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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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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Surface-Mediated Interconnections of Nanoparticles in Cellulosic Fibrous Materials toward 3D Sensors

Fibrous materials serve as an intriguing class of 3D materials to meet the growing demands for flexible, foldable, biocompatible, biodegradable, dis- posable, inexpensive, and wearable sensors and the rising desires for higher sensitivity, greater miniaturization, lower cost, and better wearability. The use of such materials for the creation of a fibrous sensor substrate that interfaces with a sensing film in 3D with the transducing electronics is however difficult by conventional photolithographic methods. Here, a highly effective pathway featuring surface-mediated interconnection (SMI) of metal nanoclusters (NCs) and nanoparticles (NPs) in fibrous materials at ambient conditions is demon- strated for fabricating fibrous sensor substrates or platforms. Bimodally distrib- uted gold–copper alloy NCs and NPs are used as a model system to demonstrate the semiconductive-to-metallic conductivity transition, quantized capacitive charging, and anisotropic conductivity characteristics. Upon coupling SMI of NCs/NPs as electrically conductive microelectrodes and surface-mediated assembly (SMA) of the NCs/NPs as chemically sensitive interfaces, the resulting fibrous chemiresistors function as sensitive and selective sensors for gaseous and vaporous analytes. Finally, this new SMI–SMA strategy has significant implications for manufacturing high-performance fibrous platforms to meet the growing demands of the advanced multifunctional sensors and biosensors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Novel 3D Force Sensors for a Cost-Effective 3D Force Plate for Biomechanical Analysis

Three-dimensional force plates are important tools for biomechanics discovery and sports performance practice. However, currently, available 3D force plates lack portability and are often cost-prohibitive. To address this, a recently discovered 3D force sensor technology was used in the fabrication of a prototype force plate. Thirteen participants performed bodyweight and weighted lunges and squats on the prototype force plate and a standard 3D force plate positioned in series to compare forces measured by both force plates and validate the technology. For the lunges, there was excellent agreement between the experimental force plate and the standard force plate in the X-, Y-, and Z-axes (r = 0.950–0.999, p < 0.001). For the squats, there was excellent agreement between the force plates in the Z-axis (r = 0.996, p < 0.001). Across axes and movements, root mean square error (RMSE) ranged from 1.17% to 5.36% between force plates. Although the current prototype force plate is limited in sampling rate, the low RMSEs and extremely high agreement in peak forces provide confidence the novel force sensors have utility in constructing cost-effective and versatile use-case 3D force plates.

42 ENGINEERING↗
DOE OSTI2021

Performance of Embedded Sensors in 3D Printed SiC

This report summarizes recent advances in embedding sensors in 3D printed silicon carbide (SiC) ceramic components under the Transformational Challenge Reactor (TCR) program. The additive manufacturing technologies developed under this program will enable fabrication of complex structures with embedded fuels and sensors. The sensors will be capable of characterizing fuel performance using spatially distributed measurements at the most strategic locations that would be otherwise inaccessible using conventional manufacturing techniques. While previous programmatic updates describe initial concepts for embedding sensors, materials selection, and initial characterization of the embedded sensors, the technology requires further demonstration, and quality-significant procedures must be established before the embedding technology is ready for adoption by industry. To this end, this report describes the most effective techniques that have been used to embed functional sensors in 3D printed components using a combination of binder-jet additive manufacturing and chemical vapor infiltration (CVI). A detailed procedure describes each step in the process and is available upon request. Molybdenum (Mo)-sheathed thermocouples have been successfully embedded in complex SiC components, and temperatures were monitored in situ during the embedding process. Post-embedding measurements showed no significant hysteresis, and characterization of the interface revealed qualitatively strong bonding around the entire perimeter of the sensor sheath. Distributed fiber-optic temperature sensors were able to briefly measure temperature profiles during CVI, but they ultimately failed prior to completion of the CVI run. The failure appears to be related to the fiber coating at temperatures close to 1,000°C. Future work will focus on irradiation testing of embedded thermocouples and other sheathed electrical sensors, as well as the identification of fiber-optic sensor coatings that can survive CVI.

42 ENGINEERING↗
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 OSTI2022

Performance Before and After Irradiation of Pixelated 3D Silicon Sensors for the HL-LHC CMS Tracker

