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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Separating Miscible Liquid–Liquid Mixtures Using Supported Ionic Liquid Membranes

Supported liquid membranes (SLMs) are promising in separating miscible liquid–liquid mixtures, which has been a key challenge in wastewater treatment and other applications. However, SLMs suffer from poor durability due to the loss of the liquid phase. In current work, ionic liquids (ILs) with high stability have been impregnated into polyvinylidene fluoride membranes to separate miscible benzene–heptane mixtures. The two imidazolium-based ILs, that is, 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF 6 ]) and 1-butyl-3-methylimidazolium tris(pentafluoroethyl) trifluorophosphate ([BMIM][FAP]), were tested in supported ionic liquid membranes (SILMs) for the benzene–heptane separation. Both ILs show successful separation within 48 h as indicated by nuclear magnetic resonance results. Compared to the SILM with [BMIM][FAP], the SILM with [BMIM][PF 6 ] has lower throughput and higher selectivity. The higher selectivity can be attributed to the higher hydrophilicity of [BMIM][PF 6 ], which results in strong repulsion against heptane. The lower throughput can be attributed to the higher hydrophilicity as well since it lowers the solubility of benzene in [BMIM][PF 6 ]. The stability of IL in SILMs has also been investigated via multiple separation cycles. The scanning electron microscopy, weight change of SILMs, and separation results indicate that the separation efficiency of the [BMIM][PF 6 ] SILM does not degrade for up to 144 h. The SILM has been further optimized with curvature design (i.e., curved SILM) to increase the interfacial area and thus increase the separation throughput, where the curved SILM separation device was 3D-printed. Here, the findings here have important implications on design and application of SILMs in separating miscible liquid–liquid mixtures.

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

Synergistic Combination of Living Ring-Opening Metathesis Polymerization and Atom Transfer Radical Polymerization to Synthesize Structurally Tailored and Engineered Macromolecular Networks

Structurally tailored and engineered macromolecular (STEM) networks are attractive materials for soft robotics, stretchable electronics, tissue engineering, and 3D printing due to their tunable properties. To date, STEM networks have been synthesized by atom transfer radical polymerization (ATRP) or the combination of reversible addition–fragmentation chain-transfer (RAFT) polymerization and ATRP. RAFT polymerization could have limited selectivity with ATRP inimer sites that can participate in radical-transfer processes. On the other hand, living ring-opening metathesis polymerization (ROMP) can produce a polymeric network with latent ATRP initiator sites in high selectivity. Herein, for the first time, we report the syntheses of STEM zero-generation (STEM-0) networks using a monomer, a cross-linker, and an ATRP/ROMP inimer via living ROMP, followed by their modification using a second monomer via ATRP to synthesize STEM first-generation (STEM-1) networks. The mechanical property and swelling capacity analyses of these networks were carried out. A change in mechanical properties and swelling capacity of these networks was observed due to their structural modification.

Absorption↗
DOE OSTI2021

Yielding Behavior of Bottlebrush and Linear Block Copolymers

Block copolymers can exhibit a pronounced yield stress, but the impact of molecular architecture, chemistry, and self-assembly on macroscopic rheology remains poorly understood. Here, we study the linear-viscoelastic and yield-stress fluid behavior of two architectures—bottlebrush copolymers (with statistical or blocky sequences) and linear diblocks—that self-assemble into body-centered cubic (BCC) spheres and hexagonally close-packed cylinders (HEX). The dynamic properties of these polymers were probed by oscillatory frequency and amplitude sweeps at temperatures well below the order–disorder transition (TODT) to furnish insights into the yielding transition. All BCC-forming polymers have a similar signature of yielding: smaller yield strains (γ yBCC ≈ 0.053 < γ y,HEX ≈ 0.18), sharper solid–liquid transitions, and better reversibility than HEX. Statistical bottlebrushes show the most frequency-independent structural modulus (G 0 ) and no signs of defect relaxation. A simple power-law relationship captures the dependence of the normalized structural modulus (G 0 /RT) on the inter-micelle distance (d) across different architectures and morphologies [G 0 /(RT) = 1.31 × 10 4 (nm 2.6 mol/m 3 ) d –2.6 ]. These studies establish quantitative structure–property relationships that are relevant in contemporary applications, for example, extrusion-based 3D printing.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Interfacial Assembly and Jamming of Soft Nanoparticle Surfactants into Colloidosomes and Structured Liquids

