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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

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

Additive manufacturing (AM) techniques to directly integrate phase change materials (PCMs) are of interest for efficient thermal energy storage (TES) architectures. Complex, high surface-to-volume ratio composites embedded with PCM can improve thermal management with reduced material waste for customizable device fabrication. Reducing feature sizes of TES-integrated heat exchangers using AM can increase heat transfer without thermal conductivity enhancement. Here, composite AM materials containing 60 wt% microencapsulated phase change materials (MEPCM) are fabricated using off-the-shelf printers at common speeds and resolutions. High MEPCM loading in filaments is achieved with powder extrusion using two polymers, thermoplastic-polyurethane (TPU) and polycaprolactone (PCL), that mediate flexibility and rigidity for effective extrusion and printing without filament fracture or buckling. Furthermore, with PCL and TPU at 20 wt% each and 60 wt% MEPCM (P 20 T 20 M 60 ), smooth, form-stable filaments are consistently printed. Powder-based extrusion displays negligible damaging effects on the MEPCM. Printed P 20 T 20 M 60 demonstrates 105 J/g of energy storage with no degradation through 250 thermal cycles, within 5% of the theoretical storage enthalpy. Combining PCL/TPU shows good interfacial adhesion between print layers and produces high surface area objects, like 15% gyroids, and dense, 100% infilled pucks. Prints are also scalable to a 900 cm 3 honeycomb heat exchanger with an estimated 9 Wh energy storage.

25 ENERGY STORAGE↗
DOE OSTI2024

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Insight Into Sulfur‐Containing Additive to Boost Anti‐Oxidation Ability of the Ether‐Based Electrolyte for Sodium‐Ion Full Batteries

Ether-based electrolytes are considered as promising candidates for sodium-ion batteries (SIBs) due to their high ionic conductivity and good compatibility with hard carbon (HC) anode. However, they suffer from poor anti-oxidative ability with unstable cathode electrolyte interface, inducing successive electrolyte decomposition and rapid capacity fading. Herein, the sulfur-containing additive (1,3-propanediol cyclic sulfate, PCS) is introduced to boost the stability of the electrode-electrolyte interface (EEI) in ether-based electrolyte. PCS largely participates in the inner Na + sheath, causing more diglyme (G2) molecules and fewer PF 6 - anions to occupy the inner Na + solvation sheath, avoiding the decomposition of G2 molecules at high operation voltage. Moreover, PCS is beneficial for simultaneously constructing thin and robust sulfur-containing EEI on both Prussian blue (PB) cathode and HC anode, maintaining the structural stability of PB and alleviating the dissolution of transition metals. These enable PB||HC pouch cells to deliver a capacity retention of 60.3% after 400 cycles, significantly higher than the 32.1% in PCS-free electrolytes. In conclusion, this work discloses the underlying mechanism of PCS to evoke the anti-oxidation ability of ether-based electrolyte and provides a promising method for realizing advanced sodium-ion full cells.

anti-oxidation ability↗
DOE OSTI2020

Highly Tunable Thiol-Ene Photoresins for Volumetric Additive Manufacturing

Volumetric additive manufacturing (VAM) forms complete 3D objects in a single photocuring operation without layering defects, enabling 3D printed polymer parts with mechanical properties similar to their bulk material counterparts. This study presents the first report of VAM-printed thiol-ene resins. With well-ordered molecular networks, thiol-ene chemistry accesses polymer materials with a wide range of mechanical properties, moving VAM beyond the limitations of commonly used acrylate formulations. Since free-radical thiol-ene polymerization is not inhibited by oxygen, the nonlinear threshold response required in VAM is introduced by incorporating 2,2,6,6-tetramethyl-1-piperidinyloxy (TEMPO) as a radical scavenger. Tuning of the reaction kinetics is accomplished by balancing inhibitor and initiator content. Coupling this with quantitative measurements of the absorbed volumetric optical dose allows control of polymer conversion and gelation during printing. Importantly, this work thereby establishes the first comprehensive framework for spatial–temporal control over volumetric energy distribution, demonstrating structures 3D printed in thiol-ene resin by means of tomographic volumetric VAM. Mechanical characterization of this thiol-ene system, with varied ratios of isocyanurate and triethylene glycol monomers, reveals highly tunable mechanical response far more versatile than identical acrylate-based resins. This broadens the range of materials and properties available for VAM, taking another step toward high-performance printed polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Additive‐Free, Low‐Temperature Crystallization of Stable α‐FAPbI 3 Perovskite

