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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Grass xylan structural variation suggests functional specialization and distinctive interaction with cellulose and lignin

SUMMARY Xylan is the most abundant non‐cellulosic polysaccharide in grass cell walls, and it has important structural roles. The name glucuronoarabinoxylan (GAX) is used to describe this variable hemicellulose. It has a linear backbone of β‐1,4‐xylose (Xyl) residues that may be substituted with α‐1,2‐linked (4‐ O ‐methyl)‐glucuronic acid (GlcA), α‐1,3‐linked arabinofuranose (Ara f ), and sometimes acetylation at the O ‐2 and/or O ‐3 positions. The role of these substitutions remains unclear, although there is increasing evidence that they affect the way xylan interacts with other cell wall components, particularly cellulose and lignin. Here, we used substitution‐dependent endo‐xylanase enzymes to investigate the variability of xylan substitution in grass culm cell walls. We show that there are at least three different types of xylan: (i) an arabinoxylan with evenly distributed Ara f substitutions without GlcA (AXe); (ii) a glucuronoarabinoxylan with clustered GlcA modifications (GAXc); and (iii) a highly substituted glucuronoarabinoxylan (hsGAX). Immunolocalization of AXe and GAXc in Brachypodium distachyon culms revealed that these xylan types are not restricted to a few cell types but are instead widely detected in Brachypodium cell walls. We hypothesize that there are functionally specialized xylan types within the grass cell wall. The even substitutions of AXe may permit folding and binding on the surface of cellulose fibrils, whereas the more complex substitutions of the other xylans may support a role in the matrix and interaction with other cell wall components.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Heterogeneous Multilayer Nanopores via Chemically Tuned Dielectric Breakdown for Single‐Molecule Sensing

Solid-state nanopores are powerful platforms for single-molecule sensing, yet their performance is often constrained by fabrication complexity, noise, and limited control over surface properties. Here we report a direct method to fabricate heterogeneous multilayer nanopores using chemically tuned controlled dielectric breakdown (CT-CDB). We integrate hBN, MoS 2 , or graphene atop a silicon nitride membrane to form five distinct bilayer and tri-layer architectures, with bare SiN x nanopore as a control. CT-CDB achieves pore formation reproducibly through material-stacks with high efficiency, good pore size control, and strong yield, validated by various characterizations. Transferrin protein translocation experiments, supported by simulations, reveal that multilayer configurations modulate protein conformations, ionic current blockade and dwell time distributions, reflecting combined effects of membrane type, interfacial chemistry, and local electric field gradients. A supervised machine learning framework is implemented to assist identifying multilayer structure effects embedded in signal signatures, with over 96% accuracy. This work presents a modular and scalable framework for functional nanopore engineering with complex structural integration, thereby expanding the potential of 2D materials in single-molecule sensing applications.

2D materials↗
DOE OSTI2020

Steering Molecular Dynamics Simulations of Membrane-Associated Proteins with Neutron Reflection Results

Herein, we present a novel method to incorporate structural results from surface-sensitive scattering, such as X-ray or neutron reflectometry, into molecular dynamics simulations. While reflectometry techniques generally provide a means to determine the molecular-scale structures of organized interfacial films, they were recently shown to offer the capability to characterize the structures of protein-membrane complexes supported by a solid substrate. One-dimensional information inherent in the experimental results is used in the form of component volume occupancy (CVO) profiles, which describe the distribution of molecular components within an interfacial architecture, to construct real-space constraints in the form of a biasing potential for the simulation that vanishes when the simulated and experimental profiles agree. This approach improves the correspondence between simulation and experiment, as shown in the re-evaluation of an neutron-reflection-derived structure which was approximated by an independent molecular dynamics simulation in earlier work, and it also leads to faster equilibration of ensemble structures. We further show that time averaging the CVO profile that develops in the simulation while biasing with this approach permits fluctuations about the average that are necessary for conformational exploration of the system. This method is particularly valuable for studies of proteins at interfaces that contain disordered regions since the conformation of such regions is difficult to judge from the analysis of one-dimensional experimental profiles and may take prohibitively long to equilibrate in simulations.

