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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

More science with less: evaluation of a 3D-printed weather station

Abstract. A weather station built using 3D-printed parts and low-cost sensors, based on plans and guidance provided by the University Corporation for Atmospheric Research 3D-Printed Automatic Weather Station Initiative, was deployed alongside an Oklahoma Mesonet station to compare its performance against standard commercial sensors and determine the longevity and durability of the system. Temperature, relative humidity, atmospheric pressure, wind speed and direction, solar radiation, and precipitation measurements were collected over an 8-month field deployment in Norman, Oklahoma. Measurements were comparable to the commercial sensors except for wind direction, which proved to be problematic. Longevity and durability of the system varied, as some sensors and 3D-printed components failed during the deployment. Overall, results show that these low-cost sensors are comparable to the more expensive commercial counterparts and could serve as viable alternatives for researchers and educators with limited resources for short-term deployments. Long-term deployments are feasible with proper maintenance and regular replacement of sensors and 3D-printed components.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Real-Time Bayesian Inference at Extreme Scale: A Digital Twin for Tsunami Early Warning Applied to the Cascadia Subduction Zone

We present a Bayesian inversion-based digital twin that employs acoustic pressure data from seafloor sensors, along with 3D coupled acoustic–gravity wave equations, to infer earthquake-induced spatiotemporal seafloor motion in real time and forecast tsunami propagation toward coastlines for early warning with quantified uncertainties. Our target is the Cascadia subduction zone, with one billion parameters. Computing the posterior mean alone would require 50 years on a 512 GPU machine. Instead, exploiting the shift invariance of the parameter-to-observable map and devising novel parallel algorithms, we induce a fast offline–online decomposition. The offline component requires just one adjoint wave propagation per sensor; using MFEM, we scale this part of the computation to the full El Capitan system (43,520 GPUs) with 92% weak parallel efficiency. Moreover, given real-time data, the online component exactly solves the Bayesian inverse and forecasting problems in 0.2 seconds on a modest GPU system, a ten-billion-fold speedup.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Identification of multiple eigenmode growth rates towards real time detection in DIII-D and KSTAR tokamak plasmas

Abstract The successful application of three-dimensional (3D) magnetohydrodynamic (MHD) spectroscopy enables us to identify the multi-mode eigenvalues in DIII-D and KSTAR tokamak experiments with stable plasmas. The temporal evolution of the multi-modes’ stabilities have been detected. The new method is numerically efficient allowing the real time detection of MHD modes’ stabilities during the discharge. The method performs active detection of the plasma stability by utilizing the upper and lower rows of internal non-axisymmetric coils to apply a wide variety of 3D fields. Multi-mode eigenvalues are extracted using subspace system identification of the plasma response measured by 3D-field magnetic sensors distributed at different poloidal locations. The equivalence of this new method with the one introduced by Wang (2019 Nucl. Fusion 59 024001) has been numerically corroborated. The more robust and efficient calculation developed here will enable real time monitoring of the plasma stability based on the extracted eigenvalues of stable modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Bridging Additive Manufacturing and Electronics Printing in the Age of AI

Printing techniques have been instrumental in developing flexible and stretchable electronics, including organic light-emitting diode displays, organic thin film transistor arrays, electronic skins, organic electrochemical transistors for biosensors and neuromorphic computing, as well as flexible solar cells with low-cost processes such as inkjet printing, ultrasonic nozzle, roll-to-roll coating. The rise of additive manufacturing provides even more opportunities to print electronics in automated and customizable ways. In this work, we will review the current technologies of printing electronics (including printed batteries, supercapacitors, fuel cells, and sensors), especially with 3D printing. In this age of ongoing AI revolution, the application of AI algorithms is discussed in terms of combining them with 3D printing and electronics printing for a future with automated optimization, sustainable design, and customizable and scalable manufacturing.

Chemistry↗
DOE OSTI2022

Novel Sensors for Particle Tracking: a Contribution to the Snowmass Community Planning Exercise of 2021

Five contemporary technologies are discussed in the context of their potential roles in particle tracking for future high energy physics applications. These include sensors of the 3D configuration, in both diamond and silicon, submicron-dimension pixels, thin film detectors, and scintillating quantum dots in gallium arsenide. Drivers of the technologies include radiation hardness, excellent position, vertex, and timing resolution, simplified integration, and optimized power, cost, and material.

