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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Fingerprints of composite fermion Lambda levels in scanning tunneling microscopy

A composite fermion (CF) is a topological quasiparticle that emerges from a nonperturbative attachment of vortices to electrons in strongly correlated two-dimensional materials. Similar to noninteracting fermions that form Landau levels in a magnetic field, CFs can fill analogous “Lambda” levels, giving rise to the fractional quantum Hall (FQH) effect of electrons. Here, we show that Lambda levels can be directly visualized through the characteristic peak structure in the signal obtained via spectroscopy with scanning tunneling microscopy (STM) on a FQH state. Complementary to transport, which probes the low-energy properties of CFs, we show that high-energy features in STM spectra can be interpreted in terms of Lambda levels. We numerically demonstrate that STM spectra can be accurately modeled using Jain's CF theory. Our results show that STM provides a powerful tool for revealing the anatomy of FQH states and identifying physics beyond the noninteracting CF paradigm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Detecting Symmetry Breaking in Magic Angle Graphene Using Scanning Tunneling Microscopy

A growing body of experimental work suggests that magic angle twisted bilayer graphene exhibits a "cascade" of spontaneous symmetry-breaking transitions, sparking interest in the potential relationship between symmetry breaking and superconductivity. However, it has proven difficult to find experimental probes which can unambiguously identify the nature of the symmetry breaking. Here, we show how atomically resolved scanning tunneling microscopy can be used as a fingerprint of symmetry-breaking order. Further, by analyzing the pattern of sublattice polarization and "Kekulé" distortions in small magnetic fields, order parameters for each of the most competitive symmetry-breaking states can be identified. In particular, we show that the "Kramers intervalley coherent state," which theoretical work predicts to be the ground state at even integer fillings, shows a Kekulé distortion which emerges only in a magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Cathode Electrolyte Diagnostics Based on Scanning Probe Microscopy

Various processes lead to degradation of cathodes in lithium-ion batteries. Questions remain regarding mechanisms of many of these processes. Probe microscopy methods including scanning electrochemical microscopy (SECM) are capable of directly probing processes at the cathode/electrolyte interface. SECM uses a small electrode to perform rapid electrochemical analysis of transient species generated at an active cathode/electrolyte interface. This paper discusses the background of the SECM instrument and its application to lithium-ion battery research. We also describe the application of SECM methods to the study of cathode degradation processes observed in lithium-ion batteries. Specifically, we focus on characterizing the dissolution of manganese from LiMn2O4 (LMO) based on recent debate in the literature. We describe experiments to observe and characterize the electrochemical properties of manganese complexes emerging from degrading LMO electrode materials.

cathode/electrolyte interface↗
DOE OSTI2019

EGS Collab Testbed 2: Laser Scanned 4100 L Drift Map

The EGS Collab project is evaluating a site for Experiment 2 (hydraulic fracturing/shearing) at a depth of 1.25 km in the Sanford Underground Research Facility (SURF) on the 4100 Level. Two early test holes were drilled in an alcove (formerly known as Battery Charging Station) near Yates Shaft. Recently, we conducted a laser survey around the Testbed 2 to capture the details of the drift. This submission package includes the laser scanned drift map around the Testbed 2. The drift map data are presented in AutoCAD (*dxf), Leapfrog mesh (*.msh), and point cloud (*.csv) file formats. Note: The coordinate system used is local Homestake Mine Coordinate (HMC) system from an old gold mine that was in operation for over 100 years.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Basal Plane Hydrogen Evolution Activity from Mixed Metal Nitride MXenes Measured by Scanning Electrochemical Microscopy

2D early transition metal carbide and nitride MXenes have intriguing properties for electrochemical energy storage and electrocatalysis. These properties can be manipulated by modifying the basal plane chemistry. Here, mixed transition metal nitride MXenes, M-Ti 4 N 3 T x (M = V, Cr, Mo, or Mn; T x = O and/or OH), are developed by modifying pristine exfoliated Ti 4 N 3 T x MXene with V, Cr, Mo, and Mn salts using a simple solution-based method. The resulting mixed transition metal nitride MXenes contain 6–51% metal loading (cf. Ti) that exhibit rich electrochemistry including highly tunable hydrogen evolution reaction (HER) electrocatalytic activity in a 0.5 m H 2 SO 4 electrolyte as follows: V-Ti 4 N 3 T x > Cr-Ti 4 N 3 T x > Mo-Ti 4 N 3 T x > Mn-Ti 4 N 3 T x > pristine Ti 4 N 3 T x with overpotentials as low as 330 mV at -10 mA cm -2 with a charge-transfer resistance of 70 O. Scanning electrochemical microscopy (SECM) reveals the electrochemical activity of individual MXene flakes. The SECM data corroborate the bulk HER activity trend for M-Ti 4 N 3 T x as well as provide the first experimental evidence that HER results from catalysis on the MXene basal plane. These electrocatalytic results demonstrate a new pathway to tune the electrochemical properties of MXenes for water splitting and related electrochemical applications.

