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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Simultaneous suppression of lignin, tricin and wall‐bound phenolic biosynthesis via the expression of monolignol 4‐ O ‐methyltransferases in rice

Summary Grass lignocelluloses feature complex compositions and structures. In addition to the presence of conventional lignin units from monolignols, acylated monolignols and flavonoid tricin also incorporate into lignin polymer; moreover, hydroxycinnamates, particularly ferulate, cross‐link arabinoxylan chains with each other and/or with lignin polymers. These structural complexities make grass lignocellulosics difficult to optimize for effective agro‐industrial applications. In the present study, we assess the applications of two engineered monolignol 4‐ O ‐methyltransferases (MOMTs) in modifying rice lignocellulosic properties. Two MOMTs confer regiospecific para ‐methylation of monolignols but with different catalytic preferences. The expression of MOMTs in rice resulted in differential but drastic suppression of lignin deposition, showing more than 50% decrease in guaiacyl lignin and up to an 90% reduction in syringyl lignin in transgenic lines. Moreover, the levels of arabinoxylan‐bound ferulate were reduced by up to 50%, and the levels of tricin in lignin fraction were also substantially reduced. Concomitantly, up to 11 μmol/g of the methanol‐extractable 4‐ O ‐methylated ferulic acid and 5–7 μmol/g 4‐ O ‐methylated sinapic acid were accumulated in MOMT transgenic lines. Both MOMTs in vitro displayed discernible substrate promiscuity towards a range of phenolics in addition to the dominant substrate monolignols, which partially explains their broad effects on grass phenolic biosynthesis. The cell wall structural and compositional changes resulted in up to 30% increase in saccharification yield of the de‐starched rice straw biomass after diluted acid‐pretreatment. These results demonstrate an effective strategy to tailor complex grass cell walls to generate improved cellulosic feedstocks for the fermentable sugar‐based production of biofuel and bio‐chemicals.

4-O-methylated↗
DOE OSTI2023

Data for Simultaneous Suppression of Lignin, Tricin and Wall-Bound Phenolic Biosynthesis via the Expression of Monolignol 4- O -Methyltransferases in Rice

Grass lignocelluloses feature complex compositions and structures. In addition to the presence of conventional lignin units from monolignols, acylated monolignols and flavonoid tricin also incorporate into lignin polymer; moreover, hydroxycinnamates, particularly ferulate, cross-link arabinoxylan chains with each other and/or with lignin polymers. These structural complexities make grass lignocellulosics difficult to optimize for effective agro-industrial applications. In the present study, we assess the applications of two engineered monolignol 4- O -methyltransferases (MOMTs) in modifying rice lignocellulosic properties. Two MOMTs confer regiospecific para-methylation of monolignols but with different catalytic preferences. The expression of MOMTs in rice resulted in differential but drastic suppression of lignin deposition, showing more than 50% decrease in guaiacyl lignin and up to an 90% reduction in syringyl lignin in transgenic lines. Moreover, the levels of arabinoxylan-bound ferulate were reduced by up to 50%, and the levels of tricin in lignin fraction were also substantially reduced. Concomitantly, up to 11 μmol/g of the methanol-extractable 4- O -methylated ferulic acid and 5–7 μmol/g 4- O -methylated sinapic acid were accumulated in MOMT transgenic lines. Both MOMTs in vitro displayed discernible substrate promiscuity towards a range of phenolics in addition to the dominant substrate monolignols, which partially explains their broad effects on grass phenolic biosynthesis. The cell wall structural and compositional changes resulted in up to 30% increase in saccharification yield of the de-starched rice straw biomass after diluted acid-pretreatment. These results demonstrate an effective strategy to tailor complex grass cell walls to generate improved cellulosic feedstocks for the fermentable sugar-based production of biofuel and bio-chemicals.

