9.3% more reused water for other well development and 6.2% savings in water-related costs, compared to flexible management of only conventional facilities. Furthermore, this work suggests that taking modular device as auxiliary equipment for shale gas water management is most beneficial to increase the capacity utilization of treatment facilities and achieve a more economic and sustainable shale gas production system.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2026

Leveraging Hydration Forces for Size-Specific Nanoparticle Enrichment with a Redox-Responsive Silica-Binding Elastin-Like Polypeptide

Elastin-like polypeptides (ELPs) are low-complexity proteins that coacervate above a characteristic lower critical solution temperature (LCST). While the thermoresponsiveness of ELPs has been widely exploited in the biomedical and biomaterials fields, their ability to mediate nanoparticle assembly below their transition temperature remains largely unexplored. Here, we show that unmodified ELPs induce the reversible flocculation of silica nanoparticles (SiNPs) by forming backbone hydrogen bonds with surface silanols. Interparticle bridging is modulated by ELP length and concentration and by the presence of N- and C-terminal anchoring groups such as a cysteine residue and a Car9 silica-binding peptide. Using a redox-responsive fusion protein consisting of disulfide-bonded ELP domains terminated by Car9 segments, we stabilize 20 nm SiNPs under oxidizing conditions while triggering particle flocculation upon addition of reductant. We find that SiNP sedimentation under reducing conditions exhibits a sharp dependency on particle size that arises from the curvature-dependent structure of surface silanols. While the isolated silanols of SiNPs smaller than 30 nm are efficiently engaged by the ELP domains of Car9-anchored proteins, repulsion forces associated with the presence of a layer of molecular water together with increased electrostatic repulsion preclude efficient engagement of H-bonded silanols displayed on the surface of SiNPs larger than 60 nm. We harness these findings to selectively enrich SiNPs based on size and expand the concept to titania (TiO2) by demonstrating that rutile nanoparticles can be stabilized or sedimented with solid-binding ELPs by adjusting the solution pH to promote or discourage the formation of a hydration layer. These strategies should prove broadly useful for the separation of other oxides and their polymorphs and provide a tunable strategy for nanoparticle assembly and bioinspired colloidal design.

ELP↗
DOE OSTI2022

LICS Modeling [Slides]

We propose to design a new diagnostic based on laser inverse Compton scattering (LICS) to study the dynamics of runaway electron formation during killer-pellet triggered disruptions in DIII-D, and their subsequent loss. Obtaining a better understanding of transient runaway electrons (and how to suppress them) is one of the highest priorities of the US fusion program. To enable this, we need better measurements of the runaway electron population during and after disruptions. We intend to measure point-wise time-resolved spatial profile and energy distributions of the runaway electrons while they are in the core of the tokamak plasma. While LICS measurements of relativistic e-beams have been successfully made on accelerators, they have never been done in a tokamak. We bring two innovations to this diagnostic concept which should enable 10 times better signal-to-noise ratios than previously envisioned. In particular, we will marry bright short pulse (10’s of picosecond) laser technologies with the availability of short-pulse gated x-ray imagers developed at Los Alamos for the National Ignition Facility (NIF), to reject noise generated by the tokamak and plasma environment. We will generate a Conceptual Physics Basis, a Preliminary Design, and a Final Design package, with associated DIII-D reviews, along with prototype component testing for the diagnostic over the course of the two year duration of this proposal.

42 ENGINEERING↗
DOE OSTI2021

Exsolution Synthesis of Nanocomposite Perovskites with Tunable Electrical and Magnetic Properties