2D materials↗
DOE OSTI2023

Ionic Liquid-Mediated Scanning Probe Electro-Oxidative Lithography as a Novel Tool for Engineering Functional Oxide Micro- and Nano-Architectures

Functional oxides have extensively been investigated as a promising class of materials in a broad range of innovative applications. Harnessing the novel properties of functional oxides in micro- to nano-scale applications hinges on establishing advanced fabrication and manufacturing techniques able to synthesize these materials in an accurate and reliable manner. Oxidative scanning probe lithography (o-SPL), an atomic force microscopy (AFM) technique based on anodic oxidation at the water meniscus formed at the tip/substrate contact, not only combines the advantages of both “top-down” and “bottom-up” fabrication approaches, but also offers the possibility of fabricating oxide nanomaterials with high patterning accuracy. While the use of self-assembled monolayers (SAMs) broadened the application of o-SPL, significant challenges have emerged owing to the relatively limited number of SAM/solid surface combinations that can be employed for o-SPL, which constrains the ability to control the chemistry and structure of oxides formed by o-SPL. Here, in this work, a new o-SPL technique that utilizes room-temperature ionic liquids (RTILs) as the functionalizing material to mediate the electrochemistry at AFM tip/substrate contacts is reported. The results show that the new IL-mediated o-SPL (IL-o-SPL) approach allows sub-100 nm oxide features to be patterned on a model solid surface, namely steel, with an initiation voltage as low as -2 V. Moreover, this approach enables high tunability of both the chemical state and morphology of the patterned iron oxide structures. Owing to the high chemical compatibility of ILs, which derives from the possibility of synthesizing ILs able to adsorb on a wide variety of solid surfaces, IL-o-SPL can be extended to other material surfaces and provide the opportunity to accurately tailor the chemistry, morphology, and electronic properties within nanoscale domains, thus opening new pathways to the development of novel micro- and nano-architectures for advanced integrated devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Learning and Controlling Silicon Dopant Transitions in Graphene Using Scanning Transmission Electron Microscopy

A machine learning approach is introduced to determine the transition dynamics of silicon atoms on a single layer of carbon atoms, when stimulated by the electron beam of a scanning transmission electron microscope (STEM). This method is data-centric, leveraging data collected on a STEM. The data samples are processed and filtered to produce symbolic representations, which is used to train a neural network to predict transition probabilities. These learned transition dynamics are then leveraged to guide a single silicon atom throughout the lattice to pre-determined target destinations. Empirical analyses are presented that demonstrate the efficacy and generality of the approach.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Plasmon-Tunable Tip Pyramids: Monopole Nanoantennas for Near-Field Scanning Optical Microscopy

Squeezing optical fields into nanometer scale is the key step to perform spatially resolved near-field optics. In scattering-type near-field optical microscopy, this task is accomplished by nanoantennas that convert propagating radiation to local near-fields and vice versa. The usual nanoantenna is composed by an elongated metal structure whose longitudinal dimension is scaled to support dipole modes of localized surface plasmon resonances. However, monopole modes can also be explored if the elongated metal nanoparticle is electrically grounded on a flat metallic plateau that acts like a mirror providing the monopole's image that closes the dipole system. Here, a method for batch production of monopole nanoantennas for scattering-type near-field scanning optical microscopy is presented. The nanoantennas are composed of a micropyramidal body with a nanopyramidal end whose lateral dimension can be scaled to fine-tune localized surface plasmon resonance modes. In conclusion, the monopole character of the nanoantennas is revealed by electron energy loss spectroscopy, and their efficiency and reproducibility are tested in tip-enhanced Raman spectroscopy experiments performed on single-layer graphene and single-walled carbon nanotubes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy

Abstract Physics‐driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics‐based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization (BO) methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure–property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk‐ and edge plasmon discovery in MnPS 3 , a lesser‐known beam‐sensitive layered 2D material. This approach is universal, can be directly used as‐is with any specimen, and is expected to be applicable to any probe‐based microscopic techniques including other STEM modalities, scanning probe microscopies, chemical, and optical imaging.

