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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Strip Detectors Processed on High-Resistivity 6-Inch Diameter Magnetic Czochralski Silicon (MCz-Si) Substrates

Tracking detectors for future high-luminosity particle physics experiments have to be simultaneously radiation hard and cost efficient. This paper describes processing and characterization of p^+ /n^-/n^+ (n-type silicon bulk) detectors made of high-resistivity Magnetic Czochralski silicon (MCz-Si) substrates with 6-inch wafer diameter. The processing was carried out on a line used for large-scale production of sensors using standard fabrication methods, such as implanting polysilicon resistors to bias individual sensor strips. Special care was taken to avoid the creation of Thermal Donors (TD) during processing. The sensors have a full depletion voltage of 120-150 V which are uniform over the investigated sensors. All of the leakage current densities were below 55 nA/cm^2 at 200 V bias voltage. A strip sensor with 768 channels was attached to readout electronics and tested in particle beam with a data acquisition (DAQ) similar to the system used by the CMS experiment at the CERN LHC. The test beam results show a signal-to-noise ratio greater than 40 for the test beam sensor. The results demonstrate that MCz-Si detectors can reliably be manufactured in the industrial scale semiconductor process.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Reliable and redundant FPGA based read-out design in the ATLAS TileCal Demonstrator

The Tile Calorimeter at ATLAS [1] is a hadron calorimeter based on steel plates and scintillating tiles read out by PMTs. The current read-out system uses standard ADCs and custom ASICs to digitize and temporarily store the data on the detector. However, only a subset of the data is actually read out to the counting room. The on-detector electronics will be replaced around 2023. To achieve the required reliability the upgraded system will be highly redundant. Here the ASICs will be replaced with Kintex-7 FPGAs from Xilinx. This, in addition to the use of multiple 10 Gbps optical read-out links, will allow a full read-out of all detector data. Due to the higher radiation levels expected when the beam luminosity is increased, opportunities for repairs will be less frequent. The circuitry and firmware must therefore be designed for sufficiently high reliability using redundancy and radiation tolerant components. Within a year, a hybrid demonstrator including the new readout system will be installed in one slice of the ATLAS Tile Calorimeter. This will allow the proposed upgrade to be thoroughly evaluated well before the planned 2023 deployment in all slices, especially with regard to long term reliability. Different firmware strategies alongside with their integration in the demonstrator are presented in the context of high reliability protection against hardware malfunction and radiation induced errors.

ATLAS↗
DOE OSTI2016

Unattended Sensor System With CLYC Detectors

We have developed a next-generation unattended sensor for detecting anomalous radiation sources. The system combines several technologies to reduce size and weight, increase battery lifetime, and improve decision-making capabilities. Sixteen Cs2LiYCl6:Ce (CLYC) scintillators allow for gamma-ray spectroscopy and neutron detection in the same volume. Low-power electronics for readout, high voltage bias, and digital processing reduce the total operating power to 1.3 W. Computationally efficient analysis algorithms perform spectral anomaly detection and isotope identification. When an alarm occurs, the system transmits alarm information over a cellular modem. In this paper, we describe the overall design of the unattended sensor, present characterization results, and compare the performance to stock NaI:Tl and 3He detectors.

CLYC↗
DOE OSTI2017

Quality Assurance on Undoped CsI Crystals for the Mu2e Experiment

The Mu2e experiment is constructing a calorimeter consisting of 1,348 undoped CsI crystals in two disks. Each crystal has a dimension of 34 x 34 x 200 mm 3 , and is readout by a large area silicon PMT array. A series of technical specifications was defined according to physics requirements. Preproduction CsI crystals were procured from three firms: Amcrys, Saint-Gobain and Shanghai Institute of Ceramics. We report the quality assurance on crystal's scintillation properties and their radiation hardness against ionization dose and neutrons. With a fast decay time of 30 ns and a light output of more than 100 p.e./MeV measured with a bi-alkali PMT, undoped CsI crystals provide a cost-effective solution for the Mu2e experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Design and Evaluation of the LAr Trigger Digitizer Board in the ATLAS Phase-I Upgrade

The Phase-I upgrade of the trigger readout electronics for the ATLAS Liquid Argon (LAr) calorimeters will be installed during the second long shutdown of the Large Hadron Collider (LHC) in 2019-2020 which will enable enhanced instantaneous luminosities during LHC Run 3 from 2021 through 2023. In this trigger upgrade, so-called supercells are introduced to provide higher granularity, higher resolution and longitudinal shower shape information from the LAr calorimeters to the Level-1 trigger processors. A new LAr Trigger Digitizer Board (LTDB) will process and digitize up to 320 channels of supercell signals, and transmit them via 40 fiber optical links to the back end where the data are further processed and transmitted to the trigger processors. Five pairs of bidirectional GBT links are used for slow control and monitoring between LTDB and the Front-End LInk eXchange (FELIX) in the ATLAS Trigger and Data Acquisition (TDAQ) system. Here, the LTDB also outputs 64 summed analog legacy signals to the current Tower Builder Board via a new baseplane. A test system for the production of 124 LTDBs has been developed, supporting configuration and calibration of all ASICs

