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567 records · Page 32

Crystal growth, scintillation properties & fast neutron-gamma discrimination of cubic halide perovskite CsCaCl 3 :(Eu 2+ , Tl + )

The vast variety of nuclear security applications require radiation detection materials tailored to their operational needs. A scintillator’s properties are strongly influenced by the choice of luminescent dopant, which facilitates customization to different applications. In this work, transparent Ø12 mm single crystals of undoped CsCaCl 3 , CsCaCl 3 :1% Eu, CsCaCl 3 :1% Tl, and CsCaCl 3 :1% Eu, 1% Tl were grown via the Vertical Bridgman method. Their scintillation properties and fast neutron-gamma discrimination capabilities were investigated. Undoped CsCaCl 3 had a light yield of 2,500 ph/MeV, which is the highest reported to date for this CVL material. The incorporation of Eu 2+ or Tl + into CsCaCl 3 as luminescence centers resulted in significantly higher light yields of ∼16,000 ph/MeV and energy resolutions of ∼8% at 662 keV. Compared to the single dopant counterparts, CsCaCl 3 :Eu, Tl had significantly suppressed afterglow; however, this came at the cost of reduced light yield. Among the materials tested, only CsCaCl 3 :Tl showed effective fast neutron and gamma discrimination capabilities, achieving a Figure of Merit of 3.2 between gamma-rays and fast neutron captures that produce protons and 1.6 between gamma-rays and fast neutron captures that produce alpha particles.

crystal growth↗

Sample Acquisition and Analytical Chemistry Challenges to Verifying Compliance to Aviators Breathing Oxygen (ABO) Purity Specification

NASA has been developing and testing two different types of oxygen separation systems. One type of oxygen separation system uses pressure swing technology, the other type uses a solid electrolyte electrochemical oxygen separation cell. Both development systems have been subjected to long term testing, and performance testing under a variety of environmental and operational conditions. Testing these two systems revealed that measuring the product purity of oxygen, and determining if an oxygen separation device meets Aviator's Breathing Oxygen (ABO) specifications is a subtle and sometimes difficult analytical chemistry job. Verifying product purity of cryogenically produced oxygen presents a different set of analytical chemistry challenges. This presentation will describe some of the sample acquisition and analytical chemistry challenges presented by verifying oxygen produced by an oxygen separator - and verifying oxygen produced by cryogenic separation processes. The primary contaminant that causes gas samples to fail to meet ABO requirements is water. The maximum amount of water vapor allowed is 7 ppmv. The principal challenge of verifying oxygen produced by an oxygen separator is that it is produced relatively slowly, and at comparatively low temperatures. A short term failure that occurs for just a few minutes in the course of a 1 week run could cause an entire tank to be rejected. Continuous monitoring of oxygen purity and water vapor could identify problems as soon as they occur. Long term oxygen separator tests were instrumented with an oxygen analyzer and with an hygrometer: a GE Moisture Monitor Series 35. This hygrometer uses an aluminum oxide sensor. The user's manual does not report this, but long term exposure to pure oxygen causes the aluminum oxide sensor head to bias dry. Oxygen product that exceeded the 7 ppm specification was improperly accepted, because the sensor had biased. The bias is permanent - exposure to air does not cause the sensor to return to its original response - but the bias can be accounted for by recalibrating the sensor. After this issue was found, continuous measurements of water vapor in the oxygen product were made using an FTIR. The FTIR cell is relatively large, so response time is slow - but moisture measurements were repeatable and accurate. Verifying ABO compliance for oxygen produced by commercial cryogenic processes has a different set of sample acquisition and analytical chemistry challenges. Customers want analytical chemists to conserve as much as possible. Hygrometers are not exposed to hours of continuous flow of oxygen, so they don't bias, but small amounts of contamination in valves can cause a "fail". K bottles are periodically cleaned and recertified - after cleaning residual moisture can cause a "fail". Operators let bottle pressure drop to room pressure, introduce outside air into the bottle, and the subsequent fill will "fail". Outside storage of K‐bottles has allowed enough in‐leakage, so contents will "fail".

