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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Carbon Nanotubes for Space Photovoltaic Applications

Carbon nanotubes (CNTs) can be envisioned as an individual graphene sheet rolled into a seamless cylinder (single-walled, SWNT), or concentric sheets as in the case of a multi-walled carbon nanotube (MWNT) (1). The role-up vector will determine the hexagonal arrangement and "chirality" of the graphene sheet, which will establish the nanotube to be metallic or semiconducting. The optoelectronic properties will depend directly on this chiral angle and the diameter of the SWNT, with semiconductor types exhibiting a band gap energy (2). Characteristic of MWNTs are the concentric graphene layers spaced 0.34 nm apart, with diameters from 10-200 nm and lengths up to hundreds of microns (2). In the case of SWNTs, the diameters range from 0.4 - 2 nm and lengths have been reported up to 1.5 cm (3). SWNTs have the distinguishable property of "bundling" together due to van der Waal's attractions to form "ropes." A comparison of these different structural types is shown in Figure 1. The use of SWNTS in space photovoltaic (PV) applications is attractive for a variety of reasons. Carbon nanotubes as a class of materials exhibit unprecedented optical, electrical, mechanical properties, with the added benefit of being nanoscale in size which fosters ideal interaction in nanomaterial-based devices like polymeric solar cells. The optical bandgap of semiconducting SWNTs can be varied from approx. 0.4 - 1.5 eV, with this property being inversely proportional to the nanotube diameter. Recent work at GE Global Research has shown where a single nanotube device can behave as an "ideal" pn diode (5). The SWNT was bridged over a SiO2 channel between Mo contacts and exhibited an ideality factor of 1, based on a fit of the current-voltage data using the diode equation. The measured PV efficiency under a 0.8 eV monochromatic illumination showed a power conversion efficiency of 0.2 %. However, the projected efficiency of these junctions is estimated to be > 5 %, especially when one considers the enhanced absorption (from nanotubes whose bandgap is tailored to illumination) and electromagnetic coupling in a network of nanotubes.

Efstathiadis, Harry↗
DOE OSTI2024

Local Chemical Enhancement and Gating of Organic Coordinated Ionic-Electronic Transport

Superior properties in organic mixed ionic-electronic conductors (OMIECs) over inorganic counterparts have inspired intense interest in biosensing, soft-robotics, neuromorphic computing, and smart medicine. However, slow ion transport relative to charge transport in these materials is a limiting factor. Here, it is demonstrated that hydrophilic molecules local to an interfacial OMIEC nanochannel can accelerate ion transport with ion mobilities surpassing electrophoretic transport by more than an order of magnitude. Furthermore, ion access to this interfacial channel can be gated through local surface energy. This mechanism is applied in a novel sensing device, which electronically detects and characterizes chemical reaction dynamics local to the buried channel. The ability to enhance ion transport at the nanoscale in OMIECs as well as govern ion transport through local chemical signaling enables new functionalities for printable, stretchable, and biocompatible mixed conduction devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Chiral induction at the nanoscale and spin selectivity in electron transmission in chiral methylated BEDT-TTF derivatives

Great efforts have been made in the last few decades to realize electronic devices based on organic molecules. A possible approach in this field is to exploit the chirality of organic molecules for the development of spintronic devices, an applicative way to implement the chiral-induced spin selectivity (CISS) effect. In this work we exploit enantiopure tetrathiafulvalene (TTF) derivatives as chiral inducers at the nanoscale. The aim is to make use of TTF's well-known and unique semiconducting properties, to be expressed in the fields of enantio-selectivity and the chiral-induced spin selectivity (CISS) effect. Further, the experimental results shown in this paper further demonstrate how chirality and spin are deeply interrelated, as foreseen within the CISS effect theory, paving the way for the application of TTF derivatives in the field of spintronics. In this work, we demonstrate that tetramethyl-bis(ethylenedithio)-tetrathiafulvalene (TM-BEDT-TTF) (1) behaves as an efficient spin filter, as evidenced by magneto-atomic force microscopy (mc-AFM) measurements. Additionally, it is shown to be effective in transferring chirality to CdS/CdSe core–shell nanoparticles, as inferred from the analysis of circularly resolved photoluminescence spectra. This makes 1 a promising candidate for a variety of applications, ranging from plasmonics to quantum computing.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Reduced recombination via tunable surface fields in perovskite thin films