Nanostructured functional oxides play an important role in enabling clean energy technologies and novel memory and processor devices. Using thin-film La 0.6 Sr 0.4 FeO 3 (LSF) as a model system, the novel utility of exsolution in fabricating self-assembled metal oxide nanocomposites with tunable functionalities is shown. Exsolution triggers the formation of metallic iron (Fe 0 ) nanoparticles, Ruddlesden–Popper domains, and nm-scale percolated Fe-deficient channels in LSF. Combining multimodal characterization with numerical modeling, the chemical, magnetic, and electrical properties of the exsolution-synthesized nanocomposite at different stages of Fe 0 exsolution as well as during redox cycling are assessed. After exsolution, the electronic conductivity of the nanocomposite LSF increased by more than two orders of magnitude. Based on numerical analysis representing all the constituents, it is expected that this increase in conductivity originates mainly from the Fe-deficient percolating channels formed during exsolution. Moreover, the exsolved nanocomposite is redox-active even at moderate temperatures. Such redox capabilities can enable dynamic control of the nanocomposite functionality by tailoring the oxygen non-stoichiometry. This concept is demonstrated with a continuous modulation of magnetization between 0 and 110 emu cm -3 . These findings point out that exsolution may serve as a platform for scalable fabrication of complex metal oxide nanocomposites for electrochemical and electronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A reinforcement learning approach to long-horizon operations, health, and maintenance supervisory control of advanced energy systems

In this work, we develop a Reinforcement Learning (RL) approach to the supervisory control problem for advanced energy systems, such as novel nuclear reactors and other demand-driven, mission-critical, and component-health-sensitive energy plants. The inclusive problem landscape considered captures the stochastic confluence of plant performance, component health evolution, power demand from the grid, diverse maintenance actions, and operator-defined goals and constraints, all considered over meaningfully long-enough reasoning horizons. Key aspects of the proposed approach are a receding horizon control-inspired technique dictating time- or event-triggered supervisory policy (re-)constructions, as well as additional capability-enabling contributions such as timescale compression, to handle long reasoning horizons and uncertainty in parts of the problem, and practical yet demonstrably-effective handling of hybrid action spaces with continuous and discrete decision variables. The resulting algorithm consists of a simulation-based RL agent constructing stochastic supervisory control policies over nontrivial action spaces and for long horizons, applying the learned policy to the system for a much shorter interval, and perpetually repeating, to construct the next long-horizon policy. That next policy will only be applied, again, for a short interval, yet originally far-in-time events move progressively closer, their associated uncertainty decreases, and new events and aspects enter the reasoning horizon. The proposed methodology bridges fundamental receding horizon concepts with the unequivocally stronger and more scalable reasoning of contemporary RL. Numerical examples using Soft Actor–Critic Deep RL illustrate the operation and efficacy of the proposed technique for a power plant tasked with health-aware load following missions in a dynamic electricity market landscape.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Engineering of Self‐Aggregation‐Resistant MnO 2 Heterostructure with A Built‐in Field for Enhanced High‐Mass‐Loading Energy Storage

Abstract Although MnO 2 has been intensively investigated for energy storage, further applications are limited by van der Waals force‐triggered self‐aggregation that always leads to poorly exposed active sites and compromised reaction dynamics, especially under high‐mass‐loading conditions. Herein, by synergistically coupling interfacial modulation with the Kirkendall effect, this work achieves in situ topological structure reorganization of MnOOH toward the high‐aspect‐ratio MnO 2 heterostructure (Heter‐MnO 2 ) with fully exposed active sites, which is ready to assemble into self‐supporting high‐mass‐loading film (30 mg cm −2 ) with restrained self‐aggregation. Theoretical calculation and dynamics analysis results demonstrate the generation of the built‐in field within the heterostructure, thus enhancing the electronic‐transfer and ionic‐adsorption/transport rates. As such, the 30 mg cm −2 Heter‐MnO 2 electrode achieves a superior areal capacitance of 4762 mF cm −2 at 1 mA cm −2 and a sound rate performance (79% at 100 mA cm −2 ) comparable to those of low‐mass‐loading/thin‐film electrodes. As a proof of concept, the fabricated planar interdigital quasi‐solid‐state symmetric micro‐supercapacitor (MSC) based on the Heter‐MnO 2 electrode can deliver a remarkable areal capacitance of 181 mF cm −2 and a considerable volumetric energy density of 10.3 mWh cm −3 . This methodology highlights the promise of surface/interface chemistry modulation for the configuration of easy‐to‐integrate hierarchical nanostructures to better meet practical energy applications.

