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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Soft X-ray tomography to map and quantify organelle interactions at the mesoscale

Inter-organelle interactions are a vital part of normal cellular function; however, these have proven difficult to quantify due to the range of scales encountered in cell biology and the throughput limitations of traditional imaging approaches. Here, we demonstrate that soft X-ray tomography (SXT) can be used to rapidly map ultrastructural reorganization and inter-organelle interactions in intact cells. SXT takes advantage of the naturally occurring, differential X-ray absorption of the carbon-rich compounds in each organelle. Specifically, we use SXT to map the spatiotemporal evolution of insulin vesicles and their co-localization and interaction with mitochondria in pancreatic β cells during insulin secretion and in response to different stimuli. We quantify changes in the morphology, biochemical composition, and relative position of mitochondria and insulin vesicles. These findings highlight the importance of a comprehensive and unbiased mapping at the mesoscale to characterize cell reorganization that would be difficult to detect with other existing methodologies.

3D cell mapping↗
DOE OSTI2026

Classifying biophysical subpopulations of insulin secretory granules using quantitative whole-cell structure analysis

Pancreatic beta cells contain insulin secretory granules (ISGs), organelles where proinsulin is converted into insulin. As ISGs mature, they undergo extensive biophysical remodeling, producing a spectrum of subpopulations with heterogeneous molecular and spatial characteristics. However, systematic methods to define ISG subpopulations remain underdeveloped. To address this gap in knowledge, we employed soft X-ray tomography (SXT), which can quantitatively measure the biochemical density of ISGs within whole beta cells. Using unsupervised clustering, we classified subpopulations based on molecular density, size, and spatial positioning. Across different insulin secretory stimuli, we observed shifts toward mature and releasable subtypes, demonstrating that exogenous signals can dynamically remodel ISG subpopulation distributions. We extended this methodology to primary beta cells characterized using volume electron microscopy (vEM). Integrating subpopulations from SXT and vEM uncovered insights inaccessible by a single method in isolation. This strategy establishes a framework for defining therapeutic approaches aimed at enriching physiologically beneficial ISG subpopulations.

dense-core granules↗
DOE OSTI2025

Light-triggered electrochemical biosensor using singlet oxygen for self-powered operation and glucose detection

This study introduces a light-activated sensing strategy that integrates photosensitization with electrochemical detection. The sensor employs Eosin Y, a photosensitizer that generates singlet oxygen ( 1 O 2 ) via type II photosensitization. Immobilized within a thin polymer matrix on a carbon working electrode, Eosin Y produces 1 O 2 , under green light (520 nm) illumination, initiating a redox process that yields a measurable current. To incorporate biosensing capabilities and enable self-powered operation, this 1 O 2 – mediated process was coupled with glucose oxidase (GOx) to construct a fully operational glucose biosensor. The addition of glucose reverses the current flow by causing GOx to compete for electrons, with the resulting current magnitude correlating with glucose concentration providing a sensitive measure of glucose. The biosensor, as proof-of-principle, demonstrated excellent performance over a range of glucose concentrations (0–73 mM), achieving a detection limit (LOD) of 2.8 mM for steady state photocurrent under oxygen-saturated conditions. This platform leverages light and 1 O 2 as stimuli for tunable, on-demand signal control, offering a novel approach for adaptive, real-time biosensing technologies.

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

Dynamic tunability of phase-change material transition temperatures using ions for thermal energy storage

Thermal energy storage (TES) based on phase-change materials (PCMs) has many current and potential applications, such as climate control in buildings, thermal management for batteries and electronics, thermal textiles, and transportation of pharmaceuticals. Despite its promise, the adoption of TES has been limited, in part due to limited tunability of the transition temperature, which hinders TES performance for varying use temperatures. Transition temperature tuning of a material using an external stimulus, such as pressure or an electric field, typically requires very large stimuli. To circumvent this problem, here, we report on the dynamic transition temperature tunability of a PCM using ions. We achieve a transition temperature tunability up to 6°C in polyethylene glycol (PEG) by using the salt lithium oxalatodifluoroborate at a low voltage of 2.5 V, which may enable simpler and safer devices/system designs. We also explain the thermal properties of the salt/PCM solution using the Flory-Huggins theory.

