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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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50 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Large Scale Granulator Development Designed to Process Reclaimed Feedstock for Sustainable Additive Manufacturing Applications

This CRADA between UT-Battelle, LLC (Contractor) and re:3D Inc. (Participant) aims to develop an affordable large-scale granulator system designed to process reclaimed plastic feedstock suitable for additive manufacturing applications. The 24-month project will focus on testing, prototyping, and optimizing a shredder/granulator system. This project also focuses on the processing steps (e.g. washing and sorting) that can convert waste plastics, like discarded water bottles, into flake/granules which can be 3D printed using re:3D’s Fused Granular Fabrication (FGF) 3D printers. If successful, this could enable more localized 3D printing using recycled plastics, reducing waste and feedstock costs.

Wang, Peter [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2025

Accurate and Fast Anomaly Detection in Additive Composite-Based Manufacturing using Thermal Cameras

Today, large-scale additive manufacturing with plastics and composite materials requires continuous monitoring by experienced staff to prevent, detect and correct anomalous events affecting the performance of the printed part. We address the complexity of this demanding task by designing a camera-based anomaly detection system utilizing probabilistic principal component analysis (PPCA). This is a machine learning technique is trained with thermal images collected during normal operation of the large-scale printer (Cincinnati BAAM). This technique is advantageous for practical applications as there is no need to artificially introduce anomalous conditions into model training. During deployment, we challenge this model by introducing deliberate variations of the extruder speed. We reduce extrusion speed to a lower level, between 70 and 95% of the nominal value to collected test images. Our results show that images are easily identified as anomalous for extruder speeds at or below 85% of the nominal speed, meaning that an anomalous reduction of the material deposition rate can be detected within seconds of its onset. We show that our results are robust to (a) camera-to-camera variability and (b) print-to-print variability.

Pike, John [ORNL]↗
DOE OSTI2024

Development of a Colorimetric Loop-Mediated Isothermal Amplification Assay for the Detection of Trypanosoma cruzi in Low-Resource Settings

Chagas disease is an inflammatory parasitic infection caused by Trypanosoma cruzi (T. cruzi). Early diagnosis is crucial in guiding treatment and slowing disease progression; however, current diagnostic methods have insufficient detection limits and often require skilled technicians. Molecular tests, especially isothermal nucleic acid assays, are advantageous due to their excellent sensitivity, specificity, speed, and simplicity. Here, we optimized a colorimetric loop-mediated isothermal amplification (LAMP) assay for T. cruzi. We can detect as few as 2 genomic copies/reaction using three different T. cruzi strains. We examined selectivity using other parasitic protozoans and successfully detected T. cruzi DNA extracted from parasites in human whole blood down to 1.2 parasite equivalents/reaction. We also performed a blinded study using canine blood samples and established a 100% sensitivity, specificity, and accuracy for the colorimetric LAMP assay. Finally, we used a heated 3D printer bed and an insulated thermos cup to demonstrate that the LAMP incubation step could be performed with accessible, low-cost materials. Altogether, we have developed a high-performing assay for T. cruzi with a simple colorimetric output that would be ideal for rapid, low-cost screening at the point of use.

60 APPLIED LIFE SCIENCES↗
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 OSTI2025

Explainable Machine Learning for Functional Data

Black-box machine learning models are recognized as useful tools for prediction applications, but the algorithmic complexity of some models causes interpretation challenges. Explainability methods have been proposed to provide insight into these models, but there is little research focused on supervised modeling with functional data inputs. We argue that, especially in applications of high consequence, it is important to explicitly model the functional dependence in a black-box analysis to not obscure or misrepresent patterns in explanations. As such, we propose the V ariable importance E xplainable E lastic S hape A nalysis (VEESA) pipeline for training supervised machine learning models with functional inputs. The pipeline is an analysis process that includes the data preprocessing, modeling, and post-hoc explanations. The preprocessing is done using elastic functional principal components analysis, which accounts for vertical and horizontal variability in functional data and, ultimately, allows for explanations in the original data space that identify the important functional variability without bias due to correlated variables. Here, we demonstrate the pipeline on two high-consequence applications: explosives classification for national security and inkjet printer identification in forensic science. The applications exhibit the VEESA pipeline’s ability to provide an understanding of the characteristics of the functional data useful for prediction. Code for implementing the pipeline is available in the veesa R package (and supplemental python code).