The Large Hadron Collider (LHC) particle accelerator at European Center for Nuclear Research (CERN) will be shut down starting in 2026 to achieve the High Luminosity Large Hadron Collider (HL-LHC) upgrade. The upgrade will allow for higher fluences, in order to increase the probability of detecting increasingly rare particles, and to obtain higher precision measurements of known particles. To accommodate the new accelerator conditions, many aspects of the Compact Muon Solenoid (CMS) detector will be upgraded; of particular interest for this thesis are the silicon pixel detectors located in the inner tracker. These will be replaced and upgraded to accommodate the higher fluences of the HL-LHC upgrade, as well as to replace existing sensors which have sustained radiation damage. In order for the new sensors to operate under high luminosity conditions, they must be increasingly radiation hard, and in order to detect rare particles, they must be increasingly more precise. The performance of one Centro Nacional de Microelectronica (CNM) 3D silicon sensor before and after undergoing irradiation at fluences similar to those which will be observed at the HL-LHC was investigated to determine radiation hardness and precision. Data was collected at Fermi National Laboratory (Fermilab), in the Fermi National Laboratory Test Beam Facility (FTBF) silicon tracker telescope, which can be used to determine the number of particles, and tracks made by high energy protons passing through. The sensor was also irradiated at Fermilab in the Irradiation Test Area (ITA). Prior to data collection a tuning procedure is carried out to determine ideal bias voltage operating conditions, mask noisy and dead pixels, adjust to the ideal threshold, and map sensor gain. Data is then collected at the FTBF, where the sensor is installed in the center of the FTBF silicon telescope. Variables, including angle and bias voltage, are varied throughout data collection. Data is then processed using an alignment software to determine the exact telescope geometry, along with the tracks which were observed passing through the sensor and telescope. Sensor performance was found to be comparable before and after irradiation, with irradiated results showing slightly lower efficiencies and cluster sizes. Position resolution is comparable both before and after irradiation, and similar distributions of cluster shape are observed. After irradiation, the sensor shows increasing collected charge with bias, an indication of increased width of the depletion region. Peak charge pre-irradiation is higher than post-irradiation peak charge, indicating the irradiated results are not taken under fully-depleted conditions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Embedding Sensors in 3D Printed Metal Structures

The Transformational Challenge Reactor (TCR) program is leveraging recent advances in modeling and simulation, materials, and additive manufacturing (AM) technologies to design a modern nuclear reactor. Some of the main TCR technologies include in situ monitoring and the integration of sensors during the manufacturing of quality-significant nuclear reactor components. This report describes the general procedure and process optimization for embedding sensors within generic stainless steel 316 (SS316) components using laser powder bed fusion (LPBF). A more detailed, quality-significant test plan and supporting procedures are available upon request (ORNL/TM-2021/2127). LPBF involves the use of a scanning laser to selectively melt regions of a powder bed, additively building a part layer by layer. This report describes the LPBF processing technique and discusses the effects of LPBF processing parameters on the success of the sensor embedding process. Experiments used machined cavities in the form of channels in an SS316 base for the sensors to lay in while material is additively built over the top, thereby embedding them in an SS316 matrix. A preliminary investigation involved using empty SS316 sheaths as surrogates to explore the effects of various LPBF processing parameters and the dimensional requirements of the machined channels. Microstructural investigations showed that a smaller channel width/depth combination closer to the sensor’s diameter was best for the embedding process. After the desired parameters were selected, Type-K thermocouples were embedded and evaluated post-embedding using nondestructive thermal testing, as well as destructive sectioning and microscopy. Post-build characterization showed that the thermocouples were well-bonded to the SS316 matrix and were fully functional after embedding. During thermal testing to temperatures up to 500 °C, the embedded thermocouples read consistently with one another and deviated only slightly from the readings of a nonembedded thermocouple located within the furnace. This slight discrepancy was most likely due to differences in the thermal time constants for a nonembedded thermocouple vs. a thermocouple embedded in a solid SS316 block. The results presented in this report will serve as the foundation for future work that will focus on embedding sensors in relevant TCR reactor components and eventually testing those components under neutron irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

OPEN-Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture (Donald Danforth Plant Science Center Final Scientific Technical Report)

The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

3D Printed Chromophoric Sensors

Eight chromophoric indicators are incorporated into Sylgard 184 to develop sensors that are fabricated either by traditional methods such as casting or by more advanced manufacturing techniques such as 3D printing. The sensors exhibit specific color changes when exposed to acidic species, basic species, or elevated temperatures. Additionally, material properties are investigated to assess the chemical structure, Shore A Hardness, and thermal stability. Comparisons between the casted and 3D printed sensors show that the sensing devices fabricated with the advanced manufacturing technique are more efficient because the color changes are more easily detected.

3d printing↗
DOE OSTI2026

Evaluation of 3D pixel silicon sensors for the CMS Phase-2 Inner Tracker

The high-luminosity upgrade of the CERN LHC requires the replacement of the CMS tracking detector to cope with the increased radiation fluence while maintaining its excellent performance. An extensive R&D program, aiming at using 3D pixel silicon sensors in the innermost barrel layer of the detector, has been carried out by CMS in collaboration with the FBK (Trento, Italy) and CNM (Barcelona, Spain) foundries. The sensors will feature a pixel cell size of 25 × 100 µm 2 , with a centrally located electrode connected to the readout chip. The sensors are read out by the RD53A and CROCv1 chips, developed in 65 nm CMOS technology by the RD53 Collaboration, a joint effort between the ATLAS and CMS groups. This paper reports the results achieved in beam test experiments before and after irradiation, up to a fluence of approximately 2 . 6 × 1 0 16 n eq /cm 2 . Measurements of assemblies irradiated to a fluence of 1 × 10 16 n˙eq/cm 2 show a hit detection efficiency higher than 96% at normal incidence, with fewer than 2% of channels masked, across a bias voltage range greater than 50 V . Even after irradiation to a higher fluence of 1.6 × 10 16 n˙eq/cm 2 , similar performance is maintained over a bias voltage range of 30 V , remaining well within CMS requirements.

