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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Computational and Experimental Determination of the Properties, Structure, and Stability of Peptoid Nanosheets and Nanotubes

Peptoids (N-substituted glycines) are a group of highly controllable peptidomimetic polymers. Amphiphilic diblock peptoids have been engineered to assemble crystalline nanospheres, nanofibrils, nanosheets, and nanotubes with biochemical, biomedical, and bioengineering applications. The mechanical properties of peptoid nanoaggregates and their relationship to the emergent self-assembled morphologies have been relatively unexplored and are critical for the rational design of peptoid nanomaterials. In this work, we consider a family of amphiphilic diblock peptoids consisting of a prototypical tube-former (Nbrpm6Nc6, a NH 2 -capped hydrophobic block of six N-((4-bromophenyl)methyl)glycine residues conjugated to a polar NH 3 (CH 2 ) 5 CO tail), a prototypical sheet-former (Nbrpe6Nc6, where the hydrophobic block comprises six N-((4-bromophenyl)ethyl)glycine residues), and an intermediate sequence that forms mixed structures ((NbrpeNbrpm)3Nc6). We combine all-atom molecular dynamics simulations and atomic force microscopy to determine the mechanical properties of the self-assembled 2D crystalline nanosheets and relate these properties to the observed self-assembled morphologies. We find good agreement between our computational predictions and experimental measurements of Young’s modulus of crystalline nanosheets. A computational analysis of the bending modulus along the two axes of the planar crystalline nanosheets reveals bending to be more favorable along the axis in which the peptoids stack by interdigitation of the side chains compared to that in which they form columnar crystals with π-stacked side chains. Here, we construct molecular models of nanotubes of the Nbrpm6Nc6 tube-forming peptoid and predict a stability optimum in good agreement with experimental measurements. A theoretical model of nanotube stability suggests that this optimum is a free energy minimum corresponding to a “Goldilocks” tube radius at which capillary wave fluctuations in the tube wall are minimized.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In situ TEM measurement of electrical properties of individual BaTiO 3 nanocubes

We report on the measurement of the electrical properties of individual pristine and doped BaTiO 3 nanocubes by using in situ transmission electron microscopy with a two-electrode configuration. The dimensions of the nanocubes tested are between 10 and 20 nm, which rendered their in situ electrical characterization challenging. We characterized 4%Cr and 5%La (atomic percentage) doped BaTiO 3 nanocubes and compared them with the properties of pristine BaTiO3 nanocubes synthesized by the same solvothermal method. We found that the resistance of all three types of nanocubes when displayed in log-scale shows a nearly linear dependence on the applied electric field (R2 ≥ 0.95) over a wide range of electric fields (50–900 kV/cm). Compared with pristine BaTiO 3 nanocubes, the resistance of both 4%Cr and 5%La doped nanocubes showed reduced variation rates with respect to the electric field, with 5%La doping, demonstrating a better reduction in the variation rate. By developing techniques capable of evaluating the properties of individual BaTiO 3 nanocubes, we expect that our work to open the door to the use of BaTiO 3 nanomaterials in the design of future multilayer ceramic capacitors with improved volumetric efficiency and ferroelectrics-enabled nanodevices with advanced functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Engineering tertiary chirality in helical biopolymers

Tertiary chirality describes the handedness of supramolecular assemblies and relies not only on the primary and secondary structures of the building blocks but also on topological driving forces that have been sparsely characterized. Helical biopolymers, especially DNA, have been extensively investigated as they possess intrinsic chirality that determines the optical, mechanical, and physical properties of the ensuing material. Here, we employ the DNA tensegrity triangle as a model system to locate the tipping points in chirality inversion at the tertiary level by X-ray diffraction. We engineer tensegrity triangle crystals with incremental rotational steps between immobile junctions from 3 to 28 base pairs (bp). We construct a mathematical model that accurately predicts and explains the molecular configurations in both this work and previous studies. Our design framework is extendable to other supramolecular assemblies of helical biopolymers and can be used in the design of chiral nanomaterials, optically active molecules, and mesoporous frameworks, all of which are of interest to physical, biological, and chemical nanoscience.

