Forecast-based stochastic optimization for a load powered by wave energy
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Dillon, Trent (ORCID:0000000201036449)↗
SEARCH · Engineering Papers
Results for “sensor selection”
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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Microfluidic Fabrication Techniques for High-Pressure Testing of Microscale Supercritical CO 2 Foam Transport in Fractured Unconventional Reservoirs
Pressure limitations of many microfluidic platforms have been a significant challenge in microfluidic experimental studies of fractured media. As a result, these platforms have not been fully exploited for direct observation of high-pressure transport in fractures. This work introduces microfluidic platforms that enable direct observation of multiphase flow in devices featuring surrogate permeable media and fractured systems. Such platforms provide a pathway to address important and timely questions such as those related to CO 2 capture, utilization and storage. This work provides a detailed description of the fabrication techniques and an experimental setup that may serve to analyze the behavior of supercritical CO 2 (scCO 2 ) foam, its structure and stability. Such studies provide important insights regarding enhanced oil recovery processes and the role of hydraulic fractures in resource recovery from unconventional reservoirs. This work presents a comparative study of microfluidic devices developed using two different techniques: photolithography/wet-etching/ thermal-bonding versus Selective Laser-induced Etching. Both techniques result in devices that are chemically and physically resistant and tolerant of high pressure and temperature conditions that correspond to subsurface systems of interest. Both techniques provide pathways to high-precision etched microchannels and capable lab-on-chip devices. Photolithography/wet-etching, however, enables fabrication of complex channel networks with complex geometries, which would be a challenging task for laser etching techniques. This work summarizes a step-by-step photolithography, wet-etching and glass thermal-bonding protocol and, presents representative observations of foam transport with relevance to oil recovery from unconventional tight and shale formations. In conclusion, this work describes the use of a high resolution monochromatic sensor to observe scCO 2 foam behavior where the entirety of the permeable medium is observed simultaneously while preserving the resolution needed to resolve features as small as 10 μm.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Explainable machine learning for incipient anomaly detection in compact molten salt heat exchanger with overlapping feature distributions
High-temperature molten salt-cooled reactors (MSCRs) are a promising next-generation nuclear technology option, offering efficient power conversion and inherent safety features. However, the reliability of these systems depends on the robust operation of heat exchangers (HXs), which are susceptible to failure due to temperature gradients and channel plugging caused by fluid freezing. Conventional monitoring methods, relying on inlet and outlet measurements, lack the spatial resolution needed to detect early-stage faults. We propose a novel design of a compact salt-to-salt matrix-type HX design consisting of interleaved arrays of parallel tubes, with integrated synthetic fiber optic distributed temperature sensing (DTS) to enable localized detection of incipient faults. To evaluate performance of this design, we generate high-fidelity synthetic data using heat transfer computational modeling to simulate channel plugging, and introduce sensor noise for realistic modeling of measurements. The dataset comprises of 97% normal operation and 3% anomaly cases, with each anomaly class representing 1% of the data. These early anomalies result in overlapping temperature profiles between normal and faulty channels, producing a non-separable dataset that challenges traditional classification techniques. We benchmark eight supervised machine learning (ML) models and demonstrate that XGBoost achieves the highest performance. To improve transparency, we develop an explainability framework combining Shapley values and partially ordered sets (POSETs) to quantify and structurally analyze feature importance. This approach identifies both dominant predictors and ambiguous feature relationships, enhancing trust and interpretability. Our results highlight the potential of combining DTS and explainable ML with intelligent feature selection to improve predictive maintenance and ensure operational resilience in advanced nuclear systems.
