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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Deep Learning Segmentation of Complex Features in Atomic-Resolution Phase-Contrast Transmission Electron Microscopy Images

Phase-contrast transmission electron microscopy (TEM) is a powerful tool for imaging the local atomic structure of materials. TEM has been used heavily in studies of defect structures of two-dimensional materials such as monolayer graphene due to its high dose efficiency. However, phase-contrast imaging can produce complex nonlinear contrast, even for weakly scattering samples. It is, therefore, difficult to develop fully automated analysis routines for phase-contrast TEM studies using conventional image processing tools. For automated analysis of large sample regions of graphene, one of the key problems is segmentation between the structure of interest and unwanted structures such as surface contaminant layers. In this study, we compare the performance of a conventional Bragg filtering method with a deep learning routine based on the U-Net architecture. We show that the deep learning method is more general, simpler to apply in practice, and produces more accurate and robust results than the conventional algorithm. We provide easily adaptable source code for all results in this paper and discuss potential applications for deep learning in fully automated TEM image analysis.

47 OTHER INSTRUMENTATION↗
NASA NTRS1997

Carbon Nanotubes: Molecular Electronic Components

The carbon Nanotube junctions have recently emerged as excellent candidates for use as the building blocks in the formation of nanoscale molecular electronic networks. While the simple joint of two dissimilar tubes can be generated by the introduction of a pair of heptagon-pentagon defects in an otherwise perfect hexagonal graphene sheet, more complex joints require other mechanisms. In this work we explore structural characteristics of complex 3-point junctions of carbon nanotubes using a generalized tight-binding molecular-dynamics scheme. The study of pi-electron local densities of states (LDOS) of these junctions reveal many interesting features, most prominent among them being the defect-induced states in the gap.

Srivastava, Deepak↗
NASA NTRS2016

Graphene Based Ultra-Capacitors for Safer, More Efficient Energy Storage

Current power storage methods must be continuously improved in order to keep up with the increasingly competitive electronics industry. This technological advancement is also essential for the continuation of deep space exploration. Today's energy storage industry relies heavily on the use of dangerous and corrosive chemicals such as lithium and phosphoric acid. These chemicals can prove hazardous to the user if the device is ruptured. Similarly they can damage the environment if they are disposed of improperly. A safer, more efficient alternative is needed across a wide range of NASA missions. One solution would a solid-state carbon based energy storage device. Carbon is a safer, less environmentally hazardous alternative to current energy storage materials. Using the amorphous carbon nanostructure, graphene, this idea of a safer portable energy is possible. Graphene was electrochemically produced in the lab and several coin cell devices were built this summer to create a working prototype of a solid-state graphene battery.

Composite battery↗
DOE OSTI2022

Topography inversion in scanning tunneling microscopy of single-atom-thick materials from penetrating substrate states

Scanning tunneling microscopy (STM) is one of the indispensable tools to characterize surface structures, but the distinction between atomic geometry and electronic effects based on the measured tunneling current is not always straightforward. In particular, for single-atomic-thick materials (graphene or boron nitride) on metallic substrates, counterintuitive phenomena such as a larger tunneling current for insulators than for metal and a topography opposite to the atomic geometry are reported. Using first-principles density functional theory calculations combined with analytical modeling, we reveal the critical role of penetrating states of metallic substrates that surpass 2D material states, hindering the measurement of intrinsic 2D materials states and leading to topography inversion. Our finding should be instrumental in the interpretation of STM topographies of atomic-thick materials and in the development of 2D material for (opto)electronic and various quantum applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Promotion of superconductivity in magic-angle graphene multilayers

Graphene moiré superlattices show an abundance of correlated insulating, topological, and superconducting phases. Whereas the origins of strong correlations and nontrivial topology can be directly linked to flat bands, the nature of superconductivity remains enigmatic. We demonstrate that magic-angle devices made of twisted tri-, quadri-, and pentalayer graphene placed on monolayer tungsten diselenide exhibit flavor polarization and superconductivity. We also observe insulating states in the tril- and quadrilayer arising at finite electric displacement fields. As the number of layers increases, superconductivity emerges over an enhanced filling-factor range, and in the pentalayer it extends well beyond the filling of four electrons per moiré unit cell. Our results highlight the role of the interplay between flat and more dispersive bands in extending superconducting regions in graphene moiré superlattices.

