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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Novel Sensor for the In Situ Measurement of Uranium Fluxes

The goal of this project was to develop a sensor that incorporates the field-tested concepts of the passive flux meter to provide direct in situ measures of flux for uranium and groundwater in porous media. Measurable contaminant fluxes [J] are essentially the product of concentration [C] and groundwater flux or specific discharge [q ]. The sensor measures [J] and [q] by changes in contaminant and tracer amounts respectively on a sorbent. By using measurement rather than inference from static parameters, the sensor can directly advance conceptual and computational models for field scale simulations. The sensor was deployed in conjunction with DOE in obtaining field-scale quantification of subsurface processes affecting uranium transport (e.g., advection) and transformation (e.g., uranium attenuation) at the Rifle IFRC Site in Rifle, Colorado. Project results have expanded our current understanding of how field-scale spatial variations in fluxes of uranium, groundwater and salient electron donor/acceptors are coupled to spatial variations in measured microbial biomass/community composition, effective field-scale uranium mass balances, attenuation, and stability. The coupling between uranium, various nutrients and micro flora can be used to estimate field-scale rates of uranium attenuation and field-scale transitions in microbial communities. This research focuses on uranium (VI), but the sensor principles and design are applicable to field-scale fate and transport of other radionuclides. Laboratory studies focused on sorbent selection and calibration, along with sensor development and validation under controlled conditions. Field studies were conducted at the Rifle IFRC Site in Rifle, Colorado. These studies were closely coordinated with existing SBR (formerly ERSP) projects to complement data collection. Small field tests were conducted during the first two years that focused on evaluating field-scale deployment procedures and validating sensor performance under controlled field conditions. In the third and fourth year a suite of larger field studies were conducted. For these studies, the uranium flux sensor was used with uranium speciation measurements and molecular-biological tools to characterize microbial community and active biomass at synonymous wells distributed in a large grid. These field efforts quantified spatial changes in uranium flux and field-scale rates of uranium attenuation (ambient and stimulated), uranium stability, and quantitatively assessed how fluxes and effective reaction rates were coupled to spatial variations in microbial community and active biomass. Analyses of data from these field experiments were used to generate estimates of Monod kinetic parameters that are ‘effective’ in nature and optimal for modeling uranium fate and transport at the field-scale. This project provided the opportunity to develop the first sensor that provides direct measures of both uranium (VI) and groundwater flux. A multidisciplinary team was assembled to include two geochemists, a microbiologist, and two quantitative contaminant hydrologists. Now that the project is complete, the sensor can be deployed at DOE sites to evaluate field-scale uranium attenuation, source behavior, the efficacy of remediation, and off-site risk. Because the sensor requires no power, it can be deployed at remote sites for periods of days to months. The fundamental science derived from this project can be used to advance the development of predictive models for various transport and attenuation processes in aquifers. Proper development of these models is critical for long-term stewardship of contaminated sites in the context of predicting uranium source behavior, remediation performance, and off-site risk.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Demonstration and Validation of a Portable Raman Sensor for In-Situ Detection and Monitoring of Perchlorate (ClO 4 - )

