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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Portable and Cost-Effective Device for Reliable Detection of Counterfeit and Non-compliant Refrigerants in Diverse Applications

Counterfeit refrigerants pose significant challenges to safety, system reliability, and operational effectiveness due to their harmful contaminants or incompatible chemical compositions. Utilizing these noncompliant products can lead to reduced efficiency, equipment failures, and expensive repairs. Additionally, heightened demand for alternative refrigerants during the industry's transition has created supply gaps, enabling counterfeit products to proliferate. Accurate detection and analysis tools are therefore essential to verify refrigerant authenticity and ensure system integrity in diverse applications. This paper presents the development of a portable device designed for reliable identification and detailed analysis of refrigerant composition. By integrating precision gas sampling, controlled pressure regulation, and automated sensor technology, the device not only detects deviations from standard refrigerant properties but also provides a comprehensive composition breakdown. Pre-calibrated sensors measure the refrigerant gas to identify specific concentrations and contaminants, with an intuitive LED-based indicator system ensuring quick interpretation of results. The user-friendly interface enables operators to select refrigerant types for targeted testing, further enhancing accuracy and usability for field technicians. Comprehensive testing was conducted on mildly flammable A2L refrigerants, showcasing the device’s robustness and adaptability in analyzing composition and detecting discrepancies. The device demonstrated consistent accuracy across a range of refrigerant samples, affirming its reliability in diverse operational environments. Its design minimizes contamination risks during sampling and provides detailed composition results within 90 seconds, ensuring efficient and precise analysis. With a projected price point under $150, the proposed solution delivers affordability alongside its lightweight portability and straightforward operation. Unlike complex and costly alternatives, such as gas chromatography systems, this device provides an accessible option for technicians, customs personnel, and industry operators in need of quick and effective refrigerant verification. Compatible with both current formulations and emerging refrigerant technologies, the device addresses critical counterfeit detection needs across a range of applications. By delivering accurate composition analysis and counterfeit identification, this innovation enhances system performance, safety, and operational reliability in crucial industries.

Cheekatamarla, Praveen [ORNL] (ORCID:0000000248827↗
DOE OSTI2018

Thermoelectric Generator Powered Wireless Sensor Node Prototype for Nuclear Applications

This report presents the development a TEG-powered WSN prototype that could be used in nuclear applications. Different design considerations that are important in assembling different components of a WSN were carefully taken into consideration. In designed WSN is compatible to operate with low-power generating TEG and high-power generating TEG based on application requirements. Also, to maintain appropriate power level across different sensor node components, direct current-to-direct current converter with maximum peak power tracking algorithm is implemented. Storage device with real-time clock is embedded to enable local data storage and real-time time stamping. The wireless communication module selected and implemented is Zig Bee protocol. To accommodate different operating conditions and any loss of power from TEG due to unforeseen reasons, backup battery system is also implemented. Entire assembly is performed on a 2-layer printed circuit board and tested for operation. The outcome was successful and it also provided data to validate the mathematical model developed to estimate average power consumption of a WSN under different operating conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Functional Data Analysis in Wearable Body Sensor Networks

Improving response time of indirect room-size calorimeters is still an outstanding problem in metabolic research. Accurate estimates of instantaneous rates of gaseous exchange require numerical differentiation of measured gaseousgas concentrations. We propose a new method to estimate the instantaneous gaseousgas exchange rates in indirect calorimetry. In contrast to the previously developed techniques, the method addresses the problem of differentiation of gaseous concentrations as an ill-posed problem. By applying the method of regularization, the problem of differentiation is converted into a well-posed problem resulting in smooth and consistent gaseous exchange rates. The validity of the method is tested on a large dataset of calorimeter experiments which included 313 human experiments along with 231 alcohol combustion experiments. It is demonstrated that the method is able to reliably differentiate between the “unphysiological” process of alcohol combustion and physiological variations produced by human metabolism. The method also allowed unraveling the previously unreported relative kinetics of O2 consumption and Respiratory Quotient (RQ) in humans. It was found that the kinetics of oxidative fuel selection lags behind the energy expenditure in humans exhibiting some sort of oxidative inertia. The time lag varies from 2-3 min up to 30 min, depending on particular individual. No such lag was found in alcohol combustion experiments. In addition to the relative kinetics of substrate oxidation, two statistical indexes reflecting variability of minute-by-minute RQ were estimated. The indexes were the RQ’s standard deviation and RQ’s first-order derivative. Both indexes showed statistically significant difference between human experiments and alcohol combustion experiments. We conclude that the proposed method can consistently extract physiologically-relevant information from noisy calorimetry data and the aforesaid information can provide additional insights into the mechanism of metabolic fuel selection in humans.

