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DOE OSTI2022

Continuous Particle Monitoring and Removal for Molten Chloride CSP Systems

This report describes the technologies that were developed as part of the Continuous Particle Monitoring and Removal for Molten Chloride CSP Systems project that was funded by the EERE Solar Energy Technologies Office during FY2021. This project consisted of two main tasks: (1) the development electrical resistance tomography (ERT) sensors to provide particle sensing capabilities for CSP-relevant molten chloride salts, and (2) the development of vortex separation technologies to enable efficient removal of particles from the salt. Both of these tasks are crucial because, although the Gen3 CSP chloride heat transfer fluid is inexpensive and can achieve high temperatures, major issues with erosion corrosion and clogging can arise from the presence of MgO particles within the salt. The particle monitoring and removal technologies were both demonstrated over the course of this project. The ERT sensors were able to achieve their performance targets by providing accurate particle concentration measurements over a range from 0.0 to 8.0 wt%. The vortex separators were able to demonstrate separation of particles from molten salt streams, but the separation efficiencies were lower than the targeted level of 90%. With further development and deployment, these technologies will ultimately help to enable successful long-term operations of CSP systems that make use of high-temperature chloride salts.

14 SOLAR ENERGY↗

DOE OSTI2022

Compact instantaneous phase-shifting Sagnac interferometer for nanoscale tilt measurement

There is a large inter disciplinary need for high precision angular sensors in state-of-the-art technologies. This particularly applies to optical metrology in the field of Extreme Ultraviolet (EUV) or X-ray where the optics are commonly characterized in terms of slope errors at a nanoradian scale level. Here, in this paper, we present the in-lab development of an angular sensor based on a single reflection compact Sagnac interferometer using instantaneous phase shifting. Our automated prototype and first results show less than 15 nrad RMS repeatability, at least 200 nrad sensitivity and 280 nrad reproducibility over 100 μrad angular range.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Advanced Frost Sensor for HVAC Applications

Frost is a common problem in heating, ventilation, and air conditioning (HVAC) systems that can degrade their efficiencies, leading to excessive electricity consumption. Appropriate defrosting is therefore essential for heat pumps and refrigeration systems. However, these systems typically run the defrost cycle based on a predetermined time interval, a method that does not accurately identify the amount of frost and thus consume excessive electricity. To substantially improve defrosting initiation and termination, this paper describes development of a smart sensor based on a capacitive sensing technique that can quantify frost accumulation and difference between frost, ice, and water. The reported sensor adopts interdigitated comb electrodes and can be updated to a potential multifunctional sensor array for the enhancing identification of frost, ice, and water with the integrated measurement of surface temperature, frost capacitance, and resistance. The proposed frost sensor is potentially expected to have widespread applications in HVAC systems, including heat pumps, refrigerators, and commercial refrigeration systems.

Gao, Zhiming↗

DOE OSTI2026

Fluorescence Signatures of Rare Earth Metals during Precipitation in Various Conditions

Fluorescence spectroscopy is a widely used sensor methodology that analyzes light emitted from a compound or element as it decays from an excited state. This technique is very sensitive and selective, which is ideal to characterize analytes at lower limits of detection. Key example targets of significant industry and research interest include rare earth elements (REEs) such as dysprosium (Dy) and europium (Eu). These are widely used in advanced technologies including semiconductors, electric vehicle motors, lasers, and permanent magnets. Identifying new sources and responsible reutilization of REEs is essential, and new approaches to extract and recycle REEs could be notably enhanced through the integration of on-line sensors. The sensors can support faster process design, informed scale-up, and cost-effective deployment. This study covers the initial exploration of applying fluorescence-based on-line monitoring to REEs within a precipitation process. This study demonstrates the successful scale-up of a fluorescence -based sensing approach, from stationary cuvettes and small-volume microfluidic devices to continuous flow systems operating at the bench scale (10-25mL). This work also provides initial insight into the challenges of signal’s effects and utility within a turbid environment. Using a modular design for monitoring flowing solutions in a flow tube, fluorescence can be characterized for a variety of analytical targets. In this study, detection performance parameters between the cuvette and flow tube system were compared. Additionally, the response of Dy during precipitation by sodium bicarbonate in the two measurement designs was explored. This letter represents a starting point to bridge the gap between traditional fluorescence sensor measurements in a cuvette to future developments that explore the ability to integrate fluorescence sensors into extraction and separation processes at industrially relevant scales.