Costs for environmental analysis and monitoring are increasing at a rapid rate and represent a significant percentage of the total and future remedial expenses at many U.S. Department of Defense (DoD) contaminated sites. It has been reported that about 30 to 40% of the remediation budget is usually spent on long-term monitoring (LTM), of which a large percentage represents laboratory analytical costs. Energetics such as perchlorate (ClO 4 - ) are among the most frequently detected contaminants in groundwater and surface water at or near military installations due to their persistence and mobility. Currently, the standard protocol entails collecting samples in the field, packaging them, and shipping them overnight to a designated laboratory for analysis. This process requires significant sample preparation and handling, and analytical results may not be available for several days to weeks. In this project, we developed and demonstrated a portable Raman sensor based on surface enhanced Raman scattering (SERS) technology to detect ClO 4 - in contaminated water. We summarize major accomplishments as follows: • A SERS sensor based on elevated gold (Au) nano-ellipse dimer architectures was designed and developed for ClO 4 - with a detection limit of ~10 -6 M (or 100 μg/L); The performance of these sensors was evaluated and optimized through variation of their geometric characteristics (i.e., dimer aspect ratio, dimer separation, etc.). • Large-scale commercial production of SERS substrate sensors via nanoimprinting by Nanova Inc. and Nanoimprint lithography (NIL) technology was successfully demonstrated. This is a substantial step forward toward the commercialization of the SERS sensors and may potentially lead to significantly reduced fabrication costs of SERS substrates. • Commercially produced SERS sensors were demonstrated to detect ClO 4 - at levels above 10 -6 M using a portable Raman analyzer. The performance of the commercial SERS sensors for ClO 4 - detection in the presence and absence of interferences was determined for a series of standard solutions. Sulfate (SO 4 2- ) was found to exhibit the greatest interference for the anions tested, which included Cl-, NO 3 - , and SO 4 2- . • Field demonstration of the portable Raman sensor with commercially produced SERS substrates was completed at two Department of Defense (DoD) sites; twice at the Indian Head Naval Surface Warfare Center, Indian Head, MD, and once at Redstone Arsenal, Huntsville, AL. Multiple wells were sampled at both DoD sites, where a standard addition method was employed using the sensor to determine the ClO 4 - 4 - and possibly other energetics that are both important for environmental monitoring and of interest for national security. However, we point out that SERS technology is also prone to interferences due to its sensitivity and responses to other ionic species, such as NO 3 - , SO 4 2- , and dissolved organics or co-contaminants present in the groundwater, which could potentially mask the SERS signal of the target analyte (i.e., ClO 4 - ). As such, SERS analysis was subject to significant variations (e.g., ±20% or more), and its detection limit for ClO 4 - -8 M) and was substantially higher than what we anticipated from laboratory studies. However, despite these complications, the portable Raman sensor developed in this project could be used as a rapid screening tool for ClO 4 - at concentrations above 10 -6 M. Future studies are warranted to further develop the technology and to optimize its performance, and eventually to bring the technology to the market. With additional development and demonstration, the sensor has the potential to reduce analytical costs by eliminating shipping and typical costs associated with laboratory analysis. A cost savings of 30–45% may be realized during a typical sampling event and, more importantly, the technology could allow rapid turn-around of information to decision makers for site characterization and remediation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Performance Results for Sensor Assignment Problem as Solved on a Multi-Node Cluster

An earlier report described a procedure for optimal sensor set selection and its implementation on a computational cluster. This new and innovative capability was developed to facilitate a reduction in operations staffing levels to improve plant economics. By automating surveillance and maintenance tasks through early detection of degrading sensors and equipment, staff can be more efficiently deployed. The method uses automated reasoning and domain knowledge in the form of the conservation equations to infer from plant measurements the state of equipment health. Inclusion of domain knowledge addresses the problem that exists with pure data-driven methods that there are no rigorous guidelines for determining what constitutes an adequate sensor set. Formalizing the procedure for sensor set selection as we have done results in a more reliable and explainable diagnosis of plant equipment health. Importantly, from the standpoint of the plant owner, personnel are provided with an early and explicit diagnosis of an equipment problem. That in principle automates the process and eliminates having to send personnel into the plant to find the cause as typically occurs when a data-driven method detects an anomaly. In this report we describe first results obtained using a computational cluster to solve the sensor set selection problem as framed above. The case described addresses the problem of equipment health monitoring in the high-pressure (HP) feedwater system of a pressurized light water reactor as seen through the eyes of our collaborating utility partner. Maintenance of this system can amount to millions of dollars per year if equipment health issues go undiagnosed and lead to loss of function. On examining the potential that is inherent in the installed sensor set for diagnosing equipment health degradation, it was found that greater fault resolution capability can be achieved using a sensor set that is 20 percent fewer in number. The take-away is that compared to the installed sensor set there exists a more strategic assignment of sensors that will furnish better health monitoring capability and with fewer sensors. Where the problem defies solution by manual inspection, as is the case here, one can be found by an algorithm. The solution was obtained in four hours using 30 computational cores. The HP feedwater problem as posed above illustrates the added value of approaching the sensor selection problem as one amenable to algorithmic solution. This problem is of interest to advanced reactor designers and to utilities that are setting up remote monitoring and diagnostic centers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