Graf, John↗

Software Tool for Tracking & Mapping the NASA Orion AA-2 Test Flight Ejectable Data Recorders in Real Time

On 2 July 2019, the NASA Ascent Abort 2 flight took place off the Florida coast to test the emergency systems to separate the Orion Crew Module (CM) from the future Space Launch System rocket in the event of a malfunction. During this high-altitude test, instrumentation data was recorded on twelve customized buoyant Ejectable Data Recorders (EDRs) and subsequently jettisoned from the CM in mid-air. Upon release, the EDRs activated their GPS-Iridium beacon systems and began transmitting Short Burst Data (SBD) messages via the Iridium satellite network to relay their individual location and system health information. To locate, track and retrieve each EDR from the ocean surface in real-time, multiple open-source programming tools (Python and Linux shells) were developed for parsing the incoming Iridium binary SBD messages. For this, a Linux laptop was used to receive the Iridium-generated emails containing the SBD messages and autonomously execute the parsing tools. The received SBD data contained location, timestamp and health status information that was translated, saved, and subsequently used for simultaneously generating a continuously updated color-coded tabular display summary and unique KML files used with Google Earth to track their locations. Once their locations were known, dedicated recovery vessels retrieved all EDRs from the ocean. An additional tool was also developed in order to generate 5- and 10-minute geolocation predictions for each EDR by deriving the displacement distance, elapsed time, displacement heading and velocity based on the latest known information available. The recovery vessels were also tracked with the use of a separate commercial GPS beacon system. After jettison, 67% of the EDRs transmitted valid data by the time they were retrieved from the ocean. However, the real-time information presented by the plotting tool allowed for the ready depiction of EDR dispersal patterns and reference drift trajectories, which contributed to the recovery of all twelve EDRs and the AA-2 flight data. Lastly, the available data showed that the distance between the software’s reported drift/predicted locations and the recovery locations did not exceed 38 meters, therefore demonstrating the advantages of this software tool for supporting real-time tracking and recovery efforts of beacon devices.

Moxey, Lucas↗

Recommended Actions to Improve Adapter Safety

With the rapid advancement and acceleration in the electric vehicle (EV) industry within the United States, major automakers and EV charging companies are increasingly adopting the North American Charging Standard (NACS) connector style, now officially known as J3400. This shift is expected to enhance charging infrastructure, providing a better customer experience by making it easier for all EV drivers to access a wider network of direct-current (DC) fast chargers (DCFCs). However, the adoption of the J3400 standard presents challenges for many EVs already on the roads and some currently coming off production lines that are equipped with the Combined Charging System (CCS) connector, which this report will refer to as the North American standard, CCS1. These vehicles will need adapters to use new or existing J3400 infrastructure. During this transition, several issues have emerged. Firstly, there is a need to standardize the new connector type to ensure it is interoperable, safe, and reliable. Second, existing CCS EV drivers need a way to access the J3400 network, which will require electric vehicle supply equipment (EVSE) or sites with both connector types, driver-provided adapters to physically convert from CCS to J3400, or EVSE with retained adapters designed for use with the EVSE. Third, adapter standards will need to be written to specify how they will be designed and what evaluations will be needed to ensure safe and reliable performance. To address these challenges, adapters that support different types of charging connectors will be essential. These adapters will play a crucial role in supporting the transition and ensuring continued service for legacy EVs with CCS inlets as the J3400 standard becomes the predominant one in the United States. Consequently, the National Charging Experience (ChargeX) Consortium has investigated and performed a teardown analysis on the different adapter versions on the market. The aim is to create a failure mode and effects analysis (FMEA) on what are expected to be the most common adapter types used in this transition. In order to support this work, we executed an FMEA exercise with the main goal of identifying gaps in the existing adapters' performance and conformance to the most common safety requirements of high-power and high-voltage devices. This effort focused on adapters provided by the driver, as these may present the highest safety and reliability risks. The recommendations made here apply to both retained and driver-provided adapters.