fluorescence↗

DOE OSTI2023

Skin-integrated stretchable actuators toward skin-compatible haptic feedback and closed-loop human-machine interactions

Abstract Skin-integrated haptic interfaces that can relay a wealth of information from the machine to the human are of great interest. However, existing haptic devices are not yet able to produce haptic cues that are compatible with the skin. In this work, we present the stretchable soft actuators for haptic feedback, which can match the perception range, spatial resolution, and stretchability of the skin. Pressure-amplification structures are fabricated using a scalable self-assembly process to ensure an output pressure beyond the skin perception threshold. Due to the minimized device size, the actuator array can be fabricated with a sufficiently high spatial resolution, which makes the haptic device applicable for skin locations with the highest spatial acuity. A haptic feedback system is demonstrated by employing the developed soft actuators and highly sensitive pressure sensors. Two proof-of-concept applications are developed to illustrate the capability of transferring information related to surface textures and object shapes acquired at the robot side to the user side.

Chen, Si↗

DOE OSTI2025

Silicon wafer fracture stress for tracking sensors in particle physics experiments

For the construction of the ATLAS Inner Tracker strip detector, silicon strip sensor modules are glued directly onto carbon fibre support structures using a soft silicone gel. During tests at temperatures below -35°C, several of the sensors were found to crack due to a mismatch in coefficients of thermal expansion between polyimide circuit boards with copper metal layers (glued onto the sensor) and the silicon sensor itself. While module assembly procedures were developed to minimise variations between modules, cold tests showed a wide range of temperatures at which supposedly comparable modules failed. The observed variance (fracture temperatures between -35°C and -70°C) for supposedly comparable modules suggests an undetected variation between modules suspected to be intrinsic to the silicon wafer itself. Therefore, a test programme was developed to investigate the fracture stress of representative sensor wafer cutoffs. This paper presents results for the fracture stress of silicon sensors used in detector modules.

Detector design and construction technologies and ↗

DOE OSTI2022

Barriers to Broader Utilization of Fault Detection Technologies for Improving Residential HVAC Equipment Efficiency

Faults in residential heating, ventilating, and air conditioning (HVAC) equipment may occur due to poor installation practices or develop over time, and these faults can negatively impact system efficiency, thermal comfort, and equipment lifespan. Automated fault detection and diagnostic (AFDD) technologies identify energy wasting HVAC faults, such as low indoor airflow and improper refrigerant charge, and guide technicians in improving system efficiency. For residential HVAC, AFDD consists of a range of fault detecting and diagnostic capabilities, sensor configurations, and target applications. AFDD technology can either be permanently installed by the original equipment manufacturer (OEM) using embedded sensors or as an add-on product either during or after installation. Additionally, several advanced installation tools and refrigerant gauge sets include AFDD features for temporary use during equipment installation and tune-ups. Some technologies can detect a fault but have limited diagnostic capabilities. For example, a single-point measurement from the home's thermostat or energy monitor can provide certain fault detection capability by analyzing the equipment runtime or energy consumption. These technologies, though limited at determining the cause of a given fault, may have significant energy savings potential due to their low cost and prevalence in the residential HVAC market. Despite the potential benefits, fault detection technologies face many technical and market barriers preventing broad adoption. Beyond the cost barriers due to the added sensor requirements and technology development, fault detection technologies face many implementation and adoption barriers such as installer training, customer awareness, standardized communication protocols, and methods of test for evaluating accuracy. The purpose of this whitepaper is to characterize market and technical barriers impeding broader utilization of fault detection technology for residential HVAC energy efficiency applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Casing Annulus Monitoring of CO 2 Injection Using Wireless Autonomous Distributed Sensor Networks