WIRE-21 Sensor Irradiation Experiment Ready for HFIR Insertion

The ability to deploy new nuclear fuels for current or future reactor concepts requires a wealth of data regarding fuel performance during normal operation, anticipated operational occurrences, and design-basis accidents. Most of these data have historically been collected during experiments in materials test reactors, ideally with online instrumentation to collect as much data as possible. However, advanced instrumentation could also allow for in situ monitoring of fuel operating conditions during commercial reactor operation to maximize fuel utilization, reduce unnecessary conservativism in design margins, and improve operator understanding of limiting peaking factors. The latter approach would complicate fuel handling, particularly during refueling, unless the instrumentation could be placed inside the fuel rods and transmitted wirelessly to a receiver located outside the fuel’s primary pressure boundary. To this end, Westinghouse Electric Company (WEC) developed wireless sensors based on inductive coupling that can transmit information regarding fuel centerline temperatures and rod internal pressures wirelessly from within a fuel rod to a nearby instrument thimble. After testing these sensors in lower-power university research reactors, the next step is to perform high neutron fluence testing to characterize the performance of these wireless sensors under conditions that are more representative of the intended application—in this case, light-water reactors (LWRs). The removable Be (RB) positions of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) provide the neutron flux, experiment volume, and access to instrument leads required to achieve these sensor testing goals. This report summarizes the design, analysis, and assembly of the Wireless Instrumented RB Experiment 2021 (WIRE-21). This is the most highly instrumented irradiation experiment ever performed in HFIR. The experiment will use seven different sensing techniques to measure temperature, pressure, neutron flux, and neutron fluence during reactor operation. In addition to WEC’s wireless temperature and pressure sensors, WIRE-21 includes an array of thermocouples, self-powered neutron detectors, spatially distributed fiber optic temperature sensors, passive SiC temperature monitors, and flux wires. The design of WIRE-21 and the cabling that was installed in HFIR also provide the infrastructure to enable accelerated, economical testing of advanced sensor technologies while leveraging the extremely high neutron flux that is available in HFIR. The containment for WIRE-21 is similar to previous RB irradiation vehicles but includes a few modifications, most notably the use of integrated compression seals to pass a larger number of sensor leads through the experiment’s pressure boundary. In addition to the sensor leads, inert gas lines are passed into the experiment to enable active temperature control and the ability to pneumatically actuate a bellows-driven pressure sensor. WIRE-21 is targeting component temperatures (300–350°C) and neutron fluence levels (~10 22 n/cm 2 ) that would be expected in the plenum region of LWR fuels, except for the active sensing region of the wireless temperature sensor, which is targeting LWR fuel centerline temperatures (~800–1,100°C). WIRE-21 was successfully assembled, passed all nondestructive examination, and was delivered to HFIR for insertion during upcoming cycle 498 (April 2022).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Assessment of Flow-Enhanced Electrochemical Sensor Testing and Deployments