Detectors↗
DOE OSTI2022

Novel Sensors for Particle Tracking: a Contribution to the Snowmass Community Planning Exercise of 2021

Five contemporary technologies are discussed in the context of their potential roles in particle tracking for future high energy physics applications. These include sensors of the 3D configuration, in both diamond and silicon, submicron-dimension pixels, thin film detectors, and scintillating quantum dots in gallium arsenide. Drivers of the technologies include radiation hardness, excellent position, vertex, and timing resolution, simplified integration, and optimized power, cost, and material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

3D printed graphene-based self-powered strain sensors for smart tires in autonomous vehicles

The transition of autonomous vehicles into fleets requires an advanced control system design that relies on continuous feedback from the tires. Smart tires enable continuous monitoring of dynamic parameters by combining strain sensing with traditional tire functions. Here, we provide breakthrough in this direction by demonstrating tire-integrated system that combines direct mask-less 3D printed strain gauges, flexible piezoelectric energy harvester for powering the sensors and secure wireless data transfer electronics, and machine learning for predictive data analysis. Ink of graphene based material was designed to directly print strain sensor for measuring tire-road interactions under varying driving speeds, normal load, and tire pressure. A secure wireless data transfer hardware powered by a piezoelectric patch is implemented to demonstrate self-powered sensing and wireless communication capability. Combined, this study significantly advances the design and fabrication of cost-effective smart tires by demonstrating practical self-powered wireless strain sensing capability.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Sensorium: commissioning abundant sensors with augmented reality and QR codes

In the future, it will be possible to build high-quality models of building interiors based on data from a dense fleet of sensors reporting on air volumes much smaller than a room or zone. To enable such models, we are creating technologies that allow a fleet of sensors to be commissioned quickly at low cost. Our sensor commissioning process builds a 3D model of each building interior that includes sensor positions and sensor networking information such as sensor MAC addresses. It employs multiple technologies, including augmented reality, LiDAR, QR codes, and computer vision. Sensors can be commissioned at more than 10x the speed and at less than one tenth the cost of traditional approaches.

Bier, Eric A.↗
DOE OSTI2023

Boosting Piezoelectricity by 3D Printing PVDF‐MoS 2 Composite as a Conformal and High‐Sensitivity Piezoelectric Sensor

Abstract Additively manufactured flexible and high‐performance piezoelectric devices are highly desirable for sensing and energy harvesting of 3D conformal structures. Herein, the study reports a significantly enhanced piezoelectricity in polyvinylidene fluoride (PVDF) achieved through the in situ dipole alignment of PVDF within PVDF‐2D molybdenum disulfide (2D MoS 2 ) composite by 3D printing. The shear stress‐induced dipole poling of PVDF and 2D MoS 2 alignment are harnessed during 3D printing to boost piezoelectricity without requiring a post‐poling process. The results show a remarkable, more than the eight‐fold increment in the piezoelectric coefficient ( d 33 ) for 3D printed PVDF‐8wt.% MoS 2 composite over cast neat PVDF. The underlying mechanism of piezoelectric property enhancement is attributed to the increased volume fraction of β phase in PVDF, filler fraction, heterogeneous strain distribution around PVDF‐MoS 2 interfaces, and strain transfer to the nanofillers as confirmed by microstructural analysis and finite element simulation. These results provide a promising route to design and fabricate high‐performance 3D piezoelectric devices via 3D printing for next‐generation sensors and mechanical–electronic conformal devices.

2D MoS2↗
DOE OSTI2026

Advancing Industry 4.0: Multimodal Sensor Fusion for AI-Based Fault Detection in 3D Printing

Additive manufacturing, particularly fused deposition modeling, is transforming modern production by enabling rapid prototyping and complex part fabrication. However, its layer-by-layer process remains vulnerable to faults such as nozzle clogging, filament runout, and layer misalignment, which compromise print quality and reliability. Traditional inspection methods are costly, time-intensive, and often limited to post-process analysis, making them unsuitable for real-time intervention. In this current study, the authors developed a novel, low-cost, and portable faultdetection system that leverages multimodal sensor fusion and artificial intelligence for real-time monitoring in FDM-based 3D printing. The system integrates acoustic, vibration, and thermal sensing into a non-intrusive architecture, capturing complementary data streams that reflect both mechanical and process-related anomalies. Acoustic and thermal sensors operate in a fully contactless manner, while the vibration sensor requires minimal attachment such that it will not interfere with printer hardware, thereby preserving portability and ease of deployment. The multimodal signals are processed into spectrograms and time-frequency features, which are classified using convolutional neural networks for intelligent fault detection. The proposed system advances Industry 4.0 objectives by offering an affordable, scalable, and practical monitoring solution that improves faultdetection accuracy, reduces waste, and supports sustainable, adaptive manufacturing.