Nanoparticle surfactant (NPS) offers a powerful strategy to generate all-liquid constructs that integrate the inherent properties of the NPs into 3D architectures. In this report using the co-assembly of fluorescent polymeric nanoparticles and amine-functionalized polyhedral oligomeric silsesquioxane, the assembly and jamming behavior of a new type of NPS at the oil-water interface is uncovered. Unlike "solid" inorganic nanoparticles, "soft" polymeric nanoparticles can reorganize when jammed, leading to a relaxation and deformation of the interfacial assemblies, for example, the 3D printed sugar-coated haw stick-like liquid tubules. With NPS serving as emulsifiers, stable Pickering emulsions are prepared that can be converted into robust colloidosomes with pH responsiveness, showing numerous potential applications for encapsulation and controlled release.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Diels–Alder Augmented Epoxies with Plasmonic Nanoparticle Fillers for Efficient Photothermal Depolymerization

Thermally reversible epoxies through the Diels–Alder (DA) reaction have been used for applications such as recycling, self-healing, and 3D printing. Depolymerization by bulk heating, however, would be a slow and inefficient process due to its low thermal conductivity. In this paper, photothermal conversion using refractory plasmonic titanium nitride (TiN) nanoparticles was employed for efficient and rapid depolymerization of reversible epoxies. TiN nanoparticles have superior thermal stability, broader light absorption, and higher light-to-heat conversion efficiency. They are also less expensive than more common plasmonic gold nanoparticles. Photothermal behavior of TiN nanoparticle-filled reversible epoxies was investigated as a function of concentration of TiN nanoparticles and as a function of the intensity of a light source. TiN nanoparticles could induce sufficient heat for depolymerization with a trace content, 0.01% by weight, under a broad-spectrum white light of intensity 1760 mW/cm 2 instead of a strong light source such as a laser. The reversible epoxies were prepared by a reaction between furan precursors and a bismaleimide compound. Crosslinking density was controlled by altering the architecture of furan precursors and the feed ratio between the furan precursor and the bismaleimide compound. These changes in chemical structure and degree of crosslinking permit the control of the thermomechanical properties of the reversible epoxy from soft elastomers to hard elastomers. Here, the reversible epoxies display a flow region at around 110 °C. Depolymerization through the retro-DA was confirmed by Fourier transform infrared spectroscopy as a function of duration at a high temperature. Light-induced removability and recyclability were demonstrated by adhesion tests using the reversible epoxy/nanoparticle composites.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Plastic Scintillators via Rapid Photoinitiated Cationic Polymerization of Vinyltoluene

Cationic photopolymerization is applied for the rapid curing of a vinyltoluene and fluorophore solution into an efficient plastic scintillator. A hard solid is obtained via UV light-initiated polymerization of vinyltoluene, diaryliodonium salt, 9,9-dimethyl-2-phenylfluorene (PhF), and 9,9-dimethyl-2,7-distyrlfluorene (SFS) at ambient conditions with high conversion rates under a range of cationic photoinitiator concentrations, fluorophore concentrations, and light intensities. Insight into photopolymerization kinetics via photo differential scanning calorimetry (photoDSC) revealed photocuring time scales similar to those achieved in a commercial 3D printing resin. Furthermore, scintillator samples prepared cationically performed well compared to samples of equivalent compositions prepared by a lengthy thermally initiated radical polymerization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Warpage-Resistant, Under-Extrusion-Free, High-Surface-Quality Additive Manufacturing Process for Polyethylene-Based Composite Radiation Shielding Material

Polyethylene (PE) is one of the best shielding materials for primary space radiation due to its high hydrogen content. For effective secondary neutron shielding, boron-rich fillers are incorporated to enhance performance. The semicrystalline nature and high thermal expansion coefficient of PE impede its adoption for in situ additive manufacture in space via the fused deposition modeling (FDM) 3D printing. Here, we developed an optimized PE blend to mitigate the effects of under-extrusion and warpage. Guided by studies on extrusion and warpage, we developed an optimal set of printing parameters for the proposed PE blend. The optimum PE blend─both in its pure form and when doped with fillers─has been tested on different FDM printers. The printed structures exhibit high and uniform density, smooth surfaces, no warpage, and competitive mechanical properties. The FDM-printed plates demonstrate efficient shielding from thermal neutrons, predicted via modeling and confirmed experimentally using extended Q-range small-angle neutron scattering.

additive manufacturing↗
DOE OSTI2025

Adhesion of Self-Complementary, Sinusoidal Surfaces Fabricated Using Two-Photon Polymerization