Prantikos, Konstantinos [Argonne National Laborato↗
Sensing Electrical Networks Securely & Economically (SENSE)
The growing adoption of distributed energy resources (DERs) like battery energy storage systems and roof top solar/PV and the rapid penetration of electric vehicles (EVs), the electric grid is undergoing a major transformation with elevated stress on legacy grid assets. Despite a lot of expenditure to address these challenges, both in dollars and manpower, utilities have not been able to receive the value that was promised. The gains have been most visible at the transmission and substation level, especially where the main objective was improving operational and economic efficiency for the utility. Improving visibility and control at a few select points enhances the existing and established paradigm of centralized command and control. With changing load patterns, load types and the overall transition to an “active grid”, the centralized control and coordination paradigm gets challenged. To address the challenges, a new architecture and mechanism is needed, one that supports decentralized control and decision making, extracting value streams at the grid edge, particularly as the changes are fueled by transitions occurring in the distribution system. To address this, a communications and data processing platform, “GAMMA” was developed and demonstrated through the project. At the heart of the platform, are distributed, intelligent edge nodes with sensing and compute capabilities, that can record and analyze information locally. They are embedded in sensors and actuators specific to different distribution system applications. Phase 1 of the project focused on developing novel sensor technology that can be used for monitoring utility pole top distribution transformers. The sensors were designed with the objective of being low-cost, communicating with the GAMMA cloud using novel “delay-tolerant” networking using Bluetooth and a secure mobile application. They were non-intrusive in nature so that they can be installed quickly in the field, resulting in overall low cost of deployment and operations. Following the successful completion of Phase 1, the team manufactured 100 units for a field demonstration in Phase 2. The field demonstration was carried out on two real feeder systems with the local utility partner. In total, 100 sensors were installed and operated over a period of 6 months in the state of Georgia. The platform is operational end to end, with the cloud infrastructure deployed on a distributed, serverless environment that can serve multiple data streams, an analytics engine and a portal to securely view the data from multiple assets. The data collected through the GAMMA Mobile Phone app showcased the viability of the novel delay tolerant networking architecture, and the data processing algorithms developed through the course of the project, were successful in extracting important information about the overall network, improving the utility’s visibility and situational awareness in the distribution feeder.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Quantitative measurements of reactive oxygen species partitioning in electron transfer flavoenzyme magnetic field sensing
Biological magnetic field sensing that gives rise to physiological responses is of considerable importance in quantum biology. The radical pair mechanism (RPM) is a fundamental quantum process that can explain some of the observed biological magnetic effects. In magnetically sensitive radical pair (RP) reactions, coherent spin dynamics between singlet and triplet pairs are modulated by weak magnetic fields. The resulting singlet and triplet reaction products lead to distinct biological signaling channels and cellular outcomes. A prevalent RP in biology is between flavin semiquinone and superoxide (O 2 •–) in the biological activation of molecular oxygen. This RP can result in a partitioning of reactive oxygen species (ROS) products to form either O 2 •– or hydrogen peroxide (H 2 O 2 ). Here, we examine magnetic sensing of recombinant human electron transfer flavoenzyme (ETF) reoxidation by selectively measuring O 2 •– and H 2 O 2 product distributions. ROS partitioning was observed between two static magnetic fields at 20 nT and 50 μT, with a 13% decrease in H 2 O 2 singlet products and a 10% increase in O 2 •– triplet products relative to 50 µT. RPM product yields were calculated for a realistic flavin/superoxide RP across the range of static magnetic fields, in agreement with experimental results. For a triplet born RP, the RPM also predicts about three times more O 2 •– than H 2 O 2 , with experimental results exhibiting about four time more O 2 •– produced by ETF. The method presented here illustrates the potential of a novel magnetic flavoprotein biological sensor that is directly linked to mitochondria bioenergetics and can be used as a target to study cell physiology.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Experimental Capabilities to Support Design, Development and Demonstration of Microreactors
This work provides a summary of selected experimental capabilities being developed to support non-nuclear demonstration of microreactors under the U.S. Department of Energy’s (DOE’s) Microreactor Program. Major capabilities include the single primary heat extraction and removal emulator (SPHERE) and the microreactor agile non-nuclear experimental test bed (MAGNET). The SPHERE facility allows for controlled testing of the steady-state and transient heat rejection capabilities of a single heat pipe using electrical heaters that simulate nuclear heating. The facility is capable of monitoring axial temperature profiles along the heat pipe and surrounding test articles during startup, steady-state operation, and transients. Instrumentation includes non-contact infrared thermal imaging, surface thermocouples, spatially distributed fiber-optic temperature and strain sensors, electrical power meters, and a water-cooled, gas gap calorimeter for quantifying heat rejection from the heat pipe. The facility can be operated under both vacuum and inert-gas conditions.
