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

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At least 307 records · Page 17

Texture Formation in Polycrystalline Thin Films of All‐Inorganic Lead Halide Perovskite

Abstract Controlling grain orientations within polycrystalline all‐inorganic halide perovskite solar cells can help increase conversion efficiencies toward their thermodynamic limits; however, the forces governing texture formation are ambiguous. Using synchrotron X‐ray diffraction, mesostructure formation within polycrystalline CsPbI 2.85 Br 0.15 powders as they cool from a high‐temperature cubic perovskite (α‐phase) is reported. Tetragonal distortions (β‐phase) trigger preferential crystallographic alignment within polycrystalline ensembles, a feature that is suggested here to be coordinated across multiple neighboring grains via interfacial forces that select for certain lattice distortions over others. External anisotropy is then imposed on polycrystalline thin films of orthorhombic (γ‐phase) CsPbI 3‐ x Br x perovskite via substrate clamping, revealing two fundamental uniaxial texture formations; i) I‐rich films possess orthorhombic‐like texture (<100> out‐of‐plane; <010> and <001> in‐plane), while ii) Br‐rich films form tetragonal‐like texture (<110> out‐of‐plane; <110> and <001> in‐plane). In contrast to relatively uninfluential factors like the choice of substrate, film thickness, and annealing temperature, Br incorporation modifies the γ‐CsPbI 3− x Br x crystal structure by reducing the orthorhombic lattice distortion (making it more tetragonal‐like) and governs the formation of the different, energetically favored textures within polycrystalline thin films.

Steele, Julian A.↗

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↗

Photoenzymatic enantioselective intermolecular radical hydroalkylation

Enzymes are increasingly explored for asymmetric synthesis, but their applications are generally limited by the reactions available to naturally occurring enzymes. Recently, interest in photocatalysis has spurred the discovery of new reactivity from known enzymes. Yet, so far photo-induced enzymatic catalysis has not been used for cross-coupling of two molecules. For instance, intermolecular coupling of alkenes with α-halo carbonyl compounds through a visible-light-induced radical hydroalkylation, which could provide access to important γ-chiral carbonyl compounds, has not yet been achieved by enzymes. The major challenges are the inherent poor photoreactivity of enzymes and the difficulty in stereochemical control of the remote prochiral radical intermediate. Here we show a new-to-nature, visible-light-induced ene-reductase catalysed intermolecular radical hydroalkylation of terminal alkenes with readily available α-halo carbonyl compounds. This method provides an efficient approach to various carbonyl compounds bearing a γ-stereocentre with excellent yields and enantioselectivities (up to 99% yield, 99% enantiomeric excess), which otherwise are difficult to access by chemocatalysis. Mechanistic studies suggest that the substrates/ene-reductase complex formation at the enzyme active site triggers the enantioselective photo-induced radical reaction. Our research further expands the reactivity repertoire of biocatalytic, synthetically-useful asymmetric transformations by the merger of photocatalysis and enzyme catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modification of Fractured Rock Permeability Field Using Polymer Foam to Improve Geothermal System Efficiency

The project aims at developing novel methods for blocking high-permeability pathways in geothermal reservoirs to improve heat exchange efficiency. While the project was at DRI, and now when it has been transferred to UNR, the goal of blocking high-permeability pathways is achieved through targeted injection of heat-sensitive polymer foams, particularly foamed epoxy resins, whose activation and curing are triggered by the ambient thermal field.

15 GEOTHERMAL ENERGY↗

Hypercars: The next industrial revolution

The auto industry -- one-seventh of the GNP, and the highest expression of the Iron Age -- is about to trigger the biggest transformation in industrial structure since the microchip. Ultralight cars molded from net-shape advanced composites can be several-fold lighter than present steel cars, yet safer, sportier, and more comfortable, durable, and beautiful. Modern hybrid-electric drives boost efficiency approximately 1.3-1.5x in heavy steel cars, but approximately 5-20x in ultralight, very slippery plafforms. Synergistically combined into ultralight-hybrid 'hypercars,' these elements can yield state-of-the-shelf family cars that average 150-300+ mi/gal -- twice that with state-of-the-art technologies -- yet can also be superior in all other respects, probably including cost: carbon-fiber monocoques can actually be cheaper to mass-produce that steel unibodies. Designing cars more like aircraft and less like tanks requires not only an approximately 400-500 kg curb mass and very low air and road drag, but also an aerospace philosophy of engineering integration. Mass, cost, and complexity turn out to compound with heavy hybrids but to decompound with ultralight hybrids, owing partly to radical simplification. Excellent aerodynamics, preferable including advanced techniques for passive boundary-layer control, will be the key to successful design integration. Transforming automaking is a competitive and environmental imperative, could form the nucleus of a green industrial Renaissance, and would enhance national security by, among other things, saving as much oil as OPEC now extracts. However, this transformation faces serious cultural barriers. For example, hypercars will be more like computers with wheels than like cars with chips -- they'll have an order of magnitude more code than today's cars -- but Detroit is not a software culture. Just the transition from stamped and welded steel to integrated and adhesive-joined synthetics is difficult enough. Nonetheless, hypercars are rapidly heading to market in the late 1990s, because approximately 25 current and intending automakers are eager to capture their potentially decisive competitive advantages -- including order-of-magnitude reductions in product cycle time, tooling cost, assembly effort, and parts count. Hypercars will succeed, and may well sweep the market, not because of mandates or subsidies, but because of manufacturers' quest for competitive advantage and customers' desire for better, smarter cars.