Microscale, pick-and-place assembly is a non-lithographic assembly method poised to impact diverse fields including flexible electronics, microfluidics and robotics. However, a major technological challenge is the need to deterministically control adhesion between parts. Here, switchable adhesion involving 3D-printed, self-complementary surfaces is demonstrated. Mechanical properties of metasurfaces pressed against flat, rigid substrates are modeled using finite element methods. A series of flat slabs and metastructured slabs with 2D sinusoidal surfaces are printed using two-photon polymerization (2PP) of a shape-memory resin. The surface frequency of featured slabs was varied between $3.\bar3$ mm −1 and $26.\bar6$ mm −1 with similar amplitudes. Adhesion between printed metasurfaces and glass and between printed, self-complementary metasurfaces is studied above and below the cured resin’s glass transition temperature (∼45 °C). Simple heating of adhering surfaces to above 60 °C lowers adhesion, and compression of surfaces while above the glass transition temperature followed by cooling to room temperature elevates adhesion. The nominal adhesive strength between printed, self-complementary surfaces, as determined by the maximum observable pull-off stress, exceeds 3 MPa. Further tailoring complementary surfaces for adhesion control may facilitate microscale disassembly for recovery of components or precious metals.

amorphous materials↗
DOE OSTI2024

Interpenetrating 3D Electrodes for High-Rate Alkaline Water Splitting

Mass transfer is critical for the reaction kinetics and efficiency of alkaline water splitting (AWS). For AWS to operate at high current densities (hundreds of mA/cm 2 ), the device architecture must ensure a large catalytic surface area, rapid ion diffusion, and minimal solution and charge transfer resistances. Effective electrodes should also facilitate gas bubble detachment and release. 3D-printed electrodes have shown promise, but stacking them increases the ion diffusion length and solution resistance. Here we demonstrate a new device architecture with interpenetrating gyroid electrodes, providing a large ion-accessible surface area and gas diffusion channels. This design significantly reduces the interelectrode distance, lowering ion diffusion length and solution resistance. Simulations show faster ion diffusion and higher current density in the interpenetrating configuration compared with separate electrodes. This improved performance, especially at low temperatures and high current densities, highlights a promising strategy for enhancing AWS and other electrochemical systems limited by slow ion diffusion.

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

Prospects of Nanoscience with Nanocrystals: 2025 Edition

Abstract Nanocrystals (NCs) of various compositions have made important contributions to science and technology, with their impact recognized by the 2023 Nobel Prize in Chemistry for the discovery and synthesis of semiconductor quantum dots (QDs). Over four decades of research into NCs has led to numerous advancements in diverse fields, such as optoelectronics, catalysis, energy, medicine, and recently, quantum information and computing. The last 10 years since the predecessor perspective “Prospect of Nanoscience with Nanocrystals” was published in ACS Nano have seen NC research continuously evolve, yielding critical advances in fundamental understanding and practical applications. Mechanistic insights into NC formation have translated into precision control over NC size, shape, and composition. Emerging synthesis techniques have broadened the landscape of compounds obtainable in colloidal NC form. Sophistication in surface chemistry, jointly bolstered by theoretical models and experimental findings, has facilitated refined control over NC properties and represents a trusted gateway to enhanced NC stability and processability. The assembly of NCs into superlattices, along with two-dimensional (2D) photolithography and three-dimensional (3D) printing, has expanded their utility in creating materials with tailored properties. Applications of NCs are also flourishing, consolidating progress in fields targeted early on, such as optoelectronics and catalysis, and extending into areas ranging from quantum technology to phase-change memories. In this perspective, we review the extensive progress in research on NCs over the past decade and highlight key areas where future research may bring further breakthroughs.

Chemistry↗
DOE OSTI2020

High-Strength Polylactic Acid (PLA) Biocomposites Reinforced by Epoxy-Modified Pine Fibers

The stiffness and tensile strength of biopolymers (e.g., polylactic acid (PLA)) are less than desirable for load-bearing applications in their neat form. The use of natural fibers as reinforcements for composites (for large-scale three-dimensional (3D) printing) has expanded rapidly, attributable to their low weight, low cost, high stiffness, and renewable nature. Silane and acid/alkali are typically used to modify the surface of natural fibers to improve the fiber/polymer interfacial adhesion. In this study, a simple method of impregnation was developed to modify pine fibers (loblolly, mesh size of 90–180 μm, 30 wt %) with a solvent-borne epoxy to reinforce PLA. As a benefit of the epoxy modification (0.5–10 wt %), the tensile strengths and Young’s moduli of the epoxy-modified pine/PLA composites increased by up to 20 and 82%, respectively, as compared to that of neat PLA. Furthermore, the epoxy-modified pine/PLA composites, with an optimum epoxy modification (1.0 wt %), had fewer voids on the fracture surface as compared with pine/PLA composites without the modification of pine fibers via epoxy. Finally, results confirmed that epoxy partially penetrated the pore/hollow inner structures of pine fibers and improved the fiber/matrix interfacial adhesion. Epoxy modification is found to be a simple and effective technique to improve the properties of biocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Thermodynamic Control of Interface Directs MnO 2 Nucleation Chemistry for Dense and Conformal Electrodeposition

