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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Versatile acid solvents for pristine carbon nanotube assembly

Chlorosulfonic acid and oleum are ideal solvents for enabling the transformation of disordered carbon nanotubes (CNTs) into precise and highly functional morphologies. Currently, processing these solvents using extrusion techniques presents complications due to chemical compatibility, which constrain equipment and substrate material options. Here, we present a novel acid solvent system based on methanesulfonic or p-toluenesulfonic acids with low corrosivity, which form true solutions of CNTs at concentrations as high as 10 g/liter (≈0.7 volume %). The versatility of this solvent system is demonstrated by drop-in application to conventional manufacturing processes such as slot die coating, solution spinning continuous fibers, and 3D printing aerogels. Through continuous slot coating, we achieve state-of-the-art optoelectronic performance (83.6 %T and 14 ohm/sq) at industrially relevant production speeds. This work establishes practical and efficient means for scalable processing of CNT into advanced materials with properties suitable for a wide range of applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2018

Freeze Casting of LAGP for 3D Textured Solid-State Structural Electrolytes

In this study, all-solid-state structural lithium-ion batteries, a type of load bearing electrochemical energy storage that provides systems-level weight savings is being pursued for the realization of inherently safe next generation hybrid-electric and all-electric green aerospace propulsion systems. Currently investigated all-solid-state batteries do not meet the requirements for specific power and mechanical stability. To address these issues, freeze casting of lithium aluminum germanium phosphate (LAGP) electrolyte material has been explored for the creation of a textured 3D electrolyte scaffold with large interfacial surface area for high power discharge and hierarchical porosity for accommodation of active material volume changes during electrochemical cycling. We report the effects of freeze casting processing parameters on the microstructural development and mechanical performance of the scaffolds, characterized through scanning electron microscopy and ring-on-ring mechanical testing. Slurry composition and casting parameters such as solids loading, casting speed, tape angle, and temperature gradients have been modified to determine the impact on density, lamellar morphology, and final load-bearing performance.

ceramics↗
DOE OSTI2022

Size-Dependent Adsorption and Adhesion Energetics of Ag Nanoparticles on Graphene Films on Ni(111) by Calorimetry

Interest in the use of carbon supports for late transition metal nanoparticle catalysts has expanded rapidly due to the increasing importance of electrocatalysts for clean energy and environmental technologies and the use and storage of renewable electricity. Compared to oxide supports, almost nothing is known about the effect of metal nanoparticle size on the energies of the metal atoms within carbon-supported nanoparticles, yet these energies are crucial for understanding their surface reactivity and sintering kinetics. Here, the growth morphology and adsorption energetics of vapor-deposited Ag onto clean graphene/Ni(111) surfaces have been studied using a combination of single-crystal adsorption calorimetry (SCAC) and He + low-energy ion scattering (LEIS). The differential heat of Ag adsorption is 207 kJ/mol for making ~30 atom Ag particles on graphene terraces at 100 K and 16 kJ/mol higher for making ~9 atom Ag clusters at defect sites at the same temperature. The heat of adsorption increases rapidly with Ag coverage as 3D Ag nanoparticles nucleate and grow in size, asymptotically reaching within 5 kJ/mol of the bulk Ag sublimation enthalpy (285 kJ/mol) by 2 ML. The heats of adsorption and Ag nanoparticle densities from LEIS (~10 16 /m 2 ) were combined to provide the Ag/graphene adhesion energy (E adh = 1.8 J/m 2 in the large-particle limit) and the Ag chemical potential (μ) versus effective particle diameter (D). The Ag chemical potential was well-fitted by μ(D) = (3γ v /M – E adh )(1 + (1.5 nm)/D)(2V m /D), where γ v /M is the surface energy of bulk Ag and V m is its molar volume. The same equation is known to fit similar data for late transition metals on clean surfaces of metal oxide single crystals. The adhesion energy of Ag measured here on graphene falls within the wide range measured for Ag on those oxide surfaces and is almost as large as on the oxide that binds Ag particles most strongly, namely CeO 2 (111), which is well-known to be very effective at resisting catalyst deactivation by metal sintering. Furthermore, these results imply that carbon supports will be effective at resisting sintering and that Ag particles smaller than 6 nm on graphene will bind small adsorbed reaction intermediates more weakly than supports with weaker adhesion to Ag, like MgO(100).