Science & Technology - Other Topics↗
DOE OSTI2021

RNA nanotechnology to build a dodecahedral genome of single-stranded RNA virus

The quest for artificial RNA viral complexes with authentic structure while being non-replicative is on its way for the development of viral vaccines. RNA viruses contain capsid proteins that interact with the genome during morphogenesis. The sequence and properties of the protein and genome determine the structure of the virus. For example, the Pariacoto virus ssRNA genome assembles into a dodecahedron. Virus-inspired nanotechnology has progressed remarkably due to the unique structural and functional properties of viruses, which can inspire the design of novel nanomaterials. RNA is a programmable biopolymer able to self-assemble sophisticated 3D structures with rich functionalities. RNA dodecahedrons mimicking the Pariacoto virus quasi-icosahedral genome structures were constructed from both native and 2'-F modified RNA oligos. The RNA dodecahedron easily self-assembled using the stable pRNA three-way junction of bacteriophage phi29 as building blocks. The RNA dodecahedron cage was further characterized by cryo-electron microscopy and atomic force microscopy, confirming the spontaneous and homogenous formation of the RNA cage. The reported RNA dodecahedron cage will likely provide further studies on the mechanisms of interaction of the capsid protein with the viral genome while providing a template for further construction of the viral RNA scaffold to add capsid proteins for the assembly of the viral nucleocapsid as a model. Understanding the self-assembly and RNA folding of this RNA cage may offer new insights into the 3D organization of viral RNA genomes. Finally, the reported RNA cage also has the potential to be explored as a novel virus-inspired nanocarrier.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Universal progression of structure and dynamics in colloidal nanocrystal gels during salt-accelerated aging

Controlling the structure and function of colloidal gels requires a detailed understanding of how the various components govern network formation and aging. In particular, molecular additives like salts are widely used to tune interparticle interactions, yet their influence on gelation pathways in complex systems such as colloidal nanocrystal gels remains inadequately understood. Here, we investigate how noncoordinating salts modulate the evolution of gels formed using chemically linked tin-doped indium oxide nanocrystals. Through combined structural, dynamic, and kinetic analyses, we demonstrate that increasing salt concentration accelerates gelation. When rescaled by salt-dependent characteristic times, the evolution collapses onto universal trajectories, revealing a time-salt superposition principle. The universality extends across length scales, suggesting a consistent salt-dependent mechanism that controls both local structuring and macroscopic network formation. This observed salt modulation of structure and dynamics provides a predictive basis for controlling the kinetics of nonequilibrium nanocrystal gel assembly, enhancing the rational design of functional nanomaterials with tunable properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

2019 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is necessary to meet the continual challenging national workforce needs that arise as computational science and engineering problems continue to grow in scope and complexity. Computational science and engineering (CSE) is a multidisciplinary approach that uses scientific computing to solve practical problems methods and to supply technical tools across the scientific discovery spectrum. In particular, the DOE CSGF emphasizes high-performance computing (HPC) that enables CSE that advances science and engineering in directions important to the DOE and the economy in general. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines, such as biology and cosmology, have been transformed through the augmentation of scientific observation via HPC. At government laboratories and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, renewable energy, fusion-reactor design, additive manufacturing, nanomaterials for next-generation batteries and transistors, and turbine and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development — including continuing to rise to the challenge of pandemic-related research. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing.” An explosion in scientific and technological data has driven the need for increasingly sophisticated HPC to transform those data into scientific understanding. With access to more and more data and the proliferation of HPC, Machine Learning and Artificial Intelligence are experiencing a renaissance, complementing the now well-established use of computational simulation. Indeed, in its September 2020 subcommittee report on “AI/ML, Data Intensive Science and High-Performance Computing”, the DOE Advanced Scientific Computing Advisory Committee (ASCAC) explicitly called for a fellowship program to train computational and data scientists to tackle exascale and data-intensive computing challenges. This collaboration of empirical and theory-based modeling will increasingly inform federal policymakers whose decisions affect American society and future generations, and it requires highly skilled and intellectually agile computational scientists who can support the fast-moving DOE National Laboratory research environment. In fact, the DOE CSGF program has explicitly and consistently addressed this need.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2014

