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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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Adding multiple electrons to helicenes: how they respond?
An overview of structural responses of helicenes with increasing dimensions and complexity to stepwise electron addition reveals charge- and topology-dependent outcomes ranging from reversible to irreversible core transformations and site-specific reactivity.
Adsorptive behavior of poly (vinylidene fluoride) membranes for the recovery of lignin-derived hydrophobic deep eutectic solvents
Abstract Recently, membrane technology has gained significant traction as an energy-efficient alternative to traditional thermal processes for solvent recovery. Deep eutectic solvents (DESs) have emerged as sustainable alternatives to conventional organic solvents, yet a systematic methodology for selecting compatible membrane materials for their recovery remains underdeveloped. This study established a predictive framework for membrane material selection in hydrophobic DES applications using Hansen Solubility Parameters (HSP) with inverted criteria targeting materials with relative energy difference (RED) values greater than 1.0. Flat sheet membranes were fabricated via the non-solvent induced phase separation (NIPS) technique. Four NIPS fabricated polymer membranes were evaluated: polysulfone, cellulose acetate, polyvinylidene fluoride (PVDF) fabricated with polyethylene glycol (PEG) as a pore-forming agent, and polybenzimidazole (PBI). The HSP approach successfully predicted membrane-solvent compatibility, with polysulfone (RED = 0.6) and cellulose acetate (RED = 0.9) dissolving completely within 24 h, while PVDF (RED = 1.9) and PBI (RED = 1.1) maintained structural integrity throughout a 7-day exposure period. Furthermore, PVDF demonstrated superior performance with minimal weight gain (3.0%), hydrophobic surface characteristics (122° water contact angle), and enhanced mechanical properties following DES exposure. Comprehensive chemical and morphological characterization confirmed PVDF’s chemical stability and revealed a surface-selective interaction mechanism involving simultaneous PEG (pore-forming agent) extraction and DES component adsorption. Adsorption kinetics followed pseudo-first-order behavior with reversible characteristics, best described by the Temkin isotherm model (R² = 0.9987). PVDF membranes-maintained separation functionality with average lignin rejection (75.2 ± 7.69%) and demonstrated filtration permeability of 2.0 ± 0.34 LMH/bar. This methodology provides a rational approach for membrane selection in emerging solvent systems, contributing to the advancement of sustainable separation technologies for DES-based biomass processing applications.
PROBABALISTIC RISK ANALYSIS AND THERMAL MARGIN PROCESS FOR AN INFLATABLE AEROSHELL
Atmospheric entry vehicle thermal protection systems (TPS) are margined due to the uncertainties that exist in entry aeroheating environments and the thermal response of the materials and structures. Traditional approaches typically over-margin TPS and offer very little insight into the risk of over-temperature during flight. A probabilistic margin process can be used to apply thermal margin to an aeroshell based on a rigorously calculated risk of failure. This probabilistic margin process allows engineers to make informed aeroshell design, entry-trajectory modifications, and risk trades while preventing excessive margin from being applied. This methodology can also be applied to other TPS applications, hot structures, and other engineering disciplines.
Tough polycyclooctene nanoporous membranes from etchable block copolymers
Polycyclooctene-polylactide triblock copolymer synthesis and subsequent processingviasolvent casting, polylactide etching, and plasma etching to yield tunable and tough nanoporous membranes with high surface porosities and hydrophilic properties.
Surface phase diagrams from nested sampling
From nested sampling, we compute the partition function and, from that, the phase diagram of gas adsorbates, including their anharmonic and configurational degrees of freedom, on flat and stepped surfaces of the Lennard-Jones solid.
Heavy Element Spectroscopy in the Gas Phase
Actinides are inherently unstable and undergo nuclear decay processes with a concurrent release of energy. Consequently, they are used for nuclear power generation, nuclear weapons, and nuclear medicine. However, the radioactive decay processes also pose significant technological problems for the safe treatment and storage of spent nuclear materials. Cost-effective extraction of the actinides is the key first step in the remediation of nuclear waste, but the appropriate chemical means have yet to be determined. Our present understanding of the chemistry of actinides is limited, with the role of the 5f electrons posing a set of particularly challenging questions. The work reported here is focused on the use of electronic spectroscopy to probe the bonding of small molecules in the gas phase that contains thorium or uranium. Analyses of these data, carried out within the framework of ligand field theory, reveal clear evidence that the 5f electrons are spectators that retain their atomic metal ion character.
Flow synthesis of iron oxide nanoparticles: using multiple precursor additions to improve size control
Controlling the size of iron oxide nanoparticles while maintaining uniformity in flow-based synthesis systems has been a great challenge in nanoparticle synthesis. Using an extended LaMer mechanism, we improve both the size and shape uniformity as compared to a conventional flow synthesis. The key to this approach is the injection of additional Fe precursor during the flow reaction, providing extra precursor during the growth process leading to a size focusing step. This approach has also allowed for the systematic variation of the nanoparticle size produced in the flow reaction. This work represent a new synthetic concept for improving the size uniformity of iron oxide nanoparticles in flow-based synthesis and has potential for application across a wide range of nanoparticle systems.
Effect of depth of discharge (DOD) on cycling in situ formed Li anodes
This study demonstrates that the stability of cyclingin situLi anodes depends on their depth of discharge (DOD). High DOD cycling results in unstable performance due to the accumulation of interfacial degradation at Li/LLZO interfaces.
Enhancing lithium metal batteries with a nano-silicon nitride-based solid electrolyte interface layer
Artificial nano Si 3 N 4 derived solid electrolyte interphase enables dendrite-free lithium cycling, effectively suppressing dendrite growth and delivering stable, long-term Li metal anode performance.
Corrosion kinetics of pure metals (Fe, Cr, Ni) and alloys (A709, SS316) in thermal and chemical purified molten chloride salt
This paper applied electrochemical methods to explore the corrosion mechanisms of metals and steels in purified molten chloride salt, especially under conditions dominated by cathodic diffusion limitations.
Identifying structure-function relationships to modulate crossover in nonaqueous redox flow batteries
QSPR analyses can be used to identify useful descriptors leading to statistical models for membrane crossover. This data-driven approach can be used to evaluate ROMs for asymmetric non-aqueous redox flow batteries.
Water-enhanced CO 2 capture with molecular salt sodium guanidinate
Solid-state amine absorbent materials, including those containing guanidine derivatives, have received tremendous attention as the world combats the challenges of climate change.
Microscopy modality transfer of steel microstructures: Inferring scanning electron micrographs from optical microscopy using generative AI
Scanning electron microscopy (SEM) is resource intensive, which limits its throughput in some applications. As an alternative, we propose applying computer vision and machine learning to generate high-quality synthetic SEM micrographs from micrographs obtained using light optical microscopy (LOM). Working with a correlated LOM/SEM dataset of dual-phase steel images, we test generative models of various architectures, including encoder-decoder networks, generative adversarial networks (GANs), and diffusion-based models. We find that the diffusion models significantly outperform other methods on both qualitative and quantitative assessments, while preserving key metallurgical meaning. This work establishes diffusion as the state-of-the-art for microscopy modality transfer and demonstrates the potential of AI-powered microscopy to enhance LOM with micron scale structural recreation.