Biomass Analytics↗
DOE OSTI2022

What is in a name: Defining “high entropy” oxides

High entropy oxides are emerging as an exciting new avenue to design highly tailored functional behaviors that have no traditional counterparts. Study and application of these materials are bringing together scientists and engineers from physics, chemistry, and materials science. The diversity of each of these disciplines comes with perspectives and jargon that may be confusing to those outside of the individual fields, which can result in miscommunication of important aspects of research. In this Perspective, we provide examples of research and characterization taken from these different fields to provide a framework for classifying the differences between compositionally complex oxides, high entropy oxides, and entropy stabilized oxides, which is intended to bring a common language to this emerging area. We highlight the critical importance of understanding a material’s crystallinity, composition, and mixing length scales in determining its true definition.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Machine Learning Approach for the Prediction of Formability and Thermodynamic Stability of Single and Double Perovskite Oxides

Perovskite oxides continue to attract huge interest due to their fascinating and wide-ranging properties for diverse applications. The tunability of these properties may be further enhanced by increasing their compositional complexity via double perovskite-ordered configurations containing multiple cations. In this work, we focus on an exhaustive chemical space of single and double oxide perovskites and optimally explore this space to identify novel compositions that are likely to form stable compounds. Critically, we examine the relationship between formability, the practical ability to synthesize a compound, and stability, the thermodynamic preference to form the structure. Our formability and stability training data sets were enumerated from the available experimental literature and in-house density functional theory computations and contained 1505 and 3469 examples, respectively, representing state-of-the-art in the current open literature in perovskite and double perovskite compounds. Subsequently, cross-validated and highly accurate machine learning classification models are built using these training data sets and employed to screen for novel stable oxide perovskites. The study identifies (1) atomic features relevant to prediction of formability and stability in perovskite and double perovskite compounds, (2) the importance of including energy contributions due to local structural relaxations going beyond the high symmetry perovskite phase, and (3) 437,828 double perovskite compounds that are likely to be stable and 891,188 compounds that are likely to be formable. From the intersection of this large chemical space of formable and stable oxide perovskites, 414 compositions are identified as the most promising candidates for future experimental synthesis of novel oxide perovskites. The developed models may be generalized and have implications beyond perovskite discovery if applied to other families of compounds.

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

A First-Principles Approach to Modeling Surface Site Stabilities on Multimetallic Catalysts

The study of multimetallic alloys and the multitude of possible surface compositions have sparked a tremendous interest in engineering low-cost materials with high activity and selectivity in heterogeneous catalysis. Multimetallic systems provide complementary functionalities and an unprecedented tunability when designing catalyst formulations. However, due to their immense structural and compositional complexity, the investigation and identification of an optimal catalyst is a tedious and time-consuming process, both experimentally and theoretically. Therefore, theoretical design principles are highly desirable to accelerate the screening of catalyst structures across the vast compositional space. In this paper, we introduce a simple and general model for predicting the site stability of multimetallic surfaces and nanoparticles, which is based on physical principles. The model requires only a small set of density functional theory (DFT) calculations of metal atom binding energies on monometallic and dilute alloy surface slabs to optimize the parameters in the simple model. The resulting model allows for the quantification of the stability of any particular atom site in any conceivable chemical environment across a wide range of morphologies, sizes, and arrangements by interpolating the derived parameters from a monometallic system to a completely diluted alloyed system. Herein, we demonstrate the robustness of the model across an extensive data set of transition metal alloy surfaces and 147-atoms cuboctahedral nanoparticles (NPs) composed of IrRhRu and PtPdRu. In conclusion, our approach yields mean absolute errors of ≈0.15 (IrRhRu), 0.20 (PtPdRu), 0.19 (IrRhRu NP), and 0.26 (PtPdRu NP) eV relative to site binding energies calculated using DFT.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Machine learning-enabled prediction of chemical durability of A 2 B 2 O 7 pyrochlore and fluorite

Pyrochlore-structure type and its derivative in a general formula A 2 B 2 O 7 (A = rare earth elements and actinides; B = Ti, Sn, Zr, Hf, Pb, Si, etc.) display excellent structural flexibility and rich crystal chemistry as promising nuclear waste form materials capable of immobilizing actinides and fission products. It is essential to understand these materials’ chemical durability and element release of radionuclides in order to evaluate their performance in near-field environment. However, it is a formidable grand technological challenge to experimentally perform durability testing across hundreds of thousands of possibilities resulting from their extreme compositional complexities due to cation substitutions at both A and B-sites. In this work, we demonstrate a machine learning approach to determine the key materials parameters and structural characteristics governing the leaching behaviors from a small set of selected compositions as model systems, enabling a science-based prediction of their chemical durability that can be extended to a wide range of chemical compositions. The combination of four key structural characteristics and materials parameters, including ionic radius size difference , ionic potential difference , electronegativity difference , and lattice parameter , creates features an optimized prediction of the chemical durability. Two machine learning models, linear regression and Kernel ridge regression models, are trained on the randomly-split training dataset derived from the experimentally-determined elemental release rates, and subsequently tested on the testing dataset. The predicted leaching rates from both machine learning models show an excellent agreement with the experimental data, demonstrating the feasibility of rapidly evaluating the material properties of new compositions. These results highlight the immense potential of synergizing informatics through machine learning-based models and well-controlled experiments of selected model systems to accelerate materials design and discovery with optimized compositions and performance of promising materials for effective nuclear waste management.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Deformation Mechanism Transition in Additively Manufactured Compositionally Graded Fe-Base Alloys