42 ENGINEERING↗
DOE OSTI2023

Simulation of two nanoparticle melting to understand the conductivity drop of 3D-printed silver nanowires

The future flexible sensor technology will require low-temperature, fast processing 3D printing techniques that will rely heavily on the quality of nanoparticle (NP) Ink. Electrical conductivity has been found to decrease in majority of the 3D printed electronic wires. Herein we report a fundamental understanding in drop of electrical conductivity in processed silver (Ag) line wire, generally found in Ag-nanoparticle Ink, using large-scale atomistic molecular dynamics (MD) simulations of sintering of five different sizes of Ag NPs. To preserve the high conductivity of pure silver wires, the integrity of the pristine face-centered cubic (FCC) crystalline structure must be retained in the processed line wires. Simulations show that the pristine Ag FCC structures of the nanoparticles are not recovered after melting and resolidification, instead, the resolidified material is paracrystaline. The breakdown of pristine FCC structures might be the cause of the drop in conductivity of processed Ag wires. Simulation results suggest that the intermediate size nanoparticles retain highest percentage of the pristine silver face-centered cubic (FCC) structure after pulse treatments. Our results show that the most promising Ag-Ink should contain smaller to medium size silver NPs that can retain FCC structure after 3D printing of the Ag-Ink.

42 ENGINEERING↗
DOE OSTI2022

AC compensation of 3D magnetic diagnostic signals in DIII-D and National Spherical Torus Experiment-Upgrade (NSTX-U) for real-time application

A time domain algorithm has been developed to remove the vacuum pickup generated by both coil current (DC) and induced vessel current (AC) in real time from three dimensional (3D) magnetic diagnostic signals in the National Spherical Torus Experiment-Upgrade (NSTX-U) and DIII-D tokamaks. The possibility of detecting 3D plasma perturbations in real time is essential in modern and future tokamaks to avoid and control MHD instabilities. The presence of vacuum field pickup, due to toroidally asymmetric (3D) coils or to misalignment between sensors and axisymmetric (2D) coils, pollutes the measured plasma 3D field, making the detection of the magnetic field produced by the plasma challenging. Although the DC coupling between coils and sensors can be easily calculated and removed, the AC part is more difficult. Here, an algorithm based on a layered low-pass filter approach for the AC compensation and its application for DIII-D and NSTX-U data is presented, showing that this method reduces the vacuum pickup to the noise level. Comparison of plasma response measurements with and without vacuum compensation shows that accurate mode locking detection and plasma response identification require precise AC and DC compensations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Tailoring Piezoelectricity of 3D Printing PVDF-MoS 2 Nanocomposite via In Situ Induced Shear Stress

3D printing of unique structures with tunable properties offers significant advantages in the fabrication of complex and customized electronic devices. Here, this study introduces a process-microstructure–property-guided manufacturing route to fabricate PVDF-2D MoS 2 piezoelectric nanocomposites with tunable piezoelectric properties without having a postprocess. We control PVDF’s microstructure through direct ink writing (DIW) 3D printing while tuning PVDF-MoS 2 interfacial strain by controlling rheology and 3D printing parameters, such as nozzle size and printing speed. Our approach demonstrates tunable piezoelectricity in PVDF-MoS 2 , achieving a 15-fold increase in the piezoelectric coefficient (d 33 ) at a printing-induced shear stress of 6685 Pa. This enhancement arises from the electrostatic interactions between PVDF and MoS 2 and the filler distribution and alignment caused by the in situ shear stress in 3D printing, as confirmed by XPS and Raman mapping analyses. Our findings advance the understanding of piezoelectric mechanisms in PVDF-based nanocomposites, laying the foundation for 3D printing of piezoelectric sensors in wearable device applications with enhanced performance and customization capabilities.

2D MoS2↗
DOE OSTI2022

High-Frequency 3D Photoacoustic Computed Tomography Using an Optical Microring Resonator

3D photoacoustic computed tomography (3D-PACT) has made great advances in volumetric imaging of biological tissues, with high spatial-temporal resolutions and large penetration depth. The development of 3D-PACT requires high-performance acoustic sensors with a small size, large detection bandwidth, and high sensitivity. In this work, we present a new high-frequency 3D-PACT system that uses a microring resonator (MRR) as the acoustic sensor. The MRR sensor has a size of 80 μ m in diameter and was fabricated using the nanoimprint lithography technology. Using the MRR sensor, we have developed a transmission-mode 3D-PACT system that has achieved a detection bandwidth of ~23 MHz, an imaging depth of ~8 mm, a lateral resolution of 114 μ m, and an axial resolution of 57 μ m. We have demonstrated the 3D PACT’s performance on in vitro phantoms, ex vivo mouse brain, and in vivo mouse ear and tadpole. The MRR-based 3D-PACT system can be a promising tool for structural, functional, and molecular imaging of biological tissues at depths.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Milone eTape Liquid Level Sensor Laboratory Calibration with a Commercial 12.2 cm HS-Flume and 3D Printed 4 cm Micro-HS-Flumes