Development of a Batch Fabrication Process for Chemical Nanosensors: Recent Advancements at NASA Glenn Research Center

A major objective in aerospace sensor development is to produce sensors that are small in size, easy to batch fabricate and low in cost, and have low power consumption. Chemical sensors involving nanostructured materials can provide these characteristics as well as the potential for the development of sensor systems with unique properties and improved performance. However, the fabrication and processing of nanostructures for sensor applications currently is limited by the ability to control their location on the sensor platform, which in turn hinders the progress for batch fabrication. This presentation will discuss the following: the development of a novel room temperature methane (CH4) sensor fabricated using porous tin oxide (SnO2) nanorods as the sensing material, the advantages of using nanomaterials in sensor designs, the challenges encountered with the integration of nanostructures into microsensordevices, and the different methods that have been attempted to address these challenges. An approach for the mass production of sensors with nanostructures using a method developed by our group at the NASA Glenn Research Center to control the alignment of nanostructures onto a sensor platform will also be described.

Nanotechnology↗
NASA NTRS2015

Integration of Nanostructures into Microsensor Devices on Whole Wafers

Chemical sensors are used in a wide variety of applications, such as environmental monitoring, fire detection, emission monitoring, and health monitoring. The fabrication of chemical sensors involving nanostructured materials holds the potential for the development of sensor systems with unique properties and improved performance. However, the fabrication and processing of nanostructures for sensor applications currently are limited in the ability to control their location on the sensor, which in turn hinders the progress for batch fabrication. This report discusses the advantages of using nanomaterials in sensor designs, some of the challenges encountered with the integration of nanostructures into microsensor / devices, and then briefly describes different methods attempted by other groups to address this issue. Finally, this report will describe how our approach for the controlled alignment of nanostructures onto a sensor platform was applied to demonstrate an approach for the mass production of sensors with nanostructures.

Nanostructures (Devices)↗
DOE OSTI2022

Augmented DNA Nanoarchitectures: A Structural Library of 3D Self-Assembling Tensegrity Triangle Variants

The DNA tensegrity triangle is known to reliably self-assemble into a 3D rhombohedral crystalline lattice via sticky-end cohesion. Here, in this study, the library of accessible motifs is expanded through covalent extensions of intertriangle regions and sticky-end-coordinated linkages of adjacent triangles with double helical segments using both geometrically symmetric and asymmetric configurations. The molecular structures of 18 self-assembled architectures at resolutions of 3.32–9.32 Å are reported; the observed cell dimensions, cavity sizes, and cross-sectional areas agree with theoretical expectations. These data demonstrate that fine control over triclinic and rhombohedral crystal parameters and the customizability of more complex 3D DNA lattices are attainable via rational design. It is anticipated that augmented DNA architectures may be fine-tuned for the self-assembly of designer nanocages, guest–host complexes, and proscriptive 3D nanomaterials, as originally envisioned. Finally, designer asymmetric crystalline building blocks can be seen as a first step toward controlling and encoding information in three dimensions.

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

Top-down design of protein architectures with reinforcement learning

As a result of evolutionary selection, the subunits of naturally occurring protein assemblies often fit together with substantial shape complementarity to generate architectures optimal for function in a manner not achievable by current design approaches. We describe a “top-down” reinforcement learning–based design approach that solves this problem using Monte Carlo tree search to sample protein conformers in the context of an overall architecture and specified functional constraints. Cryo–electron microscopy structures of the designed disk-shaped nanopores and ultracompact icosahedra are very close to the computational models. The icosohedra enable very-high-density display of immunogens and signaling molecules, which potentiates vaccine response and angiogenesis induction. Our approach enables the top-down design of complex protein nanomaterials with desired system properties and demonstrates the power of reinforcement learning in protein design.