Effective and secure carbon subsurface storage, involving the deep underground injection of CO 2 into geological formations where it is permanently trapped, is paramount to mitigating CO 2 emissions (Figure I). Ensuring the integrity of these storage sites and detecting potential leakage through the casing annulus necessitates robust monitoring. This work provides the first integrated demonstration of a wireless casing-annulus monitoring architecture that can operate in highly attenuating cement-brine environments relevant to CO 2 storage. This project focused on developing and validating a novel sensor system for integration with autonomous monitoring near the cement reservoir interface. The goal was a fully integrated Technology Readiness Level (TRL) 4/5 field validation of a distributed wireless intelligent sensor system providing real-time, direct subsurface formation measurements to enhance fluid movement monitoring in the cemented casing annulus. Achieving this objective required the development and integration of 1) wireless autonomous microsensor technology by California Institute of Technology (Caltech); 2) sensor packaging and emplacement technology by Research Triangle Institute (RTI); and 3) smart well completions using wireless active casing collars and NOV pipe by the Sandia National Lab (SNL). The collaboration with the Caltech team in this project aimed to develop millimeter-scale radio frequency identification (RFID) sensors capable of detecting CO 2 , pH, and/or methane levels. These sensors are engineered to be impervious to fluids, allowing them to be mixed with cement and installed within the casing annulus. They operate using RFID protocols at frequencies of 902–928 MHz for both power and communication. A Sandia National Laboratories’ team engaged their expertise in the development of a Smart Collar system designed for the wireless data collection from these RFID sensors embedded in the cement annulus and transmission of this information to the ground surface via IntelliPipe/IntelliServ NOV drill pipe. This is accomplished through inductive coupling at the collar, which facilitates data transfer through each segment of the pipe. Because the system cannot transmit a direct current signal to power the Smart Collar, both power and communication were implemented using alternating current and electromagnetic signals at varying frequencies. Furthermore, the developed microsensor technology had to be demonstrated and validated in comparison with reference transducer measurements in a field test site at The University of Texas at Austin (UT-Austin). Although the full sensor suite did not reach field-deployment readiness, the system-level integration achieved in this project establishes a validated pathway for future incorporation of advanced microsensors.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Bio‐Imaging quorum sensing signal molecules in a soil‐mimic gel

Rhizosphere, the narrow region surrounding plant roots directly influenced by root exudates and the root associated microbiome, plays an important role in plant productivity and the rhizosphere is well known for stimulating microbial metabolic activities. How microbial communities interact to form stable, metabolically interconnected functional communities is an area of intense interest. The question remains on how microbially produced secreted molecules that function as intercellular communication signals shape the structure and function of microbial communities. Our goal is to detect and quantify signal molecules produced by microbes or plants in the root‐soil environment, spatially and temporarily. As a proof‐of‐concept, we are imaging diffusible extracellular microbial metabolites involved in a bacteria‐bacteria communication process called quorum‐sensing. Quorum‐sensing relies on the accumulation of high concentrations of signal molecules in the environment to control bacterial gene expression, influencing rhizosphere colonization and plant health. Local concentration of quorum sensing molecules are determined using aptamer based sensors. Aptamers that can specifically bind the desired signal molecules are selected through SELEX and immobilized on the surface of nano‐porous membranes. Binding of the signal molecules and aptamer covered surface results in changes in surface charge distribution and steric hinderance and thus modifying the transmembrane ionic transport. Changes in transmembrane impedance can be measured through electrochemical impedance spectroscopy methods to monitor local concentrations of signal molecules. Sensor responses were determined for different concentrations of signal molecules and results showed detection of C4‐HSL in a soil‐mimic solution with K D of 10 nM. We demonstrate that the quorum‐sensing signal molecule C4‐homoserine lactone and (C4‐HSL) can rapidly diffuse in a soil‐mimic gel, providing evidence for our use of a soil‐mimic for further aptasensor development and validation. The sensors were then inserted into soil mimic gel for monitoring C4‐HSL diffusion and the resulted impedance changes were used to determine the C4‐HSL concentration at different positions in the gel. Measurements of local C4‐HSL concentrations variation and numerical solution of diffusion equation were used to create 4D images of C4‐HSL molecule diffusion in the soil‐mimic gel.