The NGEE Arctic Rainfall Simulator (NARS) is a variable intensity rainfall simulator (RFS) with a frame design based on the Humphry et al. (2002) RFS and a water delivery system based on the Walnut Gulch (Paige et al., 2004) RFS. The NARS uses an aluminum frame that is fully deconstructable for transportation to field locations and a water system that enables variable rain intensity. Prior to field deployment, H-flume discharge and the corresponding Milone eTape Liquid Level Sensor (eTape) resistance values were measured in the laboratory so that discharge measurements from the NGEE Arctic Rainfall Simulator could be automated. eTape resistance was measured with increasing fluid heights for the full range of the eTape to calculate sensor detection limits and resolution. The eTape was calibrated to both a commercially available 12.2 cm HS-flume and a 3D printed 4 cm Micro-HS-flume. This data package contains two .csv files, one for the eTape calibration and the other for the flume calibrations, and two .stl files to 3D print the 4 cm Micro-HS-Flume design with a 1 cm x 3.6 cm stilling well opening. The .stl files can be opened in most 3D printing or CAD programs/software. Two .kml files of the laboratory location and broader area where testing was conducted are also included in this data package.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Coaxial Direct Ink Writing of Cholesteric Liquid Crystal Elastomers in 3D Architectures

Abstract Cholesteric liquid crystal elastomers (CLCEs) hold great promise for mechanochromic applications in anti‐counterfeiting, smart textiles, and soft robotics, thanks to the structural color and elasticity. While CLCEs are printed via direct ink writing (DIW) to fabricate free‐standing films, complex 3D structures are not fabricated due to the opposing rheological properties necessary for cholesteric alignment and multilayer stacking. Here, 3D CLCE structures are realized by utilizing coaxial DIW to print a CLC ink within a silicone ink. By tailoring the ink compositions, and thus, the rheological properties, the cholesteric phase rapidly forms without an annealing step, while the silicone shell provides encapsulation and support to the CLCE core, allowing for layer‐by‐layer printing of self‐supported 3D structures. As a demonstration, free‐standing bistable thin‐shell domes are printed. Color changes due to compressive and tensile stresses can be witnessed from the top and bottom of the inverted domes, respectively. When the domes are arranged in an array and inverted, they can snap back to their base state by uniaxial stretching, thereby functioning as mechanical sensors with memory. The additive manufacturing platform enables the rapid fabrication of 3D mechanochromic sensors thereby expanding the realm of potential applications for CLCEs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine Learning Analysis of Temperature-Strain Relationships for Structural Health Monitoring of Pipes: Self-powered wireless sensor system for health monitoring of liquid-sodium cooled fast reactors

This report presents machine learning (ML) analysis of temperature-strain relationships for structural health monitoring of nuclear reactor stainless steel (SS) pipes with the strain gauge sensor directly printed on the pipe with a 3D conformal aerosol jet printer. We investigate correlations for two sensor pairs installed on the same SS304 pipe: commercial K-type thermocouple with a printed gold strain gauge (TC3-SG3), and commercial K-type thermocouple with commercial Kyowa strain gauge (TC0-SG0). The temperature ranges for the sensor pairs TC0-SG0 and TC3-SG3 are 20.00°C to 266.37°C and 39.95°C to 219.28°C respectively. ML algorithms in this study include Linear Regression (baseline method), Ridge Regression, Lasso Regression, and Gradient Boosting. Performance evaluation metrics include Root Mean Square Error (RMSE), Mean Square Error (MSE), Mean Absolute Error (MAE), R 2 Score, and Explained Variance. Using advanced feature engineering techniques, we extracted 27 temperature-based features and 30 strategic inclusion features. The best performance was obtained with the Gradient Boosting method, which achieves prediction accuracy of R 2 = 0.9999 and RMSE = 7.69 μStrain for TC0-SG0, and R 2 = 0.9998 and RMSE = 18.03 μStrain for TC3-SG3. While the temperature-strain correlations are weaker for the gauge directly printed on the pipe than for the commercial strain gauge, deployment-ready performance exceeding industry standards is achieved for both sensor pairs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