Chemistry↗
DOE OSTI2021

Modulating the Surface Ligand Orientation for Stabilized Anionic Redox in Li‐Rich Oxide Cathodes

Abstract Anionic redox chemistry is emerging as a key concept in the development of high‐energy lithium‐ion batteries, as it enables a nearly doubled charge storage capacity, aiding the development of high‐capacity batteries. However, the anionic reactivity is frequently irreversible from charge to discharge, leading to rapid decay of the capacity and voltage of batteries over long‐term cycling. Although the possibility of controlling the anionic redox reactions by tuning the geometric and electronic structures has recently been proposed, the implementation of this strategy is still a critical challenge. Herein, a strategy is proposed to improve the anionic redox reversibility of a model anionic redox active cathode material, Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2 , by tuning the surface ligand geometry via the growth of a lattice‐compatible spinel LiCoO 2 coating layer on the particle surface. Detailed local structure and first principles investigations reveal that the shape and orientation of the octahedral layer in the host lattice are modified. Accordingly, a two‐band oxygen redox behavior is triggered in the ligand‐orientation‐regulated Li‐rich cathode, leading to enhanced reversibility, and thus, remarkably improved capacity and voltage retention over cycling. This study highlights the importance of controllable ligand orientation, carving a new path for the development and design of Li‐rich cathodes in the future.

Liu, Yanchen↗
DOE OSTI2024

Development of a New Aggregation Method to Remove Nanoplastics from the Ocean: Proof of Concept Using Mussel Exposure Tests

The overproduction and mismanagement of plastics has led to the accumulation of these materials in the environment, particularly in the marine ecosystem. Once in the environment, plastics break down and can acquire microscopic or even nanoscopic sizes. Given their sizes, microplastics (MPs) and nanoplastics (NPs) are hard to detect and remove from the aquatic environment, eventually interacting with marine organisms. This research mainly aimed to achieve the aggregation of micro- and nanoplastics (MNPs) to ease their removal from the marine environment. To this end, the size and stability of polystyrene (PS) MNPs were measured in synthetic seawater with the different components of the technology (ionic liquid and chitosan). The MPs were purchased in their plain form, while the NPs displayed amines on their surface (PS NP-NH2). The results showed that this technology promoted a significant aggregation of the PS NP-NH2, whereas, for the PS MPs, no conclusive results were found, indicating that the surface charge plays an essential role in the MNP aggregation process. Moreover, to investigate the toxicological potential of MNPs, a mussel species (M. galloprovincialis) was exposed to different concentrations of MPs and NPs, separately, with and without the technology. In this context, mussels were sampled after 7, 14, and 21 days of exposure, and the gills and digestive glands were collected for analysis of oxidative stress biomarkers and histological observations. In general, the results indicate that MNPs trigger the production of reactive oxygen species (ROS) in mussels and induce oxidative stress, making gills the most affected organ. Yet, when the technology was applied in moderate concentrations, NPs showed adverse effects in mussels. The histological analysis showed no evidence of MNPs in the gill’s tissues.

Cid-Samamed, Antonio (ORCID:0000000205073394)↗
DOE OSTI2024

Large eddy simulation of lean blow-off in swirl-stabilized flame with the subgrid dissipation concept

The lean blow-off mechanism of the premixed swirl flame is numerically investigated by large eddy simulation (LES) with the subgrid dissipation concept (SDC) combustion model. Three simulated cases cover stable, near blow-off, and transient conditions. Compared with the experiment, the LES-SDC approach captures the flow and combustion features for stable and near blow-off conditions. More importantly, the predictions of the blowoff procedure and duration agree satisfactorily with the experiment, indicating that the LES-SDC approach is a promising tool for predicting strong, unsteady turbulent combustion processes. Further, the numerical results are used to investigate the blow-off mechanism. Two stages in the blow-off procedure are specified. The first is the necking and extinction of the downstream flame surface, and the second is the shrinking of the upstream flame surface. The blow-off mechanism is well explained by the theory of stretched flame extinction. At the end of the recirculation zone, the large negative radial velocity pushes the flame to the central line. The combustion process here can be abstracted as the stretched counter-flame of the reactant-reactant configuration. The excessive flame stretch dominates the flame extinction and triggers the blow-off event. The upstream flame resists the intense stretch with the help of hot product recirculation, and the combustion here can be idealized as the counter-flame of the reactant-product configuration. The alignment of the temperature gradient and flow velocity, together with the excessive stretch, clearly indicates the tendency of flame local extinction. A Damköhler number-based blow-off criterion is raised from the mean flow strain rate and laminar flame bulk extinction strain rate.