Jiang, Nianyu↗

DOE OSTI2024

Design Optimization and Measurement Uncertainty of an Electromagnetic Level Sensor for Liquid Metal Reactors

Here, this article describes the design and operation of a prototype mutual inductance level sensor (MILS) and the development and validation of a finite-element analysis (FEA) model describing its behavior. The MILS was designed for use in liquid sodium up to temperatures of 650 °C in the Mechanisms Engineering Test Loop (METL) at Argonne National Laboratory (ANL). Preliminary testing was performed in a room temperature test stand with aluminum acting as an analog for the sodium to better understand sensor performance and provide accurate code validation data. This experimental data, along with material properties found in literature, were used to validate an FEA model in ANSYS Maxwell. The validated ANSYS Maxwell model was used to examine the performance of the MILS in various environments and under various operating conditions. Simulations suggest the following: The MILS will perform adequately in liquid sodium and liquid lead at temperatures up to 650 °C . The temperature dependence of electrical conductivity imposes a temperature dependence on the sensor that requires proper compensation. The MILS signal sensitivity is maximized when mutual inductance between sensor coils is maximized, and sensor geometry should be selected to account for this factor. The operating frequency of the MILS can be optimized and is dependent on process fluid material, operating temperature, and materials/geometry of sensor system. Finally, the use of a stainless-steel isolating thimble does not adversely affect the sensor signal. The primary sources of error for this MILS system are the accuracy of the calibration standard against which the sensor is calibrated, and the temperature dependence of the sensor. This work contains all the necessary details to recreate the FEA model and results. This model can be used to optimize the performance of a MILS in any operating environment to read any electrically conductive working fluid.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Adapting Secure MultiParty Computation to Support Machine Learning in Radio Frequency Sensor Networks

In this project we developed and validated algorithms for privacy-preserving linear regression using a new variant of Secure Multiparty Computation (MPC) we call "Hybrid MPC" (hMPC). Our variant is intended to support low-power, unreliable networks of sensors with low-communication, fault-tolerant algorithms. In hMPC we do not share training data, even via secret sharing. Thus, agents are responsible for protecting their own local data. Only the machine learning (ML) model is protected with information-theoretic security guarantees against honest-but-curious agents. There are three primary advantages to this approach: (1) after setup, hMPC supports a communication-efficient matrix multiplication primitive, (2) organizations prevented by policy or technology from sharing any of their data can participate as agents in hMPC, and (3) large numbers of low-power agents can participate in hMPC. We have also created an open-source software library named "Cicada" to support hMPC applications with fault-tolerance. The fault-tolerance is important in our applications because the agents are vulnerable to failure or capture. We have demonstrated this capability at Sandia's Autonomy New Mexico laboratory through a simple machine-learning exercise with Raspberry Pi devices capturing and classifying images while flying on four drones.

42 ENGINEERING↗

DOE OSTI2025

Plant-Enhanced Degradation Of Munitions by Engineered TERrestrial microbes (PEDOMETER) (Final Report)

LLNL led two major Technical Areas (TAs) within the PEDOMETER program: TA3 focused on biocontainment and TA4 focused on developing electrochemical TNT degradation sensors and testbeds. A key takeaway from our work is the importance of chassis host strain choice for kill switch design and actuator choice. Genetic instability of the kill switch circuit is a major barrier toward establishing a kill switch, which is host dependent. Addition of a host down-selection step to regulator and actuator screening stages would be beneficial to hasten kill switch development.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Optimal Traffic Signal Control Using Priority Metric Based on Real-Time Measured Traffic Information