The goal of our activities in FY24 was to enable advanced materials accountancy for molten salt reactors (MSRs) through the development and optimization of robust flow-enhanced electrochemical sensors (FEES) using a safeguards-focused sensor testing platform called the modular flow instrumentation testbed (MFIT). Flow-enhanced electrochemical sensors are a type of electroanalytical sensor that have been developed at Argonne National Laboratory to be installed directly into MSR flow conduits to make measurements of the salt composition. These sensors represent a significant improvement in capabilities compared to earlier electroanalytical sensors that instead can only be operated in quiescent conditions. Previous work has focused on testing of the FEES in flowing conditions provided by the MFIT to assess the accuracy and precision of the sensor measurements. This year, the FEES technical readiness was increased by (1) demonstrating the use of optimized sensor techniques to achieve measurements in very high-concentration MSR-relevant salts, (2) leveraging new multimodal sensors and automation approaches to reduce measurement uncertainties, and (3) fabricating and deploying sensors to industrial partners to improve their ability to make measurements in challenging environments. Additionally, we also ran the sensors during complex system operations involving combined flow and purification activities to demonstrate safeguards-relevant measurements during online processing for MSRs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Nanomaterials for Sensor Applications

A large part of the advances in nanotechnology have been directed towards the development of highspeed electronics, more efficient catalysts, and sensors. This latter group of applications has great relevance and unprecedented development potential for the coming years. Some of the main objectives for the development of sensors have focused on making more sensitive, effective and specific sensing devices. The improvement of these systems and the increase of specificity are clearly associated with a decrease in size of the components, which can lead to obtaining more rapid action, almost in real time. Nanomaterials currently used in sensor development include a long list of nanostructured systems, as for example: Metal nanotubes, nanowires, nanofibers, nanocomposites, nanorods, nanoparticles, nanostructured polymers, and different allotropes of carbon as carbon nanotubes, graphene or fullerenes, among others [1]. These nanomaterials are characterized by having unique physicochemical properties, including high electrical and thermal conductivity, extremely high surface area/volume ratio, high mechanical strength and even excellent catalytic properties [1] [2]. These materials, may exhibit relevant physicochemical behavior, such as quantization or electronic confinement effects, which can be used in the development of all kinds of sensors [2]. So far, sensors have been developed for determination and quantification of gases, radiation, biomolecules, microorganisms, etc. [2] [3]. The sensors developed so far usually use the system lock and key, wherein the selective receptor (lock) is selectively anchored to the analyte of interest (or key). This system has great limitations when analyzing the analyte in the presence of other analytes, which can alter the sensitivity or specificity of the measure, as occurs in sensors used in biomedical applications [3] [4]. One possible solution is based on the development of sensor arrays, consisting of a combination of different and specific sensors, which may enable simultaneous measurements of one or more analytes in a less favorable environment [5] in these cases. These sensors are now a reality, although there is still a long way to go before the levels of precision and accuracy are reached. Future challenges for the development and commercialization of efficient sensors are mainly focused on improving the specificity, reproducibility, and the ability to detect trace levels. We hope that in the coming years nanotechnology and nanomaterials allow reaching previously unimaginable advances in the development of these systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2012

Transducer Signal Noise Analysis for Sensor Authentication

The abstract is being passed through STIMS for submision to the conference. International safeguards organizations charged with promoting the peaceful use of nuclear energy employ unattended and remote monitoring systems supplemented with onsite inspections to ensure nuclear materials are not diverted for weaponization purposes. These systems are left unattended for periods of several months between inspections. During these periods physical security means are the main deterrent used to detect intentional monitoring system tampering. The information gathering components are locked in secure and sealed rooms. The sensor components (i.e. neutron and gamma detectors) are located throughout the plant in unsecure areas where sensor tampering could take place during the periods between inspections. Sensor tampering could allow the diversion of nuclear materials from the accepted and intended use to uses not consistent with the peaceful use of nuclear energy. A method and an apparatus is presented that address the detection of sensor tampering during the periods between inspections. It was developed at the Idaho National Laboratory (INL) for the Department of Energy (DOE) in support of the IAEA. The method is based on the detailed analysis of the sensor noise floor after the sensor signal is removed. The apparatus consists of a 2.1” x 2.6” electronic circuit board containing all signal conditioning and processing components and a laptop computer running an application that acquires and stores the analysis results between inspection periods. The sensors do not require any modification and are remotely located in their normal high radiation zones. The apparatus interfaces with the sensor signal conductors using a simple pass through connector at the normal sensor electronics interface package located in the already secure and sealed rooms. The apparatus does not require hardening against the effects of radiation due to its location. Presented is the apparatus design, the analysis method, and the test results as applied to tamper detection using three HE3 neutron sensors and two gamma sensors designed and built for safeguards monitoring.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