60 - APPLIED LIFE SCIENCES↗
DOE OSTI2020

Data-Driven Modeling and Optimization of Building Energy Consumption: a Case Study

Installing sensors and Building Automation Systems (BAS) allows controlling the facility operations while generating data that can be analyzed for model development. This work focuses on data-driven modeling of the building to optimize energy consumption. The City of Orlando aims to reduce its energy consumption so, they provided us access to their BAS for data and studying the operation of its facilities. We selected a mid-size pilot building to conduct data analysis and modeling. We develop an Application Programming Interface (API) to login to the servers and scrape data. The scraped data contains features ranging from environmental conditions to equipment activity. This dataset is a time series so, it's handled in accordance and analyzed to investigate patterns and relations between data points that help choose parameters for predictive models for building and equipment. Finally, the models are optimized to reduce the energy consumption of the facility.

Grover, Divas↗
DOE OSTI2014

Qualification of Daiichi Units 1, 2, and 3 Data for Severe Accident Evaluations - Process and Illustrative Examples from Prior TMI-2 Evaluations

The accidents at the Three Mile Island Unit 2 (TMI-2) Pressurized Water Reactor (PWR) and the Daiichi Units 1, 2, and 3 Boiling Water Reactors (BWRs) provide unique opportunities to evaluate instrumentation exposed to severe accident conditions. Conditions associated with the release of coolant and the hydrogen burn that occurred during the TMI-2 accident exposed instrumentation to harsh conditions, including direct radiation, radioactive contamination, and high humidity with elevated temperatures and pressures. As part of a program initiated in 2012 by the Department of Energy Office of Nuclear Energy (DOE-NE), a review was completed to gain insights from prior TMI-2 sensor survivability and data qualification efforts. This initial review focused on the set of sensors deemed most important by post-TMI-2 instrumentation evaluation programs. Instrumentation evaluation programs focused on data required by TMI-2 operators to assess the condition of the reactor and containment and the effect of mitigating actions taken by these operators. In addition, prior efforts focused on sensors providing data required for subsequent forensic evaluations and accident simulations. To encourage the potential for similar activities to be completed for qualifying data from Daiichi Units 1, 2, and 3, this report provides additional details related to the formal process used to develop a qualified TMI-2 data base and presents data qualification details for three parameters: primary system pressure; containment building temperature; and containment pressure. As described within this report, sensor evaluations and data qualification required implementation of various processes, including comparisons with data from other sensors, analytical calculations, laboratory testing, and comparisons with sensors subjected to similar conditions in large-scale integral tests and with sensors that were similar in design to instruments easily removed from the TMI-2 plant for evaluations. As documented in this report, results from qualifying data for these parameters led to key insights related to TMI-2 accident progression. Hence, these selected examples illustrate the types of activities completed in the TMI-2 data qualification process and the importance of such a qualification effort. These details are documented in this report to facilitate implementation of similar process using data and examinations at the Daiichi Units 1, 2, and 3 reactors so that BWR-specific benefits can be obtained.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Characterization of local parameters of inclined upward air–water bubbly two-phase flows in a round pipe

The present work seeks to develop a detailed experimental database and characterize the local effects of inclination on horizontal and upward bubbly air–water two-phase flows. Experimental conditions are selected to investigate bubbly flows at a variety of orientations while reducing the influence of flow regime transition. Detailed time-averaged data is collected using state-of-the-art four-sensor conductivity probes for measurements across the flow area for five flow conditions at five inclination orientations in a 25.4 mm inner diameter pipe. Using the newly established database, effects of inclination on bubbly flows are analyzed, as are changes in liquid and gas flow rate at different orientations. The observations include (1) bubble migration and agglomeration at the top pipe wall as orientation changes from vertical to horizontal; (2) reducing the angle from vertical reduces the local gas velocity, and correspondingly reduces the global slip from greater than unity at 90° to less than unity for 60° and lower; (3) changes in the bubble size distribution are primarily at the interface between the bubble cluster and the liquid region of the pipe, not coalescence within the bubble cluster. In conclusion, physical mechanisms for these observations are proposed, and the present trends at different orientations support previous experiments in horizontal two-phase flows.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Machine-Learning Identification of the Sensing Descriptors Relevant in Molecular Interactions with Metal Nanoparticle-Decorated Nanotube Field-Effect Transistors