Science & Technology - Other Topics↗
DOE OSTI2024

Observing the Surface Termination of LaScO 3 Perovskite Using Solid-State Nuclear Magnetic Resonance

Materials with well-defined surfaces are drawing increased attention for the design of bespoke catalysts and nanomaterials. Gaining a detailed understanding of the surfaces of these materials is an important challenge, which is often complicated by surface polymorphism and dynamic restructuring. We introduce the use of surface-enhanced NMR spectroscopy for the observation of such surfaces, focusing on LaScO 3 as an example. Here, we show that double-resonance NMR experiments correlating surface oxygen and probe molecules to the 139 La and 45 Sc nuclei at the surface reveal the material to be terminated by a ScO x monolayer. Surface-selective 17 O and 45 Sc NMR experiments further showed the material to be hydroxyl terminated and that the surface may be prone to dynamic restructuring as a result of moisture exposure. Perhaps most interestingly, surface-selective 139 La NMR experiments revealed the existence of previously undetected surface lanthanum defects, suggesting that surface-enhanced NMR may be useful as a guide in the synthesis of defect-free surfaces in the design of various nanomaterials.

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

Design of multi-scale protein complexes by hierarchical building block fusion

A systematic and robust approach to generating complex protein nanomaterials would have broad utility. We develop a hierarchical approach to designing multi-component protein assemblies from two classes of modular building blocks: designed helical repeat proteins (DHRs) and helical bundle oligomers (HBs). We first rigidly fuse DHRs to HBs to generate a large library of oligomeric building blocks. We then generate assemblies with cyclic, dihedral, and point group symmetries from these building blocks using architecture guided rigid helical fusion with new software named WORMS. X-ray crystallography and cryo-electron microscopy characterization show that the hierarchical design approach can accurately generate a wide range of assemblies, including a 43 nm diameter icosahedral nanocage. The computational methods and building block sets described here provide a very general route to de novo designed protein nanomaterials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Molecular Engineering of 2D Nanomaterial Field-Effect Transistor Sensors: Fundamentals and Translation across Innovation Spectrum

We report over the last decade, 2D layered nanomaterials have attracted significant attention across the scientific community due to their rich and exotic properties. Various nanoelectronic devices based on these 2D nanomaterials have been explored and demonstrated, including those for environmental applications. Here, the fundamental attributes of 2D layered nanomaterials for field-effect transistor (FET) sensors and tunneling FET (TFET) sensors, which provide versatile detection of water contaminants such as heavy-metal ions, bacteria, nutrients, and organic pollutants, are discussed. The major challenges and opportunities are also outlined for designing and fabricating 2D nanomaterial FET/TFET sensors with superior performance. Translation of these FET/TFET sensors from fundamental research to applied technology is illustrated through a case study on graphene-based real-time FET water sensors. A second case study centers on large-scale sensor networks for water-quality monitoring to enable intelligent drinking water and river-water systems. Overall, 2D nanomaterial FET sensors have significant potential for enabling a human-centered intelligent water system that can likely be applied to other precarious water supplies around the globe.

2D nanomaterials↗
DOE OSTI2022

Chemistry-mediated Ostwald ripening in carbon-rich C/O systems at extreme conditions

Abstract There is significant interest in establishing a capability for tailored synthesis of next-generation carbon-based nanomaterials due to their broad range of applications and high degree of tunability. High pressure (e.g., shockwave-driven) synthesis holds promise as an effective discovery method, but experimental challenges preclude elucidating the processes governing nanocarbon production from carbon-rich precursors that could otherwise guide efforts through the prohibitively expansive design space. Here we report findings from large scale atomistically-resolved simulations of carbon condensation from C/O mixtures subjected to extreme pressures and temperatures, made possible by machine-learned reactive interatomic potentials. We find that liquid nanocarbon formation follows classical growth kinetics driven by Ostwald ripening (i.e., growth of large clusters at the expense of shrinking small ones) and obeys dynamical scaling in a process mediated by carbon chemistry in the surrounding reactive fluid. The results provide direct insight into carbon condensation in a representative system and pave the way for its exploration in higher complexity organic materials. They also suggest that simulations using machine-learned interatomic potentials could eventually be employed as in-silico design tools for new nanomaterials.