RF Energy Harvesting Peel-and-Stick Sensors

PARC, a Xerox Company, is developing a low-cost system of peel-and-stick wireless sensors that will enable widespread building environment sensor deployment with the potential to deliver up to 30% energy savings. The system is embodied by a set of RF hubs that provide power to the automatically located sensor nodes, and relays data wirelessly to the building management system (BMS). The sensor nodes are flexible electronic labels powered by rectified RF energy transmitted by a RF hub and can contain multiple printed and conventional sensors. The system design overcomes limitations in wireless sensors related to power delivery, lifetime, and cost by eliminating batteries and photovoltaic devices. The sensor localization is performed automatically by the inclusion of a programmable multidirectional antenna array in the RF hub. Comparison of signal strengths when the RF beam is swept allows for sensor localization, further reducing installation effort and enabling automatic recommissioning of sensors that have been relocated, overcoming a significant challenge in building operations. PARC has already demonstrated wireless power and temperature data transmission up to a distance of 20m with a duty cycle less than a minute between measurements, using power levels well within the FCC regulation limits in the 902-928 MHz ISM band. The sensor’s RF energy harvesting antenna dimensions was less than 5cmx9cm, demonstrating the possibility of small form factor for the sensor nodes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Sensor network system

A sensor network system that includes a sensor array having a plurality of sensor units that include a plurality of sensor elements, each sensor element configured to generate an electrical signal in response to a chemical environment in the vicinity of the sensor unit. The set of electrical signals generated by the sensor elements of the sensor unit represents a measured signature of the environment in the vicinity of the sensor unit. An analyzer is configured to extract the measured signatures of each sensor unit from sensor unit information signals and to detect a presence and concentration of one or more of the gases of interest based on the measured signatures.

Schwartz, David E.↗
DOE OSTI2019

Sensor Error Estimation for Reactor Coolant System with Generalization Error Equations

We consider a simplified version of the sensor error estimation problem in pressure sensors in the primary coolant system of a nuclear power plant under the condition that a majority of sensors are error-free. We present a sensor fusion method to estimate sensor errors in the primary coolant system of a power reactor by using measurements collected by multiple sensors. The underlying relationship between the measured and estimated parameters is inferred using measurements collected under controlled no-error conditions of the plant. We propose a machine learning approach to train fusers that provide an estimate of the sensor measurement by using measurements from other sensors, and the difference between the actual sensor measurement and its estimate provides the sensor estimate. We present generalization error equations for these methods that characterize the performance of their sensor error estimates on future measurements using the distribution-free machine learning formulation.

Rao, Nageswara S.↗
DOE OSTI2016

High Accuracy Signal Validation Framework for Sensor Calibration Assessment in NPPs