We report that carbon nanotube-based field-effect transistors (NTFETs) are ideal sensor devices as they provide rich information regarding carbon nanotube interactions with target analytes and have potential for miniaturization in diverse applications in medical, safety, environmental, and energy sectors. Herein, we investigate chemical detection with cross-sensitive NTFETs sensor arrays comprised of metal nanoparticle-decorated single-walled carbon nanotubes (SWCNTs). By combining analysis of NTFET device characteristics with supervised machine-learning algorithms, we have successfully discriminated among five selected purine compounds, adenine, guanine, xanthine, uric acid, and caffeine. Interactions of purine compounds with metal nanoparticle-decorated SWCNTs were corroborated by density functional theory calculations. Furthermore, by testing a variety of prepared as well as commercial solutions with and without caffeine, our approach accurately discerns the presence of caffeine in 95% of the samples with 48 features using a linear discriminant analysis and in 93.4% of the samples with only 11 features when using a support vector machine analysis. Lastly, we also performed recursive feature elimination and identified three NTFET parameters, transconductance, threshold voltage, and minimum conductance, as the most crucial features to analyte prediction accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Synthesis, characterization, and gas-sensing properties of monodispersed SnO{sub 2} nanocubes

Monodispersed single-crystalline SnO{sub 2} nanocubes with exposed a large percentage of high-energy surfaces have been synthesized by a simple solvothermal process at low temperature without any templates and catalysts. The as-prepared samples have been characterized by X-ray diffraction and transmission electron microscopy. Many outstanding characters of the final products have been shown, such as uniform particle size, high purity, and monodispersity. In property, superior gas-sensing properties such as high response, rapid response-recovery time, and good selectivity have also been shown to ethanol at an optimal working temperature of as low as 280 °C. It indicates that the as-prepared SnO{sub 2} nanocubes are promising for gas sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Orientation Sensitive SEIRA Sensors Based on Single-Walled Carbon Nanotube Near Fields

Molecular vibrations that bear information about intrinsic properties of chemical compounds are challenging to detect at submonolayer densities. Surface-enhanced infrared absorption (SEIRA) spectroscopy has been proven to be a viable approach to enhance and detect weak vibration signals. Here, in this study, we report a SEIRA sensor based on mid-infrared surface plasmon resonances supported by single-walled carbon nanotubes (SWCNTs). Due to the 1D nature of SWCNTs, their plasmon modes are highly polarized with the electromagnetic fields spatially confined to nanometer scales. Leveraging these characteristics of SWCNTs, we observe a polarization selective coupling between their surface plasmons and vibrational modes of chemical bonds introduced onto their surfaces. A maximum modulation of similar to 15% to the plasmon resonance peak is obtained for a submonolayer chemical group coverage. These findings suggest that SWCNTs may potentially serve as a highly sensitive SEIRA platform for revealing intricate information about molecular compositions and bond orientations.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Uranium Enrichment Standards of the Y-12 Nuclear Detection and Sensor Testing Center

The Y-12 National Security Complex has recently fabricated and characterized a new series of metallic uranium standards for use in the Nuclear Detection and Sensor Testing Center (NDSTC). Ten uranium metal disks with enrichments varying from 0.2 to 93.2% {sup 235}U were designed to provide researchers access to a wide variety of measurement scenarios in a single testing venue. Special care was taken in the selection of the enrichments in order to closely bracket the definitions of reactor fuel at 4% {sup 235}U and that of highly enriched uranium (HEU) at 20% {sup 235}U. Each standard is well characterized using analytical chemistry as well as a series of gamma-ray spectrometry measurements. Gamma-ray spectra of these standards are being archived in a reference library for use by customers of the NDSTC. A software database tool has been created that allows for easier access and comparison of various spectra. Information provided through the database includes: raw count data (including background spectra), regions of interest (ROIs), and full width half maximum calculations. Input is being sought from the user community on future needs including enhancements to the spectral database and additional Uranium standards, shielding configurations and detector types. A related presentation are planned for the INMM 53rd Annual Meeting (Hull, et al.), which describe new uranium chemical compound standards and testing opportunities at Y-12 Nuclear Detection and Sensor Testing Center (NDSTC).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Development of a coolant channel helium and nitrogen gas ratio sensor for a high temperature gas reactor