25 ENERGY STORAGE↗
DOE OSTI2021

Combining stretching and gallic acid to decrease inflammation indices and promote extracellular matrix production in osteoarthritic human articular chondrocytes

Osteoarthritis (OA) patients undergo cartilage degradation and experience painful joint swelling. OA symptoms are caused by inflammatory molecules and the upregulation of catabolic genes leading to the breakdown of cartilage extracellular matrix (ECM). Here, we investigate the effects of gallic acid (GA) and mechanical stretching on the expression of anabolic and catabolic genes and restoring ECM production by osteoarthritic human articular chondrocytes (hAChs) cultured in monolayers. hAChs were seeded onto conventional plates or silicone chambers with or without 100 μM GA. A 5% cyclic tensile strain (CTS) was applied to the silicone chambers and the deposition of collagen and glycosaminoglycan, and gene expressions of collagen types II (COL2A1), XI (COL11A2), I (COL1A1), and X (COL10A1), and matrix metalloproteinases (MMP-1 and MMP-13) as inflammation markers, were quantified. CTS and GA acted synergistically to promote the deposition of collagen and glycosaminoglycan in the ECM by 14- and 7-fold, respectively. Furthermore, the synergistic stimuli selectively upregulated the expression of cartilage-specific proteins, COL11A2 by 7-fold, and COL2A1 by 47-fold, and, in contrast, downregulated the expression of MMP-1 by 2.5-fold and MMP-13 by 125-fold. GA supplementation with CTS is a promising approach for restoring osteoarthritic hAChs ECM production ability making them suitable for complex tissue engineering applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Combining Spatial and Temporal Resolution in Cryo-TEM of Device Materials: Preprint

Cryogenic transmission electron microscopy (cryo-TEM) has been instrumental to reducing the effects of electron-beam sample interactions and enabling higher spatial resolution studies of beam sensitive materials. However, the process of thinning and freezing samples for cryo-TEM characterization is often complex and frequently involves removing materials from their environment or stimuli of interest for extended times. This can allow for structural relaxation, diffusion, and other dynamic processes to occur prior to characterization; for energy materials like battery electrodes, this makes it difficult to precisely correlate the imaged structure with native structures that evolve in-situ during device processing, operation, or aging. Here, we present methods to prepare cryo-TEM samples from energy materials during these critical processes in the relevant device lifetimes. This offers insights into improving the temporal resolution of cryo-TEM, while still exploiting its ability to achieve high spatial resolutions in characterizing beam sensitive materials.

BASIC BIOLOGICAL SCIENCES,MATERIALS SCIENCE↗
DOE OSTI2020

Single Entity Electrochemistry in Nanopore Electrode Arrays: Ion Transport Meets Electron Transfer in Confined Geometries

Electrochemical measurements conducted in confined volumes provide a powerful and direct means to address scientific questions at the nexus of nanoscience, biotechnology, and chemical analysis. How are electron transfer and ion transport coupled in confined volumes and how does understanding them require moving beyond macroscopic theories? Also, how do these coupled processes impact electrochemical detection and processing? We address these questions by studying a special type of confined-volume architecture, the nanopore electrode array, or NEA, which is designed to be commensurate in size with physical scaling lengths, such as the Debye length, a concordance that offers performance characteristics not available in larger scale structures. The experiments described here depend critically on carefully constructed nanoscale architectures that can usefully control molecular transport and electrochemical reactivity. We begin by considering the experimental constraints that guide the design and fabrication of zero-dimensional nanopore arrays with multiple embedded electrodes. These zero-dimensional structures are nearly ideal for exploring how permselectivity and unscreened ion migration can be combined to amplify signals and improve selectivity by enabling highly efficient redox cycling. Our studies also highlight the benefits of arrays, in that molecules escaping from a single nanopore are efficiently captured by neighboring pores and returned to the population of active redox species being measured, benefits that arise from coupling ion accumulation and migration. These tools for manipulating redox species are well-positioned to explore single molecule and single particle electron transfer events through spectroelectrochemistry, studies which are enabled by the electrochemical zero-mode waveguide (ZMW), a special hybrid nanophotonic/nanoelectronic architecture in which the lower ring electrode of an NEA nanopore functions both as a working electrode to initiate electron transfer reactions and as the optical cladding layer of a ZMW. Furthermore, while the work described here is largely exploratory and fundamental, we believe that the development of NEAs will enable important applications that emerge directly from the unique coupled transport and electron-transfer capabilities of NEAs, including in situ molecular separation and detection with external stimuli, redox-based electrochemical rectification in individually encapsulated nanopores, and coupled sorters and analyzers for nanoparticles.