Here, the ability to reduce energy loss at semiconductor surfaces through passivation or surface field engineering is an essential step in the manufacturing of efficient photovoltaic (PV) and optoelectronic devices. Similarly, surface modification of emerging halide perovskites with quasi-two-dimensional (2D) heterostructures is now ubiquitous to achieve PV power conversion efficiencies (PCEs) >25%, yet a fundamental understanding to how these treatments function is still generally lacking. Here we use a unique combination of depth-sensitive nanoscale characterization techniques to uncover a tunable passivation strategy and mechanism found in perovskite PV devices that were the first to reach the >25% PCE milestone. Namely, treatment with hexylammonium bromide leads to the simultaneous formation of an iodide-rich 2D layer along with a Br halide gradient that extends from defective surfaces and grain boundaries into the bulk three-dimensional (3D) layer. This interface can be optimized to extend the charge carrier lifetime to record values >30 μs and to reduce interfacial recombination velocities to values as low as <7 cm s −1 .

Devices for energy harvesting↗
DOE OSTI2021

Inherent stochasticity during insulator–metal transition in VO 2

Vanadium dioxide (VO 2 ), which exhibits a near-room-temperature insulator–metal transition, has great potential in applications of neuromorphic computing devices. Although its volatile switching property, which could emulate neuron spiking, has been studied widely, nanoscale studies of the structural stochasticity across the phase transition are still lacking. In this study, using in situ transmission electron microscopy and ex situ resistive switching measurement, we successfully characterized the structural phase transition between monoclinic and rutile VO 2 at local areas in planar VO 2 /TiO 2 device configuration under external biasing. After each resistive switching, different VO 2 monoclinic crystal orientations are observed, forming different equilibrium states. We have evaluated a statistical cycle-to-cycle variation, demonstrated a stochastic nature of the volatile resistive switching, and presented an approach to study in-plane structural anisotropy. Furthermore, our microscopic studies move a big step forward toward understanding the volatile switching mechanisms and the related applications of VO 2 as the key material of neuromorphic computing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Graph Dynamical neural network approach for decoding dynamical states in ferroelectrics.

Ferroelectric materials such as BaTiO 3 show tremendous potential for emerging advances in memory devices, particular neuromorphic type devices. High density of memory can be obtained by stabilising polar domain walls at the nanoscale, regions of discontinuity between the well-defined polarization order parameter, but little is known about what controls their structure and dynamics in real nanoscale materials. Indeed, chiral polar domain walls have been observed in heterogeneous ferroelectrics, such as oxygen-deficient BaTiO 3 , but very little is known about how such polar-domains walls interact with defects. Indeed, a critical understanding of how dynamics of domain-walls depend on point-defects is crucial to create engineered ferroelectric memory devices. For this work, we perform large-scale simulations of nansocale domain-wall dynamics in pristine and defective BaTiO 3 using reactive force-field developed by us earlier (Phys. Chem. Chem. Phys., 2019, 21, 18240–18249), and capture their dynamical dependence on point defects using a graph dynamical neural-network approach, which we adapted to interrogate solids with well-defined order-parameters, and implemented using Pytorch based libraries. Our machine learning (ML) approach goes beyond the traditional post-processing methods to capture both spatial and temporal heterogeneities of large-scale molecular dynamics simulations of complex defective ferroelectric oxide materials. We crucially find that isolated oxygen vacancies introduce very localized spatial regions (~1–2 unit-cell in length) that show slow dipole relaxation due to formation of defect-dipoles, and that these defect-dipoles in turn slow the intrinsic dynamics of domain walls. Further, the roughness of domain walls, also influenced by vacancies, introduce dynamic heterogeneity along the domain-wall. As such we find a novel mechanism by which quenched disorder due to defects introduce dynamic heterogeneity thereby influencing response to external fields (particularly time varying fields) in a ferroelectric. Our study also emphasizes the need for creating digital twins of dynamical quantities to achieve autonomous in operando control of nanoscale switching.