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

Wave ripples formed in ancient, ice-free lakes in Gale crater, Mars

Symmetrical wave ripples identified with NASA’s Curiosity rover in ancient lake deposits at Gale crater provide a key paleoclimate constraint for early Mars: At the time of ripple formation, climate conditions must have supported ice-free liquid water on the surface of Mars. These features are the most definitive examples of wave ripples on another planet. The ripples occur in two stratigraphic intervals within the orbitally defined Layered Sulfate Unit: a thin but laterally extensive unit at the base of the Amapari member of the Mirador formation, and a sandstone lens within the Contigo member of the Mirador formation. In both locations, the ripples have an average wavelength of ~4.5 centimeters. Internal laminae and ripple morphology show an architecture common in wave-influenced environments where wind-generated surface gravity waves mobilize bottom sediment in oscillatory flows. Their presence suggests formation in a shallow-water (<2 meters) setting that was open to the atmosphere, which requires atmospheric conditions that allow stable surface water.

Science & Technology - Other Topics↗
DOE OSTI2024

Next-Generation Materials Design: Quantum Mechanics and Data-Driven Modeling

The future of materials design is rapidly advancing through the combination of quantum mechanics and data-driven modeling. These approaches integrate quantum principles with advanced data analysis, enabling precise insights into material behavior. This talk will highlight recent progress in using these methods for computational design, particularly in high-entropy alloy catalysts, emphasizing the role of hierarchical machine-learning architectures for accurate predictions. Additionally, I will discuss our work on developing machine learning interatomic potentials (MLPs) for single-element metals, metal oxides, and alloys under extreme conditions, focusing on melting behavior and phase properties at high temperatures and pressures. We have also refined our MLP models to capture dynamic surface interactions, such as CO2 and CO adsorption on MgO, using both static and molecular dynamics simulations. These models maintain high accuracy while significantly reducing computational costs compared to first-principles calculations. By enabling efficient and accurate simulations, this work supports broader community adoption, optimizes datasets for materials discovery, and extends the accessible time, size, and environmental conditions beyond the limits of experiments and traditional simulations.

machine learning↗
DOE OSTI2025

Energy metric prediction for double insertion mutants via the RoseNet deep learning framework

Studying the structural and functional implications of protein mutations is an important task in computational biology and bioinformatics. We leverage our previously proposed RoseNet neural network architecture to predict energy metrics of proteins with double amino acid insertions or deletions (InDels). We train models on previously generated benchmark datasets containing the exhaustive double InDel mutations for three proteins, as well as an additional three proteins for which ∼145k random mutants, each with two InDels, have been generated. We expand on our previous work by evaluating three additional proteins and analyzing domain features that impact the prediction capabilities of RoseNet. These features include InDels into secondary structures and the solvent accessible surface area (SASA) scores of the residues. We uncover further evidence to support that RoseNet has a higher proficiency of generalizing to unseen residue combinations than unseen insertion positions. We also observe that RoseNet produces higher-quality predictions when inserting into a β-sheet over an α-helix. Additionally, when the insertions fall in an area of high SASA, RoseNet often displays better performance than inserting into areas of low SASA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Non-Equilibrium Synthesis of Highly Active Nanostructured, Oxygen-Incorporated Amorphous Molybdenum Sulfide HER Electrocatalyst

Molybdenum sulfide emerged as promising hydrogen evolution reaction (HER) electrocatalyst thanks to its high intrinsic activity, however its limited active sites exposure and low conductivity hamper its performance. To address these drawbacks, the non-equilibrium nature of pulsed laser deposition (PLD) is exploited to synthesize self-supported hierarchical nanoarchitectures by gas phase nucleation and sequential attachment of defective molybdenum sulfide clusters. Furthermore, the physics of the process are studied by in situ diagnostics and correlated to the properties of the resulting electrocatalyst. The as-synthesized architectures have a disordered nanocrystalline structure, with nanodomains of bent, defective S-Mo-S layers embedded in an amorphous matrix, with excess sulfur and segregated molybdenum particles. Oxygen incorporation in this structure fosters the creation of amorphous oxide/oxysulfide nanophases with high electrical conductivity, enabling fast electron transfer to the active sites. The combined effect of the nanocrystalline pristine structure and the surface oxidation enhances the performance leading to small overpotentials, very fast kinetics (35.1 mV dec -1 Tafel slope) and remarkable long-term stability for continuous operation up to -1 A cm -2 . This work shows possible new avenues in catalytic design arising from a non-equilibrium technique as PLD and the importance of structural and chemical control to improve the HER performance of MoS-based catalysts.