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Characterization of a Small-Scale Prototype Detector With Wide Dynamic Range for Time-Resolved High-Energy X-Ray Applications

We present characterization measurements of a fast-framing, wide-dynamic-range x-ray area detector intended for high-energy applications (≥20 keV photons). The MM-PAD-2.1 combines an integrating pixel front-end with a charge-removal mechanism to extend the maximum measurable signal to > 107 20-keV ph/pixel/frame. The charge-removal mechanism is dead-time-less (i.e., incoming signal continues to be integrated by the front-end while charge removal is taking place) up to an incoming photon rate of > 109 20-keV ph/pix/s. A 16×16 pixel prototype was fabricated and characterized using both laboratory and synchrotron x-ray sources, allowing for measurements from single-photon to high-flux conditions. High-flux measurements show linear performance up to ~1010 ph/s in a spot spanning approximately 2×1.5 pixels (FWHM). The onset of temporary radiation damage in the detector was observed during these measurements, manifesting as failure of the digital readout from the detector. These effects were seen to reverse after annealing at 30° C for several hours.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

The VMM3a ASIC

The VMM3a is a custom low-noise Application Specific Integrated Circuit. It is intended to be used in the front end readout electronics of both the Micromegas and sTGC detectors of the ATLAS New Small Wheels upgrade project at CERN. It is fabricated in the 130 nm GlobalFoundries 8RF-DM process. Here, the 64 channels with highly configurable parameters, although designed for a specific project, can meet the processing needs of signals from various detector types in several other applications. In this note, the VMM3a, which is the production version of the VMM family, will be presented along with the features incorporated and its performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Testing of a Line Driver With Configurable Pre-Emphasis on Lossy Transmission Lines

Rare-event physics experiments such as the Deep Underground Neutrino Experiment (DUNE) or the next Enriched Xenon Observatory (nEXO) experiment search for rare, low-energy events, detected by sensitive detectors immersed in a cryogenic noble liquid (e.g., liquid argon or xenon). Readout electronics used within such detectors must consume minimal power while operating reliably in cryogenic environments. Furthermore, in the case of nEXO, maximizing the radiopurity of the environment is vital to minimize background noise, thus placing strict limits on the volume of dielectric materials, leading to high-loss data cables spanning distances up to 12 m. Such cables cause high attenuation and intersymbol interference (ISI), resulting in a high bit-error rate (BER). These issues were addressed by developing an integrated line driver with configurable pre-emphasis in a 65-nm CMOS process. The pre-emphasis parameters can be programmed to minimize BER for specific cables and data rates under power constraints. Here, the driver was tested at both room and cryogenic temperatures. In both cases, the output BER was found to be strongly correlated with the pre-emphasis settings. Furthermore, analysis and simulation showed that adapting the pre-emphasis settings based on the incoming bit sequence can further improve performance with minimal changes to the current solution.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

The DUNE-DAQ Application Framework

The deep underground neutrino experiment (DUNE) is a next-generation neutrino experiment that will probe the properties of these elusive particles with unparalleled precision. It will also act as an observatory for neutrino bursts caused by nearby supernovae, in the event that one occurs, while the experiment is in operation. Given these goals, the DUNE trigger and DAQ system must be able to maintain extremely high uptime and provide a path for full readout of the detectors for very long times (up to 100 s). To achieve these ends, we have designed the DUNE DAQ system around a flexible “application framework,” which provides a modular interface for specific tasks while handling the interconnections between them. The application framework collects modules into applications, which can then be interacted with as units by the control, configuration, and monitoring systems. One of the key features of the framework is its communication abstraction layer, which allows for modules to interact with both internal queues and external network connections with a single transport-agnostic interface. We will report on the architecture and features of the framework.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

A Ce-Doped LiI Scintillator Film-Based High Rate, High Spatial Resolution Neutron Anger Camera for Neutron Scattering Facilities