25 ENERGY STORAGE↗

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗

MEMS Microshutter Array System for James Webb Space Telescope

A complex MEMS microshutter array system has been developed at NASA Goddard Space Flight Center (GSFC) for use as a multi-object aperture array for a Near-Infrared Spectrometer (NIRSpec). The NIRSpec is one of the four major instruments carried by the James Webb Space Telescope (JWST), the next generation of space telescope after the Hubble Space Telescope retires. The microshutter arrays (MSAs) are designed for the selective transmission of light with high efficiency and high contrast. It is demonstrated in Figure 1 how a MSA is used as a multiple object selector in deep space. The MSAs empower the NIRSpec instrument simultaneously collect spectra from more than 100 targets therefore increases the instrument efficiency 100 times or more. The MSA assembly is one of three major innovations on JWST and the first major MEMS devices serving observation missions in space. The MSA system developed at NASA GSFC is assembled with four quadrant fully addressable 365x171 shutter arrays that are actuated magnetically, latched and addressed electrostatically. As shown in Figure 2, each MSA is fabricated out of a 4' silicon-on-insulator (SOI) wafer using MEMS bulk-micromachining technology. Individual shutters are close-packed silicon nitride membranes with a pixel size close to 100x200 pm (Figure 3). Shutters are patterned with a torsion flexure permitting shutters to open 90 degrees with a minimized mechanical stress concentration. In order to prevent light leak, light shields are made on to the surrounding frame of each shutter to cover the gaps between the shutters and the Game (Figure 4). Micro-ribs and sub-micron bumps are tailored on hack walls and light shields, respectively, to prevent sticktion, shown in Figures 4 and 5. JWST instruments are required to operate at cryogenic temperatures as low as 35K, though they are to be subjected to various levels of ground tests at room temperature. The shutters should therefore maintain nearly flat in the entire temperature range between 35K and 300K. Through intensive numerical simulations and experimental studies, an optically opaque and electrically conductive metal-nitride thin film was selected as a coating material deposited on the shutters with the best thermal-expansion match to silicon nitride - the shutter blade thin film material. A shutter image shown in Figure 6 was taken at room temperature, presenting shutters slightly bowing down as expected. Shutters become flat when the temperature decreases to 35K. The MSAs are then bonded to silicon substrates that are fabricated out of 6" single-silicon wafers in the thickness of 2mm. The bonding is conducted using a novel single-sided indium flip-chip bonding technology. Indium bumps fabricated on a substrate are shown in Figure 7. There are 180,000 indium bumps for bonding a flight format MSA array to its substrate. Besides a MSA, each substrate houses five customer-designed ASIC (Application Specific Integrated Circuit) multiplexer/address chips for 2-dimensional addressing, twenty capacitors, two temperature sensors, numbers of resistors and all necessary interconnects, as shown in Figure 8. Complete MSA quadrant assemblies have been successfully manufactured and fully functionally tested. The assemblies have passed a series of critical reviews required by JWST in satisfying all the design specifications. The qualification tests cover programmable 2-D addressing, life tests, optical contrast tests, and environmental tests including radiation, vibration, and acoustic tests. A 2-D addressing pattern with 'ESA' letters programmed in a MSA is shown in Figure 9. The MSAs passed 1 million cycle life tests and achieved high optical contrast over 10,000. MSA teams are now making progress in final fabrication, testing and assembly (Figure 10). The delivery of flight-format MSA system is scheduled at the end of 2008 for being integrated to the focal plane of the NIRSpec detectors.

Li, Mary J.↗

Instrumentation for Examining Microbial Response to Changes In Environmental Pressures

The Automated Adaptive Directed Evolution Chamber (AADEC) is a device that allows operators to generate a micro-scale analog of real world systems that can be used to model the local-scale effects of climate change on microbial ecosystems. The AADEC uses an artificial environment to expose cultures of micro-organisms to environmental pressures, such as UV-C radiation, chemical toxins, and temperature. The AADEC autonomously exposes micro-organisms to selection pressures. This improves upon standard manual laboratory techniques: the process can take place over a longer period of time, involve more stressors, implement real-time adjustments based on the state of the population, and minimize the risk of contamination. We currently use UV-C radiation as the main selection pressure, UV-C is well studied both for its cell and DNA damaging effects as a type of selection pressure and for its related effectiveness as a mutagen; having these functions united makes it a good choice for a proof of concept. The AADEC roadmap includes expansion to different selection pressures, including heavy metal toxicity, temperature, and other forms of radiation.The AADEC uses closed-loop control to feedback the current state of the culture to the AADEC controller that modifies selection pressure intensity during experimentation, in this case culture density and growth rate. Culture density and growth rate are determined by measuring the optical density of the culture using 600 nm light. An array of 600 nm LEDs illuminate the culture and photodiodes are used to measure the shadow on the opposite side of the chamber.Previous experiments showed that we can produce a million fold increase to UV-C radiation over seven iterations. The most recent implements a microfluidic system that can expose cultures to multiple different selection pressures, perform non-survival based selection, and autonomously perform hundreds of exposure cycles. A scalable pump system gives the ability to pump in various different growth media to individual cultures and introduce chemical toxins during experimentation; AADEC can perform freeze and thaw cycles. We improved our baseline characterization by building a custom UV-C exposure hood, a shutter operates on a preset timer allowing the user to set exposure intensity consistently for multiple iterations.