Manganese dioxide (MnO 2 ) is widely recognized as a promising material for high-energy-density energy storage systems due to its broad applicability and facile electrodeposition. However, achieving uniform, thin, and high-mass-loading MnO 2 coatings on high-surface-area electrodes remains a significant challenge. Conventional electrodeposition methods typically yield nonuniform, thick layers with poor conductivity and limited material utilization, restricting their practical use. Here, we uncover a thermodynamically engineered vanadyl/pervanadyl (VO 2+ /VO 2 + ) interface that fundamentally reshapes MnO 2 electrodeposition chemistry, enabling highly uniform and dense coatings. Here, combining in situ AFM measurement, Classical Nucleation Theory, and Johnson–Mehl–Avrami–Kolmogorov modeling, we show that this interface reduces early-stage detectable MnO 2 island size by 35-fold and shifts the MnO 2 growth from diffusion-limited to reaction-limited progressive nucleation. This thermodynamically controlled interface yields highly dense and conformal MnO 2 films with record-high mass loading of 241 mg cm –2 (1607 mg cm –3 ) on 3D-printed graphene aerogels, without compromising porosity or inducing thickness gradient. As a prototype demonstration, the resulting MnO 2 electrodes deliver record-setting volumetric performance in both capacitors (106 F cm –3 ) and Zn//MnO 2 pouch cells (162 mAh cm –3 ). Beyond energy storage, our findings demonstrate the significance of thermodynamic interface control in MnO 2 nucleation chemistry for achieving dense and uniform coatings on various substrates, with implications for electrocatalysis, semiconductor processing, and advanced materials manufacturing.

Batteries↗
DOE OSTI2025

Stemflow Hydrodynamics

Stemflow hydrodynamics is the study of water movement along the exterior surface area of plants. Its primary goal is to describe water velocity and water depth along the stem surface area. Its significance in enriching the rhizosphere with water and nutrients is not in dispute. Yet, the hydrodynamics of stemflow have been entirely overlooked. This review seeks to fill this knowledge gap by drawing from thin film theories to seek outcomes at the tree scale. The depth‐averaged conservation equations of water and solute mass are derived at a point. These equations are then supplemented with the conservation of momentum that is required to describe water velocities or relations between water velocities and water depth. Relevant forces pertinent to momentum conservation are covered and include body forces (gravitational effects), surface forces (wall friction), line forces (surface tension), and inertial effects. The inclusion of surface tension opens new vistas into the richness and complexity of stemflow hydrodynamics. Flow instabilities such as fingering, pinching of water columns into droplets, accumulation of water within fissures due to surface tension and their sudden release are prime examples that link observed spatial patterns of stemflow fronts and morphological characteristics of the bark. Aggregating these effects at the tree‐ and storm‐ scales are featured using published experiments. The review discusses outstanding challenges pertaining to stemflow hydrodynamics, the use of dynamic similarity and 3D printing to enable the interplay between field studies and controlled laboratory experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Snapshot multispectral imaging using a diffractive optical network

Abstract Multispectral imaging has been used for numerous applications in e.g., environmental monitoring, aerospace, defense, and biomedicine. Here, we present a diffractive optical network-based multispectral imaging system trained using deep learning to create a virtual spectral filter array at the output image field-of-view. This diffractive multispectral imager performs spatially-coherent imaging over a large spectrum, and at the same time, routes a pre-determined set of spectral channels onto an array of pixels at the output plane, converting a monochrome focal-plane array or image sensor into a multispectral imaging device without any spectral filters or image recovery algorithms. Furthermore, the spectral responsivity of this diffractive multispectral imager is not sensitive to input polarization states. Through numerical simulations, we present different diffractive network designs that achieve snapshot multispectral imaging with 4, 9 and 16 unique spectral bands within the visible spectrum, based on passive spatially-structured diffractive surfaces, with a compact design that axially spans ~72 λ m , where λ m is the mean wavelength of the spectral band of interest. Moreover, we experimentally demonstrate a diffractive multispectral imager based on a 3D-printed diffractive network that creates at its output image plane a spatially repeating virtual spectral filter array with 2 × 2 = 4 unique bands at terahertz spectrum. Due to their compact form factor and computation-free, power-efficient and polarization-insensitive forward operation, diffractive multispectral imagers can be transformative for various imaging and sensing applications and be used at different parts of the electromagnetic spectrum where high-density and wide-area multispectral pixel arrays are not widely available.