Optimizing traffic control systems at traffic intersections can reduce network-wide fuel consumption as well as improve traffic flow. While traffic signals have conventionally been controlled based on predetermined schedules, various adaptive control systems have been developed recently using advanced sensors such as cameras, radars, and LiDARs. By utilizing rich traffic information enabled by the advanced sensors, more efficient or optimal traffic signal control is possible in response to varying traffic conditions. This paper proposes an optimal traffic signal control method to minimize network-wide fuel consumption utilizing real-time traffic information provided by advanced sensors. This new method employs a priority metric calculated by a weighted sum of various factors, including the total number of vehicles, total vehicle speed, vehicle waiting time, and road preference. Genetic Algorithm (GA) is used as a global optimization method to determine the optimal weights in the priority metric. In order to evaluate the effectiveness of the proposed method, a traffic simulation model is developed in a high-fidelity traffic simulation environment called SUMO, based on a real-world traffic network. The traffic flow within this model is simulated using actual measured traffic data from the traffic network, enabling a comprehensive assessment of the novel optimal traffic signal control method in realistic conditions. The simulation results show that the proposed priority metric-based real-time traffic signal control algorithm can significantly reduce network-wide fuel consumption compared to the conventional fixed-time control and coordinated actuated control methods that are currently used in the modeled network. Additionally, incorporating truck priority in the priority metric leads to further improvements in fuel consumption reduction.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Distributed Magnetic Field and Temperature Monitoring for Superconducting Radio Frequency Cavities

The overall objective of the proposed Phase I program was to design, construct and demonstrate a fiber optic sensing system capable of providing temperature and magnetic field measurements with an enhanced spatial resolution that can be implemented over a large surface area (cryomodules) to survey superconducting radio frequency cavities and magnets. A magnetic field sensor capable of detecting fluxes on the order of 1 μT is required to detect the distribution of trapped flux on the cavity surface. A unique distributed magnetic field sensor was successfully designed and constructed to demonstrate the detection of magnetic fluxes less than 500 nT. The sensor leveraged the ultra-high sensitivity of Sentek’s picoDAS to measure the magnetostriction induced vibrations in a commercially available Metglas 2605 SC ribbon that was in physical contact with sensing fiber. Static magnetic fields were detected by applying an alternating current a copper wire proximate to the Metglas 2605SC ribbon to create an AC bias magnetic field. In an alternative approach, an AC bias magnetic field was applied to a special magnetic field sensing fiber with Metglas 2605SC cladding successfully detect a magnetic field flux of a 3 μT. Exhaustive testing was performed to characterize the dependency of sensor response on the direction of the applied magnetic field. Although the special sensing fiber based magnetic field sensor did not exhibit an observable dependence on the direction of the magnetic field, the Metglas 2605SC ribbon sensor exhibited a clear directional dependence. A wide variety of polymer materials were evaluated to enhance the temperature response of an FBG based sensor at cryogenic temperatures. The processing and performance challenges provided the motivation to develop a new simple cryogenic temperature sensor that uses a commercially available fiber optic splice protector. The EVA hot melt tube that becomes adhered to the optical fiber and the polyolefin outer tube that shrinks upon heating in the fusion splicer heater provide the high thermal expansion coefficient necessary to impart a significant strain on the FBG when exposed to cryogenic temperatures. The temperature sensitivity (Δ𝜆𝐵𝑟𝑎𝑔𝑔~ 62 𝑝𝑝𝑚/℃) of the FBG-based sensor was on par with the best reported to date. The simple design, use of readily available cost-effective materials, and well-established processing techniques lends this approach to the creation of hundreds to thousands of temperature sensors on one single optical fiber length. The inherently small form factor also allows for co-location with the distributed magnetic field sensor. In preparation for field testing of the prototype sensing system at the Jefferson Labs in potential Phase II program, several different cable designs were evaluated to package the sensors. The preliminary successful demonstration of fully functional sensing cables provides the foundation for subsequent development efforts to advance the Technology Readiness Level of the technology. The technical feasibility of the proposed approach was successfully demonstrated in this Phase I effort.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Leak Detection and Sensor Importance Within a Solvent Extraction Process Abstract