42 ENGINEERING↗
Progress on Advancing Robotic Ultrasonic Volumetric Inspection Technology for Hanford Under-tank Inspection - 19474
The Hanford River Protection Project is reliant on safe interim storage of high-level waste at the Hanford site and will continue to depend on it until the waste has been treated and vitrified by the Hanford Waste Treatment and Immobilization Plant (WTP). The Hanford double-shell tanks (DSTs) have provided interim storage since the DSTs were put into service (1971 - 1986) and the RPP will continue to rely on their service until least 2050, at which time the 27 in-service DSTs will be 14-54 years beyond their original design lives. As the DSTs continue to age and be operated beyond design life, reliable leak integrity assessments of primary tanks and secondary liners will become increasingly important in order to provide situational awareness to tank operations personnel and to support risk-informed decisions on the selection of DSTs as waste feed staging tanks and the order and timing of future DST refurbishment or, alternatively, DST retrieval sequence. This paper summarizes progress made in fiscal year (FY) 2018 on the engineering of a robotic air-slot volumetric inspection system (RAVIS) that is designed to perform ultrasonic (volumetric) leak integrity inspections of physically inaccessible primary tank bottom plates and welds. Leak integrity inspections performed with the RAVIS will supplement today's primary tank leak integrity inspections, which are currently limited to physically accessible sidewall plates and welds. The RAVIS will be deployed into air slots of the insulating concrete (refractory) pad beneath the primary tanks and use its ultrasonic guided wave phased-array (GWPA) sensor to electronically steer an ultrasonic beam 360-degrees around the sensor to volumetrically examine adjacent carbon steel plates and welds covered by refractory pad material. Deployments of RAVIS down multiple air-slots will be performed to determine which regions of a tank bottom have sound leak integrity or which regions are in need of future wall thickness restoration or weld repair due to pitting corrosion, general corrosion, or heat/stress-induced cracks. The initial RAVIS design and the flaw detection test results for the first air-slot GWPA sensor that was designed to fit inside the air-slots will be presented in this paper. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Results of South-East Flux Trap Dosimetry Measurements for the Advanced Test Reactor Critical Facility in support of Advanced Sensors and Instrumentation Development
Reactor dosimetry measurements are commonly used to validate simulation and modeling in nuclear reactor tests. Numerous standard dosimeter materials exist which are commonly utilized with sensitivities to different energy ranges of neutrons. At the Advanced Test Reactor (ATR), cobalt alloy and pure nickel wires are installed every cycle to monitor thermal- and fast-neutron fluence rates. However, there is growing interest in exploring less commonly used materials which are either more sensitive to different parts of the neutron energy spectrum or which can incorporate multiple activation paths in a single material. Epithermal and fast-neutron energies beyond the typical 1-MeV threshold are of particular interest. Two ATR-C Flux Runs took place during 2024; each flux run included supplemental dosimetry packages in the South-East Flux Trap (SEFT) Filler. The focus of the dosimetry package for flux run 23-4 was to test two novel dosimetry methods that can provide simultaneous thermal and threshold (fast) sensitivity in a single dosimeter wire. A selection of 3% Au in Cu alloyed wires were available that provided sensitivity to fast and thermal neutrons through 5 different reactions. Likewise, Fe offers multiple interaction pathways with sensitivity to both thermal and fast neutrons. The main question to be answered by these irradiations was if sufficient radioactivation would take place in the ATR-C SEFT during a nominal 20-minute irradiation at typical power levels (near 600Wth) to observe the threshold reactions that have smaller activation cross-sections than the thermal reactions without being saturated by interfering interactions and Compton continuum during the High-Purity Germanium (HPGe) measurements. The results from comparing the measurement results to anticipated activity levels provide confidence in our ability to activate both traditional and novel dosimetry materials in ATR-C, however not all the measured values matched with the predicted activities. This leaves further room for investigation both on the experimental and computational approaches for future irradiation experiments.
46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
Synergistic effects of Pd single atoms and nanoclusters boosting SnO 2 gas sensing performance
Tin(IV) oxide-supported Pd is a promising heterogenous catalyst for CO oxidation relevant for environmental cleanup reactions. In this study, an atomically dispersed Pd catalyst on SnO 2 (ADC Pd/SnO 2 ) hybrid material is successfully synthesized via a straightforward wet chemistry method and is found to exhibit superior performance toward CO sensing. Ex situ EXAFS analysis confirms the formation of single Pd atoms and small Pd nanoclusters stabilized on the SnO 2 (110) surface. Further, the material exhibits high efficiency in generating adsorbed O 2 - as well as high activity in catalyzing CO oxidation at low temperatures, resulting in exceptional sensitivity and selectivity toward CO in comparison to pure SnO 2 and Pd nanoparticles loaded on SnO 2 respectively. In situ FTIR measurements unravel CO adsorption kinetics on ADC Pd/SnO 2 under reaction conditions, and a possible sensing mechanism is put forth in which CO is transformed into CO 2 by reaction with active oxygen species; and concurrently, carbon-related species (bicarbonates and carbonates) are formed and decomposed into CO 2 .