Abstract Formamidinium lead triiodide (FAPbI 3 ) is attractive for photovoltaic devices due to its optimal bandgap at around 1.45 eV and improved thermal stability compared with methylammonium‐based perovskites. Crystallization of phase‐pure α‐FAPbI 3 conventionally requires high‐temperature thermal annealing at 150 °C whilst the obtained α‐FAPbI 3 is metastable at room temperature. Here, aerosol‐assisted crystallization (AAC) is reported, which converts yellow δ‐FAPbI 3 into black α‐FAPbI 3 at only 100 °C using precursor solutions containing only lead iodide and formamidinium iodide with no chemical additives. The obtained α‐FAPbI 3 exhibits remarkably enhanced stability compared to the 150 °C annealed counterparts, in combination with improvements in film crystallinity and photoluminescence yield. Using X‐ray diffraction, X‐ray scattering, and density functional theory simulation, it is identified that relaxation of residual tensile strains, achieved through the lower annealing temperature and post‐crystallization crystal growth during AAC, is the key factor that facilitates the formation of phase‐stable α‐FAPbI 3 . This overcomes the strain‐induced lattice expansion that is known to cause the metastability of α‐FAPbI 3 . Accordingly, pure FAPbI 3 p–i–n solar cells are reported, facilitated by the low‐temperature (≤100 °C) AAC processing, which demonstrates increases of both power conversion efficiency and operational stability compared to devices fabricated using 150 °C annealed films.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hot-Casting-Assisted Liquid Additive Engineering for Efficient and Stable Perovskite Solar Cells

High-performance inorganic–organic lead halide perovskite solar cells (PSCs) are often fabricated with a liquid additive such as dimethyl sulfoxide (DMSO), which retards crystallization and reduces roughness and pinholes in the perovskite layers. However, DMSO can be trapped during perovskite film formation and induce voids and undesired reaction byproducts upon later processing steps. Here, it is shown that the amount of residual DMSO can be reduced in as-spin-coated films significantly through use of preheated substrates, or a so-called hot-casting method. Hot casting increases the perovskite film thickness given the same concentration of solutions, which allows for reducing the perovskite solution concentration. By reducing the amount of DMSO in proportion to the concentration of perovskite precursors and using hot casting, it is possible to fabricate perovskite layers with improved perovskite–substrate interfaces by suppressing the formation of byproducts, which increase trap density and accelerate degradation of the perovskite layers. The best-performing PSCs exhibit a power conversion efficiency (PCE) of 23.4% (23.0% stabilized efficiency) under simulated solar illumination. Furthermore, encapsulated devices show considerably reduced post-burn-in decay, retaining 75% and 90% of their initial and post-burn-in efficiencies after 3000 h of operation with maximum power point tracking (MPPT) under high power of ultraviolet (UV)-containing continuous light exposure.

perovskite-substrate interface↗
DOE OSTI2023

Acoustic‐Modulated, Selective Particle Deposition for Muti‐Material Additive Manufacturing

Powder‐based additive manufacturing (AM) is an important technology in fabricating complex 3D products. In powder‐based AM, a powder deposition system plays a key role in determining the resolution, density, and properties of printed parts. An acoustic‐actuated particle deposition approach, which utilizes acoustic waves to actuate a glass nozzle, enables the deposition of particles in a cost‐effective way. However, the capability to programmably deposit different particles using acoustic waves has yet to be fully demonstrated. Herein, a selective particle deposition approach via acoustic modulation for muti‐material AM is demonstrated. Sequential and parallel depositions of two types of particles by modulating the signal inputs and resonant frequencies of piezo transducers are demonstrated. An AM process is demonstrated by integrating this acoustic‐actuated particle deposition approach with a heat‐curing mechanism. Several products from this system are produced as well. It is expected that this particle deposition approach can be used in a wide spectrum of applications, such as direct manufacturing of multi‐functional materials/devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Virtual Volumetric Additive Manufacturing (VirtualVAM)

Abstract Tomographic volumetric additive manufacturing (VAM) produces arbitrary 3D geometries by exposure of a rotating volume of photopolymer resin to tomographically‐patterned illumination. This enables high speed, layer‐less printing of parts from a wide range of photopolymers not amenable to layer‐by‐layer processes. Since the entire geometry is produced at once over the course of a few seconds to minutes, molecular diffusion length scales become significant to the printing process. Understanding these molecular reaction and diffusion processes is imperative for advancing VAM to a usable technology. These processes are experimentally very difficult to monitor and measure. Herein, VirtualVAM ‐ a simulation framework for modeling the tomographic VAM process, is developed and experimentally validated. VirtualVAM simulates reaction, diffusion, and heat generation processes over the course of a print with single‐voxel resolution. From a few experimentally‐determined input parameters and a set of images for projection, VirtualVAM is able to generate a large spatio‐temporal data set for any given tomographic VAM print. Using VirtualVAM, a number of experimentally‐unattainable aspects of the VAM process are investigated such as single‐voxel conversion profiles, effect of molecular oxygen, and stopping time determination. VirtualVAM also enables the optimization of exposure patterns to further improve contrast between in‐part and out‐of‐part delivered dose.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dielectric Barrier Discharge Electrothermal Heating and Additive Manufacturing of Thermoset Parts