In anticipation of the Special Nuclear Material test bed (Beartooth), Idaho National Laboratory has developed a smaller, multi-sensor system for analyzing the solvent extraction process. These systems will allow for research into nuclear fuel processing operations. The multi-sensor system consists of a row of centrifugal contactors and allows for measurement sources that are not traditionally used in the solvent extraction process to be explored including temperature, vibration, acoustics, pH, color, flow, and motor current. Currently, the solvent extraction process is very labor intensive and requires vigilant operators to identify the occurrence of leaks, which can be common during startup or after any change to the system. This study aims to locate leaks using non-traditional measurement sources then to identify which signals were of greatest importance in making this classification using Local Interpretable Model-agnostic Explanations. These results can be used to help solvent extraction process operators detect leaks and to inform future test beds designers to which sensors contain relevant, actionable information in this scenario.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Test Beam Results of Planar Pixel Sensor for the CMS Phase 2 Inner Tracker Upgrade

Results of the test beam measurements that characterise the performance of CMS Readout Chip (CROC) sensors to be used in the High Luminosity era of the Large Hadron Collider (HL-LHC) are presented. The HL-LHC peak instantaneous luminosity of $7.5 \times 10^{34} \ \text{cm}^{-2} s^{-1}$ corresponds to an average of around 200 inelastic proton-proton collisions per beam-crossing every 25 ns. In order to efficiently reconstruct and track particles in this extreme and challenging conditions, the present CMS tracking detector will be completely replaced. The new tracking detector consists of an Inner Tracker closest to the beamline and an Outer Tracker surrounding it. These are populated with modules that comprise of readout chips and silicon sensors. The test beam measurements of these modules are vital to understand the performance of the related technologies. Using a primary 120 GeV proton beam from the Main Injector at Fermilab, data was collected at the Fermilab Test Beam Facility (FTBF) using the silicon tracker telescope that provides a precision position measurement of the track impact point with less than 5 $\mu$m uncertainty. The proton beam was incident on a 1x2 planar CROC module developed by Hamamatsu. The sensor has 100x25 $\mu m^2$ standard pixels and also a smaller number of 225x25 $\mu m^2$ longer pixels at the boundary between the two ROCs. We present characterization of these modules that includes pixel efficiency, resolution, cluster size and charge distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Sensor Impact Evaluation at Different Sensor Locations in a Multi-zone Office Building

FY 2022 Q1 deliverables include the development of an emulator that can evaluate the sensor impacts at different sensor locations (i.e., thermostat locations) in a multizone office building. This report presents the detailed procedure of developing the emulator and using the emulator for preliminary sensor impact analysis. In designing new multizone buildings or retrofitting existing buildings, the room thermostat locations or subzoning design has been often determined by best practices without considering the effects of this design in terms of energy or thermal comfort. In subzoning design, the total number of thermostats is usually smaller than the total number of rooms. As a result, one thermostat in one room often controls the indoor temperature of several other adjacent rooms. For example, five zones might share one thermostat located in one of the zones. Because the demands for thermal load in different zones could be different for the multizone buildings, this subzoning design can compromise control performance and waste building energy consumption. Furthermore, for multizone buildings, subzoning could introduce thermal discomfort for zones. This issue has not be thoroughly investigated in simulation/field studies, and the US Department of Energy’s Oak Ridge National Laboratory explored the impacts of subzoning design through modeling and experimental study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Machine Straightness Error Measurement Based on Optical Fiber Fabry–Pérot Interferometer Monitoring Technique

Abstract In this research, we propose an Error Separation Technique (EST) based on optical fiber sensors for on-machine straightness error measurement. Two fiber optic Fabry–Pérot interferometers have been developed serving as two displacement sensors. The displacement distance is computed according to the reflected spectrum from interferometers, which can achieve a sub-micrometer resolution. The two-point method has been employed to separate the straightness error of the slides and the profile error of a fine-polished standard block. The spacing distance between two interferometers is determined by the diameter of optical fibers so that the EST's resolution has the potential to reach the sub-millimeter scale. In the experiment, the straightness error has been measured on a commercially available computer numerical control machine tool, and the measurement has been conducted on its x-axis. The spacing distance between two optical fiber sensors is 1.5 mm which equals the EST's resolution along the machine tool's x-axis. The separated profile error of the measured standard block is around 30 µm which has been verified by a high precision Coordinate Measurement Machine (CMM). The magnitude of the separated straightness error is around 40 µm. This technique is flexible and simple to be conducted, which can contribute to the micro-machine tool calibration and other straightness error applications.

Engineering↗