Science & Technology - Other Topics↗
DOE OSTI2025

Harnessing ferro-valleytricity in pentalayer rhombohedral graphene for memory and compute

Two-dimensional materials with multiple degrees of freedom, including spin, valleys, and orbitals, open up an exciting avenue for engineering multifunctional devices. Beyond spintronics, these degrees of freedom can lead to novel quantum effects such as valley-dependent Hall effects and orbital magnetism, which could revolutionize next-generation electronics. However, achieving independent control over valley polarization and orbital magnetism has been a challenge due to the need for large electric fields. A recent breakthrough involving pentalayer rhombohedral graphene has demonstrated the ability to individually manipulate anomalous Hall signals and orbital magnetic hysteresis, forming what is known as a valley-magnetic quartet. Here, we leverage the electrically tunable ferro-valleytricity of pentalayer rhombohedral graphene to develop nonvolatile memory and in-memory computation applications. We propose an architecture for a dense, scalable, and selector-less nonvolatile memory array that harnesses the electrically tunable ferro-valleytricity. In our designed array architecture, nondestructive read and write operations are conducted by sensing the valley state through two different pairs of terminals, allowing for independent optimization of read/write peripheral circuits. The power consumption of our PRG-based array is remarkably low, with only ∼6 nW required per write operation and ∼2.3 nW per read operation per cell. This consumption is orders of magnitude lower than that of the majority of state-of-the-art cryogenic memories. Additionally, we engineer in-memory computation by implementing majority logic operations within our proposed nonvolatile memory array without modifying the peripheral circuitry. In conclusion, our framework presents a promising pathway toward achieving ultra-dense cryogenic memory and in-memory computation capabilities.

2D materials↗
DOE OSTI2025

Chemical Vapor Deposition-Grown Hexagonal Boron Nitride and Graphene for Tandem Dielectric Capacitive Polymer Devices

To address the low energy density of polymeric capacitors, this work explores how tandem combinations of antagonistic properties can enhance energy storage. We introduce multilayer architecture integrating chemical vapor deposition (CVD)-grown ≈2 nm hexagonal boron nitride (hBN) and graphene with ferroelectric polyvinylidene fluoride (PVDF) and linear polyetherimide (PEI) layers to suppress leakage paths, reduce loss, and promote Maxwell–Wagner–Sillars polarization. Raman spectroscopy, X-ray diffraction (XRD), atomic force microscopy (AFM), scanning electron microscopy (SEM), and plasma focused ion beam (PFIB) analyses confirm robust material integration. In conclusion, for the tandem device, E BD ≈600 V/μm, while individual layers show lower values (PVDF|Graphene (Gr)|PVDF ≈ 50 V/μm and PEI|hBN|PEI ≈ 275 V/μm), yielding an overall ≈6000% enhancement and demonstrating the effectiveness of the 2D multilayer design.

Chemical vapor deposition (CVD)↗
DOE OSTI2025

Properties of Electronic Materials

This final technical report summarizes the research conducted under DOE Grant DE-SC0002623, "Properties of Electronic Materials," led by Principal Investigator Shengbai Zhang at Rensselaer Polytechnic Institute. Over the 16-year period, the project employed first-principles computational methods to investigate the structural, electronic, and dynamic properties of a wide range of electronic materials, with applications in energy technologies, optoelectronics, and data storage. Key areas included topological insulators, phase-change materials, graphene and two-dimensional systems, perovskites for photovoltaics, defect engineering in semiconductors, kagome lattices, and ultrafast carrier dynamics. The research resulted in 115 peer-reviewed publications, advancing fundamental understanding of material behaviors at the atomic scale and contributing to innovations in renewable energy, memory devices, and quantum materials. Findings have implications for improving energy efficiency, developing lead-free solar cells, and enabling high-speed data processing. The work has trained numerous graduate students and postdocs, fostering the next generation of computational materials scientists. The original goals were to develop theoretical models and computational tools to predict and optimize electronic properties of materials for energy applications. All objectives were accomplished, with no major departures from planned methodologies. Challenges in computational scaling were addressed through access to high-performance computing resources.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Symmetry-Protected Moiré Band Engineering and Enhanced Electron–Phonon Coupling in Xe/Bi 2 Se 3 Superlattices: Path to Topological Superconductivity