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

Formation of niobium hydride precipitates in superconducting qubits

We report evidence for the formation of niobium hydride phase within niobium films on silicon substrates in superconducting qubits fabricated at Rigetti Computing. For this study, we combined complementary techniques—including room-temperature and cryogenic atomic force microscopy (AFM), synchrotron x-ray diffraction, and time-of-flight secondary ion mass spectroscopy (ToF-SIMS)—to directly reveal the existence of niobium hydride precipitates on the surface of superconducting qubits. Upon cryogenic cooling, we observed variation in the size and morphology of the hydrides, ranging from small (∼5 nm) irregular shapes to large (∼10–100 nm) domains within the Nb grains, which were fully converted to niobium hydrides. Since niobium hydrides are nonsuperconducting and can easily change in size and location upon different cooldowns to cryogenic temperature, our finding highlights a previously unknown source of decoherence in superconducting qubits. This contributes to quasiparticle losses, offering a potential explanation for changes in qubit performance upon cooldowns. Finally, by leveraging the RF performance of a 3D bulk Nb resonator, we quantify RF dissipation in a superconducting qubit caused by hydrogen concentration variation, and propose a practical engineering pathway to mitigate the formation of Nb hydrides for superconducting qubit applications.

Sung, Zuhawn [Fermi National Accelerator Laborator↗
DOE OSTI2022

Viral Capsid Change upon Encapsulation of Double-Stranded DNA into an Infectious Hypodermal and Hematopoietic Necrosis Virus-like Particle

In this study, we aimed to encapsulate the sizable double-stranded DNA (dsDNA, 3.9 kbp) into a small-sized infectious hypodermal and hematopoietic necrosis virus-like particle (IHHNV-VLP; T = 1) and compared the changes in capsid structure between dsDNA-filled VLP and empty VLP. Based on our encapsulation protocol, IHHNV-VLP was able to load dsDNA at an efficiency of 30–40% (w/w) into its cavity. Structural analysis revealed two subclasses of IHHNV-VLP, so-called empty and dsDNA-filled VLPs. The three-dimensional (3D) structure of the empty VLP produced in E. coli was similar to that of the empty IHHNV-VLP produced in Sf9 insect cells. The size of the dsDNA-filled VLP was slightly bigger (50 Å) than its empty VLP counterpart; however, the capsid structure was drastically altered. The capsid was about 1.5-fold thicker due to the thickening of the capsid interior, presumably from DNA–capsid interaction evident from capsid protrusions or nodules on the interior surface. In addition, the morphological changes of the capsid exterior were particularly observed in the vicinity of the five-fold axes, where the counter-clockwise twisting of the “tripod” structure at the vertex of the five-fold channel was evident, resulting in a widening of the channel’s opening. Whether these capsid changes are similar to virion capsid maturation in the host cells remains to be investigated. Nevertheless, the ability of IHHNV-VLP to encapsulate the sizable dsDNA has opened up the opportunity to package a dsDNA vector that can insert exogenous genes and target susceptible shrimp cells in order to halt viral infection.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Quick and Correlative TOF-SIMS Analysis of Dispersoid Content in Powder Feedstock and Printed Oxide Dispersion Strengthened Alloys

Oxide dispersion strengthening (ODS) of metal alloys, when combined with additive manufacturing (AM), can be used to solve high-temperature material application problems. The performance of ODS materials is dependent on nano-scale oxide being distributed uniformly throughout the metal matrix; a homogenous distribution is critical to the creep and yield strength. Therefore, quantifying and analyzing these oxide nanoparticles is essential for ODS alloy development. Assessing the chemistry and morphology of dispersoids in a material can be conducted using a variety of X-ray and electron-based methods. Time of Flight Secondary Ion Mass Spectrometry (TOF-SIMS), which assesses chemical concentrations from ion masses, provides the necessary spatial resolution and avoids potential spectral overlap of all elements present. In this work, preparing ODS powder feedstock and Laser Powder Bed Fusion AM was conducted with a NiCoCr alloy and yttria dispersoid, mixed with a Resodyn resonance mixer and printed on an EOS M100 3D printer at NASA Glenn. TOF-SIMS was performed on a Physical Electronics NanoTOF TRIFT V TOF-SIMS at Case Western Reserve University. The TOF-SIMS results collected on the feedstock powder samples correspond to the qualitative interpretation of the homogeneity of the oxide coating on the metal powder from SEM images. This provides quantitative support to the qualitative microscopy images collected earlier in the process design phase. The variance in the yttrium distribution on the powder feedstock samples also correlated with the variance of the yttrium distribution detected in the printed samples. This correlation supported the hypothesis that an even coating of yttria on the metal powders contributes to an even distribution of yttria in the printed material.

