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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Deriving Material Properties from Feedback Error Signals in Scanning Tunneling Microscopy

Imperfections in measurements, e.g., deviations and broadening, are not devoid of information; rather, they can reveal valuable physical properties and processes. Scanning tunneling microscopy leverages a negative feedback loop to regulate the tunneling current. Practically, current fluctuates around its set point, and such deviations are considered insignificant and ignored. Here, in this study, we investigate the information embedded in these deviations. In the constant-current mode with an active feedback loop, we observe an unexpected persistent DC current offset from its set point when the tunneling junction is periodically perturbed. We demonstrate both experimentally and theoretically that such error signals encode local tunneling barrier heights and the square of local differential conductance as a consequence of the interplay between rectification and active feedback compensation. We provide evidence on the generalizability of this phenomenology to other negative feedback systems. This new approach has the potential to broadly impact physical sciences by allowing rapid measurements without lock-in amplifiers.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Topography and transport properties of oligo(phenylene ethynylene) molecular wires studied by scanning tunneling microscopy

Conjugated phenylene(ethynylene) molecular wires are of interest as potential candidates for molecular electronic devices. Scanning tunneling microscopic study of the topography and current-voltage (I-V) characteristics of self-assembled monolayers of two types of molecular wires are presented here. The study shows that the topography and I-Vs, for small scan voltages, of the two wires are quite similar and that the electronic and structural changes introduced by the substitution of an electronegative N atom in the central phenyl ring of these wires does not significantly alter the self-assembly or the transport properties.

Polymers/chemistry↗
DOE OSTI2023

Nanomechanics and Electronic Structure of Organic Photovoltaics in Real Application Conditions by Advanced Scanning Probe Microscopy (Final Technical Report for Project DE-SC0018041)

This project report consists of the following three sections: A.) Investigation of Charge Transport Properties in Semiconducting Conjugated Polymer Blends Using Computational Chemistry and Experiments: This section provides unpublished but valuable research results that correlate the electronic structure of PCBM:PCDTBT organic photovoltaic systems with their current-voltage characteristics. The presentation is structured in the form of a scientific publication. B.) Scanning Probe Microscopy Methodology Development Efforts for Organic Photovoltaic Materials: This section summarizes various published works focusing on advancements in scanning probe microscopy methods. Each sub-section corresponds to a scientific publication for which the abstract and citation are provided. C.) Other Publications Supported by the Project: This section lists additional published works partially supported by the project, which are not included in the previous two sections.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Exploring Physics of Ferroelectric Domain Walls in Real Time: Deep Learning Enabled Scanning Probe Microscopy

The functionality of ferroelastic domain walls in ferroelectric materials is explored in real-time via the in situ implementation of computer vision algorithms in scanning probe microscopy (SPM) experiment. The robust deep convolutional neural network (DCNN) is implemented based on a deep residual learning framework (Res) and holistically nested edge detection (Hed), and ensembled to minimize the out-of-distribution drift effects. The DCNN is implemented for real-time operations on SPM, converting the data stream into the semantically segmented image of domain walls and the corresponding uncertainty. Further the pre-defined experimental workflows perform piezoresponse spectroscopy measurement on thus discovered domain walls, and alternating high- and low-polarization dynamic (out-of-plane) ferroelastic domain walls in a PbTiO 3 (PTO) thin film and high polarization dynamic (out-of-plane) at short ferroelastic walls (compared with long ferroelastic walls) in a lead zirconate titanate (PZT) thin film is reported. This work establishes the framework for real-time DCNN analysis of data streams in scanning probe and other microscopies and highlights the role of out-of-distribution effects and strategies to ameliorate them in real time analytics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Stabilizing the heavily-doped and metallic phase of MoS 2 monolayers with surface functionalization