42 ENGINEERING↗
DOE OSTI2024

Towards predictive control of reversible nanoparticle assembly with solid-binding proteins

Although a broad range of ligand-functionalized nanoparticles and physico-chemical triggers have been exploited to create stimuli-responsive colloidal systems, little attention has been paid to the reversible assembly of unmodified nanoparticles with non-covalently bound proteins. Previously, we reported that a derivative of green fluorescent protein engineered with oppositely located silica-binding peptides mediates the repeated assembly and disassembly of 10-nm silica nanoparticles when pH is toggled between 7.5 and 8.5. We captured the subtle interplay between interparticle electrostatic repulsion and their protein-mediated short-range attraction with a multiscale model energetically benchmarked to collective system behavior captured by scattering experiments. Here, in this work, we show that both solution conditions (pH and ionic strength) and protein engineering (sequence and position of engineered silica-binding peptides) provide pathways for reversible control over growth and fragmentation, leading to clusters ranging in size from 25 nm protein-coated particles to micrometer-size aggregate. We further find that the higher electrolyte environment associated with successive cycles of base addition eventually eliminates reversibility. Our model accurately predicts these multiple length scales phenomena. The underpinning concepts provide design principles for the dynamic control of other protein- and particle-based nanocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Emittance preservation for the electron arm in a single PWFA-LC stage using quasi-adiabatic plasma density ramp matching sections

Plasma-based acceleration (PBA) is being considered for a next generation linear collider (LC). In some PBA-LC designs for the electron arm, the extreme beam parameters are expected to trigger background ion motion within the witness beam, which can lead to longitudinally varying nonlinear focusing forces and result in an unacceptable emittance growth of the beam. To mitigate this, we propose to use quasi-adiabatic plasma density ramps as matching sections at the entrance and exit of each stage. We match the witness electron beam to the low density plasma entrance, where the beam initially has a large matched spot size so the ion motion effects are relatively small. As the beam propagates in the plasma density upramp, it is quasi-adiabatically focused, and its distribution maintains a non-Gaussian equilibrium distribution in each longitudinal slice throughout the process, even when severe ion collapse has occurred. This only causes small amounts of slice emittance growth. The phase mixing between slices with different betatron frequencies leads to additional projected emittance growth within the acceleration stage. A density downramp at the exit of an acceleration section can eliminate much of the slice and projected emittance growth as the beam and ion motion adiabatically defocuses and decreases, respectively. Simulation results from QuickPIC with Azimuthal Decomposition show that within a single acceleration stage with a 25 GeV energy gain, this concept can limit the projected emittance growth to only ∼2% for a 25 GeV, 100 nm emittance witness beam and ∼20% for a 100 GeV, 100 nm normalized emittance witness beam. The trade-off between the adiabaticity of the plasma density ramp and the initial ion motion at the entrance for a given length of the plasma density ramp is also discussed.