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

Enhanced Spatial Mapping of Histone Proteoforms in Human Kidney Through MALDI-MSI by High-Field UHMR-Orbitrap Detection

Core histones including H2A, H2B, H3, and H4 are key modulators of cellular repair, transcription, and replication within eukaryotic cells, playing vital roles within the pathogenesis of disease and cellular responses to environmental stimuli. Traditional mass spectrometry (MS) based bottom-up and top-down proteomics allows for the comprehensive identification of proteins and of post-translational modification (PTM) harboring proteoforms. However, these methodologies have difficulties preserving near cellular spatial distributions because they typically require laser capture microdissection (LCM) and advanced sample preparation techniques. Herein, we coupled matrix-assisted laser desorption/ionization (MALDI) source with a Thermo Scientific Q-Exactive HF Orbitrap MS upgraded with ultra-high mass range (UHMR) boards for the first demonstration of complementary high-resolution accurate mass measurements of proteoforms directly from tissue using this benchtop mass spectrometer. The platform achieved isotopic resolution throughout the detected mass range, providing confident assignments of proteoforms with low ppm mass error and a vastly improved duty cycle over other Fourier transform mass analyzers. Proteoform mapping of core histones was demonstrated on sections of human kidney at near-cellular spatial resolution, with several key distributions of histone and other proteoforms noted within both healthy biopsy and a section from a renal cell carcinoma (RCC) containing nephrectomy. Further, the use of MALDI-MS imaging (MSI) for proteoform mapping demonstrates several steps towards high-throughput accurate identification of proteoforms and provides a new tool for mapping biomolecule distributions throughout tissue sections in extended mass ranges.

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

Three-Dimensional Printable, Extremely Soft, Stretchable, and Reversible Elastomers from Molecular Architecture-Directed Assembly

3D printing elastomers enables the fabrication of many technologically important structures and devices such as tissue scaffolds, sensors, actuators, and soft robots. However, conventional 3D printable elastomers are intrinsically stiff; moreover, the process of printing often requires external mechanical support and/or post-treatment. In this work, we exploit the self-assembly of a responsive linear-bottlebrush-linear triblock copolymer to create stimuli-reversible, extremely soft, and stretchable elastomers and demonstrate their applicability as inks for in situ direct-write printing 3D structures without the aid of external mechanical support or post-treatment. By developing a procedure for controlled synthesis of such architecturally designed block copolymers, we create elastomers with extensibility up to 600% and Young’s moduli down to ~10 2 Pa, 10 6 times softer than plastics and more than 102 times softer than all existing 3D printable elastomers. Moreover, the elastomers are thermostable and remain to be solid up to 180 °C, yet they are 100% solvent-reprocessable. Their extreme softness, stretchability, thermostability, and solvent-reprocessability bode well for future applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bridging the Void: Halogen Bonding and Aromatic Interactions to Program Luminescence and Electronic Properties of π -Conjugated Materials in the Solid State