Additive manufacturing of thermosets requires a mechanism for solidifying deposited layers in order to prevent part collapse. To accomplish this, non‐equilibrium plasma is proposed for its ability to target, heat, and cure printed thermosetting resin. Non‐equilibrium plasmas have not been used for the curing of liquid thermoset composites, and so their impact on an uncured resin is unknown. Here this work investigates the mechanism through which dielectric barrier discharge (DBD) heats an epoxy/carbon nanotube (CNT) composite under atmospheric conditions. Plasma applied to resin surfaces is found to cause rapid heating, with heating rate controlled by adjusting the applied power. Heating is localized to within the top 0.5 mm of the sample surface and maximum temperature is found to depend on sample conductivity, indicating the heating reaction occurs through a combination of electron conduction and ion bombardment. Characterization of composites cured using plasma shows oxidation and roughening of the surface. Based on the heating and surface studies, several demonstrative prints are performed using in situ plasma curing. This work shows the potential of DBD plasma to rapidly heat liquid substrates and demonstrates how plasma curing expands the capability of existing direct ink write (DIW) printer technologies.

3D printing↗
DOE OSTI2025

Hybrid Additive and Subtractive Manufacturing of Dual‐Wavelength Photopolymer Thermosets

Additive manufacturing (AM) techniques such as digital light processing (DLP) AM and stereolithography enable the production of highly complex structures with speed and ease as not previously possible. However, many traditional thermosetting photopolymers used in these processes result in a permanently crosslinked structure incapable of being broken down or modified without the use of energy-intensive processes such as mechanical machining or ablation. To overcome this limitation, this production is described of thiol-ene photopolymer thermosets with dual-wavelength photopolymerization and photodegradation reaction pathways. The dual wavelength selectivity of the polymerization (405 nm) and degradation (365 nm) processes, combined with dual-wavelength DLP AM technology, enables hybrid manufacturing with the ability to add and sequentially subtract material with excellent spatiotemporal control. 2D lithographs and complex 3D architectures with soft elastomeric properties are produced with resolutions as small as 50 µm. Furthermore, the ability to selectively subtract supports from 3D printed structures with deliberate and accurate control is demonstrated. In conclusion, the ability to correct or modify existing structures enables a new paradigm of adaptable materials for corrective manufacturing techniques and temporary structures.

3D Printing↗
DOE OSTI2022

Continuous Additive Manufacturing using Olefin Metathesis

Abstract The development of chemistry is reported to implement selective dual‐wavelength olefin metathesis polymerization for continuous additive manufacturing (AM). A resin formulation based on dicyclopentadiene is produced using a latent olefin metathesis catalyst, various photosensitizers (PSs) and photobase generators (PBGs) to achieve efficient initiation at one wavelength (e.g., blue light) and fast catalyst decomposition and polymerization deactivation at a second (e.g., UV‐light). This process enables 2D stereolithographic (SLA) printing, either using photomasks or patterned, collimated light. Importantly, the same process is readily adapted for 3D continuous AM, with printing rates of 36 mm h –1 for patterned light and up to 180 mm h –1 using un‐patterned, high intensity light.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Cation Additive Enabled Rechargeable LiOH-Based Lithium–Oxygen Batteries

Lithium-oxygen (Li-O 2 ) batteries have attracted extensive research interest due to their high energy density. Other than Li 2 O 2 (a typical discharge product in Li-O 2 batteries), LiOH has proved to be electrochemically active as an alternative product. Here we report a simple strategy to achieve a reversible LiOH-based Li-O 2 battery by using a cation additive, sodium ions, to the lithium electrolyte. Without redox mediators in the cell, LiOH is detected as the sole discharge product and it charges at a low charge potential of 3.4 V. A solution-based reaction route is proposed, showing that the competing solvation environment of the catalyst and Li+ leads to LiOH precipitation at the cathode. It is critical to tune the cell chemistry of Li-O 2 batteries by designing a simple system to promote LiOH formation/decomposition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Improve durability and surface quality of additively manufactured molds using carbon fiber prepreg

Hybrid tooling is an emerging concept introduced in the aerospace industries to reduce weight and cost of traditional tools. A hybrid tool features a skin, which provides desired surface quality, durability, and a low-density substrate to reduce the weight of the mold. The big area additive manufacturing (BAAM) technology permits rapid production of thermoplastic polymer intensive large-scale structures. The present study features a carbon fiber reinforced polyphenylene sulfide (CF-PPS) substrate fabricated using Oak Ridge National Laboratory's BAAM system. Carbon fiber-bismaleimide (CF-BMI) prepreg skin was then bonded to the BAAM tool through high-pressure autoclave molding. Process optimization was conducted to improve the bonding between CF-PPS and CF-BMI (transverse tensile strength increased from 0.54 to 4.8 MPa). Durability of the mold was demonstrated from fabricating seven (7) carbon fiber-Huntsman epoxy hand lay-up parts utilizing the mold.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Anisotropic thermal behavior of extrusion-based large scale additively manufactured carbon-fiber reinforced thermoplastic structures