Microstructure-dependent deformation and fracture behavior was investigated for an additively manufactured compositionally graded alloy (CGA) printed using the laser-directed energy deposition (L-DED) method to explore an alternative approach for dissimilar metal joints in nuclear energy systems. The electron backscatter diffraction (EBSD) maps from scanning electron microscopy (SEM) display a clear microstructural transition with decreasing austenite-forming elements (Ni and Mn), from an austenite (γ) dominant structure, to a complex composite structure containing ferrite (α), martensite (α') and retained austenite, and then to a fully ferritic structure. EBSD data were recorded in situ during tensile testing in SEM, and the evolution of the deformation mechanism and microstructure was characterized using Kikuchi diffraction pattern analysis. Complementary analysis for high-resolution features was also performed using scanning transmission electron microscopy (STEM). The Ni/Mn-rich austenite-dominant microstructures showed a complex deformation mechanism of two-step martensitic transformation (γ→ε→α'), whereas the minor austenite phase retained in the ferrite and/or martensite matrix showed a single transformation route (γ→α'). Ordinary dislocation glide and twinning via partial dislocation glide were observed in the austenite deformation. Meanwhile, the ferrite and martensite grains deformed mainly by ordinary dislocation slips and grain rotation. Furthermore, static tensile fracture was also highly dependent on local composition and phase constituents.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Atomic Force Microscopy to Characterize Antimicrobial Peptide-Induced Defects in Model Supported Lipid Bilayers

Antimicrobial peptides (AMPs) interact with bacterial cell membranes through a variety of mechanisms, causing changes extending from nanopore formation to microscale membrane lysis, eventually leading to cell death. Several AMPs also disrupt mammalian cell membranes, despite their significantly different lipid composition and such collateral hemolytic damage hinders the potential therapeutic applicability of the AMP as an anti-microbial. Elucidating the mechanisms underlying the AMP–membrane interactions is challenging due to the variations in the chemical and structural features of the AMPs, the complex compositional variations of cell membranes and the inadequacy of any single experimental technique to comprehensively probe them. (1) Background: Atomic Force Microscopy (AFM) imaging can be used in combination with other techniques to help understand how AMPs alter the orientation and structural organization of the molecules within cell membranes exposed to AMPs. The structure, size, net charge, hydrophobicity and amphipathicity of the AMPs affect how they interact with cell membranes of differing lipid compositions. (2) Methods: Our study examined two different types of AMPs, a 20-amino acid, neutral, α-helical (amphipathic) peptide, alamethicin, and a 13-amino acid, non-α-helical cationic peptide, indolicidin (which intramolecularly folds, creating a hydrophobic core), for their interactions with supported lipid bilayers (SLBs). Robust SLB model membranes on quartz supports, incorporating predominantly anionic lipids representative of bacterial cells, are currently not available and remain to be developed. Therefore, the SLBs of zwitterionic egg phosphatidylcholine (PC), which represents the composition of a mammalian cell membrane, was utilized as the model membrane. This also allows for a comparison with the results obtained from the Quartz Crystal Microbalance with Dissipation (QCM-D) experiments conducted for these peptides interacting with the same zwitterionic SLBs. Further, in the case of alamethicin, because of its neutrality, the lipid charge may be less relevant for understanding its membrane interactions. (3) Results: Using AFM imaging and roughness analysis, we found that alamethicin produced large, unstable defects in the membrane at 5 µM concentrations, and completely removed the bilayer at 10 µM. Indolicidin produced smaller holes in the bilayer at 5 and 10 µM, although they were able to fill in over time. The root-mean-square (RMS) roughness values for the images showed that the surface roughness caused by visible defects peaked after peptide injection and gradually decreased over time. (4) Conclusions: AFM is useful for helping to uncover the dynamic interactions between different AMPs and cell membranes, which can facilitate the selection and design of more efficient AMPs for use in therapeutics and antimicrobial applications.