Monolayer molybdenum disulfide (MoS 2 ) is one of the most studied two-dimensional (2D) transition metal dichalcogenides that is being investigated for various optoelectronic properties, such as catalysis, sensors, photovoltaics, and batteries. One such property that makes this material attractive is the ease in which 2D MoS 2 can be converted between the semiconducting (2H) and metallic/semi-metallic (1T/1T') phases or heavily n-type doped 2H phase with ion intercalation, strain, or excess negative charge. Using n-butyl lithium (BuLi) immersion treatments, we achieve 2H MoS 2 monolayers that are heavily n-type doped with shorter immersion times (10–120 mins) or conversion to the 1T/1T' phase with longer immersion times (6–24 h); however, these doped/converted monolayers are not stable and promptly revert back to the initial 2H phase upon exposure to air. To overcome this issue and maintain the modification of the monolayer MoS 2 upon air exposure, we use BuLi treatments plus surface functionalization p-(CH 3 CH 2 ) 2 NPh-MoS 2 (Et 2 N-MoS 2 )—to maintain heavily n-type doped 2H phase or the 1T/1T' phase, which is preserved for over two weeks when on indium tin oxide or sapphire substrates. We also determine that the low sheet resistance and metallic-like properties correlate with the BuLi immersion times. These modified MoS 2 materials are characterized with confocal Raman/photoluminescence, absorption, x-ray photoelectron spectroscopy as well as scanning Kelvin probe microscopy, scanning electrochemical microscopy, and four-point probe sheet resistance measurements to quantify the differences in the monolayer optoelectronic properties. We will demonstrate chemical methodologies to control the modified monolayer MoS 2 that likely extend to other 2D transition metal dichalcogenides, which will greatly expand the uses for these nanomaterials.

2D TMDC↗
NASA NTRS1989

A scanning electron microscopy study of the macro-crystalline structure of 2-(2,4-dinitrobenzyl) pyridine

The compound, 2-(2,4-dinitrobenzyl) pyridine, was synthesized in the laboratory; an introductory level electron microscopy study of the macro-crystalline structure was conducted using the scanning electron microscope (SEM). The structure of these crystals was compared with the macrostructure of the crystal of 2-(2,4-dinitrobenzyl) pyridinium bromide, the hydrobromic salt of the compound which was also synthesized in the laboratory. A scanning electron microscopy crystal study was combined with a study of the principle of the electron microscope.

Ware, Jacqueline↗
DOE OSTI2022

Size Effect of Local Current-Voltage Characteristics of MX 2 Nanoflakes: Local Density of States Reconstruction from Scanning Tunneling Microscopy Experiments

Local current-voltage characteristics for low-dimensional transition-metal dichalcogenides (LDTMD), as well as the reconstruction of their local density of states (LDOS) from scanning tunneling microscopy (STM) experiments, are of fundamental interest and can be useful for advanced applications. Most of the existing models either have limited applicability for complex-shaped LDTMDs (e.g., those based on the Simmons approach) or require solving of an ill-defined integral equation to deconvolute the unknown LDOS (e.g., those based on the Tersoff approach). Using a serial expansion of the Tersoff formulas, we propose a flexible method to reconstruct the LDOS from local current-voltage characteristics measured in STM experiments. We establish a set of key physical parameters, which characterize the tunneling current of a STM-probe–sample contact and the sample LDOS expanded in Gaussian functions. Using a direct variational method coupled with probabilistic analysis, we determine these parameters from the STM experiments for MoS2 nanoflakes with different numbers of layers. The main result is the reconstruction of the LDOS in a relatively wide energy range around the Fermi level, which allows us to gain insight into the local band structure of LDTMDs. The reconstructed LDOS reveal pronounced size effects for the single-layer, two-layer, and three-layer MoS 2 nanoflakes, which we relate to the low dimensionality and strong bending or corrugation of the nanoflakes. We hope that the proposed elaboration of the Tersoff approach, allowing LDOS reconstruction, will be of critical interest for the quantitative description of STM experiments and also of use to better understand the microscopic physical aspects of the surface, strain, and bending contributions to the LDTMDs’ electronic properties.

42 ENGINEERING↗
NASA NTRS1999

Near-Field Scanning Optical Microscopy of Soft, Biological, or Rough Objects in Aqueous Environment: Challenges and some Remedies to Circumvent

Near-field scanning optical microscopy is an established technique for sub-wavelength spatial resolution in imaging, spectroscopy, material science, surface chemistry, polarimetry, etc. A significant amount of confidence has been established for thin hard specimens in air. However when soft, biological, rough, in aqueous environment object, or a combination is involved, the progress has been slow. The tip-sample mechanical interaction, heat effects to sample, drag effects to the probe, difficulty in controlling tip-sample separation in case of rough objects, light scattering from sample thickness, etc. create problems. Although these problems are not even fully understood, there have been attempts to study them with the aim of performing reliable operations. In this review we describe these attempts. Starting with general problems encountered, various effects like polarization, thermal, and media are covered. The roles of independent tip-sample distance control tools in the relevant situations are then described. Finally progress in fluid cell aspect has been summarized.