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

Ultrasmall amorphous zirconia nanoparticles catalyse polyolefin hydrogenolysis

Carbon–carbon bond cleavage reactions, adapted to deconstruct aliphatic hydrocarbon polymers and recover the intrinsic energy and carbon value in plastic waste, have typically been catalysed by metal nanoparticles or air-sensitive organometallics. Metal oxides that serve as supports for these catalysts are typically considered to be inert. Here we show that Earth-abundant, non-reducible zirconia catalyses the hydrogenolysis of polyolefins with activity rivalling that of precious metal nanoparticles. To harness this unusual reactivity, our catalytic architecture localizes ultrasmall amorphous zirconia nanoparticles between two fused platelets of mesoporous silica. Macromolecules translocate from bulk through radial mesopores to the highly active zirconia particles, where the chains undergo selective hydrogenolytic cleavage into a narrow, C18-centred distribution. Calculations indicated that C–H bond heterolysis across a Zr–O bond of a Zr(O) 2 adatom model for unsaturated surface sites gives a zirconium hydrocarbyl, which cleaves a C–C bond via β-alkyl elimination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

TChem v2.0 - A Software Toolkit for the Analysis of Complex Kinetic Models

TChem is an open source software library for solving complex computational chemistry problems and analyzing detailed chemical kinetic models. The software provides support for: complex kinetic models for gas-phase and surface chemistry; thermodynamic properties based on NASA polynomials; species production/consumption rates; stable time integrator for solving stiff time ordinary differential equations; and, reactor models such as homogenous gas-phase ignition (with analytical Jacobian matrices), continuously stirred tank reactor, plug-flow reactor. This toolkit builds upon earlier versions that were written in C and featured tools for gas-phase chemistry only. The current version of the software was completely refactored in C++, uses an object-oriented programming model, and adopts Kokkos as its portability layer to make it ready for the next generation computing architectures i.e., multi/many core computing platforms with GPU accelerators. We have expanded the range of kinetic models to include surface chemistry and have added examples pertaining to Continuously Stirred Tank Reactors (CSTR) and Plug Flow Reactor (PFR) models to complement the homogenous ignition examples present in the earlier versions. To exploit the massive parallelism available from modern computing platforms, the current software interface is designed to evaluate samples in parallel, which enables large scale parametric studies, e.g. for sensitivity analysis and model calibration.

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

Applications of Decellularized Plant Tissues in Regenerative Medicine and Tissue Engineering

The development of biomaterials capable of supporting complex tissue growth remains a central challenge in regenerative medicine and tissue engineering, particularly in replicating the structural, mechanical, and transport functions of native extracellular matrices. While decellularized animal tissues have demonstrated significant success as scaffolds for tissue engineering, they are still constrained by cost, immunogenicity, and ethical concerns. In recent years, decellularized plant tissues have emerged as a compelling alternative scaffold platform due to their inherent vascular architectures, ethical sourcing, tunable mechanical properties, cytocompatibility, and sustainability. This review summarizes current strategies for the decellularization of plant tissues, including chemical, enzymatic, and physical approaches, and discusses how these methods preserve plant cell wall structure while removing immunogenic components. Advances in surface loading and functionalization, including protein coatings, oxidation, nanoparticle incorporation, peptide conjugation, and bioactive molecule loading, have further enhanced cell adhesion, differentiation, biodegradability, and immunomodulation. Recent applications of decellularized plant scaffolds in cardiac, skeletal muscle, bone, nerve, and wound healing contexts are reviewed, highlighting proof-of-concept successes and remaining challenges. Beyond therapeutic applications, plant-derived scaffolds have also enabled physiologically relevant in vitro models for vascular biology, mechanotransduction, cancer, metabolic tissues, and drug response studies. Collectively, these advances position decellularized plant tissues as versatile, low-cost, and ethically favorable biomaterials with growing relevance for both regenerative medicine and tissue modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