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Machine learning substitutional defect formation energies in ABO 3 perovskites
Perovskite oxides are a promising material platform for use in a wide range of technological applications including electronics, sensors, fuel cells, and catalysis. This is owing to the extraordinary tunability of their physical and chemical properties via defect engineering. The feasibility and the stability of a defect, such as a substitutional dopant, in the host lattice is usually obtained via experiments and/or through detailed quantum mechanical calculations. Both of these conventional routes are expensive and time consuming. An alternative is a data-driven machine learning (ML)-based approach. In this work, we have applied ML techniques to identify the factors that influence defect formation energy, which is an important measure of the stability of the defects, in perovskite oxides. Using 13 elemental properties as features and random forest regression, we demonstrate a systematic approach to down-selecting from the larger set of features to those that are important, establishing a framework for accurate predictions of the defect formation energy. We quantitatively show that the most important factors that control the dopant stability are the dopant ionic size, heat of formation, effective tolerance factor, and oxidation state. Our work reveals previously unknown correlations, chemical trends, and the interplay between stability and underlying chemistries. Hence, these results showcase the efficacy of ML tools in identifying and quantifying different feature-dependencies and provide a promising route toward dopant selection in the perovskites. Herein, we have developed a framework that itself is general and can be potentially applied to other material classes.
36 MATERIALS SCIENCE↗
Nonnuclear Experimental Capabilities to Support Design, Development, and Demonstration of Microreactors
This work provides a summary of selected experimental capabilities being developed to support nonnuclear testing and demonstration of technology in support of microreactors under the U.S. Department of Energy’s (DOE’s) Microreactor Program. Major capabilities include the Single Primary Heat Extraction and Removal Emulator (SPHERE) and the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET). The SPHERE facility allows for controlled testing of the steady-state and transient heat rejection capabilities of a single heat pipe using electrical heaters that simulate nuclear heating. The facility is capable of monitoring axial temperature profiles along the heat pipe and surrounding test articles during startup, steady-state operation, and transients. Instrumentation includes noncontact infrared thermal imaging, surface thermocouples, spatially distributed fiber optic temperature and strain sensors, electrical power meters, and a water-cooled, gas-gap calorimeter for quantifying heat rejection from the heat pipe. The facility can be operated under both vacuum and inert-gas conditions. The MAGNET facility is a large-scale, 250-kW electrically heated microreactor test bed to enable nonnuclear experimental evaluation of a variety of microreactor concepts. It can be supplied to electrically heat a scaled section of a microreactor and further test the capabilities of heat rejection systems. The initial MAGNET experiments will support technology maturation and reduce uncertainty and risk associated with the design, operation, and deployment of monolithic heat pipe–based reactors. However, this test bed can broadly be applied to multiple microreactor concepts to evaluate a wide range of thermal-hydraulic and structural phenomena such as interface coupling with power conversion units and other collocated systems. MAGNET can evaluate integral thermomechanical effects during electrical heating of an array of heat pipes in a larger test article. Examples of initial testing will include thermal stresses in the monolith and the impact of debonding of a heat pipe from the core block and how that failure could impact surrounding heat pipes, i.e., understanding the potential for cascading failure. This work also discusses some modeling capabilities that can support experiment design, analysis, and interpretation, including the heat pipe code Sockeye and a comparison of thermal-structural simulations performed using ABAQUS and STAR-CCM+.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Traffic Control via Connected and Automated Vehicles (CAVs): An Open-Road Field Experiment with 100 CAVs