Lovins, Amory B.↗

Deactivation of redox mediators in lithium-oxygen batteries by singlet oxygen

Non-aqueous lithium-oxygen batteries cycle by forming lithium peroxide during discharge and oxidizing it during recharge. The significant problem of oxidizing the solid insulating lithium peroxide can greatly be facilitated by incorporating redox mediators that shuttle electron-holes between the porous substrate and lithium peroxide. Redox mediator stability is thus key for energy efficiency, reversibility, and cycle life. However, the gradual deactivation of redox mediators during repeated cycling has not conclusively been explained. Here, we show that organic redox mediators are predominantly decomposed by singlet oxygen that forms during cycling. Their reaction with superoxide, previously assumed to mainly trigger their degradation, peroxide, and dioxygen, is orders of magnitude slower in comparison. The reduced form of the mediator is markedly more reactive towards singlet oxygen than the oxidized form, from which we derive reaction mechanisms supported by density functional theory calculations. Redox mediators must thus be designed for stability against singlet oxygen.

25 ENERGY STORAGE↗

Ice nucleation by aerosols from anthropogenic pollution

Formation of ice particles in the atmosphere strongly affects cloud properties and Earth’s climate. While mineral dust has been known as an effective ice nucleating particle, the role of aerosols from anthropogenic pollution in ice nucleation is still under debate. Here we probe the ice nucleation ability of different aerosol types by combining 11-year observations from multiple satellites and cloud-resolving model simulations. We find that, for strong convective systems, ice particle effective radius near the cloud top decreases with increasing loading of polluted continental aerosols, because the ice formation is dominated by homogeneous freezing of cloud droplets that are smaller under more polluted conditions. In contrast, an increase in ice particle effective radius with polluted continental aerosols is found under moderate convection. Our simulations suggest that enhanced heterogeneous ice nucleation and prolonged ice particle growth are key to explaining the positive correlation. The results indicate that polluted continental aerosols contain a significant fraction of ice nucleating particles triggering heterogeneous nucleation. Similar aerosol-ice relationships are observed for dust aerosols, further corroborating the ice nucleation ability of polluted continental aerosols. By catalyzing ice formation, aerosols from anthropogenic pollution can have profound impacts on cloud lifetime and radiative effect as well as precipitation efficiency.

Zhao, Bin↗

End-to-end codesign of Hessian-aware quantized neural networks for FPGAs

Here, we develop an end-to-end workflow for the training and implementation of co-designed neural networks (NNs) for efficient field-programmable gate array (FPGA) hardware. Our approach leverages Hessian-aware quantization of NNs, the Quantized Open Neural Network Exchange intermediate representation, and the hls4ml tool flow for transpiling NNs into FPGA firmware. This makes efficient NN implementations in hardware accessible to nonexperts in a single open sourced workflow that can be deployed for real-time machine-learning applications in a wide range of scientific and industrial settings. We demonstrate the workflow in a particle physics application involving trigger decisions that must operate at the 40-MHz collision rate of the CERN Large Hadron Collider (LHC). Given the high collision rate, all data processing must be implemented on FPGA hardware within the strict area and latency requirements. Based on these constraints, we implement an optimized mixed-precision NN classifier for high-momentum particle jets in simulated LHC proton-proton collisions.