S-band acoustoelectric amplifier in an InGaAs-AlScN-SiC architecture

Here, we report on an acoustoelectric slab waveguide heterostructure for phonon amplification using a thin Al 0.58 Sc 0.42 N film grown directly on a 4H-SiC substrate with an ultra-thin In 0.53 Ga 0.47 As epitaxial film heterogeneously integrated onto the surface of the Al 0.58 Sc 0.42 N. The aluminum scandium nitride film grown directly on silicon carbide enables a thin (∼850 nm thick) piezoelectric film to be deposited on a thermally conductive bulk substrate (370 W/m K for 4H-SiC); the high thermal conductivity of the substrate, large mobility of the semiconductor (∼7000 cm 2 /V s), and low carrier concentration (∼5 × 10 15 cm −3 ) yield low self-heating. A Sezawa mode with optimal overlap between the peak of its evanescent electric field and the semiconductor charge carriers is supported. The high velocity of the heterostructure materials allows us to operate the Sezawa mode amplifier at 3.05 GHz, demonstrating a gain of 500 dB/cm (40 dB in 800 μm). Additionally, a terminal end-to-end radio frequency gain of 7.7 dB and a nonreciprocal transmission of 52.6 dB are achieved with a dissipated DC power of 2.3 mW. In conclusion, the power added efficiency and acoustic noise figure are also characterized.

Hackett, L.↗
DOE OSTI2020

Liquid–Solid Boundaries Dominate Activity of CO 2 Reduction on Gas-Diffusion Electrodes

Electrochemical CO 2 electrolysis to produce hydrocarbon fuels or material feedstocks offers a renewable alternative to fossilized carbon sources. Gas-diffusion electrodes (GDEs), composed of solid electrocatalysts on porous supports positioned near the interface of a conducting electrolyte and CO 2 gas, have been able to demonstrate the substantial current densities needed for future commercialization. These higher reaction rates have often been ascribed to the presence of a three-phase interface, where solid, liquid, and gas provide electrons, water, and CO 2 , respectively. Conversely, mechanistic work on electrochemical reactions implicates a fully two-phase reaction interface, where gas molecules reach the electrocatalyst’s surface by dissolution and diffusion through the electrolyte. Because the discrepancy between an atomistic three-phase versus two-phase reaction has substantial implications for the design of catalysts, gas-diffusion layers, and cell architectures, the nuances of nomenclatures and governing phenomena surrounding the three-phase-region require clarification. In this paper we outline the macro, micro, and atomistic phenomena occurring within a gas-diffusion electrode to provide a focused discussion on the architecture of the often-discussed three-phase region for CO 2 electrolysis. From this information, we comment on the outlook for the broader CO 2 electroreduction GDE cell architecture.