Elastic Shape Analysis↗
DOE OSTI2025

Understanding Fracture Aperture and Permeability Evolution due to Carbonate Mineralization Utilizing 3D Printing

Caprock formations are a crucial part of subsurface-engineered systems. Composed largely of shale, caprocks act as natural barriers that prevent the upward migration of fluids, thereby ensuring the containment of stored substances in subsurface formations. Fractures in these formations are potential leakage pathways for stored fluids. Mineral precipitation reactions in these fractures, particularly calcite, can significantly restrict the fluid permeability, reducing leakage potential. However, predictive capabilities of mineral precipitation in fractures and associated permeability evolution are limited due to a lack of fundamental understanding of such reactions in natural samples, complicated by mineral heterogeneity and the complexity of the fracture structure. In this study, 3D-printed fracture samples are used to understand the impact of carbonate mineralization on fracture aperture and permeability evolution. Samples were printed using a digital light processing (DLP) 3D printer and commercial liquid resin. Calcite precipitation was first tested on printed 2D films before conducting plug flow column experiments aimed to understand fracture permeability changes due to mineral precipitation. Contact angle measurement and Fourier transform infrared (FTIR) spectroscopy on printed 2D films show evidence of a substantial amount of surface energy for calcite nucleation and precipitation. Surface topography analysis of printed fractured surfaces reveals comparable values, highlighting the high replicability of the printed samples. During the column experiments, the permeability reduces exponentially due to a decrease in fracture aperture. Reductions in fracture aperture estimated from effluent concentration and 3D X-ray computed tomography (CT) show comparable results. Moreover, 3D X-ray CT images suggest the impact of local flow velocities on precipitation. The insights gained from this research contribute to a deeper understanding of the permeability evolution due to carbonate mineralization in caprock formations.

3D printing↗
DOE OSTI2024

Designing Track for Electrospinning Unit and Cost-Effective Laser Scanning System

Nanofibers are produced in the Targeted Systems Department (TSD) by applying a large voltage to the nanofiber fluid and the collection apparatus known as the electrospinner. The fiber is then shot out of nozzles and collected onto the electrospinner into a nanofiber mat. The problem is that since the nozzle heads are stationary, there is non-uniform deposition of nanofiber on the collection drum leading to variation in thickness of the produced nanofiber mat. To mitigate this issue, a reciprocating mechanism is designed to move the nozzle along the drum collector along with the ability to vary its stroke length. This design was realized using Siemens NX and several parts were printed using a 3D printer, but is, as of writing, untested. Second project involved providing an alternative method to scan a large sample that had undergone certain surface deformation by beam interaction and detect out of plane deformation such as micro-scale swelling and surface roughness. Systems to carry out this scanning already exist; however, they are expensive and produce many files that need to be stitched together and are cumbersome to deal with. The solution is to create a scanning system using an already purchased scanning laser and linear stage motor. The laser and stage motor were combined to produce length results that aligned with a digital microscope but differing height results.

Ruffolo, Leopoldo↗
DOE OSTI2024

Designing a track for an electrospinning unit and cost-effective laser scanning system

Nanofibers are produced in the Targeted Systems Department (TSD) by applying a large voltage to the nanofiber fluid and the collection apparatus known as the electrospinner. The fiber is then shot out of nozzles and collected onto the electrospinner into a nanofiber mat. The problem is that since the nozzle heads are stationary, there is non-uniform deposition of nanofiber on the collection drum leading to variation in thickness of the produced nanofiber mat. To mitigate this issue, a reciprocating mechanism is designed to move the nozzle along the drum collector along with the ability to vary its stroke length. This design was realized using Siemens NX and several parts were printed using a 3D printer, but is, as of writing, untested. Second project involved providing an alternative method to scan a large sample that had undergone certain surface deformation by beam interaction and detect out of plane deformation such as micro-scale swelling and surface roughness. Systems to carry out this scanning already exist; however, they are expensive and produce many files that need to be stitched together and are cumbersome to deal with. The solution is to create a scanning system using an already purchased scanning laser and linear stage motor. The laser and stage motor were combined to produce length results that aligned with a digital microscope but differing height results.