47 OTHER INSTRUMENTATION↗

The Accelerator Neutrino Neutron InteractionExperiment: Design, Construction and Preparationfor First Physics

This thesis covers work performed for the Accelerator Neutrino Neutron Interaction Experiment (ANNIE) between 2015 and 2020. ANNIE is a beamline neutrino experiment located at the Fermi National Accelerator Laboratory in Chicago. Its primary physics goals are the measurement of neutrino interaction cross-sections on oxygen, and a measurement of the multiplicity of final state neutrons from these interactions, both as functions of final state kinematics. In order to achieve these goals ANNIE will be pioneering the use of Large Area Picosecond Photodetectors and the use of gadolinium doping to enhance neutron visibility in a water Cherenkov detector. Over the time period of this thesis the ANNIE detector was constructed, an initial 'Phase I' background run was completed, the detector was decommissioned and then substantially upgraded in preparation for the main 'Phase II' physics run. At the time of writing ANNIE is being re-commissioned, with Phase II data taking anticipated to begin in 2021. During this time I spent 21/2 years on-site contributing to almost all aspects of hardware work, while performing software development for the simulation and analysis frameworks. As my first software task I developed Monte Carlo simulations of the detector response, based on the WCSim framework. While thismore » framework provided a starting point for the tank simulation significant modifications were required to implement the complete ANNIE detector system. This included a rewrite of the geometry, along with modifications to the photosensor definitions, hit collections, digitization, triggering, input and output interfaces, etc. To take advantage of improved modelling of neutrons in Geant4.10 the physics lists were also reimplemented in the new version format. As part of this work I determined performance metrics based on the output files, calculating kinematic acceptance, detector efficiency and expected event rates. My contributions on reconstruction focused primarily on the MRD, for which I implemented two track reconstruction algorithms, specialised for high and low energy muons. The high energy algorithm achieves >90% efficiency for tracks with at least 8 hits, and is robust against dead paddles and unrelated hits. The low energy algorithm performs a search in combination with tank information to provide sensitivity down to a single MRD hit. Early data handling work for the Phase I background run included writing the code for handling TDC hits and performing studies on neutron detection without the requirement of multi-hit coincidence. As the collaboration moved to a new framework for the Phase II analysis I performed a substantial amount of work to develop the codebase, implementing tools to perform tasks such as file IO, data parsing, waveform processing, event building, timestamp alignment, time clustering, hit residual calculation, event visualisation etc. I helped develop the python API for integrating multi-language tools, and ported the framework into a Singularity container to provide a self-contained environment that…« less

43 PARTICLE ACCELERATORS↗

Flg22‐induced Ca 2+ increases undergo desensitization and resensitization

The flagellin epitope flg22, a pathogen-associated molecular pattern (PAMP), binds to the receptor-like kinase FLAGELLIN SENSING2 (FLS2), and triggers Ca 2+ influx across the plasma membrane (PM). The flg22-induced increases in cytosolic Ca 2+ concentration ([Ca 2+ ]i) (FICA) play a crucial role in plant innate immunity. It's well established that the receptor FLS2 and reactive oxygen species (ROS) burst undergo sensitivity adaptation after flg22 stimulation, referred to as desensitization and resensitization, to prevent over responses to pathogens. However, whether FICA also mount adaptation mechanisms to ensure appropriate and efficient responses against pathogens remains poorly understood. Here, we analysed systematically [Ca 2+ ]i increases upon two successive flg22 treatments, recorded and characterized rapid desensitization but slow resensitization of FICA in Arabidopsis thaliana. Pharmacological analyses showed that the rapid desensitization might be synergistically regulated by ligand-induced FLS2 endocytosis as well as the PM depolarization. The resensitization of FICA might require de novo FLS2 protein synthesis. FICA resensitization appeared significantly slower than FLS2 protein recovery, suggesting additional regulatory mechanisms of other components, such as flg22-related Ca 2+ permeable channels. Taken together, we have carefully defined the FICA sensitivity adaptation, which will facilitate further molecular and genetic dissection of the Ca 2+ -mediated adaptive mechanisms in PAMP-triggered immunity.

59 BASIC BIOLOGICAL SCIENCES↗

Metal Oxide-Induced Instability and Its Mitigation in Halide Perovskite Solar Cells

Halide perovskite solar cells (PSCs) have emerged as a promising photovoltaic technology for sustainable energy solutions due to their impressive power conversion efficiency and a path to be manufactured by low-cost, high-throughput methods. To reach PSCs’ full potential for practical implementation, it is crucial to solving the issues related to its long-term operational stability. Furthermore, given that PSCs consist of many layers of dissimilar materials which form multiple internal interfaces, it is prudent to examine whether there exist interfacial interactions, most importantly between transport layers and perovskite absorbers, that can trigger device performance and instability. In this perspective, we bring to the attention of the PSC research community the lesser-known interfacial degradation of halide perovskites promoted by contact with metal oxide transport layers and highlight the deleterious effects on the PSCs’ performance and stability. We also discuss various mitigation strategies that have shown promises to achieve high-performing and stable PSCs.