Swana, Kathleen W.↗
DOE OSTI2025

Atomic-scale understanding of oxide growth and dissolution kinetics of Ni-Cr alloys

Aqueous corrosion of metals is governed by formation and dissolution of a passivating, multi-component surface oxide. Unfortunately, a detailed atomistic description is challenging due to the compositional complexity and the need to consider multiple kinetic factors simultaneously. To this end, we combine experiments with a first-principles-derived, multiscale computational framework that transcends thermodynamic descriptions to explicitly simulate the kinetic evolution of surface oxides of Ni-Cr alloys as a function of composition, temperature, pH, and applied voltage. In the absence of pitting, we identify three distinct voltage regimes, which are kinetically dominated by oxide growth, dissolution, and competitive dissolution and reprecipitation. Evolving compositional gradients and oxide thickness are revealed, including a transition between a metastable Ni-Cr mixed oxide and a thick, porous Ni-dominated oxide. Beyond elucidating the underlying physics, we highlight the need for competing kinetics in models to properly predict the transition from passivation to corrosion. Our results provide a key step towards co-design of alloy composition alongside environmental conditions for sustainable use across a variety of critical energy and infrastructure applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Lipoprotein Particles in Cerebrospinal Fluid

The brain is the most lipid-rich organ in the body, and the intricate interplay between lipid metabolism and pathologies associated with neurodegenerative disorders is being increasingly recognized. The brain is bathed in cerebrospinal fluid (CSF), which, like plasma, contains lipid-protein complexes called lipoproteins that are responsible for extracellular lipid transport. Multiple CSF lipoprotein populations exist, some of which are produced de novo in the central nervous system and others that appear to be generated from protein constituents that are produced in the periphery. These CSF lipoproteins are thought to play key roles in maintaining lipid homeostasis in the central nervous system, while little else is known due to their limited accessibility and their low abundance in CSF. Recent work has provided new insights into the compositional complexity of CSF lipoprotein families and their metabolism in cerebral circulation. Finally, the purpose of this review is to summarize our current state of knowledge on the composition, origin, and metabolism of CSF lipoproteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Effects of composition and canister centerline cooling on microstructure, phase distribution, and chemical durability of dehalogenated iron phosphate waste forms

This paper discusses the effects of composition and canister centerline cooling (CCC) on the microstructures, phase distribution, and chemical durability of dehalogenated iron phosphate waste forms starting from chloride-based salt simulants including KCl (Simple-1), NdCl3 (Simple-2), SrCl2 (Simple-3), LaCl3 (Simple-4), LiCl (Simple-5), CsCl (Simple-6), as well as a complex simulant containing LiCl, KCl, NaCl, CsI, SrCl2, CeCl3, and NdCl3 called ERV2. The simulants represent salt constituents present in salt wastes from electrorefiners used for electrochemical reprocessing. These salts are reacted with ammonium dihydrogen phosphate (ADP) resulting in a NH4Cl (dechlorination) byproduct that is captured and phosphate product containing oxides of the salt cations. This product is further stabilized using Fe2O3 through vitrification at higher temperatures. The results presented herein describe the properties of CCC-treated materials following dechlorination and vitrification including phase identification and quantification, elemental distributions, and chemical durabilities. The chemical durability in the CCC-cooled samples are lower durability than quenched materials for the ERV2 samples. The phases formed upon CCC cooling are very complex compositionally and microstructurally.

iron phosphate glass, iron phosphate waste forms, ↗
DOE OSTI2025

Challenges and strategies for probing the composite interface of PEM electrolyzers and fuel cells using operando AP-XPS