π-Conjugated materials are promising candidates for emerging organic optoelectronic devices empowered by molecular design. The unsolved challenges of predicting and controlling their packing as solids, central to their properties and performance, currently limits their practical application. As noncovalent interactions drive packing, control over such interactions are critical to bridging from chemical structure to functional properties. In molecular crystals, halogen bonding and interactions of aromatic rings have emerged as versatile tools for noncovalent control with tailored luminescence and electronic properties. Here, we describe how the interplay of these directional and tunable interactions can engineer properties, including stimuli-responsive behavior. Specifically, halogen bonding can provide robust designs for directing 2D molecular assembly, whereas the intentional interactions of aromatic rings can yield metastable, switchable packing modes, as well as programmed stacking between layers of chromophores. Examples, herein, demonstrate clear relationships between assembly by design and resulting solid-state properties, and strategies presented offer guidance for future designs of π-conjugated molecular materials using specific aromatic interactions and halogen bonding.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Study of Void Formation at the Lithium|Solid Electrolyte Interface

There is growing recognition of the critical role of void formation in lithium metal anodes in solid-state batteries and its impact on electrochemical performance. While experimental studies have demonstrated the challenges ensuing from void formation at the lithium metal interface with the solid electrolyte, there is a need to understand and quantify the role of intrinsic transport properties in lithium metal and the impact of external stimuli, such as temperature, pressure, and current density. Here, we develop this understanding by constructing a phase field-based model that captures the evolution of void domains at the lithium-solid electrolyte interface. Growth of the pores is driven by the fast removal of lithium from the interface during stripping at high current densities. Relative magnitudes of the bulk and surface lithium diffusivities, along with the applied current density, dictate the final pore morphology. Increasing the temperature results in faster diffusion, while external applied pressure causes creep flow of lithium, both of which help to mitigate the evolution of voids by quickly transporting metal from the bulk to the interface. Finally, a phase map as a function of temperature and pressure is developed as a guide to determine the regions that can lead to the stable cycling of lithium metal.

25 ENERGY STORAGE↗
DOE OSTI2022

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature’s own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and “smart” architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Furthermore, continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

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

Flow-Assisted Selective Mineral Extraction from Seawater

The sustainable production of critical materials from natural sources requires a paradigm shift away from currently used resource-intensive processes. In this paper, we report a single-step, laminar co-flow method (LCM) that leverages non-equilibrium conditions to selectively extract pure Mg(OH) 2 from natural seawater. Conventional seawater-based Mg extraction involves adding individual or a combination of precipitants to obtain Mg(OH) 2 , but the co-existence of Ca 2+ unavoidably results in CaCO 3 impurities requiring additional purification steps. Here we show that the non-equilibrium conditions in LCM achieved using a microfluidics device and by simply co-injecting a NaOH solution with seawater can result in improved selectivity for Mg(OH) 2 unlike in conventional bulk mixing method. The resulting precipitates are characterized for composition and the process yield and purity are optimized through systematic variations of the reaction time and the concentration of NaOH. This is the first demonstration of LCM for selective separation, and as a one-step process that does not rely on novel sorbents, membranes, or external stimuli, it is easy to scale-up. LCM has the potential to be broadly relevant to selective separations from complex feed streams and diverse chemistries—enabling more sustainable materials extraction and processing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dinickel-Catalyzed N═N Bond Rotation

Azoarenes function as molecular switches that can be triggered by external stimuli, such as heat, light, and electrochemical potential. Here, in this work, we show that a dinickel catalyst can induce cis/trans isomerization in azoarenes through a N═N bond rotation mechanism. Catalytic intermediates containing azoarenes bound in both the cis and trans forms are characterized. Solid-state structures reveal the importance of π-back-bonding interactions from the dinickel active site in lowering the N═N bond order and accelerating bond rotation. The scope of the catalytic isomerization includes high-performance acyclic, cyclic, and polymeric azoarene switches.

adducts↗
DOE OSTI2020

Nature of Hyperfine Interactions in TbPc 2 Single-Molecule Magnets: Multiconfigurational Ab Initio Study