The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. Also called “phantom jams” or “stop-and-go waves,” these instabilities are a significant source of wasted energy. Toward this goal, the CIRCLES project designed a control system, referred to as the MegaController by the CIRCLES team, that could be deployed in real traffic. Our field experiment, the MegaVanderTest (MVT), leveraged a heterogeneous fleet of 100 longitudinally controlled vehicles as Lagrangian traffic actuators, each of which ran a controller with the architecture described in this article. The MegaController is a hierarchical control architecture that consists of two main layers. The upper layer is called the Speed Planner and is a centralized optimal control algorithm. It assigns speed targets to the vehicles, conveyed through the LTE cellular network. The lower layer is a control layer, running on each vehicle. It performs local actuation by overriding the stock adaptive cruise controller, using the stock onboard sensors. The Speed Planner ingests live data feeds provided by third parties as well as data from our own control vehicles and uses both to perform the speed assignment. The architecture of the Speed Planner allows for the modular use of standard control techniques, such as optimal control, model predictive control (MPC), kernel methods, and others. The architecture of the local controller allows for the flexible implementation of local controllers. Corresponding techniques include deep reinforcement learning (RL), MPC, and explicit controllers. Depending on the vehicle architecture, all onboard sensing data can be accessed by the local controllers or only some. Likewise, control inputs vary across different automakers, with inputs ranging from torque or acceleration requests for some cars to electronic selection of adaptive cruise control (ACC) setpoints in others. The proposed architecture technically allows for the combination of all possible settings proposed previously, that is {Speed Planner algorithms} × {local Vehicle Controller algorithms} × {full or partial sensing} × {torque or speed control}. As a result, most configurations were tested throughout the ramp up to the MegaVandertest (MVT).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Quantum Sensing of Electric Fields Using Spin-Correlated Radical Ion Pairs
Quantum sensing affords the possibility of using quantum entanglement to probe electromagnetic fields with exquisite sensitivity. In this work, we show that a photogenerated spin-correlated radical ion pair (SCRP) can be used to sense an electric field change created at one radical ion of the pair using molecular recognition. The SCRP is generated within a covalent donor–chromophore–acceptor system PXX–PMI–NDI, 1, where PXX = peri-xanthenoxanthene, PMI = 1,6-bis(p-t-butylphenoxy)perylene-3,4-dicarboximide, and NDI = naphthalene-1,8:4,5-bis(dicarboximide). The electron-rich PXX donor in 1 acts as a guest molecule that can be encapsulated selectively by a tetracationic cyclophane ExBox4+ host to give a supramolecular complex 1 ⊂ ExBox 4+ . Selective photoexcitation of the PMI chromophore results in ultrafast generation of the PXX •+ –PMI–NDI •– SCRP. When PXX is encapsulated by ExBox 4+ , the cyclophane generates an electric field that repels the positive charge on PXX •+ within PXX •+ –PMI–NDI •– , reducing the SCRP distance, i.e., the distance between the centers-of-charge on the donor and acceptor. Pulse-EPR measurements are used to measure the coherent oscillations created primarily by the electron–electron dipolar coupling in the SCRP, which yields the distance between the two charges (spins) of PXX •+ –PMI–NDI •– . Here, the experimental results show that the distance between PXX •+ and NDI •– decreases when ExBox 4+ encapsulates PXX •+ , which demonstrates that the SCRP can function as a quantum sensor to detect electric field changes in the vicinity of the radical ions.
Anions↗
Small molecule inhibition of cGAS reduces interferon expression in primary macrophages from autoimmune mice
Cyclic GMP-AMP synthase is essential for innate immunity against infection and cellular damage, serving as a sensor of DNA from pathogens or mislocalized self-DNA. Upon binding double-stranded DNA, cyclic GMP-AMP synthase synthesizes a cyclic dinucleotide that initiates an inflammatory cellular response. Mouse studies that recapitulate causative mutations in the autoimmune disease Aicardi-Goutières syndrome demonstrate that ablating the cyclic GMP-AMP synthase gene abolishes the deleterious phenotype. Here, we report the discovery of a class of cyclic GMP-AMP synthase inhibitors identified by a high-throughput screen. These compounds possess defined structure-activity relationships and we present crystal structures of cyclic GMP-AMP synthase, double-stranded DNA, and inhibitors within the enzymatic active site. We find that a chemically improved member, RU.521, is active and selective in cellular assays of cyclic GMP-AMP synthase-mediated signaling and reduces constitutive expression of interferon in macrophages from a mouse model of Aicardi-Goutières syndrome. RU.521 will be useful toward understanding the biological roles of cyclic GMP-AMP synthase and can serve as a molecular scaffold for development of future autoimmune therapies.