Ruffolo, Leopoldo↗
DOE OSTI2024

Additive Manufacturing of Thermal Energy Storage Composites with Microencapsulated Phase Change Materials Supported in a Multi-Polymer Matrix

Advanced manufacturing techniques, such as additive manufacturing (AM), that can directly integrate phase change materials (PCMs) have garnered interest in recent years due to their potential for development of highly efficient thermal energy storage architectures. Complex, high surface area geometries embedded with PCMs that are only feasible with AM can improve thermal management with reduced material waste. Our work focuses on developing composite filaments with microencapsulated phase change materials (MEPCM) bound within a single or dual polymer matrix that can be processed through standard filament extruders and additively manufactured using off-the-shelf 3D printers. Polymer powders, rather than polymer pellets, were key to homogenously mixed filaments achieving high MEPCM loadings with no deterioration in thermal energy storage (TES) capability during extrusion. Composite filaments contain upwards of 60 wt% MEPCM and were printed without loss in feature resolution, print speed, or layer adhesion. Storage enthalpies of printed composites range from 100 - 130 kJ/kg, which were within 5% of the theoretical enthalpy based on weight fraction of MEPCM and maintained enthalpies within 1% over 500 thermal cycles. We can reliably manufacture low density, high surface area structures like 15% gyroid infill, along with dense, compact pucks at a 100% concentric infill. Prints were also scalable to a 900 cm3 honeycomb infill heat exchanger model that has an estimated energy storage capacity of 9 Wh.

3D printing↗
DOE OSTI2025

Novel technology of non-contact real-time radiation damage sensors for high power targets.

This report summarizes the contributions of an intern participating in the Community College Internship (CCI) program at Fermilab, focusing on the development of a novel, non-contact, real-time radiation damage sensor technology. The core objective is to create a reliable sensor capable of measuring radiation-induced degradation on high-power targets without physical contact. The experiment involves using a Class 3B supercontinuum laser directed toward a single material sample placed within a vacuum test chamber. The laser beam reflects off the sample's surface, with changes in reflectivity, indicative of radiation damage, measured by a spectrometer positioned at the chamber’s output port. The intern’s primary responsibilities included designing an interlock system to ensure laser operational safety, developing a camera-based monitoring system using Raspberry Pi devices, and creating structural supports using 3D modeling and printing techniques. Components for the interlock and camera systems were successfully designed and ordered, with preliminary 3D models printed and refined through iterative testing. Challenges encountered in the 3D printing process, such as fragile initial prototypes and difficult support removal, were overcome by adjusting printer settings and incorporating design enhancements like chamfered edges. Future activities, pending component delivery, involve installing and configuring the interlock and camera systems, as well as further improving the structural supports. Overall, the internship significantly enhanced the intern’s technical proficiency in hardware design, software integration, and advanced 3D printing, contributing directly to Fermilab’s operational safety standards and experimental effectiveness in high-energy physics research.

Pumarino Meza, Rafael [Unlisted; Fermilab]↗
DOE OSTI2025

Internal-Gelation Production of Uranium Oxide Sol-Gel Particles for Forensic Applications

The purpose of this project was to develop and demonstrate a novel method for the production of uranium oxide microsphere particles with tunable chemical compositions via a sol-gel process using a 3D-printer setup. These particles can serve several purposes in research and development as a forensic training tool or as standard reference materials. A key component of the project was to demonstrate the ability to control physical and chemical parameters of the particles created. First, we demonstrated the ability to employ an internal gelation sol-gel process to create individual uranium oxide particles. The particles were successfully dispensed using a unique 3D-printing setup onto a substrate to react and then were collected and thermally processed. A series of temperatures for the annealing process was tested on individual samples to investigate the effect on the sol-gel chemical composition and physical integrity. Next, we demonstrated the ability to control matrix composition of the particles by separately incorporating fission product isotopes as well as Np-237 into the sol-gel solution. It was shown by gamma-ray spectroscopy that these matrix elements were successfully retained during the gelation process. We studied the retention of the elements across a series of annealing temperatures. Additionally, we demonstrated the ability to quantitatively control the isotopic composition of the particles by altering the U-237/U-238 ratio to a controlled value. Finally, X-ray diffraction analysis (XRD) was used to investigate the oxidation state of the sol-gel after annealing at different temperatures.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2026