Laura G. Wilson↗
DOE OSTI2024

Uncovering grain and subgrain microstructure at the scale of additive manufacturing melt tracks with a scalable cellular automaton solidification model

Metal additive manufacturing, characterized by rapid solidification, yields refined grains with a distinctive cellular subgrain microstructure that plays a pivotal role in determining material properties. Due to the significant computational expense demanded to simulate the required physics with submicron spatial resolution, their numerical simulations have been limited to proof-of-concept studies to either 2D or small subregions of a melt pool. In this study, an open-source, scalable, solidification code, muMatScale, based on the cellular automaton method, has been developed to predict the grain and the underlying subgrain microstructure over an entire melt pool. The model incorporates flexible parallelization schemes, utilizing MPI and OpenMP GPU Offloading, in addition to appropriate multi-physics specific to non-equilibrium rapid solidification in AM. The impact of nucleation parameters on grain microstructures was investigated with a focus on grain size variations and morphology transitions. With selected nucleation parameters, the simulation predicted the grain size, subgrain morphology, crystallographic orientation, and microsegregation aligned with experimental measurements. The model demonstrates that epitaxial grain growth is a dominant factor at the melt pool boundary, influencing grain size variation under different grain sizes in the build plate while maintaining consistent primary dendrite arm spacing under identical thermal conditions. Here, the highly efficient numerical model enables large-scale simulations with a spatial resolution of 100 nm or less, unveiling unprecedented insights into thermal and solutal diffusion driven grain growth, and the subgrains with microsegregation within grains in 3D across scales. muMatScale will enable the linking of submicron length-scale microstructure to part-level material behavior by investigating fundamental solidification problems at the intercellular scale in many-track and many-layer builds.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Cast Net Thrown onto an Interface: Wrapping 3D Objects with an Interfacially Jammed Amphiphilic Sheet

Wrapping a 3D object with a 2D sheet is not uncommon, but the wrapping behavior becomes complex and interesting when the sheet is bestowed with strong interfacial activities. Amphiphilic lignin macromolecules, isolated from biomass, form a scalable thin surfactant sheet at an oil/water interface through the interfacial jamming process. The process marks three distinct stages of interfacial behavior: a) diffusive assembly, b) viscous assembly with retarded mobility, and c) flexible yet irreversibly jammed rigid sheets. The surfactant sheet wraps, traps, and promptly stabilizes both oil and water droplets in nonequilibrium morphologies upon environmental stimulus. Finally, beyond preserving exotic morphologies, the highly interfacially active surfactant sheet also participates in morphology evolution by creating a vanishing interfacial tension and driving interfacial instability around the wrapped content, leading to novel morphologies as well as many potential applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics

Abstract Background The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain‐relevant assessments via the analysis of relevant image statistics. Methods As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108 000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10 000 DGM‐generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Results Fifty‐eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top‐ranked submission employed a conditional latent diffusion model, whereas the joint runners‐up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID‐based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. Conclusions This Grand Challenge highlighted the need for domain‐specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.

Radiology, Nuclear Medicine & Medical Imaging↗
DOE OSTI2025

Mineralized sclerites in the gorgonian coral Leptogorgia chilensis as a natural jamming system

The soft corals (Cnidaria, Octocorallia), a diverse group of colonial marine invertebrates, can reversibly tune their body stiffness in response to external stimuli. This capability is attributed to their dynamic skeletal systems, which consist of thousands of mineralized skeletal elements, called sclerites, embedded within a gel-like matrix that swells/deswells and unjams/jams the sclerites, thus modulating skeletal stiffness. While sclerite morphology is widely used for species identification, its role in the mechanical performance of a soft coral’s skeletal system is largely unknown. Here, we investigated structure-jamming relationships in sclerite-based skeletal architectures using the red gorgonian octocoral Leptogorgia chilensis as a model system. The sclerites of L. chilensis exhibit a shaft-like geometry with two axial branches and two sets of triradiate side branches, which are aligned with the crystallographic symmetry of the constituent magnesium-containing calcite. By combining multiscale three-dimensional (3D) structural characterization, parametric geometrical modeling, 3D printing, mechanical testing, and discrete element simulations, we demonstrate how sclerite geometry achieves a balanced jamming performance in terms of stiffness, weight, strength, and fracture resistance in comparison to alternative geometries parametrically modified from the native sclerites (e.g., changes in the length and number of side branches). Here, we also found that these performance metrics are achieved through the effective interlocking among side and axial branches, which is further enhanced by the fractal-like microscopic spikes on the branch tips. The findings in this natural jamming system offer insights for designing synthetic mechanotunable material architectures for a wide range of applications, from soft robotics to mechanical dampeners.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Kinematic Evidence for an Embedded Planet in the IM Lupi Disk