The 2-D position sensitive neutron detectors featuring a significantly improved count rate capacity and a sub-mm spatial resolution are in high demand by neutron scattering facilities, especially the next generation high-flux spallation neutron sources (SNSs). They are anticipated to play a crucial role in fully utilizing the unprecedentedly high neutron brightness offered by these sources. In this work, a high rate and high spatial resolution neutron Anger camera has been successfully developed based on a Ce-doped microcolumnar LiI scintillator film and the PETsys TOFPET2 ASIC readout electronics. The performance evaluation was conducted in a standard laboratory environment as well as the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) with regard to light yield, γ-ray sensitivity, neutron detection efficiency, count rate capability, spatial resolution, and position linearity. The LiI:Ce scintillator was found to have a higher light yield and a lower γ-ray sensitivity than GS20 (i.e., 11729 versus 6000 photons/n and 1.67 × 10 −5 versus on the order of 10 −4 ). The neutron detection efficiency was measured to be 63% at 4.2 Å. This camera demonstrated an exceptional count rate capability, up to at least 481 kHz without rate loss. The spatial resolution was as good as 0.47 mm. Here, the position linearity was also enhanced.

High rate↗
DOE OSTI2026

Data-Driven Optimization of Pixelated CdZnTe Spectrometers for Uranium Enrichment Assay

Here, in recent work [Vavrek et al. (2025)], we developed the performance optimization framework spectre-ml for gamma spectrometers with variable performance across many readout channels. The framework uses non-negative matrix factorization (NMF) and clustering to learn groups of similarly-performing channels and sweep through various learned channel combinations to optimize the performance tradeoff of including worse-performing channels for better total efficiency. In this work, we integrate the pyGEM uranium enrichment assay code with our spectre-ml framework, and show that the U-235 enrichment relative uncertainty can be directly used as an optimization target. We find that this optimization reduces relative uncertainties after a 30 -minute measurement by an average of 20%, as tested on six different H3D M400 CdZnTe spectrometers, which can significantly improve uranium non-destructive assay measurement times in nuclear safeguards contexts. Additionally, this work demonstrates that the spect re-ml optimization framework can accommodate arbitrary end-user spectroscopic analysis code and performance metrics, enabling future optimizations for complex Pu spectra.

Gamma-ray detection↗
DOE OSTI2026

Data-Driven Performance Optimization of Gamma Spectrometers With Many Channels

In gamma spectrometers with variable spectroscopic performance across many channels (e.g., many pixels or voxels), a tradeoff exists between including data from successively worse-performing readout channels and increasing efficiency. Brute-force calculation of the optimal set of included channels is exponentially infeasible as the number of channels grows, and approximate methods are required. In this work, we present a data-driven framework for attempting to find near-optimal sets of included detector channels. The framework leverages non-negative matrix factorization (NMF) to learn the behavior of gamma spectra across the detector and clusters similarly-performing detector channels together. Performance comparisons are then made between spectra with channel clusters removed, which is more feasible than brute force. The framework is general and can be applied to arbitrary, user-defined performance metrics depending on the application. We apply this framework to optimizing gamma spectra measured by H3D M400 CdZnTe (CZT) spectrometers, which exhibit variable performance across their crystal volumes. In particular, we show several examples optimizing various performance metrics for uranium and plutonium gamma spectra in non-destructive assay (NDA) for nuclear safeguards, and explore trends in performance versus parameters such as clustering algorithm type. We also compare the NMF + clustering pipeline to several non-machine-learning (ML) algorithms, including several greedy algorithms. Although, we find that the NMF + clustering pipeline tends to find the best-performing set of detector voxels, significantly improving over the unoptimized spectra, but that a greedy accumulation of spectra segmented by detector depth can, in some cases, give similar performance improvements in much less computation time.

Energy resolution↗
DOE OSTI2025

Limitations of Fault-Tolerant Quantum Linear System Solvers for Quantum Power Flow

Quantum computers hold promise for solving problems intractable for classical computers, especially those with high time or space complexity. Practical quantum advantage can be said to exist for such problems when the end-to-end time for solving such a problem using a classical algorithm exceeds that required by a quantum algorithm. Reducing the power flow (PF) problem into a linear system of equations allows for the formulation of quantum PF (QPF) algorithms, which are based on solving methods for quantum linear systems such as the Harrow-Hassidim-Lloyd (HHL) algorithm. Speedup from using QPF algorithms is often claimed to be exponential when compared to classical PF solved by state-of-the-art algorithms. Here, we investigate the potential for practical quantum advantage in solving QPF compared to classical methods on gate-based quantum computers. Notably, this paper does not present a new QPF solving algorithm but scrutinizes the end-to-end complexity of the QPF approach, providing a nuanced evaluation of the purported quantum speedup in this problem. Our analysis establishes a best-case bound for the HHL-based quantum power flow complexity, conclusively demonstrating that the HHL-based method has higher runtime complexity compared to the classical algorithm for solving the direct current power flow (DCPF) and fast decoupled load flow (FDLF) problem. Notably, our analysis and conclusions can be extended to any quantum linear system solver with rigorous performance guarantees, based on the known complexity lower bounds for this problem. Additionally, we establish that for potential practical quantum advantage (PQA) to exist it is necessary to consider DCPF-type problems with a very narrow range of condition number values and readout requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Evidence for lack of direct causality between pain and affective disturbances in a rat peripheral neuropathy model