CO2 reduction↗
DOE OSTI2022

Image transformers for classifying acute lymphoblastic leukemia

Cancer is the leading cause of death by disease in American children. Each year, nearly 16,000 children in the United States and over 300,000 children globally are diagnosed with cancer. Leukemia is a form of blood cancer that originates in the bone marrow and accounts for one-third of pediatric cancers. This disease occurs when the bone marrow contains 20% or more immature white blood cell blasts. Acute lymphoblastic leukemia is the most prevalent leukemia type found in children, with half of all annual cases in the U.S. diagnosed for subjects under 20 years of age. To diagnose acute lymphoblastic leukemia, pathologists often conduct a morphological bone marrow assessment. This assessment determines whether the immature white blood cell blasts in bone marrow display the correct morphological characteristics, such as size and appearance of nuclei. Pathologists also use immunophenotyping via multi-channel flow cytometry to test whether certain antigens are present on the surface of blast cells; the antigens are used to identify the cell lineage of acute lymphoblastic leukemia. These manual processes require well-trained personnel and medical professionals, thus being costly in time and expenses. Computerized decision support via machine learning can accelerate the diagnosis process and reduce the cost. Training a reliable classification model to distinguish between mature and immature white blood cells is essential to the decision support system. Here, we adopted the Vision Transformer model to classify white blood cells. The Vision Transformer achieved superb classification performance compared to state-of-the-art convolutional neural networks while requiring less computational resources for training. Additionally, the latent self-attention architecture provided attention maps for a given image, providing clues as to which portion(s) of the image were significant in decision-making. We applied the Vision Transformer model and a convolutional neural network model to an acute lymphoblastic leukemia classification dataset of 12,528 samples and achieved accuracies of 88.4% and 86.2%.

Cho, Priscilla↗
DOE OSTI2023

Open and Close-Packed, Shape-Engineered Polygonal Nanoparticle Metamolecules with Tailorable Fano Resonances

In this study, a top-down lithographic patterning and deposition process is reported for producing nanoparticles (NPs) with well-defined sizes, shapes, and compositions that are often not accessible by wet-chemical synthetic methods. These NPs are ligated and harvested from the substrate surface to prepare colloidal NP dispersions. Using a template-assisted assembly technique, fabricated NPs are driven by capillary forces to assemble into size- and shape-engineered templates and organize into open or close-packed multi-NP structures or NP metamolecules. The sizes and shapes of the NPs and of the templates control the NP number, coordination, interparticle gap size, disorder, and location of defects such as voids in the NP metamolecules. The plasmonic resonances of polygonal-shaped Au NPs are exploited to correlate the structure and optical properties of assembled NP metamolecules. Comparing open and close-packed architectures highlights that introduction of a center NP to form close-packed assemblies supports collective interactions, altering magnetic optical modes and multipolar interactions in Fano resonances. Decreasing the distance between NPs strengthens the plasmonic coupling, and the structural symmetries of the NP metamolecules determine the orientation-dependent scattering response.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Interligand Coupling Drives Fast Triplet Energy Transfer Routes in PbS/Tetracene Quantum Dot Hybrids

The binding of photoactive organic ligands to inorganic quantum dots (QDs) creates a versatile hybrid architecture that allows access to photophysical processes such as efficient triplet exciton generation with near-infrared radiation. Here we report the subnanosecond generation of a hybrid triplet state with mixed ligand-QD character by replacing native oleate ligands on small PbS QDs with 5,12-tetracenepropiolic acid, a bifunctional ligand with two carboxylic acids that tends to lie face-on with the QD surface at low loadings. The face-on geometry engenders a regime of strong electronic coupling that is evident in steady-state absorption and hastens triplet energy flow by several orders of magnitude compared with more typical tetracene-based ligands exhibiting weak coupling. We further determined via Fourier transform infrared (FTIR) and supported by density functional theory (DFT)-based geometry optimizations that high ligand loading causes a shift in QD-ligand mutual disposition toward an edge-on geometry that instigates the formation of intermolecular excited states characterized by triplet excimer-like features in photoluminescence and transient absorption. Our results demonstrate the ability to control strongly coupled ligand-QD systems toward ultrafast generation of photophysically relevant species such as triplets that are valuable for photon upconversion and catalysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Monolayer Films of Binary Metal Oxide Nanoparticles for Carbon Nanotube Synthesis