3D pixel↗
DOE OSTI2024

Embedding sensors in 3D-printed silicon carbide

An improved method for embedding one or more sensors in SiC is provided. The method includes depositing a binder onto successive layers of a SiC powder feedstock to produce a dimensionally stable green body have a true-sized cavity. A sensor component is then press-fit into the true-sized cavity. Alternatively, the green body is printed around the sensor component. The assembly (the green body and the sensor component) is heated within a chemical vapor infiltration (CVI) chamber for debinding, and a precursor gas is introduced for densifying the SiC matrix material. During infiltration, the sensor component becomes bonded to the densified SiC matrix, the sensor component being selected to be thermodynamically compatible with CVI byproducts at elevated temperatures, including temperatures in excess of 1000° C.

Petrie, Christian M.↗
DOE OSTI2024

Sensor response and radiation damage effects for 3D pixels in the ATLAS IBL Detector

Pixel sensors in 3D technology equip the outer ends of the staves of the Insertable B Layer (IBL), the innermost layer of the ATLAS Pixel Detector, which was installed before the start of LHC Run 2 in 2015. 3D pixel sensors are expected to exhibit more tolerance to radiation damage and are the technology of choice for the innermost layer in the ATLAS tracker upgrade for the HL-LHC programme. While the LHC has delivered an integrated luminosity of ≃ 235 fb -1 since the start of Run 2, the 3D sensors have received a non-ionising energy deposition corresponding to a fluence of ≃ 8.5 × 10 14 1 MeV neutron-equivalent cm -2 averaged over the sensor area. This paper presents results of measurements of the 3D pixel sensors' response during Run 2 and the first two years of Run 3, with predictions of its evolution until the end of Run 3 in 2025. Data are compared with radiation damage simulations, based on detailed maps of the electric field in the Si substrate, at various fluence levels and bias voltage values. These results illustrate the potential of 3D technology for pixel applications in high-radiation

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Development of green-colour-emitting pyrotechnics as a core for 3D temperature imaging sensors inside coal boilers

Efficiency in the control operation of the boilers for coal and coal with biomass can be further improved if the flue gas temperature distribution can be better characterized. This is very difficult in these harsh environmental systems, where spatially resolved measurements are nearly impossible with solid-state sensors. Here, in this work, we evaluate the development of pyrotechnic compounds that would serve as the basis for a novel optical mapping of the temperature inside coal boilers. For this purpose, various green-colour-emitting pyrotechnics using BaCl 2 · 2H 2 O and Ba(NO 3 ) 2 as the green light source were prepared, as this colour offers a distinct signal from the combustion-based background in the boiler. These pyrotechnics were characterized using thermogravimetric analysis (TGA) and X-ray diffraction (XRD) and tested using a flat-flame burner. Furthermore, the composition was varied to evaluate the effect of different metal fuels such as Sn, Co, and Mg, as well as various binders such as ethylcellulose, shellac, parlon, and PVC on green light emission. The emission intensity and the apparent ignition temperature were strongly dependent on the metal type, with Mg showing higher intensities. On the other hand, the effect of the binder showed that the ignition behaviour, emission intensity, and spectral purity were influenced by the nature and exothermicity of the binder. The addition of other potential green light-producing materials, such as boric acid, increased the intensity of emission by 17% for a BaCl 2 · 2H 2 O-based composition. This study identified prospective compositions with intense and bright green-colour emissions that have high spectral purities.

42 ENGINEERING↗
DOE OSTI2023

A Flexible Field Mapping System for Accelerator Magnets

Magnetic field mapping is a fundamental magnetic measurement method that typically uses Hall and NMR sensors. In magnet measurement facilities, such systems are likely used in various configurations suitable for a specific task at hand. To address this diversity, the authors developed a flexible field mapping system capable of being configured and tailored to each particular measurement case. Further, the system needs to address the variability introduced by differences in sensors and their readout systems, probe positioning systems, power supply systems, and required mapping geometry (mapping space and grid, measurement steps and sequences). Although the discussed field mapping systems range from a self-propelled multi-sensor mapper of a large detector magnet to a single 3D Hall sensor system to scan a small permanent magnet, they were all built with the same core mapping system. The variability present in field mapping systems, the measurement system architecture addressing this variability, as well as examples of several field mapping systems built in this architecture are presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