Large format additive manufacturing (AM) enables rapid manufacturing of large parts and structures with minimum waste in material and energy. Extrusion-based AM deposition processes provide parts with highly anisotropic thermal properties, which are not typically reflected in textbook values for these materials. In order to develop accurate models that describe the directionally dependent thermal behavior of these materials in processing and service, accurate measurements of specific heat capacity and thermal conductivity are required. Here, this work characterizes, documents, and analyzes the effect of the anisotropic nature of the extrusion-based deposition process on the specific heat capacity and thermal conductivity of the resulting AM products. All measurements were made over a temperature range of 20–180°C using the transient plane source technique, also referred to as the hot disk technique. Three of the most commonly used large format AM feedstock materials that utilize carbon fiber reinforcement were examined in this work: acrylonitrile butadiene styrene, polyphenylene sulfide and polyphenylsulfone. Finally, these findings can serve as a thermal design/process guideline for future large format AM applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Techno‐Economic Analysis of Additively‐Manufactured Wind Turbine Blade Tips That Enable Technology Integration

The Additively‐Manufactured, System‐Integrated Tip (AMSIT) project is leveraging the flexibility of 3D printing to integrate several technologies in a wind turbine blade tip, while reducing the levelized cost of electricity (LCOE) produced. The design integration is demonstrated for a 200‐kW–scale turbine with 13‐m blades, with the outer 15% of the blade replaced with a 3D‐printed design. Aerodynamic performance is enhanced without increasing swept area through inclusion of a winglet and surface texturing, both challenging for traditional manufacturing. Longevity and durability are improved through integrated lightning and leading edge erosion protection. Increased power, reduced repair frequency, and ease of repair through blade modularity all contribute to reduced LCOE. The analysis is also extended to modern MW‐scale designs to estimate the impact of the technology at scale, demonstrating the potential to reduce LCOE significantly for modern onshore turbines, with even higher potential savings offshore.

3D printing↗
DOE OSTI2024

A lipase from Lacticaseibacillus rhamnosus IDCC 3201 with thermostability and pH resistance for use as a detergent additive

Lipases are important biocatalysts and ubiquitous in plants, animals, and microorganisms. The high growth rates of microorganisms with low production costs have enabled the wide application of microbial lipases in detergent, food, and cosmetic industries. Herein, a novel lipase from Lacticaseibacillus rhamnosus IDCC 3201 (Lac-Rh) was isolated and its activity analyzed under a range of reaction conditions to evaluate its potential industrial application. The isolated Lac-Rh showed a molecular weight of 24 kDa and a maximum activity of 3438.5 ± 1.8 U/mg protein at 60 °C and pH 8. Additionally, Lac-Rh retained activity in alkaline conditions and in 10% v/v concentrations of organic solvents, including glycerol and acetone. Interestingly, after pre-incubation in the presence of multiple commercial detergents, Lac-Rh maintained over 80% of its activity and the stains from cotton were successfully removed under a simulated laundry setting. Overall, the purified lipase from L. rhamnosus IDCC 3201 has potential for use as a detergent in industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

MADE3D: Enabling the next generation of high-torque density wind generators by additive design and 3D printing

Direct-drive wind turbine generators are increasing in popularity, thanks to recent project developments—especially offshore, where reliability and efficiency are major cost drivers. Yet, high capital costs are forcing many original equipment manufacturers to consider lightweight, high-torque density generators for next-generation multi-megawatt turbines that may be difficult to realize by traditional design or manufacturing methods. In this study, we present a new design framework enabled by advanced machine learning and multimaterial additive manufacturing to perform a magnetic topology optimization that maximizes the torque per rotor active mass for a 15-megawatt direct-drive permanent magnet wind generator. A comparison of the proposed approach against conventional topology optimization demonstrated a significant increase in computational efficiency and accuracy in performance predictions. Results using single and multimaterial compositions for rotor core and magnets identify a wider choice of 3D printable designs for a given specification. A hybrid combination of sintered and dysprosium-free polymer-bonded magnets shows good potential for torque performance by saving material costs up to 8.75%. More than 30% improvement in rotor torque densities is identified which can marginally improve the overall generator torque density. With the rapid evolution of multipowder deposition technolgies, this study can greatly inspire a new paradigm for design-driven manufacturing with novel material compositions and lightweight, low-cost, high-strength multimaterial geometries that were previously unexplored for direct-drive generators.

17 WIND ENERGY↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