Physics↗
DOE OSTI2021

The case for digital twins in metal additive manufacturing

The digital twin (DT) is a relatively new concept that is finding increased acceptance in industry. A DT is generally considered as comprising a physical entity, its virtual replica, and two-way digital data communications in-between. Its primary purpose is to leverage the process intelligence captured within digital models—or usually their faster-solving surrogates—towards generating increased value from the physical entities. The surrogate models are created using machine learning based on data obtained from the field, experiments and digital models, which may be physics-based or statistics-based. Anomaly detection and correction, and diagnostic closed-loop process control are examples of how a process DT can be deployed. In the manufacturing industry, its use can achieve improvements in product quality and process productivity. Metal additive manufacturing (AM) stands to gain tremendously from the use of DTs. This is because the AM process is inherently chaotic, resulting in poor repeatability. However, a DT acting in a supervisory role can inject certainty into the process by actively keeping it within bounds through real-time control commands. Closed-loop feedforward control is achieved by observing the process through sensors that monitor critical parameters and, if there are any deviations from their respective optimal ranges, suitable corrective actions are triggered. The type of corrective action (e.g. a change in laser power or a modification to the scanning speed) and its magnitude are determined by interrogating the surrogate models. Because of their artificial intelligence (AI)-endowed predictive capabilities, which allow them to foresee a future state of the physical twin (e.g. the AM process), DTs proactively take context-sensitive preventative steps, whereas traditional closed-loop feedback control is usually reactive. Apart from assisting a build process in real-time, a DT can help with planning the build of a part by pinpointing the optimum processing window relevant to the desired outcome. Again, the surrogate models are consulted to obtain the required information. In this article, we explain how the application of DTs to the metal AM process can significantly widen its application space by making the process more repeatable (through quality assurance) and cheaper (by getting builds right the first time).

36 MATERIALS SCIENCE↗
DOE OSTI2022

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques — A proof of concept

Here, we investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Using Cosmic Ray Muons to Assess Geological Characteristics in the Subsurface

Cosmic rays are energetic nuclei and elementary particles that originate from stars and intergalactic events. The interaction of these particles with the upper atmosphere produces a wide range of secondary particles that reach the surface of the earth, of which muons are the most prominent. With enough energy, muons can travel up to a few kilometers beneath the surface of the earth before being stopped completely. The terrestrial muon flux profile and associated zenith angle can be utilized to determine geological characteristics of a location (e.g., rock overburden and density) without having to use conventional methods such as boreholes. This work uses a low-power plastic scintillator-based muon detection system as a prototype for this non-destructive geological assay methodology. Four custom designed 102 cm x 51 cm x 5 cm plastic scintillation panels are used to realize two orthogonal detection planes. Optical photons from each scintillation panel are read using OnSemi J-Series 4x4 silicon photomultiplier (SiPM) arrays in conjunction with preamplifiers. Simultaneous triggers between detectors from two planes indicate a coincidence event which is recorded using the QuarkNet data acquisition system (DAQ) from Fermi National Accelerator Laboratory. A custom detector holder was designed to securely mount the detection system and rotate the panels along the zenith to collect data at variable angles. In order to quantify the systematic uncertainties associated with the detector, such as energy depositions and angular resolution of the detector design, a Monte Carlo (MC) simulation using Geant4 is being developed. Cosmic ray flux prediction will be included in the project by adding the CORSIKA MC code to the simulation toolchain. Simulated and experimental data will drive the development and validation of a reconstruction algorithm that, upon completion, is expected to predict average overburden and rock density. Extended detector exposure to muons can be used as a means to understand changes in the surrounding environment like rock porosity. On the experimental front, muons will initially be measured at the surface, establishing the baseline flux. This is followed by recording the muon flux at variable depths and zenith angles, where the data will be used by the reconstruction algorithm to predict the overburden. The result will be benchmarked against geological surveys. The measured flux data will also be used to benchmark independent and established models. Successful proof-of-concept demonstration of this technology can open doors for long term non-invasive geological monitoring. The detector design, experimental methodology, and the benchmarking efforts are detailed in this work.