Environment↗

Physics of Hard Spheres Experiment: Significant and Quantitative Findings Made

Direct examination of atomic interactions is difficult. One powerful approach to visualizing atomic interactions is to study near-index-matched colloidal dispersions of microscopic plastic spheres, which can be probed by visible light. Such spheres interact through hydrodynamic and Brownian forces, but they feel no direct force before an infinite repulsion at contact. Through the microgravity flight of the Physics of Hard Spheres Experiment (PHaSE), researchers have sought a more complete understanding of the entropically driven disorder-order transition in hard-sphere colloidal dispersions. The experiment was conceived by Professors Paul M. Chaikin and William B. Russel of Princeton University. Microgravity was required because, on Earth, index-matched colloidal dispersions often cannot be density matched, resulting in significant settling over the crystallization period. This settling makes them a poor model of the equilibrium atomic system, where the effect of gravity is truly negligible. For this purpose, a customized light-scattering instrument was designed, built, and flown by the NASA Glenn Research Center at Lewis Field on the space shuttle (shuttle missions STS 83 and STS 94). This instrument performed both static and dynamic light scattering, with sample oscillation for determining rheological properties. Scattered light from a 532- nm laser was recorded either by a 10-bit charge-coupled discharge (CCD) camera from a concentric screen covering angles of 0 to 60 or by sensitive avalanche photodiode detectors, which convert the photons into binary data from which two correlators compute autocorrelation functions. The sample cell was driven by a direct-current servomotor to allow sinusoidal oscillation for the measurement of rheological properties. Significant microgravity research findings include the observation of beautiful dendritic crystals, the crystallization of a "glassy phase" sample in microgravity that did not crystallize for over 1 year in 1g (Earth's gravity), and the emergence of face-centered-cubic (FCC) crystals late in the coarsening process (as small crystallites lost particles to the slow ripening of large crystallites). Significant quantitative findings from the microgravity experiments have been developed describing complex interactions among crystallites during the growth process, as concentration fields overlap in the surrounding disordered phase. Time-resolved Bragg scattering under microgravity captures one effect of these interactions quite conclusively for the sample at a volume fraction of 0.528. From the earliest time until the sample is almost fully crystalline, the size and overall crystallinity grow monotonically, but the number of crystallites per unit volume (number density) falls. Apparently nucleation is slower than the loss of crystallites because of the transfer of particles from small to large crystals. Thus, coarsening occurs simultaneously with growth, rather than following the completion of nucleation and growth as is generally assumed. In the same sample, an interesting signature appears in the apparent number density of crystallites and the volume fraction within the crystallites shortly before full crystallinity is reached. A brief upturn in both indicates the creation of more domains of the size of the average crystallite simultaneous with the compression of the crystallites. Only the emergence of dendritic arms offers a reasonable explanation. The arms would be "seen" by the light scattering as separate domains whose smaller radii of curvature would compress the interior phase. In fiscal year 1999, numerous papers, a doctoral dissertation, and the PHaSE final report were produced. Although this flight project has been completed, plans are in place for a follow-on colloid experiment by Chaikin and Russel that employs a light microscope within Glenn's Fluids and Combustion Facility on the International Space Station. PHaSE is providing us with a deeper understanding of the nure of phase transitions. The knowledge derived has added to the understanding of condensed matter. In addition, the burgeoning study of the dynamics of colloidal self-assembly may lead to the development of a range of photonic materials that control the desirable properties of light. Thus, applications of ordered colloidal structures include not only ultrastructure ceramics, but also photonic crystals and photothermal nanosecond light-switching devices. Industries dealing with semiconductors, electro-optics, ceramics, and composites stand to benefit from such advancements.

Doherty, Michael P.↗