36 MATERIALS SCIENCE↗
DOE OSTI2024

All-optical image denoising using a diffractive visual processor

Abstract Image denoising, one of the essential inverse problems, targets to remove noise/artifacts from input images. In general, digital image denoising algorithms, executed on computers, present latency due to several iterations implemented in, e.g., graphics processing units (GPUs). While deep learning-enabled methods can operate non-iteratively, they also introduce latency and impose a significant computational burden, leading to increased power consumption. Here, we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images – implemented at the speed of light propagation within a thin diffractive visual processor that axially spans <250 × λ, where λ is the wavelength of light. This all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features, causing them to miss the output image Field-of-View (FoV) while retaining the object features of interest. Our results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of ~30–40%. We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz spectrum. Owing to their speed, power-efficiency, and minimal computational overhead, all-optical diffractive denoisers can be transformative for various image display and projection systems, including, e.g., holographic displays.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rapid sensing of hidden objects and defects using a single-pixel diffractive terahertz sensor

Abstract Terahertz waves offer advantages for nondestructive detection of hidden objects/defects in materials, as they can penetrate most optically-opaque materials. However, existing terahertz inspection systems face throughput and accuracy restrictions due to their limited imaging speed and resolution. Furthermore, machine-vision-based systems using large-pixel-count imaging encounter bottlenecks due to their data storage, transmission and processing requirements. Here, we report a diffractive sensor that rapidly detects hidden defects/objects within a 3D sample using a single-pixel terahertz detector, eliminating sample scanning or image formation/processing. Leveraging deep-learning-optimized diffractive layers, this diffractive sensor can all-optically probe the 3D structural information of samples by outputting a spectrum, directly indicating the presence/absence of hidden structures or defects. We experimentally validated this framework using a single-pixel terahertz time-domain spectroscopy set-up and 3D-printed diffractive layers, successfully detecting unknown hidden defects inside silicon samples. This technique is valuable for applications including security screening, biomedical sensing and industrial quality control.

Li, Jingxi (ORCID:0000000165958680)↗
DOE OSTI2023

Learning diffractive optical communication around arbitrary opaque occlusions

Abstract Free-space optical communication becomes challenging when an occlusion blocks the light path. Here, we demonstrate a direct communication scheme, passing optical information around a fully opaque, arbitrarily shaped occlusion that partially or entirely occludes the transmitter’s field-of-view. In this scheme, an electronic neural network encoder and a passive, all-optical diffractive network-based decoder are jointly trained using deep learning to transfer the optical information of interest around the opaque occlusion of an arbitrary shape. Following its training, the encoder-decoder pair can communicate any arbitrary optical information around opaque occlusions, where the information decoding occurs at the speed of light propagation through passive light-matter interactions, with resilience against various unknown changes in the occlusion shape and size. We also validate this framework experimentally in the terahertz spectrum using a 3D-printed diffractive decoder. Scalable for operation in any wavelength regime, this scheme could be particularly useful in emerging high data-rate free-space communication systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cellular fluidics

The natural world provides many examples of multiphase transport and reaction processes that have been optimized by evolution. These phenomena take place at multiple length and time scales and typically include gas–liquid–solid interfaces and capillary phenomena in porous media. Many biological and living systems have evolved to optimize fluidic transport. However, living things are exceptionally complex and very difficult to replicate, and human-made microfluidic devices (which are typically planar and enclosed) are highly limited for multiphase process engineering. In this paper, we introduce the concept of cellular fluidics: a platform of unit-cell-based, three-dimensional structures—enabled by emerging 3D printing methods—for the deterministic control of multiphase flow, transport and reaction processes. We show that flow in these structures can be ‘programmed’ through architected design of cell type, size and relative density. We demonstrate gas–liquid transport processes such as transpiration and absorption, using evaporative cooling and CO 2 capture as examples. We design and demonstrate preferential liquid and gas transport pathways in three-dimensional cellular fluidic devices with capillary-driven and actively pumped liquid flow, and present examples of selective metallization of pre-programmed patterns. Our results show that the design and fabrication of architected cellular materials, coupled with analytical and numerical predictions of steady-state and dynamic behaviour of multiphase interfaces, provide deterministic control of fluidic transport in three dimensions. Cellular fluidics may transform the design space for spatial and temporal control of multiphase transport and reaction processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