Effective and efficient health management of sensing channels and instrumentation supports reliable and accurate process monitoring capacities in any industry. Current practice in the nuclear industry relies on periodic calibration assessment and correction activities. This time based maintenance technique consists of three steps: i) removal of sensor to a test environment, ii) testing and recalibration, and iii) reinstallation of sensor into its working environment. This procedure is highly labor intensive, adds to the outage cost and timeline, and contributes to worker radiation exposure and ALARA requirements. Furthermore, the human element contributes to error factors in all stages of the procedure. The effectiveness of this calibration procedure after sensors are returned to working environmental variables also raises concerns, and the practicability of this periodic approach is uncertain for future reactor designs with longer operating cycles between refueling outages. Studies indicate that periodic calibration assessment find only 10% of sensing instrumentations with calibration issues during a single outage (18- 24 months), meaning at least 90% of sensors are undergoing unnecessary maintenance actions. This provides an opportunity to maintain the current levels of safety and functional integrity with fewer, more targeted maintenance actions and lower economic burden. Performance-based maintenance planning shows much promise over current periodic maintenance approaches. Specifically, online monitoring (OLM) utilizes the continually collected process data to non-intrusively monitor the calibration status of process instrumentation and detect the onset of de-calibration, thereby minimizing the number of recalibration procedures required. Ultimately, this can lead to termination of time based recalibration at NPPs. OLM utilizes the process measurements made for process monitoring and control to evaluate the calibration status of the sensors and instrumentation making the measurements. OLM can detect and differentiate sensor faults and process anomalies, thus providing a valuable tool to suit the industry's and regulatory body's requirements. Though supported by more than a decade of research, OLM for sensor calibration assessment is yet to be implemented in the US fleet due to regulatory requirements and constraints. As shown in Figure 1, OLM utilizes process data to train statistical models that predict normal, error-free process behavior. Measured process values are compared with error-corrected predictions to ascertain the presence of faults. The reliability of OLM is dependent on the quality of its predictions, measured in part by the uncertainty in these predictions. This research develops a framework to accurately quantify the prediction uncertainty based on Bayesian inference techniques to provide the required confidence levels for OLM systems. The expected outcomes include signal validation by high-accuracy, high-confidence uncertainty quantification for variable sensor types and operating ranges. Furthermore, the framework will facilitate fault detection capacities and so-called virtual sensors, a capability to replace faulty sensor measurements with error-corrected values when a sensor fault is detected. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Ultrahigh sensitivity of anomalous Hall effect sensor based on Cr-doped Bi 2 Te 3 topological insulator thin films

Anomalous Hall effect (AHE) was recently discovered in magnetic element-doped topological insulators (TIs), which promises low power consumption and high efficiency spintronics and electronics. This discovery broadens the family of Hall sensors. In this paper, AHE sensors based on Cr-doped Bi 2 Te 3 topological insulator thin films are studied with two thicknesses (15 and 65 nm). It is found, in both cases, that ultrahigh Hall sensitivity can be obtained in Cr-doped Bi 2 Te 3 . Hall sensitivity reaches 1666 Ω/T in the sensor with the 15 nm TI thin film, which is higher than that of the conventional semiconductor HE sensor. The AHE of 65 nm sensors is even stronger, which causes the sensitivity increasing to 2620 Ω/T. Furthermore, after comparing Cr-doped Bi 2 Te 3 with the previously studied Mn-doped Bi 2 Te 3 TI Hall sensor, the sensitivity of the present AHE sensor shows about 60 times higher in 65 nm sensors. Furthermore, the implementation of AHE sensors based on a magnetic-doped TI thin film indicates that the TIs are good candidates for ultrasensitive AHE sensors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Oxide Semiconductor Sensors for Monitoring Advanced Energy Conversion and Manufacturing Processes at High Temperature