Binary metal oxide nanoparticles (biMO-NPs) combining transition and main-group metals with well-organized atomic architectures have unique potential as robust and economical heterogeneous catalysts. Herein, metal oxide nanoparticles (CoAlxOy) using cobalt and aluminum were synthesized, and their structure, morphology, and chemical composition were investigated using various characterization techniques. The biMO-NPs, which had a Gaussian-type size distribution (∼6 nm), were assembled on plain silicon substrates modified chemically with linker molecules bearing suitable end groups. Surface analysis revealed an ordered, uniform, close-packed arrangement of biMO-NPs forming a monolayer architecture with nanoscale thickness (∼12 nm), high surface uniformity, and negligible defects. The nanoparticle monolayer film (NP-MF) was employed as a catalyst to grow carbon nanotube (CNT) forests via the thermal chemical vapor deposition (CVD) method, similar to those grown from catalyst thin films deposited by physical vapor deposition. Structural characterization confirmed the growth of a dense, uniform, high-quality vertically aligned carbon nanotube (VA-CNT) forest with a length of ∼125 µm, which is comparable to the VA-CNTs grown from expensive thin films. Thus, CNT growth was successfully catalyzed by the biMO-NPs, highlighting a simple and inexpensive alternative for catalyst deposition. In this innovative wet-chemistry approach, the catalyst and catalyst support are combined within a single nanoparticle before NP-MF assembly. Interestingly, this approach provides a scalable and cost-effective pathway for CNT growth, eliminating the need for expensive thin deposition techniques.

Regmi, Bishow [University of Cincinnati]↗
DOE OSTI2024

Multiscale embedded printing of engineered human tissue and organ equivalents

Creating tissue and organ equivalents with intricate architectures and multiscale functional feature sizes is the first step toward the reconstruction of transplantable human tissues and organs. Existing embedded ink writing approaches are limited by achievable feature sizes ranging from hundreds of microns to tens of millimeters, which hinders their ability to accurately duplicate structures found in various human tissues and organs. In this study, a multiscale embedded printing (MSEP) strategy is developed, in which a stimuli-responsive yield-stress fluid is applied to facilitate the printing process. A dynamic layer height control method is developed to print the cornea with a smooth surface on the order of microns, which can effectively overcome the layered morphology in conventional extrusion-based three-dimensional bioprinting methods. Since the support bath is sensitive to temperature change, it can be easily removed after printing by tuning the ambient temperature, which facilitates the fabrication of human eyeballs with optic nerves and aortic heart valves with overhanging leaflets on the order of a few millimeters. The thermosensitivity of the support bath also enables the reconstruction of the full-scale human heart on the order of tens of centimeters by on-demand adding support bath materials during printing. Here, the proposed MSEP demonstrates broader printable functional feature sizes ranging from microns to centimeters, providing a viable and reliable technical solution for tissue and organ printing in the future.

3D bioprinting↗
DOE OSTI2020

Improving the bulk gas transport of Fe-N-C platinum group metal-free nanofiber electrodes via electrospinning for fuel cell applications

To overcome transport limitations associated with thicker platinum group metal-free (PGM-free) electrodes, it's essential to investigate and tailor alternative electrode architectures to maximize the bulk electrode transport properties, whilst not significantly impeding electrocatalyst active site accessibility and electrode proton resistance. In this work, PGM-free nanofiber electrode mats, prepared by electrospinning a mixture of pyrolyzed Fe-N-C catalyst, Nafion ionomer and a carrier polymer Poly Acrylic acid (PAA), were compared to traditionally prepared electrodes. The morphological properties and elemental distribution of the fabricated nanofiber electrodes showed that the exterior surface of the PGM-free nanofibers was conformally covered with a thin ionomer film. Electrochemical diagnostics performed utilizing cyclic voltammetry, electrochemical impedance spectroscopy (EIS) and H 2 -limiting current measurements, revealed an increase in electric double layer capacitance, reduction in electrode proton transport and a significant improvement in bulk-electrode gas transport properties for the nanofiber electrodes, supporting the observed performance increase from electrochemical polarization data obtained in H 2 -O 2 /Air fuel cells. At 100% RH in H2/Air, the power density of the nanofiber electrodes increased ca. 50% vs. the traditionally prepared electrodes (ca. 260 vs 175 mW cm -2 ), which was attributed to a less tortuous molecular diffusion pathway and an associated reduction in the pressure dependent and independent gas transport resistances in the nanofiber electrodes.

25 ENERGY STORAGE↗