14 SOLAR ENERGY↗

Size and Structural Control of Mechanoluminescent ZnS:Mn 2+ Nanocrystals for Optogenetic Neuromodulation

Mechanoluminescent materials hold immense potential for various transformative applications, from medical imaging and diagnostics to health monitoring and wearable displays. Conventionally produced as bulk powders or microparticles, they face significant size limitations for advanced applications, particularly in biological systems and microscale devices. Here, this work presents an approach to ZnS:Mn 2+ nanocrystal synthesis that involves self-assembly and subsequent calcination. In addition to effective size control within the nanoscale, this approach promotes the formation of abundant stacking faults, significantly enhancing piezoelectric and mechanoluminescent properties by increasing trap density and reducing trap depth. Unlike mechanoluminescent materials produced using conventional methods, these nanocrystals demonstrate strong mechanoluminescence without requiring UV pre-excitation, and the light emission persists even after mechanical stress is removed. These advantageous properties make them promising candidates for optogenetic neuromodulation, as they can effectively trigger electrical signals in neurons upon ultrasound stimulation both with and without UV pre-excitation. The persistent mechanoluminescence prolongs the duration of neuronal electrical activity, providing an extended temporal window for neuromodulation compared to conventional mechanoluminescent materials. This study provides a scalable method for producing efficient mechanoluminescent nanoparticles and reveals the crucial role of particle size and defect structures in determining their mechanoluminescent behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect

High performance multi-GPU computing becomes an inevitable trend due to the ever-increasing demand on computation capability in emerging domains such as deep learning, big data and planet-scale simulations. However, the lack of deep understanding on how modern GPUs can be connected and the real impact of state-of-the-art interconnect technology on multi-GPU application performance become a hurdle. In this paper, we fill the gap by conducting a thorough evaluation on five latest types of modern GPU interconnects: PCIe, NVLink-V1, NVLink-V2, NVLink-SLI and NVSwitch, from six high-end servers and HPC platforms: NVIDIA P100-DGX-1, V100-DGX-1, DGX-2, OLCF’s SummitDev and Summit supercomputers, as well as an SLI-linked system with two NVIDIA Turing RTX-2080 GPUs. Based on the empirical evaluation, we have observed four new types of GPU communication network NUMA effects: three are triggered by NVLink’s topology, connectivity and routing, while one is caused by PCIe chipset design issue. These observations indicate that, for a multi-GPU application running in a multi-GPU node, choosing the right GPU combination can impose considerable impact on GPU communication efficiency, as well as an application’s overall performance. Our evaluation can be leveraged in building practical multi-GPU performance models, which are vital for GPU task allocation, scheduling and migration in a shared environment (e.g., AI cloud and HPC centers), as well as communication-oriented performance tuning.

Performance Evaluation, GPU, Interconnect, NUMA, P↗

Search for a low-energy excess of electron neutrinos in MicroBooNE

The Micro Booster Neutrino Experiment (MicroBooNE) is a Liquid Argon Time Projection Chamber (LArTPC) designed for short-baseline neutrino physics at the Fermi National Accelerator Laboratory. The main physics goal of MicroBooNE is to address the low-energy excess of electron-like events observed by the MiniBooNE experiment and, if confirmed, clarify its nature. The MiniBooNE experiment is a Cherenkov detector and this technology does not allow to distinguish between electrons and single photons in the final state. LArTPC detectors, instead, offer excellent granularity and powerful separation between electrons and photons. For this reason, they represent an ideal technology for the detection of electron neutrino interactions. This thesis presents the first fully-automated electron neutrino selection in a LArTPC. The selection looks for charged-current electron neutrino interactions with no pions and at least one proton in the final state. It is applied on a sub-sample of the data acquired by the detector in the Booster Neutrino Beam, corresponding to $4.34\times10^{19}$~protons-on-target. A validation of the analysis is performed on two orthogonal side-bands, enriched with neutral-current and charged-current muon neutrino interactions, respectively. The uncertainties on the neutrino cross sections, flux, and detector simulation are evaluated. The MicroBooNE detector is placed off-axis with the Neutrinos at the Main Injector (NuMI) beam. An independent dataset of events acquired by triggering on the NuMI beam is employed to measure the significance of the detection of electron neutrinos in the beam using the selection presented here. The sensitivity of the MicroBooNE experiment to the MiniBooNE low-energy excess of electron-like events is evaluated. The efficiency and background-rejection power necessary to achieve $5\sigma$ sensitivity are also quantified.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