42 ENGINEERING↗
DOE OSTI2022

Prediction of curing kinetics of resorcinol‐added resole phenolic resins using differential scanning calorimetry for the fabrication of carbon/carbon composites

Phenolic resins are commonly used as carbon precursors for the fabrication of carbon/carbon composites due to their high carbon yield and aromatic nature. To decrease curing times, acid catalysts are generally used, but the addition of resorcinol was found to have a similar effect while being incorporated into the resin matrix with no contamination or corrosion issues. In this work, the curing kinetics of pure, 10, 20, and 30 wt% resorcinol-added phenolic resins were investigated through differential scanning calorimetry. Heating rates of 0.5, 1, 2.5, and 5°C min -1 were used with several curing models to predict isothermal curing. Averaged mean absolute error (MAE) for the isoconversional mathematical approaches namely Kissinger–Akahira–Sunose (MAE = 12.9 min), Flynn–Wall–Ozawa (15.8 min), and Vyazovkin (14 min) show that these methods provide the best predictions, attributed to their adoption of an activation energy that depends on the extent of cure (E a (α)). The Kissinger method (MAE = 36 min), which depends only on peak temperature with a constant activation energy assumption, and the data noise sensitive Friedman model (MAE = 1144.7 min) provide the least accurate results. Thermogravimetric analysis revealed that resorcinol decreases the curing times by up to 71% without lowering carbon yield.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Probing the Location and Speciation of Elements in Zeolites with Correlated Atom Probe Tomography and Scanning Transmission X-Ray Microscopy

Characterizing materials at nanoscale resolution to provide new insights into structure property performance relationships continues to be a challenging research target due to the inherently low signal from small sample volumes, and is even more difficult for nonconductive materials, such as zeolites. Thus, we present the characterization of a single Cu-exchanged zeolite crystal, namely Cu-SSZ-13, used for NO X reduction in automotive emissions, that was subject to a simulated 135,000-mile aging. By correlating Atom Probe Tomography (APT), a single atom microscopy method, and Scanning Transmission X-ray Microscopy (STXM), which produces high spatial resolution X-ray Absorption Near Edge Spectroscopy (XANES) maps, we show that a spatially non-uniform proportion of the Al was removed from the zeolite framework. Here, the techniques reveal that this degradation is heterogeneous at length scales from micrometers to tens of nanometers, providing complementary insight into the long-term deactivation of this catalyst system.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nanoscale properties of lead halide perovskites by scanning tunneling microscopy

Since the introduction of lead halide perovskites, tremendous progress has been made regarding their stability, reproducibility and durability. However, one of the issues that remains is related to the interfacial atomic structure arrangement and structure-property relationship under optical and electrical stimuli. In this critical review, we highlight the recent progress using scanning tunneling microscopy (STM) to understand the nanoscale properties and dynamic processes occurring in these halide perovskite materials. STM is known to be a very challenging technique, which is reflected by the low number of relevant publications in the last years. These initial reports mirror the unique potential of STM to give Ångstrom-scale insight into the (opto)-electronic properties, morphology and underlying electronic structure and provide a path toward harnessing the full potential of these materials. However, care must be taken to understand the effects of the perturbations caused by STM and tailor the measurement conditions accordingly.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electron Microscopy Transfer System to Protect Atmosphere‐Sensitive Materials for Scanning Electron Microscopy Characterization

Atmosphere- and/or moisture-sensitive materials can be challenging to characterize using electron microscopy techniques due to sample preparation workflows that generally require exposure to ambient conditions. Here, we describe a novel preparation method that uses aluminum foil in combination with a commercial cryo-EM transfer system to circumvent undesired exposure to the atmosphere. First, hygroscopic MgCl 2 was used as a model material, and prepared samples (both protected and unprotected) were placed in a controlled-humidity environment (> 80% relative humidity) for various exposure lengths (circa seconds to hours). Following this, the effectiveness of the sample preparation method was determined by comparing qualitative photos and quantitative X-ray diffraction patterns between the two sample subsets. The combined results of these experiments suggest that the outlined preparation method effectively protects MgCl 2 from atmospheric contamination compared to MgCl 2 samples that had no protective measures taken. Finally, the preparation method was utilized to protect a highly hygroscopic crystalline BaO thin film for characterization via scanning electron microscopy, thereby demonstrating a functional application of the outlined preparation technique and an additional use for the commercial cryo-EM transfer system beyond its intended application.

atmosphere-sensitive materials↗
DOE OSTI2016

Locating the electrical junctions in Cu(In,Ga)Se 2 and Cu 2 ZnSnSe 4 solar cells by scanning capacitance spectroscopy