42 ENGINEERING↗
DOE OSTI2023

Tunable Magnetic and Optical Anisotropy in ZrO 2 ‐Co Vertically Aligned Nanocomposites

Abstract Metamaterials have gained great research interest in recent years owing to their potential for property tunability, multifunctionality, and property coupling. As a new group of self‐assembled thin films, vertically aligned nanocomposite (VAN)‐based hybrid metamaterials have been demonstrated with significant anisotropic physical properties and a broad range of property tailorability, such as optical anisotropy, magnetic anisotropy, hyperbolic dispersion, and enhanced second harmonic generation properties. Herein, self‐assembled ZrO 2 ‐Co nanocomposite films, with high epitaxial quality and ultra‐fine vertically aligned Co nanopillars (with an average diameter of ≈2 nm) embedded in a ZrO 2 matrix, are fabricated using a pulsed laser deposition (PLD) method. The Co pillar density can be effectively tuned by varying the Co concentration in the target, which results in tunable optical properties and magnetic properties. Specifically, a high saturation magnetization of 100 emu cm −3 , strong out‐of‐plane magnetic anisotropy and tailorable magnetization properties are achieved via tuning the Co nanopillar density. Coupled with hyperbolic dispersion of dielectric constant from 950 to 1500 nm in wavelength, plasmonic Co metal nanopillars, and the unique dielectric ZrO 2 matrix, this new nanoscale hybrid metamaterial shows great potential for future integrated optical and magnetic device designs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Colossal oxygen vacancy formation at a fluorite-bixbyite interface

Oxygen vacancies in complex oxides are indispensable for information and energy technologies. There are several means to create oxygen vacancies in bulk materials. However, the use of ionic interfaces to create oxygen vacancies has not been fully explored. As such, we report an oxide nanobrush architecture designed to create high-density interfacial oxygen vacancies. An atomically well-defined (111) heterointerface between the fluorite CeO 2 and the bixbyite Y 2 O 3 is found to induce a charge modulation between Y 3+ and Ce 4+ ions enabled by the chemical valence mismatch between the two elements. Local structure and chemical analyses, along with theoretical calculations, suggest that more than 10% of oxygen atoms are spontaneously removed without deteriorating the lattice structure. Our fluorite–bixbyite nanobrush provides an excellent platform for the rational design of interfacial oxide architectures to precisely create, control, and transport oxygen vacancies critical for developing ionotronic and memristive devices for advanced energy and neuromorphic computing technologies.

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

Atomistic processes of surface-diffusion-induced abnormal softening in nanoscale metallic crystals

Abstract Ultrahigh surface-to-volume ratio in nanoscale materials, could dramatically facilitate mass transport, leading to surface-mediated diffusion similar to Coble-type creep in polycrystalline materials. Unfortunately, the Coble creep is just a conceptual model, and the associated physical mechanisms of mass transport have never been revealed at atomic scale. Akin to the ambiguities in Coble creep, atomic surface diffusion in nanoscale crystals remains largely unclear, especially when mediating yielding and plastic flow. Here, by using in situ nanomechanical testing under high-resolution transmission electron microscope, we find that the diffusion-assisted dislocation nucleation induces the transition from a normal to an inverse Hall-Petch-like relation of the strength-size dependence and the surface-creep leads to the abnormal softening in flow stress with the reduction in size of nanoscale silver, contrary to the classical “alternating dislocation starvation” behavior in nanoscale platinum. This work provides insights into the atomic-scale mechanisms of diffusion-mediated deformation in nanoscale materials, and impact on the design for ultrasmall-sized nanomechanical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Solid-state rigid-rod polymer composite electrolytes with nanocrystalline lithium ion pathways