Observation of superconductivity, magnetism, and correlated insulating phases driven by the moiré potential in twisted graphene bilayer has opened the exciting new field of “twistronics”. Even richer physics is expected if moiré superlattice could be generated on topological insulators; however, until now, experimental studies have been scarce. Here, we demonstrate topological moirés generated by adsorbing a monolayer of noble gas on a topological insulator. By angle-resolved photoemission spectroscopy, we show that the moiré potential replicates the topological surface state and affects it in a way fundamentally different from the trivial states. Replicated Dirac cones generally avoid crossings, except at the time-reversal invariant momenta that remain gapless. This creates van Hove singularities at the moiré Brillouin zone corners, providing the mechanism of enhancing correlations. Indeed, we observe a strong enhancement of the electron–phonon coupling strength that, if properly tuned, might lead to topological superconductivity and Majorana Fermions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Hydrodynamic electron transport near charge neutrality

We develop the theory of hydrodynamic electron transport in a long-range disorder potential for conductors in which the underlying electron liquid lacks Galilean invariance. For weak disorder, we express the transport coefficients of the system in terms of the intrinsic kinetic coefficients of the electron liquid and the correlation function of the disorder potential. We apply these results to analyze the doping and temperature dependence of transport coefficients of graphene devices. In this work, we show that at charge neutrality, long-range disorder increases the conductivity of the system above the intrinsic value. The enhancement arises from the predominantly vortical hydrodynamic flow caused by local deviations from charge neutrality. Its magnitude is inversely proportional to the shear viscosity of the electron liquid and scales as the square of the disorder correlation radius. This is qualitatively different from the situation away from charge neutrality. In that case, the flow is predominantly potential and produces negative viscous contributions to the conductivity, which are proportional to the sum of shear and bulk viscosities and inversely proportional to the square of disorder correlation radius.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Nano-FET-enabled biosensors: Materials perspective and recent advances in North America

Field-effect transistor (FET) is a very promising platform for biosensor applications due to its magnificent properties, including label-free detection, high sensitivity, fast response, real-time measurement capability, low running power, and the feasibility to miniaturize to a portable device. 1D (e.g. carbon nanotubes, Si nanowires, conductive polymer nanowires, 1D metal oxides, and others) and 2D (e.g. graphene materials, transition metal dichalcogenides, black phosphorus, and 2D metal oxides) materials, with their unique structural and electronic properties that are unavailable in bulk materials, have helped improve the sensitivity of FET biosensors and enabled detection down to single molecule. In this article, we give insights into the rapidly evolving field of 1D and 2D materials-based FET biosensors, with an emphasis on structure and electronic properties, synthesis, and biofunctionalization approaches of these nanomaterials. In addition, the progress in the 1D/2D-FET biosensors in North America, in the last decade, is summarized in tables. Moreover, challenges and future perspectives of 1D/2D-FET biosensors are covered.

1D materials↗
DOE OSTI2022

Metaplastic and energy-efficient biocompatible graphene artificial synaptic transistors for enhanced accuracy neuromorphic computing

CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to parallel data storage and processing. In contrast, the human brain is a living computational signal processing unit that operates with extreme parallelism and energy efficiency. Although numerous neuromorphic electronic devices have emerged in the last decade, most of them are rigid or contain materials that are toxic to biological systems. In this work, we report on biocompatible bilayer graphene-based artificial synaptic transistors (BLAST) capable of mimicking synaptic behavior. The BLAST devices leverage a dry ion-selective membrane, enabling long-term potentiation, with ~50 aJ/µm 2 switching energy efficiency, at least an order of magnitude lower than previous reports on two-dimensional material-based artificial synapses. The devices show unique metaplasticity, a useful feature for generalizable deep neural networks, and we demonstrate that metaplastic BLASTs outperform ideal linear synapses in classic image classification tasks. With switching energy well below the 1 fJ energy estimated per biological synapse, the proposed devices are powerful candidates for bio-interfaced online learning, bridging the gap between artificial and biological neural networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Strain-controlled magnetic ordering in 2D carbon metamaterials