To measure the changing gas composition of the coolant during a postulated High Temperature Gas Reactor (HTGR) accident, an instrument is needed. This instrument must be compact enough to measure the ratio of the coolant versus the break gas in an individual coolant channel. This instrument must minimally impact the fluid flow and provide for non-direct signal routing to allow minimal disturbance to adjacent channels. The instrument must have a flexible geometry to allow for the measurement of larger volumes such as in the upper or lower plenum of a HTGR. The instrument must be capable of accurately functioning through the full operating temperature and pressure of a HTGR. This instrument is not commercially available, but a literature survey has shown that building off of the present work on Capacitance Sensors and Cross-Capacitors will provide a basis for the development of the desired instrument. One difficulty in developing and instrument to operate at HTGR temperatures is acquiring an electrical conductor that will not melt at 1600 deg. C. This requirement limits the material selection to high temperature ceramics, graphite, and exotic metals. An additional concern for the instrument is properly accounting for the thermal expansion of both the sensing components and the gas being measured. This work covers the basic instrument overview with a thorough discussion of the associated uncertainty in making these measurements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Chemoresponsive Nanofluidic Pump That Turns Off in the Presence of Lead Ion

There are many applications that require the integration of a pump and a chemical sensor so that the solution being pumped can be analyzed in real time for a specific chemical species and the flow adjusted according to the measured concentration of that species. In this paper, we describe an alternative strategy: a chemoresponsive pump where a single device acts as both the sensor and pump simultaneously. We demonstrate this concept with a nanofluidic Pb 2+ -responsive pump that uses electroosmotic flow as the pumping technology, and a Pb 2+ -binding ionophore that allows the device to selectively respond to Pb 2+ . The pump yields high flow rates at low Pb 2+ concentrations (<1 μM), but flow rate decreases with concentrations above this threshold and ultimately goes to zero at concentrations above 100 μM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

n-ZnO/p-4H-SiC diode: Structural, electrical, and photoresponse characteristics

Epitaxial n-type ZnO film has been grown, on a commercial 5 μm thick p-type 4H-SiC(00.1) Al doped epilayer, by atomic layer deposition. A full width at half maximum of the ZnO 00.2 diffraction peak rocking curve of 0.34°{sup }± 0.02° has been measured. Diodes formed on the n-ZnO/p-4H-SiC heterostructure show rectifying behavior with a forward to reverse current ratio at the level of 10{sup 9} at ±4 V, a leakage current density of ∼6 × 10{sup −8} A/cm{sup 2}, and a low ideality factor equal to 1.17 ± 0.04. In addition, the diodes exhibit selective photoresponse with a maximum at 367 nm, and with a current increase of ∼10{sup 3} under illuminations with respect to the dark value, which makes such devices prospective candidates for ultraviolet light sensors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Background Adaptive Radiation Detection (BARD) v1.0.0

The Background Adaptive Radiation Software can be deployed with static sensors in urban environments. It provides a real-time robust radiation detection based on a unique adaptive learning approach. Local radiation background models are automatically learnt for various environmental conditions, and monitored/re-trained, and selected over time for optimal radiation anomaly detection, informed by source templates directly derived from the data.

Abgrall, Nicolas↗
DOE OSTI2019

Permanent Electrical Loads in New Homes

Numerous electrical products and components are installed by the builder during construction and prior to occupancy. Some of these components are required by safety codes, such as smoke detectors, others are needed to support the communications infrastructure, and still others provide features that future occupants will find useful, such as remotely controlled garage door openers. We compiled a list of over 50 builder-installed devices that are likely to have continuous power consumption, and measured the power consumptions for a smaller group. A procedure to measure these loads in a home was developed based on readings from the smart meter. A typical American home can easily have 80 W of continuous power – over 650 kWh/year – devoted to these components. New homes are likely to have more of these devices and higher loads. Techniques to reduce this energy use include: selection of lowest-power solutions when a range of power consumptions are available, more efficient circuitry and power management, a separate DC circuit to serve DC-powered appliances, and use of energyscavenging sensors and controls in place of grid-powered components. A protocol to define and measure builder-installed loads, along with a recommended ceiling, might also stimulate savings.