A critical challenge for next-generation lithium-based batteries lies in development of electrolytes that enable thermal safety along with use of high-energy-density electrodes. We describe molecular ionic composite (MIC) electrolytes based on an aligned liquid crystalline polymer combined with ionic liquids and concentrated Li salt. This high strength (200 MPa) and non-flammable solid electrolyte possesses outstanding Li + conductivity (1 mS cm -1 at 25 °C) and electrochemical stability (5.6 V vs Li|Li + ) while suppressing dendrite growth and exhibiting low interfacial resistance (32 Ω cm 2 ) and overpotentials (≤ 120 mV @ 1 mA cm -2 ) during Li symmetric cell cycling. A heterogeneous salt doping process modifies a locally ordered polymer-ion assembly to incorporate an inter-grain network filled with defective LiFSI & LiBF 4 nanocrystals, strongly enhancing Li + conduction. Furthermore, this modular material fabrication platform shows promise for safe and high-energy-density energy storage and conversion applications, incorporating the fast transport of ceramic-like conductors with the superior flexibility of polymer electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2020

Strain-engineered high-responsivity MoTe 2 photodetector for silicon photonic integrated circuits

In integrated photonics, specific wavelengths are preferred such as 1550 nm due to low-loss transmission and the availability of optical gain in this spectral region. For chip-based photodetectors, layered two-dimensional (2D) materials bear scientific and technologically relevant properties such as electrostatic tunability and strong light-matter interactions. However, no efficient photodetector in the telecommunication C-band has been realized with 2D transition metal dichalcogenide materials due to their large optical bandgap. Furthermore, we demonstrate a MoTe 2 -based photodetector featuring strong photoresponse (responsivity = 0.5 A/W -1 ) operating at 1550 nm in silicon photonics enabled by strain engineering the 2D material. Non-planarized waveguide structures show a locally-induced bandgap change of 0.2 eV inside MoTe 2 , resulting in large photo-response, in an otherwise photo-inactive medium when unstrained. Unlike Graphene-based photodetectors relying on a gapless band structure, this photodetector shows a ~100X improved dark current, enabling an efficient noise equivalent power of 90 pW/Hz -0.5 . Such strain-engineered integrated photodetector provides new opportunities for integrated optoelectronic systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Nanotechnology for catalysis and solar energy conversion

This roadmap on Nanotechnology for Catalysis and Solar Energy Conversion focuses on the application of nanotechnology in addressing the current challenges of energy conversion: 'high efficiency, stability, safety, and the potential for low-cost/scalable manufacturing' to quote from the contributed article by Nathan Lewis. This roadmap focuses on solar-to-fuel conversion, solar water splitting, solar photovoltaics and bio-catalysis. It includes dye-sensitized solar cells (DSSCs), perovskite solar cells, and organic photovoltaics. Smart engineering of colloidal quantum materials and nanostructured electrodes will improve solar-to-fuel conversion efficiency, as described in the articles by Waiskopf and Banin and Meyer. Semiconductor nanoparticles will also improve solar energy conversion efficiency, as discussed by Boschloo et al in their article on DSSCs. Perovskite solar cells have advanced rapidly in recent years, including new ideas on 2D and 3D hybrid halide perovskites, as described by Spanopoulos et al 'Next generation' solar cells using multiple exciton generation (MEG) from hot carriers, described in the article by Nozik and Beard, could lead to remarkable improvement in photovoltaic efficiency by using quantization effects in semiconductor nanostructures (quantum dots, wires or wells). These challenges will not be met without simultaneous improvement in nanoscale characterization methods. Terahertz spectroscopy, discussed in the article by Milot et al is one example of a method that is overcoming the difficulties associated with nanoscale materials characterization by avoiding electrical contacts to nanoparticles, allowing characterization during device operation, and enabling characterization of a single nanoparticle. Besides experimental advances, computational science is also meeting the challenges of nanomaterials synthesis. The article by Kohlstedt and Schatz discusses the computational frameworks being used to predict structure–property relationships in materials and devices, including machine learning methods, with an emphasis on organic photovoltaics. The contribution by Megarity and Armstrong presents the 'electrochemical leaf' for improvements in electrochemistry and beyond. In addition, biohybrid approaches can take advantage of efficient and specific enzyme catalysts. These articles present the nanoscience and technology at the forefront of renewable energy development that will have significant benefits to society.