Here, we use ab initio spin-polarized density functional theory to study the magnetic order in a Kagomé-like 2D metamaterial consisting of pristine or substitutionally doped phenalenyl radicals polymerized into a nanoporous, graphene-like structure. In this and in a larger class of related structures, the constituent polyaromatic hydrocarbon molecules can be considered as quantum dots that may carry a net magnetic moment. The structure of this porous system and the coupling between the quantum dots may be changed significantly by applying moderate strain, thus allowing to control the magnetic order and the underlying electronic structure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

An SECM-Based Spot Analysis for Redoxmer-Electrode Kinetics: Identifying Redox Asymmetries on Model Graphitic Carbon Interfaces

The fundamental process in non-aqueous redox flow battery (NRFB) operation revolves around electron transfer (ET) between a current collector electrode and redox-active organic molecules (redoxmers) in solution. Here, we present an approach utilizing scanning electrochemical microscopy (SECM) to evaluate interfacial ET kinetics between redoxmers and various electrode materials of interest at desired locations. This spot-analysis method relies on the measurement of heterogeneous electron transfer rate constants (k f or k b ) as a function of applied potential (E-E 0 '). As demonstrated by COMSOL simulations, this method enables the quantification of Butler-Volmer kinetic parameters, the standard heterogeneous rate constant, k 0 , and the transfer coefficient, α. Our method enabled the identification of inherent asymmetries in the ET kinetics arising during the reduction of ferrocene-based redoxmers, compared to their oxidation which displayed faster rate constants. Similar behavior was observed on a wide variety of carbon electrodes such as multi-layer graphene, highly ordered pyrolytic graphite, glassy carbon, and chemical vapor deposition-grown graphite films. However, aqueous systems and Pt do not exhibit such kinetic effects. Our analysis suggests that differential adsorption of the redoxmers is insufficient to account for our observations. Displaying a greater versatility than conventional electroanalytical methods, we demonstrate the operation of our spot analysis at concentrations up to 100 mM of redoxmer over graphite films. Looking forward, our method can be used to assess non-idealities in a variety of redoxmer/electrode/solvent systems with quantitative evaluation of kinetics for applications in redox-flow battery research.

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

Elucidating the Role of Single-Atom Pd for Electrocatalytic Hydrodechlorination

In this study, we loaded Pd catalysts onto a reduced graphene oxide (rGO) support in an atomically dispersed fashion [i.e., Pd single-atom catalysts (SACs) on rGO or Pd 1 /rGO] via a facile and scalable synthesis based on anchor-site and photoreduction techniques. The as-synthesized Pd 1 /rGO significantly outperformed the Pd nanoparticle (Pdnano) counterparts in the electrocatalytic hydrodechlorination of chlorinated phenols. Downsizing Pd nano to Pd 1 leads to a substantially higher Pd atomic efficiency (14 times that of Pdnano), remarkably reducing the cost for practical applications. The unique single-atom architecture of Pd 1 additionally affects the desorption energy of the intermediate, suppressing the catalyst poisoning by Cl – , which is a prevalent challenge with Pdnano. Characterization and experimental results demonstrate that the superior performance of Pd 1 /rGO originates from (1) enhanced interfacial electron transfer through Pd–O bonds due to the electronic metal–support interaction and (2) increased atomic H (H*) utilization efficiency by inhibiting H 2 evolution on Pd 1 . Furthermore, this work presents an important example of how the unique geometric and electronic structure of SACs can tune their catalytic performance toward beneficial use in environmental remediation applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Edge‐Driven Fringe‐Field Effects, Reduced Screening, and Bandgap Widening in Graphene Nanoribbons Enable Single‑Molecule Sensitivity