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

Reduction-Controlled Atomic Migration for Single Atom Alloy Library

Here, picturing the atomic migration pathways of catalysts in a reactive atmosphere is of central significance for uncovering the underlying catalytic mechanisms and directing the design of high-performance catalysts. Here, we describe a reduction-controlled atomic migration pathway that converts nanoparticles to single atom alloys (SAAs), which has remained synthetically challenging in prior attempts due to the elusive mechanism. We achieved this by thermally treating the noble-metal nanoparticles M (M = Ru, Rh, Pd, Ag, Ir, Pt, and Au) on metal oxide (CuO) supports with H2/Ar. Atomic-level characterization revealed such conversion as the synergistic consequence of noble metal-promoted H2 dissociation and concomitant CuO reduction. The observed atomic migration pathway offers an understanding of the dynamic mechanisms study of nanomaterials formation and catalyst design.

36 MATERIALS SCIENCE↗
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↗
DOE OSTI2021

Thermodynamic stabilization of nanocrystalline aluminum

Nanocrystalline metals are generally unstable due to a large volume fraction of high-energy grain boundaries associated with a small grain size. Preferential dopant segregation to the high-energy grain boundaries is observed to enhance the stability of the material’s microstructure by minimizing its energy. Nanocrystalline aluminum-dopant systems were evaluated for thermodynamic stability against grain growth and phase precipitation via the mechanism of grain boundary segregation according to a modified regular nanocrystalline solution model. Fifty-one potential dopant elements have been evaluated for their efficacy in stabilizing nanostructures with three potential candidates, magnesium, lanthanum, and silicon, identified possessing the characteristics to promote grain boundary segregation and a state of thermodynamic stability in aluminum’s nanocrystalline regime. Here, the minimum dopant content required to achieve nanocrystalline microstructure stability is identified for each of the three candidate elements. Beyond this minimum content, further addition of the dopant elements decreased the final microstructure’s stability with no effects on the existence of a stable nanocrystalline state.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Self-Assembled Bolaamphiphile-Based Organic Nanotubes as Efficient Cu(II) Ion Adsorbents

Self-assembled organic nanotubes (ONTs) have been actively examined for various applications such as chemical separations and catalysis owing to their well-defined tubular nanostructures with distinct chemical environments at the wall and internal/external surfaces. Adsorption of heavy metal ions onto ONTs plays an essential role in many of these applications, but it has rarely been assessed quantitatively. Herein, we investigated interactions between Cu 2+ and single-/quadruple-wall bolaamphiphile-based ONTs having inner carboxyl groups with different inner diameters, COOH-ONT 10nm and COOH-ONT 20nm . We first examined the effects of Cu 2+ on their nanotubular structures using SAXS, STEM, and AFM. COOH-ONT 10nm was stable in aqueous Cu 2+ solution in contrast to COOH-ONT 20nm owing to the presence of polyglycine-II-type hydrogen bonding networks within its wall. Subsequently, we studied the Cu 2+ adsorption behavior of COOH-ONT 10nm by monitoring the concentration of unbound Cu 2+ using linear sweep anodic stripping voltammetry. The Cu 2+ adsorption was quick, attributable to efficient Cu 2+ partitioning through the open ends of the ONT, followed by fast Cu 2+ diffusion in the uniform, relatively large nanochannel. More importantly, the Cu 2+ adsorption capacity and affinity of COOH-ONT 10nm were measured at different pH using the Langmuir adsorption model. The adsorption capacity was similar at the pH range examined, showing the participation of approximately 25% of the inner carboxyl groups in the adsorption. The adsorption affinity increased with pH, indicating the essential role of the deprotonated carboxyl groups in the Cu 2+ adsorption. Most interestingly, the Langmuir adsorption constant was significantly higher than those of previously reported synthetic adsorbents and planar monolayer based on carboxyl binding sites. The high Cu 2+ affinity of the ONT was attributable to the highly dense binding sites on the well-defined nanoscale concave structure of the inner channel. Furthermore, these results provide a valuable guideline to designing self-assembled nanomaterials for efficient chemical separations, detection, and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