59 BASIC BIOLOGICAL SCIENCES↗
Nanoporous Gold as a Platform for a Building Block Catalyst
The porous bulk materials are of great interest in catalysis because they can be employed in heterogeneous gas and liquid phase catalysis, electrocatalysis, and in electrocatalytic sensing. Nanoporous gold gained considerable attraction in this context because it is the prime example of a corrosion-derived nanoporous bulk metal. Moreover, the material was shown to be a very active and selective Au type catalyst for a variety of oxidation reactions. In leveraging the functionalization of the surface of the material with various additives, its catalytic applications can be extended and tuned. In this review, we will summarize recent developments in using nanoporous gold as the platform for the development of high performance catalytic materials by adding metals, metal oxides, and molecular functionalities as building blocks.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Mid-infrared trace detection with parts-per-quadrillion quantitation accuracy: Expanding frontiers of radiocarbon sensing
Detection sensitivity is a critical characteristic to consider during selection of spectroscopic techniques. However, high sensitivity alone is insufficient for spectroscopic measurements in spectrally congested regions. Two-color cavity ringdown spectroscopy (2C-CRDS), based on intra-cavity pump–probe detection, simultaneously achieves high detection sensitivity and selectivity. This combination enables mid-infrared detection of radiocarbon dioxide ( 14 CO 2 ) molecules in room-temperature CO 2 samples, with 1.4 parts-per-quadrillion (ppq, 10 − 15 ) sensitivity (average measurement precision) and 4.6-ppq quantitation accuracy (average calibrated measurement error for 21 samples from four separate trials) demonstrated on samples with 14 C/C up to ∼ 1.5 × natural abundance ( ∼ 1,800 ppq). These highly reproducible measurements, which are the most sensitive and quantitatively accurate in the mid-infrared, are accomplished despite the presence of orders-of-magnitude stronger, one-photon signals from other CO 2 isotopologues. This is a major achievement in laser spectroscopy. A room-temperature-operated, compact, and low-cost 2C-CRDS sensor for 14 CO 2 benefits a wide range of scientific fields that utilize 14 C for dating and isotope tracing, most notably atmospheric 14 CO 2 monitoring to track CO 2 emissions from fossil fuels. The 2C-CRDS technique significantly enhances the general utility of high-resolution mid-infrared detection for analytical measurements and fundamental chemical dynamics studies.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Membrane potential sensing: Material design and method development for single particle optical electrophysiology
We review the development of “single” nanoparticle-based inorganic and organic voltage sensors, which can eventually become a viable tool for “non-genetic optogenetics.” The voltage sensing is accomplished with optical imaging at the fast temporal response and high spatial resolutions in a large field of view. Inorganic voltage nanosensors utilize the Quantum Confined Stark Effect (QCSE) to sense local electric fields. Engineered nanoparticles achieve substantial single-particle voltage sensitivity (~2% Δλ spectral Stark shift up to ~30% ΔF/F per 160 mV) at room temperature due to enhanced charge separation. A dedicated home-built fluorescence microscope records spectrally resolved images to measure the QCSE induced spectral shift at the single-particle level. Biomaterial based surface ligands are designed and developed based on theoretical simulations. The hybrid nanobiomaterials satisfy anisotropic facet-selective coating, enabling effective compartmentalization beyond non-specific staining. Self-spiking- and patched-HEK293 cells and cortical neurons, when stained with hybrid nanobiomaterials, show clear photoluminescence intensity changes in response to membrane potential (MP) changes. Organic voltage nanosensors based on polystyrene beads and nanodisk technology utilize Fluorescence (Förster) Resonance Energy Transfer (FRET) to sense local electric fields. Voltage sensing FRET pairs achieve voltage sensitivity up to ~35% ΔF/F per 120 mV in cultures. Non-invasive MP recording from individual targeted sites (synapses and spines) with nanodisks has been realized. However, both of these QCSE- and FRET-based voltage nanosensors yet need to reach the milestone of recording individual action potentials from individual targeted sites.
59 BASIC BIOLOGICAL SCIENCES↗
Development of a fast framing detector for electron microscopy
A high frame rate detector system is described that enables fast real-time data analysis of scanning diffraction experiments in scanning transmission electron microscopy (STEM). This is an end-to-end development that encompasses the data producing detector, data transportation, and real-time processing of data. The detector will consist of a central pixel sensor that is surrounded by annular silicon diodes. Both components of the detector system will synchronously capture data at almost 100 kHz frame rate, which produces an approximately 400 Gb/s data stream. Low-level preprocessing will be implemented in firmware before the data is streamed from the National Center for Electron Microscopy (NCEM) to the National Energy Research Scientific Computing Center (NERSC). Live data processing, before it lands on disk, will happen on the Cori supercomputer and aims to present scientists with prompt experimental feedback. This online analysis will provide rough information of the sample that can be utilized for sample alignment, sample monitoring and verification that the experiment is set up correctly. Only a compressed version of the relevant data is then selected for more in-depth processing.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