Meier, Alan↗
DOE OSTI2018

Development of a Kalman filter estimator for simulation and control of particulate matter distribution of a diesel catalyzed particulate filter

The knowledge of the temperature and particulate matter mass distribution is essential for monitoring the performance and durability of a catalyzed particulate filter. A catalyzed particulate filter model was developed, and it showed capability to accurately predict temperature and particulate matter mass distribution and pressure drop across the catalyzed particulate filter. However, the high-fidelity model is computationally demanding. Therefore, a reduced order multi-zone particulate filter model was developed to reduce computational complexity with an acceptable level of accuracy. In order to develop a reduced order model, a parametric study was carried out to determine the number of zones necessary for aftertreatment control applications. The catalyzed particulate filter model was further reduced by carrying out a sensitivity study of the selected model assumptions. The reduced order multi-zone particulate filter model with 5 × 5 zones was selected to develop a catalyzed particulate filter state estimator considering its computational time and accuracy. Next, a Kalman filter–based catalyzed particulate filter estimator was developed to estimate unknown states of the catalyzed particulate filter such as temperature and particulate matter mass distribution and pressure drop (Δ P) using the sensor inputs to the engine electronic control unit and the reduced order multi-zone particulate filter model. A diesel oxidation catalyst estimator was also integrated with the catalyzed particulate filter estimator in order to provide estimates of diesel oxidation catalyst outlet concentrations of NO 2 and hydrocarbons and inlet temperature for the catalyzed particulate filter estimator. The combined diesel oxidation catalyst–catalyzed particulate filter estimator was validated for an active regeneration experiment. The validation results for catalyzed particulate filter temperature distribution showed that the root mean square temperature error by using the diesel oxidation catalyst–catalyzed particulate filter estimator is within 3.2 °C compared to the experimental data. Similarly, the Δ P estimator closely simulated the measured total Δ P and the estimated cake pressure drop error is within 0.2 kPa compared to the high-fidelity catalyzed particulate filter model.

Engineering↗
DOE OSTI2022

Liquid Crystal‐Based Detection of Antigens with ELISA Sensitivity

Abstract A highly sensitive label‐free liquid crystal (LC)‐based technique is presented for detecting Immunoglobulin G (IgG) antigens used to uncover viral infections. The effectiveness, sensitivity, and selectivity of this detection method is demonstrated with goat IgG antigen at concentrations as low as 100 pg ml −1 , which is comparable to the sensitivity of the current enzyme‐linked immunosorbent assay (ELISA). The sensor is fabricated by decorating a transmission electron microscopy grid immobilized glass surfaces with antibodies; the target antigen is detected by a liquid crystal suspended onto the grid. This is different from previous methods where the antigen is detected either at the LC‐aqueous interface or in an LC sandwich cell with an antibody/antigen‐decorated substrate. This new approach has advantages such as easy sample preparation, higher sensitivity, and better storage capabilities. Binding the target antigen to the antibody results in a reorientation of the LC director that is detected optically. In addition to demonstrating the sensitivity, the physical principle of the detection is also discussed. This technique may apply to detect virtually any antigen of interest.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Life cycle impact assessment of home energy management systems (HEMS) using dynamic emissions factors for electricity in Finland

Decarbonising the European economy is a long-term goal in which the residential sector will play a significant role. Smart buildings for energy management are one means of decarbonisation, by reducing energy consumption and related emissions. This study investigated the environmental impacts of smart house automation using life cycle impact assessment. The ReCiPe method was selected for use, in combination with dynamic emissions factors for electricity in Finland. The results indicated that a high level of technology deployment may be counter-effective, due to high electricity consumption by the sensor network, automation system and computing devices. The results also indicated that number of inhabitants per household directly affected the environmental impacts of home automation. A single-person household saw its environmental impacts increase by 15%, while those of a five-person household increased by 3% in the worst-case scenario. The manufacturing phase contributed the major share of environmental impacts, exceeding the use phase in multiple categories. These findings indicate that finding the sweet spot in which technology can promote decarbonisation will be crucial to achieving the goal of a low‑carbon economy. - Highlights: •HEMS did not reduce the overall environmental impact of households. •Environmental impacts of HEMS are greater for single inhabitant households. •Energy efficiency of sensing devices must drastically increase to promote decarbonisation. •The highest life cycle environmental impacts of electronics are during the manufacturing phase. •Raising awareness is a critical part in decreasing the environmental impact of households.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