INFLUENCE OF SUPPLEMENTARY ARGON GAS SHIELDING ON THE MICROSTRUCTURE AND MECHANICAL BEHAVIOR OF SS316L ADDITIVELY MANUFACTURED BY DIRECTED ENERGY DEPOSITION

The dissolution of atmospheric gases into parts additively manufactured by directed energy deposition (DED) has long been of concern, and stock shielding solutions have usually proven inadequate at fully removing atmospheric gases from weld beads. The objective of this work was to design a new supplementary argon gas shroud for a specific DED printer and evaluate its effect on microstructure and macroscopic properties of SS316L and the potential for printing more reactive metals such as Ti-6Al-4V. This was investigated by printing four SS316L sample blocks, two with and two without the shroud, each printed in two different orientations. These samples were subsequently evaluated with inert gas fusion (IGF), SEM/EDS imaging, and tensile tests. The shroud reduced oxygen content by 0.019-0.031%, and SEM imaging revealed fewer oxide inclusions. A more dramatic reduction of 0.13% oxygen and 0.171% nitrogen was observed by the inert gas fusion of Ti-6Al-4V samples. Overall, the results indicated the shroud was successful at reducing atmospheric gas uptake within the print region and may enable the printing of reactive metal powders in DED systems.

Helvie, Kyle↗
DOE OSTI2026

Electronic Waste (E-Waste) Recycling: Barriers and Opportunities for State, Local, and Tribal Governments

Electronic waste, or e-waste, encompasses end-of-life electrical and electronic equipment, including computers, monitors, televisions, printers, cell phones, household appliances with electronic components, and small consumer devices containing batteries or circuitry. E-waste is one of the fastest-growing components of the U.S. waste stream, with nearly 8 million tons generated in 2022. E-waste presents two related public-interest considerations. First, e-waste contains economically and strategically important materials: base metals (copper, aluminum, iron, steel), precious metals (gold, silver, platinum group metals), and critical materials such as rare earth elements, gallium, and indium that appear on the U.S. Geological Survey's (USGS) 2025 List of Critical Minerals. Second, many electronic devices contain hazardous constituents - including lead, mercury, cadmium, and brominated flame retardants - as well as rechargeable batteries that can pose fire risks during handling. Effective management of these constituents helps protect workers, communities, and the environment. In the United States, it is estimated that less than 20% of e-waste is formally collected and recycled, leaving over 6 million tons landfilled or otherwise unrecovered. This fact sheet provides state and local decision-makers an overview of (1) e-waste composition and recoverable materials, (2) technology pathways used to recover those materials, and (3) examples of operational and partnership structures used to provide e-waste recycling capacity in the United States. It is intended to complement existing collection-program guidance available through U.S. Environmental Protection Agency (EPA) and other sources.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Thermal Conductivity Measurement of Extrusion-Printed Silver Using Modulated Photothermal Radiometry

Flexible printed electronics is a rapidly growing field with applications in conformal and flexible devices. However, the physical properties of the films created by many state-of-the-art printing methods become highly dependent on printing parameters, resulting in varying thermal properties often differing significantly from their bulk ink components. To understand the influence of the printing process, we build upon our previous work, where a noncontact optical technique, known as modulated photothermal radiometry (MPTR), was used to measure the thermal conductivity of aerosol-jet-printed thin films. In this work, we use the method to study the thermal properties of extrusion-printed silver on glass and alumina substrates. A noise-resistant data analysis fitting technique is applied using a 2-D heat transfer model. Here, the thermal conductivity measurement is validated using the Weidemann-Franz (WF) relationship from measured electrical conductivity values.

42 ENGINEERING↗