In Situ Machine Learning for Intelligent Data Capture on Exascale Platforms. Final Report

In many dynamic systems, interesting events occur locally in time and space. Examples of such systems include ignition events in combustion simulations, material fractures in mechanics simulations, and extreme weather events in climate simulations. Due to memory constraints and data I/O costs, current simulation workflows save data at regularly spaced time-steps, at a fixed rate determined before the start of the simulation. Often this mode of operation results in missed events of interest, necessitating a simulation restart from before an event occurred with more frequent data saves. This data saving workflow is grossly inefficient and is already a bottleneck in the computing process. We propose to develop machine learning algorithms that can detect when interesting dynamical events are occurring, triggering data saves. These machine learning algorithms will perform in situ anomaly detection to flag regions with different dynamical properties than those previously recorded. The adaptive data saves would be local in time and space to match the event of interest, thereby enabling a much more efficient workflow that will reduce data I/O costs and data storage memory requirements. The algorithms will be tested on two applications: auto-ignition simulations and climate simulations. A critical component of this project will be developing machine learning algorithms that can be deployed efficiently in situ on HPC platforms with out-of-the-box functionality. The development of in situ machine learning methods to detect anomalous events would enable a more efficient and effective workflow, in which all the relevant data are saved in a single simulation run, without re-starts or scientist intervention.

42 ENGINEERING↗

Manipulating the insulator–metal transition through tip-induced hydrogenation

Manipulating the insulator–metal transition in strongly correlated materials has attracted a broad range of research activity due to its promising applications in, for example, memories, electrochromic windows and optical modulators. Electric-field-controlled hydrogenation using ionic liquids and solid electrolytes is a useful strategy to obtain the insulator–metal transition with corresponding electron filling, but faces technical challenges for miniaturization due to the complicated device architecture. Here, in this work, we demonstrate reversible electric-field control of nanoscale hydrogenation into VO 2 with a tunable insulator–metal transition using a scanning probe. The Pt-coated probe serves as an efficient catalyst to split hydrogen molecules, while the positive-biased voltage accelerates hydrogen ions between the tip and sample surface to facilitate their incorporation, leading to non-volatile transformation from insulating VO 2 into conducting H x VO 2 . Remarkably, a negative-biased voltage triggers dehydrogenation to restore the insulating VO 2 . This work demonstrates a local and reversible electric-field-controlled insulator–metal transition through hydrogen evolution and presents a versatile pathway to exploit multiple functional devices at the nanoscale.

36 MATERIALS SCIENCE↗

Single photon detection and timing in the Lunar Laser Ranging Experiment.

The goals of the Lunar Laser Ranging Experiment lead to the need for the measurement of a 2.5 sec time interval to an accuracy of a nanosecond or better. The systems analysis which included practical retroreflector arrays, available laser systems, and large telescopes led to the necessity of single photon detection. Operation under all background illumination conditions required auxiliary range gates and extremely narrow spectral and spatial filters in addition to the effective gate provided by the time resolution. Nanosecond timing precision at relatively high detection efficiency was obtained using the RCA C31000F photomultiplier and Ortec 270 constant fraction of pulse-height timing discriminator. The timing accuracy over the 2.5 sec interval was obtained using a digital interval with analog vernier ends. Both precision and accuracy are currently checked internally using a triggerable, nanosecond light pulser. Future measurements using sub-nanosecond laser pulses will be limited by the time resolution of single photon detectors.

Poultney, S. K.↗

High-Energy Electromagnetic Offline Follow-Up of Ligo-Virgo Gravitational-Wave Binary Coalescence Candidate Events

We present two different search methods for electromagnetic counterparts to gravitational-wave (GW) events from ground-based detectors using archival NASA high-energy data from the Fermi Gamma-ray Burst Monitor (GBM) and RXTE All-sky Monitor (ASM) instruments. To demonstrate the methods, we use a limited number of representative GW background noise events produced by a search for binary neutron star coalescence over the last two months of the LIGO-Virgo S6/VSR3 joint science run. Time and sky location provided by the GW data trigger a targeted search in the high-energy photon data. We use two custom pipelines: one to search for prompt gamma-ray counterparts in GBM, and the other to search for a variety of X-ray afterglow model signals in ASM. We measure the efficiency of the joint pipelines to weak gamma-ray burst counterparts, and a family of model X-ray afterglows. By requiring a detectable signal in either electromagnetic instrument coincident with a GW event, we are able to reject a large majority of GW candidates. This reduces the signal-to-noise ratio of the loudest surviving GW background event by around 15-20 percent.

gamma-ray burst: general↗