14 SOLAR ENERGY↗
DOE OSTI2024

Machine Learning for Predictive Performance Analysis in Charged Particle Beam Tools

Imaging methods driven by probes, electrons, and ions have played a dominant role in modern science and engineering. Opportunities for machine vision and AI that focus on consumer problems like driving and feature recognition, are now presenting themselves for automating aspects of the scientific processes. This proposal aims to enable and drive discovery in ultra-low energy implantation by taking advantage of faster processing, flexible control and detection methods, and architecture-agnostic workflows that will result in higher efficiency and shorter scientific development cycles. Custom microscope control, collection and analysis hardware will provide a framework for conducting novel in situ experiments revealing unprecedented insight into surface dynamics at the nanoscale. Ion implantation is a key capability for the semiconductor industry. As devices shrink, novel materials enter the manufacturing line, and quantum technologies transition to being more mainstream. Traditional implantation methods fall short in terms of energy, ion species, and positional precision. Here we demonstrate 1 keV focused ion beam Au implantation into Si and validate the results via atom probe tomography. We show the Au implant depth at 1 keV is 0.8 nm and that identical results for low energy ion implants can be achieved by either lowering the column voltage, or decelerating ions using bias – while maintaining a sub-micron beam focus. We compare our experimental results to static calculations using SRIM and dynamic calculations using binary collision approximation codes TRIDYN and IMSIL. A large discrepancy between the static and dynamic simulation is found that is due to lattice enrichment with high stopping power Au and surface sputtering. Additionally, we demonstrate how model details are particularly important to the simulation of these low-energy heavy-ion implantations. Finally, we discuss how our results pave a way to much lower implantation energies, while maintaining high spatial resolution.

47 OTHER INSTRUMENTATION↗
NASA NTRS2018

Magnetic Calorimeter Arrays with High Sensor Inductance and Dense Wiring

We describe prototype arrays of magnetically coupled microcalorimeters fabricated with an approach scalable to very large format arrays. The superconducting interconnections and sensor coils have sufficiently low inductance in the wiring and sufficiently high inductance in the coils in each pixel, to enable arrays containing greater than 4000 sensors and 100,000 X-ray absorbers to be used in future astrophysics missions such as Lynx. We have used projection lithography to create submicron patterns (e.g., 400-nanometer-lines and spaces) in our niobium sensor coils and wiring, integrated with gold-erbium sensor films and gold X-ray absorbers. Our prototype devices will explore the device physics of metallic magnetic calorimeters as feature sizes are reduced to nanoscale.

Magnetism↗
DOE OSTI2021

Machine learning for deep elastic strain engineering of semiconductor electronic band structure and effective mass

Abstract The controlled introduction of elastic strains is an appealing strategy for modulating the physical properties of semiconductor materials. With the recent discovery of large elastic deformation in nanoscale specimens as diverse as silicon and diamond, employing this strategy to improve device performance necessitates first-principles computations of the fundamental electronic band structure and target figures-of-merit, through the design of an optimal straining pathway. Such simulations, however, call for approaches that combine deep learning algorithms and physics of deformation with band structure calculations to custom-design electronic and optical properties. Motivated by this challenge, we present here details of a machine learning framework involving convolutional neural networks to represent the topology and curvature of band structures in k -space. These calculations enable us to identify ways in which the physical properties can be altered through “deep” elastic strain engineering up to a large fraction of the ideal strain. Algorithms capable of active learning and informed by the underlying physics were presented here for predicting the bandgap and the band structure. By training a surrogate model with ab initio computational data, our method can identify the most efficient strain energy pathway to realize physical property changes. The power of this method is further demonstrated with results from the prediction of strain states that influence the effective electron mass. We illustrate the applications of the method with specific results for diamonds, although the general deep learning technique presented here is potentially useful for optimizing the physical properties of a wide variety of semiconductor materials.