To optimize the operation and functionality of high temperature systems such as slagging gasifiers, coal boilers and glass/steel smelters, it is important to monitor temperature, corrosion and erosion of the refractory used in such systems. Both thermocouple and failure sensors (and arrays of these) would be useful to monitor the health of any refractory or coatings in these systems. Many of such type of sensors are installed into the systems through open access ports within the refractory; however, there are some disadvantages of this approach where corrosive/erosive gas and molten materials can penetrate and compromise the system. The current work presents the development and performance of refractory with embedded high temperature sensors such as thermocouples, thermistors, and various spallation/crack monitoring sensors, which may be used within a variety of refractory brick in different high temperature processes and applications. The objective of our work is to develop high-temperature sensors composed of electroceramic materials that are chemically stable at high temperatures (750°-1500°C) and high pressures (up to 1000 psi) that can be used in monitoring temperature, corrosion and erosion process in refractory used in high energy systems. The high-temperature sensors investigated in this work were composed of various oxide composites directly embedded into the refractory oxides. The composites used for this work were synthesized by a mixed-oxide route. Metal oxides were inserted within a matrix material composed of refractory oxides (Al2O3, ZrO2, etc.). The physical and electrical properties were specifically manipulated by altering the level of percolation of the conductive species (metal oxides) within the refractory constituent (refractory oxide). An example of one of these embedded sensors consisted of an electroceramic-based thermocouple fabricated with two separate oxide composite compositions which were patterned to produce a couple within the interior of a refractory matrix. The thermocouple successfully displayed thermoelectric voltage trend (as a function of temperature), and the voltage was 220.0 mV near 1400 °C. In addition, corrosion tests on the refractory embedded sensors were performed. To evaluate corrosion in the refractory was exposed to high-temperature glass compositions over a 90 h period. The penetration of the glass through the refractory could be monitored by both an amperometric and voltametric based sensor. With this experiment, it was demonstrated that the embedded sensor could dynamically monitor the corrosion process, and thus, provide real-time feedback on both temperature and the refractory health.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Recent Advances in 3D Printed Sensors: Materials, Design, and Manufacturing

Sensors are of great importance in different aspects of research and industry. Future sensors will require high-efficient and low-cost manufacturing, as well as high-performance functionality in areas, such as mechanical sensing, biomedical, and optical applications. Recent advances in 3D printing open a new paradigm for sensors fabrication as a precision, customizable, and seamless process. Here, in this article, the state-of-the-art 3D printing methods in sensors manufacturing is reviewed and the performance of the 3D printed sensing materials and devices is summarized. Special attention is paid to emerging multimaterial printing and 4D printing technologies, which will benefit the fabrication of a new generation of structures with multifunctionalities. The content on 3D printed sensors covers piezoelectric sensors, medical, and optical sensing devices. The performance of 3D printed sensors in comparison with the sensors made by traditional manufacturing is also covered. Finally, section 4 provides the viewpoints on the future development of 3D printed sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Integrated proximity, contact and force sensing using elastomer-embedded commodity proximity sensors

Here, we describe a combined proximity, contact and force (PCF) sensor based on a commodity infrared distance sensor embedded in a transparent elastomer with applications in robotic manipulation. Prior to contact, the sensor works as a distance sensor, whereas after contact the elastomer magnifies the near field of the proximity sensors letting the sensor interpret the indentation on elastomer as force. Contact occurs at the transition of proximity and force. We describe in detail the sensor design, its principle of operation and experimentally characterize the design parameters including polymer thickness, its mixing ratio, and emitter current of the infrared sensor. We also show that the sensor response has an inflection point at contact that is independent of an object’s surface properties, making it a robust detector for contact events. We finally demonstrate a series of use cases for the proposed PCF sensor, including (1) improving pre-grasp alignment, (2) determining contact event with objects, (3) obtaining simple 3D point cloud models of objects using both proximity and contact, and (4) registering self-generated point clouds to those from a RGB-D camera using a Baxter robot and Kinova Jaco arm.

42 ENGINEERING↗
DOE OSTI2022

Sensor cost-effectiveness analysis for data-driven fault detection and diagnostics in commercial buildings