Abstract We test the hypothesis that an embedded giant planet in the IM Lupi protostellar disk can produce velocity kinks seen in CO line observations as well as the spiral arms seen in scattered light and continuum emission. We inject planets into 3D hydrodynamics simulations of IM Lupi, generating synthetic observations using Monte Carlo radiative transfer. We find that an embedded planet of 2–3 M Jup can reproduce non-Keplerian velocity perturbations, or “kinks”, in the 12 CO J = 2–1 channel maps. Such a planet can also explain the spiral arms seen in 1.25 mm dust continuum emission and 1.6 μ m scattered-light images. We show that the wake of the planet can be traced in the observed peak velocity map, which appears to closely follow the morphology expected from our simulations and from analytic models of planet–disk interaction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Multimode Metastructures: Novel Hybrid 3D Lattice Topologies

With the rapid proliferation of additive manufacturing and 3D printing technologies, architected cellular solids including truss-like 3D lattice topologies offer the opportunity to program the effective material response through topological design at the mesoscale. The present report summarizes several of the key findings from a 3-year Laboratory Directed Research and Development Program. The program set out to explore novel lattice topologies that can be designed to control, redirect, or dissipate energy from one or multiple insult environments relevant to Sandia missions, including crush, shock/impact, vibration, thermal, etc. In the first 4 sections, we document four novel lattice topologies stemming from this study: coulombic lattices, multi-morphology lattices, interpenetrating lattices, and pore-modified gyroid cellular solids, each with unique properties that had not been achieved by existing cellular/lattice metamaterials. The fifth section explores how unintentional lattice imperfections stemming from the manufacturing process, primarily sur face roughness in the case of laser powder bed fusion, serve to cause stochastic response but that in some cases such as elastic response the stochastic behavior is homogenized through the adoption of lattices. In the sixth section we explore a novel neural network screening process that allows such stocastic variability to be predicted. In the last three sections, we explore considerations of computational design of lattices. Specifically, in section 7 using a novel generative optimization scheme to design novel pareto-optimal lattices for multi-objective environments. In section 8, we use computational design to optimize a metallic lattice structure to absorb impact energy for a 1000 ft/s impact. And in section 9, we develop a modified micromorphic continuum model to solve wave propagation problems in lattices efficiently.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Developing High-Throughput Organ-on-a-Chip Models to Investigate the Effects of Ionizing Radiation on the Central Nervous System

One of the main health risks in human space exploration is central nervous system (CNS) damage by ionizing radiation due to exposure to the galactic cosmic rays (GCRs). In animal models, irradiation with simulated GCRs or their components has been shown to cause neuronal damage and neuroinflammation associated with cognitive and behavioral dysfunction. In general, the extent of CNS damage is partially regulated by the blood-brain barrier (BBB), which enables immune cells to enter the CNS. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuronal death, immune responses and oxidative stress, and thus could serve as a robust CNS-specific target for countermeasure development. However, studies on BBB permeability and astrocyte functions in regulating CNS responses to ionizing radiation have been limited, especially in human tissue/organ analogs. Therefore, we established a high-throughput 3D organ-on-a-chip system to study human CNS and BBB impairments in response to ionizing radiation, based on commercially available OrganoPlates (Mimetas, Inc.) seeded with primary or induced pluripotent stem cell-derived human cells. We investigated both immediate and delayed CNS responses to major GCR components: 0.15-0.5 Gy 250MeV/n 4-He, and 0.3-0.8 Gy 600 MeV/n 56-Fe; as well as to 0.5-1 Gy X-rays. We observed ionizing radiation-mediated increases in BBB permeability that was exacerbated by astrocyte presence and accompanied by morphological changes in endothelial cells and tight junctions, altered cytokine profile including TNFa upregulation, and increased oxidative stress. We also quantified irradiation-mediated changes in astrocyte activation and neuronal functions, revealing major astrocyte damage mediated by 600MeV/n 56-Fe particles. Thus, we demonstrate that deep space radiation may contribute to CNS damage by disrupting both astrocyte and endothelial cell components of the blood-brain barrier. Our next steps include mapping and validating the transcriptomic changes induced by simulated GCRs and their components in human CNS models. Ultimately, we aim to uncover potential novel targets for countermeasure developments to mitigate CNS damage in long duration spaceflight.