Tsymbalov, Evgenii↗
DOE OSTI2022

Micrometre-scale single-crystalline borophene on a square-lattice Cu(100) surface

Borophene, a crystalline monolayer boron sheet, is a new two-dimensional (2D) quantum material, predicted to feature tunable structure, intriguing physics and to find applications in flexible electronics, energy storage and catalysis. Nanoscale borophene flakes have been synthesized on noble-metal surfaces, but for device fabrication, one needs large single-crystal domains. In this work, we report the synthesis of borophene on a square lattice Cu(100) surface and show that incommensurate coordinations could reduce the borophene-substrate interactions and alter the borophene structures in interesting ways. Micrometer-scale single-crystal domains can form as isolated faceted islands or merge together to achieve full monolayer coverage. We have discovered a new crystal structure of borophene, with ten boron atoms and two hexagonal vacancies in the unit cell. First-principle calculations indicate that charge transfer rather than covalent bonding binds 2D boron to the copper surface, and confirm its integrity and uniformity The electronic band structure features multiple anisotropic tilted Dirac cones, heralding emergent quantum fermions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Structural properties and recrystallization effects in ion beam modified B20-type FeGe films

Disordered iron germanium (FeGe) has recently garnered interest as a testbed for a variety of magnetic phenomena as well as for use in magnetic memory and logic applications. This is partially owing to its ability to host skyrmions and antiskyrmions—nanoscale whirlpools of magnetic moments that could serve as information carriers in spintronic devices. In particular, a tunable skyrmion–antiskyrmion system may be created through precise control of the defect landscape in B20-phase FeGe, motivating the development of methods to systematically tune disorder in this material and understand the ensuing structural properties. To this end, we investigate a route for modifying magnetic properties in FeGe. In particular, we irradiate epitaxial B20-phase FeGe films with 2.8 MeV Au 4+ ions, which creates a dispersion of amorphized regions that may preferentially host antiskyrmions at densities controlled by the irradiation fluence. To further tune the disorder landscape, we conduct a systematic electron diffraction study with in situ annealing, demonstrating the ability to recrystallize controllable fractions of the material at temperatures ranging from ~150 to 250°C. Finally, we describe the crystallization kinetics using the Johnson–Mehl–Avrami–Kolmogorov model, finding that the growth of crystalline grains is consistent with diffusion-controlled one-to-two dimensional growth with a decreasing nucleation rate.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Thermoelectric Performance Enhancement by Surrounding Crystalline Semiconductors with Metallic Nanoparticles

Direct conversion of thermal energy to electricity by thermoelectric (TE) devices may play a key role in future energy production and utilization. However, relatively poor performance of current TE materials has slowed development of new energy conversion applications. Recent reports have shown that the dimensionless Figure of Merit, ZT, for TE devices can be increased beyond the state-of-the-art level by nanoscale structuring of materials to reduce their thermal conductivity. New morphologically designed TE materials have been fabricated at the NASA Langley Research Center, and their characterization is underway. These newly designed materials are based on semiconductor crystal grains whose surfaces are surrounded by metallic nanoparticles. The nanoscale particles are used to tailor the thermal and electrical conduction properties for TE applications by altering the phonon and electron transport pathways. A sample of bismuth telluride decorated with metallic nanoparticles showed less thermal conductivity and twice the electrical conductivity at room temperature as compared to pure Bi2Te3. Apparently, electrons cross easily between semiconductor crystal grains via the intervening metallic nanoparticle bridges, but phonons are scattered at the interfacing gaps. Hence, if the interfacing gap is larger than the mean free path of the phonon, thermal energy transmission from one grain to others is reduced. Here we describe the design and analysis of these new materials that offer substantial improvements in thermoelectric performance.

Kim, Hyun-Jung↗