Data-driven building fault detection and diagnostics (FDD) is heavily dependent on sensors. However, common sensors from Building Automation Systems are not optimized to maximize accuracy in FDD. Installing additional sensors that provide more detailed building system information is key to maximizing the performance of FDD solutions. Here in this paper, we present a sensor cost analysis workflow to quantify the economic implications of installing new sensors for FDD using the concept of sensor threshold marginal cost (STMC). STMC does not represent actual sensor cost. Rather, it represents a target cost based on the economic benefit that would be realized through improved FDD performance and one or more specified economic criteria. We calculate STMCs for multiple possible fault types and use fault prevalence information to aggregate STMCs into a single dollar value to determine the cost-effectiveness of a potential sensor investment. We conducted a case study using Oak Ridge National Laboratory's Flexible Research Platform (FRP) test facility as a reference. The case study demonstrates the feasibility of the analysis and highlights the key cost considerations in sensor selection for FDD. The results also indicate that identifying and installing the few key sensor(s) is critical to cost-effectively improve FDD performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Ultra-fast and sensitive magneto-optical hydrogen sensors using a magnetic nano-cap array

Magnetism in curved nano-geometries has opened a new path to design novel characteristics and phenomena that could greatly impact the future fundamental and applied studies of materials. Here, in this report, a hexagonally-packed array of magnetic nano-caps (or nano-patches, NP) exhibiting unique magnetic anisotropy and optimal nanostructure for fast hydrogen kinetics is explored as a sensing element for the spark-free magnetic-circular-dichroism (MCD) H 2 sensor. The MCD H 2 sensor outperforms the state-of-the-art optical sensors reported to date and satisfies the most challenging performance targets imposed by US Department of Energy. In particular, a Pd 67 Co 33 NP sensor exhibits response time of t 90 < 0.9 s, recovery time of t 10 < 9.0 s over the 1-100 mbar H 2 partial pressure range, and limit of detection (LOD) of ~1 ppm. The LOD improves to <700 ppb, when the signal-to-noise ratio is enhanced by stacking three NP arrays. Using a 30-nm TAF (Teflon AF 2400) polymer coating, the sorption kinetics of the Pd 67 Co 33 /TAF sensor are significantly accelerated, with t 90 < 0.4 s and t 10 < 2.8 s over the same pressure range. When the Pd 67 Co 33 /TAF sensor is further coated with a 100-nm poly(methyl methacrylate) (PMMA) layer, a rapid sorption time of t 90 < 0.5 s, LOD < 1 ppm and excellent sensor accuracy (<2.5% full scale) are maintained, while the sensor obtains strong selectivity against interference gases and moisture and a negligible aging effect. The MCD nano-cap sensor platform may have a great impact on the future deployment of H 2 fuel, H 2 environmental monitoring sensors, and fast proton-based magneto-ionic devices.

Fast and sensitive hydrogen sensors↗
DOE OSTI2020

Humidity sensitivity of large area silicon sensors: Study and implications

The production of large area sensors is one of the main challenges that the ATLAS collaboration faces for the new Inner-Tracker full-silicon detector. During the prototype fabrication phase for the High Luminosity Large Hadron Collider upgrade, several ATLAS institutes observed indications of humidity sensitivity of large area sensors, even at relative humidities well below the dew point. Specifically, prototype Barrel and End-Cap silicon strip sensors fabricated in 6-inch wafers manifest a prompt decrease of the breakdown voltage when operating under high relative humidity, adversely affecting the performance of the sensors. In addition to the investigation of these prototype sensors, a specific fabrication batch with special passivation is also studied, allowing for a deeper understanding of the responsible mechanisms. Here we present an extensive study of this behaviour on large area sensors. The locations of the hotspots at the breakdown voltage at high humidity are revealed using different infrared thermography techniques. Several palliative treatments are attempted, proving the influence of sensor cleaning methods, as well as baking, on the device performance, but no improvement on the humidity sensitivity was achieved. Furthermore, a study of the incidence of the sensitivity in different batches is also presented, introducing a hypothesis of the origins of the humidity sensitivity associated to the sensor edge design, together with passivation thickness and conformity. Several actions to be taken during sensor production and assembly are extracted from this study, in order to minimize the impact of humidity sensitivity on the performance of large area silicon sensors for High Energy Physics experiments.

47 OTHER INSTRUMENTATION↗