Radiation↗
DOE OSTI2026

Structure of Self-Generated Magnetic Fields in Laser-Solid Interaction from Proton Tomography

Self-generated magnetic fields in laser-solid interactions are experimentally characterized to reveal the 3D location and local field strength, rather than path-integrated quantities, using multi-view proton radiography and tomographic inversion. We infer magnetic fields that extend several millimeters off the target into the hot, rarefied corona, sufficient to strongly magnetize the plasma (Ω e τ e ≫ 1). The data are compared to MHD simulations incorporating recent improvements in modeling magnetic field generation and transport; the volume-averaged coronal field strength and magnetic flux agree to within 25% using a model with magnetic re-localization of transport, although the near-target morphology is not reproduced. This work demonstrates tomographic proton radiography as a valuable tool for investigating magnetic fields in laser-produced plasmas.

High-energy-density plasmas↗
NASA NTRS2013

The Spatial Extent and Distribution of Star Formation in 3D-HST Mergers at z is approximately 1.5

We present an analysis of the spatial distribution of star formation in a sample of 60 visually identified galaxy merger candidates at z greater than 1. Our sample, drawn from the 3D-HST survey, is flux-limited and was selected to have high star formation rates based on fits of their broad-band, low spatial resolution spectral energy distributions. It includes plausible pre-merger (close pairs) and post-merger (single objects with tidal features) systems,with total stellar masses and star formation rates derived from multi-wavelength photometry. Here we use near-infrared slitless spectra from 3D-HST which produce H or [OIII] emission line maps as proxies for star-formation maps. This provides a first comprehensive high-resolution, empirical picture of where star formation occurred in galaxy mergers at the epoch of peak cosmic star formation rate. We find that detectable star formation can occur in one or both galaxy centres, or in tidal tails. The most common case (58%) is that star formation is largely concentrated in a single, compact region, coincident with the centre of (one of) the merger components. No correlations between star formation morphology and redshift, total stellar mass, or star formation rate are found. A restricted set of hydrodynamical merger simulationsbetween similarly massive and gas-rich objects implies that star formation should be detectable in both merger components, when the gas fractions of the individual components are the same. This suggests that z is approximately 1.5 mergers typically occur between galaxies whose gas fractions, masses, andor star formation rates are distinctly different from one another.

Spatial↗
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↗
NASA NTRS2018

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. By combining spatial and spectral information from varying resolutions, we seek to augment and improve the classification accuracy of previously low-resolution datasets at large temporal scales.NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive learning and training software, currently being developed at NASA Ames, is aimed at assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. The latest iteration uses fully convolutional networks to segment and identify coral imagery taken by UAVs and satellites, including WorldView-2 and Sentinel. We present results taken from the Indian Ocean where classification accuracy has exceeded 91% for 24 geomorphological classes given ample training data. In addition, we utilize deep Laplacian Pyramid Super-Resolution Networks (LapSRN) to reconstruct high resolution information from low resolution imagery, trained from various UAV and satellite datasets. Finally, in the case of insufficient training data, we have developed an interactive online platform that allows users to easily segment and submit their classifications, which has been integrated with the current NeMO-Net workflow. Specifically, we present results from the Fiji islands in which preliminary user data has allowed for the accurate identification of 9 separate classes, despite issues such as cloud shadowing and spectral variation. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Neural↗
DOE OSTI2022

The Rule of Thirds: Controlling Junction Chirality and Polarity in 3D DNA Tiles

The successful self-assembly of tensegrity triangle DNA crystals heralded the ability to programmably construct macroscopic crystalline nanomaterials from rationally-designed, nanoscale components. This 3D DNA tile owes its “tensegrity” nature to its three rotationally-stacked double helices locked together by the tensile winding of a center strand segmented into 7 base pair (bp) inter-junction regions, corresponding to two thirds of a helical turn of DNA. All reported tensegrity triangles to date have employed [Z + 2/3] turn inter-junction segments, yielding right-handed, antiparallel, “J1” junctions. Here, we report here a minimal DNA triangle motif consisting of 3-bp inter-junction segments, or one third of a helical turn. Here, we find that the minimal motif exhibits a reversed morphology with a left-handed tertiary structure mediated by a locally-parallel Holliday junction—the L1 junction. This parallel junction yields a predicted helical groove matching pattern that breaks the pseudosymmetry between tile faces, and the junction morphology further suggests a folding mechanism. We identify a Rule of Thirds by which supramolecular chirality can be programmed through inter-junction DNA segment length. These results underscore the role that global topological forces play in determining local DNA architecture and ultimately point to an under-explored class of self-assembling, chiral nanomaterials for topological processes in biological systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