Chronic pain is frequently accompanied by the manifestation of emotional disturbances and cognitive deficits. While a causality relation between pain and emotional/cognitive disturbances is generally assumed, several observations suggest a temporal dissociation and independent mechanisms. We therefore studied Sprague‐Dawley rats that presented a natural resistance to pain manifestation in a neuropathy model (spared nerve injury [SNI]) and compared their performance in a battery of behavioral paradigms—anxiety, depression and fear memory—with animals that presented a pain phenotype. Afterward, we performed an extensive volumetric analysis across prefrontal, orbitofrontal and insular cortical areas. The majority of SNI animals manifested mechanical allodynia (low threshold [LT]), but 13% were similar to Sham controls (high threshold [HT]). Readouts of spontaneous hypersensivity (paw flinches) were also significantly reduced in HT and correlated with allodynia. To increase the specificity of our findings, we segregated the SNI animals in those with left (SNI‐L) and right (SNI‐R) lesions and the lack of association between pain and behavior still remains. Left‐lesioned animals, independent of the LT or HT phenotype, presented increased anxiety‐like behaviors and decreased well‐being. In contrast, we found that the insular cortex (agranular division) was significantly smaller in HT than in LT. To conclude, pain and emotional disturbances observed following nerve injury are to some extent segregated phenomena. Also, HT and LT SNI presented differences in insular volumes, an area vastly implicated in pain perception, suggesting a supraspinal involvement in the manifestation of these phenotypes.

Guimarães, Marco R.↗
DOE OSTI2025

The promising role of proteomes and metabolomes in defining the single-cell landscapes of plants

The plant community has a strong track-record of RNA sequencing technology deployment, which combined with the recent advent of spatial platforms (e.g., 10x genomics), has resulted in an explosion of outstanding single cell and nuclei datasets that can be put in an in situ context within tissues (e.g., a cell atlas)1. In the genomics era, application of proteomics technologies in the plant sciences has always trailed behind that of RNA sequencing technologies, largely due to accessibility, ease-of-use and access to expertise along with depth of analysis benefits. On the other hand, the use of early analytical tools for characterizing small molecules (metabolites) from plant systems predates nucleic acid sequencing and proteomics analysis2, as the search for plant-based natural products has played a significant role in improving human health throughout history. However, the employment of proteomics and metabolomics assays for characterizing plant cell processes now remains significantly behind transcriptional approaches, even though both provide a direct functional readout of cell states and phenotypes.

Anderton, Christopher R. [BATTELLE (PACIFIC NW LAB↗
DOE OSTI2021

Rational design and testing of abiotic stress‐inducible synthetic promoters from poplar cis ‐regulatory elements

Summary Abiotic stress resistance traits may be especially crucial for sustainable production of bioenergy tree crops. Here, we show the performance of a set of rationally designed osmotic‐related and salt stress‐inducible synthetic promoters for use in hybrid poplar. De novo motif‐detecting algorithms yielded 30 water‐deficit (SD) and 34 salt stress (SS) candidate DNA motifs from relevant poplar transcriptomes. We selected three conserved water‐deficit stress motifs (SD18, SD13 and SD9) found in 16 co‐expressed gene promoters, and we discovered a well‐conserved motif for salt response (SS16). We characterized several native poplar stress‐inducible promoters to enable comparisons with our synthetic promoters. Fifteen synthetic promoters were designed using various SD and SS subdomains, in which heptameric repeats of five‐to‐eight subdomain bases were fused to a common core promoter downstream, which, in turn, drove a green fluorescent protein (GFP) gene for reporter assays. These 15 synthetic promoters were screened by transient expression assays in poplar leaf mesophyll protoplasts and agroinfiltrated Nicotiana benthamiana leaves under osmotic stress conditions. Twelve synthetic promoters were induced in transient expression assays with a GFP readout. Of these, five promoters (SD18‐1, SD9‐2, SS16‐1, SS16‐2 and SS16‐3) endowed higher inducibility under osmotic stress conditions than native promoters. These five synthetic promoters were stably transformed into Arabidopsis thaliana to study inducibility in whole plants. Herein, SD18‐1 and SD9‐2 were induced by water‐deficit stress, whereas SS16‐1, SS16‐2 and SS16‐3 were induced by salt stress. The synthetic biology design pipeline resulted in five synthetic promoters that outperformed endogenous promoters in transgenic plants.

09 BIOMASS FUELS↗