Here, we determined the electrical junction (EJ) locations in Cu(In,Ga)Se 2 (CIGS) and Cu 2 ZnSnSe 4 (CZTS) solar cells with ~20-nm accuracy by developing scanning capacitance spectroscopy (SCS) applicable to the thin-film devices. Cross-sectional sample preparation for the SCS measurement was developed by high-energy ion milling at room temperature for polishing the cross section to make it flat, followed by low-energy ion milling at liquid nitrogen temperature for removing the damaged layer and subsequent annealing for growing a native oxide layer. The SCS shows distinct p-type, transitional, and n-type spectra across the devices, and the spectral features change rapidly with location in the depletion region, which results in determining the EJ with ~20-nm resolution. We found an n-type CIGS in the region next to the CIGS/CdS interface; thus, the cell is a homojunction. The EJ is ~40 nm from the interface on the CIGS side. In contrast, such an n-type CZTS was not found in the CZTS/CdS cells. The EJ is ~20 nm from the CZTS/CdS interface, which is consistent with asymmetrical carrier concentrations of the p-CZTS and n-CdS in a heterojunction cell. Our results of unambiguously determination of the junction locations contribute significantly to understanding the large open-circuit voltage difference between CIGS and CZTS.

14 SOLAR ENERGY↗
DOE OSTI2018

Deformation of elastomeric pyramid pen arrays in cantilever-free scanning probe lithography

Cantilever-free scanning probe lithography (SPL) employs soft elastomeric pen arrays to deliver material or energy to a surface to achieve a high-resolution, high-throughput, and low-cost nanopatterning. In particular, microscale elastomeric pyramid pen arrays are often adopted as the cantilever-free architecture owing to their distinct structural and mechanical properties. To better understand the mechanical behavior of the elastomeric pyramid pen array during the lithographic printing process, we numerically investigate the compression of an elastomeric pyramid array in a nonadhesive and frictionless contact with a rigid substrate. Simple scaling laws of the width of the contact surface with respect to the compression displacement and force are found and compared with previous models and experiments. By changing the interpyramid distance or the thickness of the base of the pyramid array, increasing deviations from the established scaling laws are observed and explained. Finally, we demonstrate that the unique morphology of a compressed pyramid primarily determines the unusual shape of the features fabricated by a specific cantilever-free SPL technique.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hollow Ptychography: Toward Simultaneous 4D Scanning Transmission Electron Microscopy and Electron Energy Loss Spectroscopy

With the recent development of high-acquisition-speed pixelated detectors, 4D scanning transmission electron microscopy (4D-STEM) is becoming routinely available in high-resolution electron microscopy. 4D-STEM acts as a “universal” method that provides local information on materials that is challenging to extract from bulk techniques. It extends conventional STEM imaging to include super-resolution techniques and to provide quantitative phase-based information, such as differential phase contrast, ptychography, or Bloch wave phase retrieval. However, an important missing factor is the chemical and bonding information provided by electron energy loss spectroscopy (EELS). 4D-STEM and EELS cannot currently be acquired simultaneously due to the overlapping geometry of the detectors. Here, the feasibility of modifying the detector geometry to overcome this challenge for bulk specimens is demonstrated, and the use of a partial or defective detector for ptycholgaphic structural imaging is explored. Here, results show that structural information beyond the diffraction-limit and chemical information from the material can be extracted together, resulting in simultaneous multi-modal measurements, adding the additional dimensions of spectral information to 4D datasets.

4D-scanning transmitting electron microscopy (STEM↗
DOE OSTI2024

A Machine Learning Approach to Quantitative Analysis of Enamel Microstructure from Scanning Electron Microscopy Images

Dental enamel, the outermost tissue of mammalian teeth, must withstand a lifetime of wear and cyclic contact. To meet this demand, enamel possesses a combination of high hardness and resistance to fracture, properties that are typically mutually exclusive. The impressive damage tolerance has been attributed largely to decussation of the enamel rods, the principal unit of its microstructure. As such, enamel is inspiring the design of next‐generation structural materials. However, quantitative descriptions of the decussated enamel rod microstructure remain limited due to challenges encountered in applying computed tomography and in acquiring quality images appropriate for traditional digital processing methods. Here, a machine learning segmentation method is applied to images of the enamel obtained using scanning electron microscopy to support quantitative analysis of the microstructure. A pretrained convolutional neural network is used to expand the input training image dataset to allow the training of a random forest classifier, which ultimately segments the image with a very small training set ( n = 3 images). A validation of this segmentation method is presented, in addition to its application to calculate relevant microstructural parameters for images of tooth enamel from selected mammalian species. The methodology applied here is equally applicable to other hard tissues.

36 MATERIALS SCIENCE↗