Gadey, Harish Reddy↗
DOE OSTI2021

A Heterogeneous System for Eagle Detection, Deterrent, and Wildlife Collision Detection for Wind Turbines (Final Technical Report)

This report summarizes the design, implementation, and test of an integrated system for automated detection and deterrence of eagles, with included wind turbine blade strike detection and imaging functionality. A machine learning approach was used in conjunction with a 360° camera system for automated detection and classification of golden eagles. This was developed using footage obtained from trained golden eagles and other raptors, in collaboration with wildlife biologists and professional bird handlers. Oregon State University developed a visual deterrent system, which uses inflatable anthropomorphic sculptures with random, kinetic motion to deter eagles, and conducted limited field testing on live eagles; the deterrent can be triggered by the visual detection of eagles using the vision system. Finally, a multi-sensor module was developed that is mounted at the turbine blade root. This module measures vibration and other motions to detect blade strikes, and an integrated on-blade camera captures an image of any impacting objects. Long-term, this blade strike detection system is intended to support an automatic monitoring and certification system for the eagle detection and deterent system. Independent field testing of each system component is described. Testing of the integrated system on an operational wind turbine was conducted across three separate field tests. This includes multi-day fields tests on a General Electric 1.5MW wind turbine at the National Renewable Energy Laboratory (NREL) National Wind Technology Center (NWTC) in Boulder, CO in October 2018 and July 2019; installation procedures, test procedures, and a summary of collected data are presented. A third multi-day on-turbine field test is also presented, which was performed using a General Electric 1.5MW wind turbine at the North American Wind Research and Training Center (NAWRTC) at Mesalands Community College, Tucumcari, NM in April 2019. Across these field tests, the vision system was demonstrated using unmanned aerial vehicles (UAV), and the eagle classification algorithm was not tested; the visual deterrent system was demonstrated, including automatic, remote deployment following surrogate visual detections; and, multi-sensor on-blade data was recorded across multiple wind turbine operational conditions and through more than 100 surrogate blade strikes using soft projectiles, including the successful demonstration of automatic image capture of striking objects. This data set was also used for offline development and validation of enhanced collision detection algorithms. As summarized in this report, the development and field validation of an integrated detection, deterrent, and blade collision detection system represents a critical proof of concept for future technology development of related detection and deterrent technologies, where both deterrent as well as collision detection recording devices are needed for future siting, monitoring, and operation of wind turbine installations, both onshore and offshore.

17 WIND ENERGY↗
DOE OSTI2024

Roadmap for Optical Metasurfaces

Metasurfaces have recently risen to prominence in optical research, providing unique functionalities that can be used for imaging, beam forming, holography, polarimetry, and many more, while keeping device dimensions small. Despite the fact that a vast range of basic metasurface designs has already been thoroughly studied in the literature, the number of metasurface-related papers is still growing at a rapid pace, as metasurface research is now spreading to adjacent fields, including computational imaging, augmented and virtual reality, automotive, display, biosensing, nonlinear, quantum and topological optics, optical computing, and more. At the same time, the ability of metasurfaces to perform optical functions in much more compact optical systems has triggered strong and constantly growing interest from various industries that greatly benefit from the availability of miniaturized, highly functional, and efficient optical components that can be integrated in optoelectronic systems at low cost. This creates a truly unique opportunity for the field of metasurfaces to make both a scientific and an industrial impact. Furthermore, the goal of this Roadmap is to mark this “golden age” of metasurface research and define future directions to encourage scientists and engineers to drive research and development in the field of metasurfaces toward both scientific excellence and broad industrial adoption.

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

The continuous readout stream of the MicroBooNE liquid argon time projection chamber for detection of supernova burst neutrinos

The MicroBooNE continuous readout stream is a parallel readout of the MicroBooNE liquid argon time projection chamber (LArTPC) which enables detection of non-beam events such as those from a supernova neutrino burst. The low energies of the supernova neutrinos and the intense cosmic-ray background flux due to the near-surface detector location makes triggering on these events very challenging. Instead, MicroBooNE relies on a delayed trigger generated by SNEWS (the Supernova Early Warning System) for detecting supernova neutrinos. The continuous readout of the LArTPC generates large data volumes, and requires the use of real-time compression algorithms (zero suppression and Huffman compression) implemented in an FPGA (field-programmable gate array) in the readout electronics. In this paper we present the results of the optimization of the data reduction algorithms, and their operational performance. To demonstrate the capability of the continuous stream to detect low-energy electrons, a sample of Michel electrons from stopping cosmic-ray muons is reconstructed and compared to a similar sample from the lossless triggered readout stream.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