Left: cross-section schematic of a membrane electrode assembly, the working electrode changing state with applied potential. Center: the operando cell design that enables snapshot data acquisition during trajectory movement. Right: resulting spectra. Understanding the surface chemistry of electrocatalyst systems under operando conditions is central to revealing the electrocatalytic cell's working mechanisms. Determination of these catalytic processes on a molecular scale and the involved components is fundamental to streamlining material design for energy conversion and storage applications. X-ray photoelectron spectroscopy (XPS) is an established technique used to study the chemical and electronic states of materials. While the surface sensitivity of XPS is typically high, use of tender X-ray energies and technical advancements have allowed for the direct probing of solid–vapor and solid–liquid interfaces. However, protocols and documentation of experimental considerations for operando XPS probing of working electrolyzers and fuel cells remain scarce. Herein, we report an approach for the study of working polymer electrolyte membrane (PEM) electrolysis cells using ambient pressure X-ray photoelectron spectroscopy (AP-XPS). This approach directly probes the composite electrode surface on the membrane electrode assembly (MEA) in 100% relative humidity to establish a meaningful liquid layer for electrocatalysis. We carry out a systematic investigation from the cell constituent components to a fully assembled working operando electrolytic system and establish a method for AP-XPS study of the complex composite MEA, providing recommendations for data acquisition and component analysis.

Hamlyn, Rebecca↗
DOE OSTI2026

An Infrared Database of n/k Optical Constants for Calculating Aerosol Spectra for the PICARD Program

The objective of the PICARD Program is to develop fieldable sensing platforms for the rapid chemical identification of aerosol particles in plumes. Standoff detection involves interrogating the aerosol cloud from a distance using optical methods and probing the signal returned from direct backscattering from the aerosol particles or transmitted through the plume after reflection from a retroreflector or surface of opportunity (SOO). The identification of chemical species, however, in aerosols is complicated by their complex compositions and morphologies, chemical interferants, and non-uniform particle sizes. To advance standoff detection of aerosols, modelling the infrared transmittance, reflectance and scattering spectra of aerosolized liquid and solid chemical compounds is required, and then testing that model experimentally via laboratory and field experiments. To perform accurate modeling, the infrared optical constants (n/k), i.e., the complex refractive index, of the compounds of interest are required. Thus, PNNL was tasked to provide the optical constants for a set of analytes relevant to the PICARD program. This report describes the experimental techniques used to derive the optical constants of both liquid and solid compounds using established “gold-standard” protocols, how the experimental data are processed to produce the wavenumber dependent optical constant vectors, and how the data are used in the aerosol absorption spectra modeling.

complex refractive index↗
DOE OSTI2024

Toward Multiscale, Multimaterial 3D Printing

Biological materials and organisms possess the fundamental ability to self-organize, through which different components are assembled from the molecular level up to hierarchical structures with superior mechanical properties and multifunctionalities. These complex composites inspire material scientists to design new engineered materials by integrating multiple ingredients and structures over a wide range. Additive manufacturing, also known as 3D printing, has advantages with respect to fabricating multiscale and multi-material structures. The need for multifunctional materials is driving 3D printing techniques toward arbitrary 3D architectures with the next level of complexity. In this paper, the aim is to highlight key features of those 3D printing techniques that can produce either multiscale or multimaterial structures, including innovations in printing methods, materials processing approaches, and hardware improvements. Several issues and challenges related to current methods are discussed. Ultimately, the authors also provide their perspective on how to realize the combination of multiscale and multimaterial capabilities in 3D printing processes and future directions based on emerging research.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The emergent field of high entropy oxides: Design, prospects, challenges, and opportunities for tailoring material properties

A new class of ceramics, called entropy stabilized oxides, High Entropy Oxides (HEOs), multicomponent oxides, compositionally complex oxides, or polycation oxides, has generated considerable research interest since the first report in 2015. This multicomponent approach has created new opportunities for materials design and discovery. This Perspective will highlight some current research developments and possible applications while also providing an overview of the many successfully synthesized HEO systems to date. The polycation approach to composition development will be discussed along with a few case studies, challenges, and future possibilities afforded by this novel class of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Holistic comparison of environmental barrier coating material candidates through design of a figure of merit