Lanthanide-based single-ion magnetic molecules can have large magnetic hyperfine interactions as well as large magnetic anisotropy. Recent experimental studies reported tunability of these properties by changes of chemical environments or by application of external stimuli for device applications. In order to provide insight onto the origin and mechanism of such tunability, here we investigate the magnetic hyperfine and nuclear quadrupole interactions for a 159 Tb nucleus in TbPc 2 (Pc = phthalocyanine) single-molecule magnets using multiconfigurational ab initio methods including spin–orbit interaction. Since the electronic ground and first-excited (quasi)doublets are well separated in energy, the microscopic Hamiltonian can be mapped onto an effective Hamiltonian with an electronic pseudospin S = 1/2. From the ab initio calculated parameters, we find that the magnetic hyperfine coupling is dominated by the interaction of the Tb nuclear spin with electronic orbital angular momentum. The asymmetric 4f-like electronic charge distribution leads to a strong nuclear quadrupole interaction with significant transverse terms for the molecule with low symmetry. The ab initio calculated electronic–nuclear spectrum including the magnetic hyperfine and quadrupole interactions is in excellent agreement with the experiment. We further find that the transverse quadrupole interactions significantly influence the avoided level crossings in magnetization dynamics and that the molecular distortions affect mostly the Fermi contact terms as well as the transverse quadrupole interactions. Synopsis Hyperfine interactions for 159 Tb nucleus in TbPc 2 single-molecule magnets are investigated from first-principles using multiconfigurational calculations. Strong nuclear quadrupole and magnetic hyperfine coupling are found, with the latter being dominated by the paramagnetic spin-orbital mechanism. Furthermore, we construct an ab initio pseudospin Hamiltonian and obtain the electronic-nuclear spectrum that is in excellent agreement with experiment. The Zeeman diagram is calculated, and the magnetization dynamics is discussed. The effects of molecular distortions are researched.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine Learning Prediction of the Experimental Transition Temperature of Fe(II) Spin-Crossover Complexes

Spin-crossover (SCO) complexes are materials that exhibit changes in the spin state in response to external stimuli, with potential applications in molecular electronics. It is challenging to know a priori how to design ligands to achieve the delicate balance of entropic and enthalpic contributions needed to tailor a transition temperature close to room temperature. Here, we leverage the SCO complexes from the previously curated SCO-95 data set [Vennelakanti et al. J. Chem. Phys. 159, 024120 (2023)] to train three machine learning (ML) models for transition temperature (T 1/2 ) prediction using graph-based revised autocorrelations as features. We perform feature selection using random forest-ranked recursive feature addition (RF-RFA) to identify the features essential to model transferability. Of the ML models considered, the full feature set RF and recursive feature addition RF models perform best, achieving moderate correlation to experimental T 1/2 values. We then compare ML T 1/2 predictions to those from three previously identified best-performing density functional approximations (DFAs) which accurately predict SCO behavior across SCO-95, finding that the ML models predict T 1/2 more accurately than the best-performing DFAs. In addition, we study ML model predictions for a set of 18 SCO complexes for which only estimated T 1/2 values are available. Upon excluding outliers from this set, the RF-RFA RF model shows a strong correlation to estimated T 1/2 values with a Pearson’s r of 0.82. In contrast, DFA-predicted T 1/2 values have large errors and show no correlation to estimated T 1/2 values over the same set of complexes. Overall, our study demonstrates slightly superior performance of ML models in comparison with some of the best-performing DFAs, and we expect ML models to improve further as larger data sets of SCO complexes are curated and become available for model training.

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

Resolving Dynamics in the Ensemble: Finding Paths through Intermediate States and Disordered Protein Structures

Proteins have been found to inhabit a diverse set of three-dimensional structures. The dynamics that govern protein interconversion between structures happen over a wide range of time scales-picoseconds to seconds. Our understanding of protein functions and dynamics is largely reliant upon our ability to elucidate physically populated structures. From an experimental structural characterization perspective, we are often limited to measuring the ensemble-averaged structure both in the steady-state and time-resolved regimes. Generating kinetic models and understanding protein structure–function relationships require atomistic knowledge of the populated states in the ensemble. Here, we present ensemble refinement methodologies that integrate time-resolved experimental signals with molecular dynamics models. We first discuss integration of experimental structural restraints to molecular models in disordered protein systems that adhere to the principle of maximum entropy for creating a complete set of ensemble structures. We then propose strategies to find kinetic pathways between the refined structures, using time-resolved inputs to guide molecular dynamics trajectories and the use of inference to generate tailored stimuli to prepare a desired ensemble of protein states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