Graphene nanoribbons (GNRs) offer promising platforms for single‐molecule sensing due to their quasi‐1D channels and discrete electronic states, providing superior sensitivity toward molecular perturbations. While prior studies emphasize smoother edges as essential for optimal performance, the potential benefits of controlled edge roughness remain largely unexplored. Additionally, most investigations focus on GNR arrays, leaving critical edge‐ and width‐dependent factors, including fringe fields, bandgap widening, interactions between adsorbing molecules and GNR atoms, density of states (DOS) suppression, and electrostatic screening lengths, and their collective impact on sensitivity, poorly understood. Here, in this work, we fabricated field‐effect transistors using individual GNRs (widths: 200–20 nm) and characterized their response to molecular adsorption with perfluorooctanoic acid as the model analyte. Narrower ribbons displayed significantly enhanced sensitivity, yielding a coverage‐normalized response of 116 ± 10 mV per molecule in 20 nm‐wide GNRs (from calibrated ensemble Dirac‐point shifts). Experimental and theoretical analyses reveal that this heightened sensitivity arises from stronger fringe fields, width‐dependent quantum confinement effects, reduced DOS, and increased edge roughness that facilitates molecular anchoring, enhanced orbital overlap, and improved charge transfer efficiency. Our findings challenge the conventional assumption that smoother edges inherently enhance sensor performance, demonstrating that controlled edge disorder substantially boosts molecular sensitivity in GNR sensors.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Influence of surface chemistry on Li nucleation energetics on graphene-based surfaces

Lithium metal is a promising high-capacity anode material for solid-state batteries, but it typically suffers from poor cyclability. Carbon scaffold hosts have the potential to improve this performance due to their high electronic conductivity and large surface area, which facilitates lithium-ion adsorption and desorption. Scaffold surface chemistry is known to significantly influence performance outcomes, but the details of these interactions are not fully understood. Here, this study employs first-principles simulations to explore lithium transport and nucleation on graphene anodes with various surface chemistries. Using enhanced sampling techniques, ab initio molecular dynamics, and density functional theory calculations, we find that although surface chemistry has a minimal impact on lithium interfacial transport, it influences surface nucleation significantly. Both heteroatom dopants and intrinsic defects lower the nucleation barrier, creating a more favorable environment for lithium nucleation compared to pristine graphene. In addition, our results reveal a complex interplay between surface lithium concentration, lithium transport, and nucleation kinetics. These findings highlight the potential of surface modifications to precisely control nucleation processes on carbon-based anodes and provide design guidance for reducing dendrite formation and improving the cycle life of solid-state batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Silver Nanoparticles Functionalized Nanosilica Grown over Graphene Oxide for Enhancing Antibacterial Effect

The continuous growth of multidrug-resistant bacteria due to the overuse of antibiotics and antibacterial agents poses a threat to human health. Silver nanoparticles, silica-based materials, and graphene-based materials have become potential antibacterial candidates. In this study, we developed an effective method of enhancing the antibacterial property of graphene oxide (GO) by growing nanosilica (NS) of approximately 50 nm on the graphene oxide (GO) surface. The structures and compositions of the materials were characterized through powdered X-ray diffraction (P-XRD), transmission electron microscopy (TEM), scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDS), ultraviolet–visible spectroscopy (UV–VIS), dynamic light scattering (DLS), Raman spectroscopy (RM), Fourier-transform infrared spectroscopy (FTIR), Brunauer–Emmet–Teller (BET) surface area, and pore size determination. The silver nanoparticles (AgNPs) with an average diameter of 26 nm were functionalized on the nanosilica (NS) surface. The composite contained approximately 3% of silver nanoparticles. The silver nanoparticles on nanosilica supported over graphene oxide (GO/NS/AgNPs) exhibited a 7-log reduction of Escherichia coli and a 5.2-log reduction of Bacillus subtilis within one hour of exposure. Both GO/NS and GO/NS/AgNPs exhibited substantial antimicrobial effects against E. coli and B. subtilis.

36 MATERIALS SCIENCE↗