The first figure of merit for environmental barrier coating (EBC) materials was designed through a ranking system for material properties pertaining to established EBC failure modes in service. Seven past, present, and novel EBC candidate materials were used in the figure of merit design: SiO 2 , Ba 0.75 Sr 0.25 Al 2 Si 2 O 8 (BSAS), HfSiO 4 , Yb 2 Si 2 O 7 , Yb 2 SiO 5 , Yb 2 O 3 , and YbPO 4 . Utilizing compiled data from the literature, the presented figure of merit verified Yb 2 Si 2 O 7 as the state-of-the-art candidate with optimal EBC properties and inferred that YbPO 4 should be considered as a potentially viable EBC material candidate. Further, the figure of merit allows for a holistic comparison of EBC candidates and informs experimental and computational search efforts for next-generation complex EBCs. Clear knowledge gaps found through this work include CaO–MgO–Al 2 O 3 –SiO 2 (CMAS)-resistant coatings, EBC lifetimes before delamination, and oxidant diffusion rates in relevant EBC microstructures. It was shown that while some materials show promise for solving a single key failure mode for EBCs (i.e., CMAS reactivity), a community-wide goal should be placed on materials development to achieve acceptable resistance against all major failure modes, which are interconnected. Novel compositionally complex EBC materials, in addition to layered EBC architectures, show promise for the optimization of material properties for long-lifetime EBCs in combustion environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High-Entropy Ceramic Coatings: Transformative New Materials for Environmentally-Compatible Thin-Film Insulators against High-T Molten Salts

An emerging new class of promising materials, High-Entropy Ceramics (HECs) or Compositionally-Complex Ceramics (CCCs), have been successfully fabricated in the last three years. This project evaluates HECs/CCCs in the concentrated solar power (CSP) context. In this project, we have identified a couple of simple, and key descriptors governing thermal conductivity in HECs. Size disorder among the cations was found to have a strong influence on the thermal conductivity across multiple systems and throughout a vast compositional space. Since identifying this, we have optimized previous compositions to achieve low thermal conductivities of $k$~$1-1.4Wm{-1}K{-1}$. We have further reduced our selection of promising compositions based on project guidelines and applied a theory that can potentially predict reactivity with molten salts to identify a small set of HECs that are suitable for further molten salt heat transfer media (HTM) stability testing. Many compositions reveal poor resistance to molten chloride salt after being exposed for 24 h compared to the reference structural alloy, Haynes 230. However, after 100 h, a few HECs/CCCs show strong parabolic rate constant effects and provide greater resistance to chloride salt compared to Haynes 230 alloy, which shows more linear kinetics. Postmortem characterization of the microstructure reveals the parabolic rate constant originates from a dense reaction layer form at the interface. This feature is absent in Haynes 230, which only shows grain boundary infiltration. The HECs/CCCs were also put in contact with the metal alloy under Ar for 800 h at 800°C and show negligible interaction. Lastly, parabolic rate constant HECs/CCCs also have low thermal conductivity $(<2 Wm^{-1} K^{-1})$ at 800°C. These specimens satisfy all project requirements and demonstrate their promising application in next-generation CSP.

14 SOLAR ENERGY↗
DOE OSTI2025

Vitamin E Acetate Causes Softening of Pulmonary Surfactant Membrane Models

The popularity of electronic cigarettes and vaping products has launched the outbreak of a condition affecting the respiratory system of users, known as electronic-cigarette/vaping-associated lung injury (EVALI). The build-up of vitamin E acetate (VEA), a diluent of some illicit vaping oils, in the bronchoalveolar lavage of patients with EVALI provided circumstantial evidence as a target for investigation. In this work, we provide a fundamental characterization of the interaction of VEA with lung cells and pulmonary surfactant (PS) models to explore the mechanisms by which vaping-related lung injuries may be present. We first confirm the localization and uptake of VEA in pulmonary epithelial cells. Further, as PS is vitally responsible for the biophysical functions of the lungs, we explore the effect of added VEA on three increasingly complex models of PS: dipalmitoylphosphatidylcholine (DPPC), a lipid-only synthetic PS, and the biologically derived extract Curosurf. Using high-resolution techniques of small-angle X-ray scattering, small-angle neutron scattering, neutron spin–echo spectroscopy, and neutron reflectometry, we compare the molecular-scale behaviors of these membranes to the bulk viscoelastic properties of surfactant monolayer films as studied by Langmuir monolayer techniques. While VEA does not obviously alter the structure or organization of PS membranes, a consistent softening of membrane systems—regardless of compositional complexity—provides a biophysical explanation for the respiratory distress associated with EVALI and yields a new perspective on the behavior of the PS system.

59 BASIC BIOLOGICAL SCIENCES↗