Vikram, C. S.↗
NASA NTRS1993

Scanning Tunneling Microscopy analysis of space-exposed polymer films

The characterization of the surface of selected space-exposed polymer films by Scanning Tunneling Microscopy (STM) is reported. Principles of STM, an emerging new technique for materials analysis, are reviewed. The analysis of several films which received up to 5.8 years of low Earth orbital (LEO) exposure onboard the NASA Long Duration Exposure Facility (LDEF) is discussed. Specimens included FEP Teflon thermal blanket material, Kapton film, and several experimental polymer films. Ultraviolet and atomic oxygen-induced crazing and erosion are described. The intent of this paper is to demonstrate how STM is enhancing the understanding of LEO space environmental effects on polymer films.

Kalil, Carol R.↗
DOE OSTI2021

Scanning SQUID microscopy in a cryogen-free dilution refrigerator

We report a scanning superconducting quantum interference device (SQUID) microscope in a cryogen-free dilution refrigerator with a base temperature at the sample stage of at least 30 mK. The microscope is rigidly mounted to the mixing chamber plate to optimize thermal anchoring of the sample. The microscope housing fits into the bore of a superconducting vector magnet, and our design accommodates a large number of wires connecting the sample and sensor. Through a combination of vibration isolation in the cryostat and a rigid microscope housing, we achieve relative vibrations between the SQUID and the sample that allow us to image with micrometer resolution over a 150 μm range while the sample stage temperature remains at base temperature. To demonstrate the capabilities of our system, we show images acquired simultaneously of the static magnetic field, magnetic susceptibility, and magnetic fields produced by a current above a superconducting micrometer-scale device.

47 OTHER INSTRUMENTATION↗
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 OSTI2025

Advancing Cross-Sectional Scanning Electron Microscopy of Perovskite Solar Cells

Organic–inorganic perovskites are an emerging class of photovoltaic materials. Despite achieving power conversion efficiencies surpassing 26%, the challenge of perovskite stability including degradation during exposure to operational conditions such as light, heat, humidity, water, oxygen, and electric fields is well known. Related, perovskite instability has limited high-resolution electron imaging and characterization techniques that can be used for understanding degradation mechanisms. Furthermore, we demonstrate perovskite device cross-section preparation using mechanical polishing in a water-free environment with cryogenic Ar ion milling. Scanning electron microscopy was then used in both backscattered electron and secondary electron imaging modes to obtain information about layer structure, grain aggregate structure, and compositional heterogeneity. Monte Carlo CASINO simulations inform optimum beam conditions and image acquisition parameters and the effects of accelerating voltage, dwell times, and frame averaging for practical image acquisition are reported.

14 SOLAR ENERGY↗
DOE OSTI2022

AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy

Over the past several decades, electron and scanning probe microscopes have become critical components of condensed matter physics, materials science and chemistry research. At the same time, the infrastructure for establishing a connection between microscopy observations and materials behaviour over a broader parameter space is lacking. In this work, we introduce AtomAI, an open-source software package bridging instrument-specific Python libraries, deep learning and simulation tools into a single ecosystem. AtomAI allows direct applications of deep neural networks for atomic and mesoscopic image segmentation converting image and spectroscopy data into class-based local descriptors for downstream tasks such as statistical and graph analysis. For atomically resolved imaging data, the output is types and positions of atomic species, with an option for subsequent refinement. AtomAI further allows the implementation of a broad range of image and spectrum analysis functions, including invariant variational autoencoders for disentangling structural factors of variation and im2spec type of encoder–decoder models for mapping structure–property relationships. Finally, our framework allows seamless connection to the first principles modelling with a Python interface on the inferred atomic positions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Decoding the shift-invariant data: applications for band-excitation scanning probe microscopy *

A shift-invariant variational autoencoder (shift-VAE) is developed as an unsupervised method for the analysis of spectral data in the presence of shifts along the parameter axis, disentangling the physically-relevant shifts from other latent variables. Using synthetic data sets, we show that the shift-VAE latent variables closely match the ground truth parameters. The shift VAE is extended towards the analysis of band-excitation piezoresponse force microscopy data, disentangling the resonance frequency shifts from the peak shape parameters in a model-free unsupervised manner. The extensions of this approach towards denoising of data and model-free dimensionality reduction in imaging and spectroscopic data are further demonstrated. This approach is universal and can also be extended to analysis of x-ray diffraction, photoluminescence, Raman spectra, and other data sets.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mic-hackathon 2024: hackathon on machine learning for electron and scanning probe microscopy

Microscopy is one of the primary sources of information on materials structure and functionality at the nanometer and atomic scales. The data generated through microscopy is often contained in well-structured datasets, enriched with extensive metadata and sample histories, although not always with the same level of detail or storage format. The broad incorporation of data management plans by major funding agencies ensures the preservation and accessibility of this data. However, deriving insights from these rich datasets remains challenging due to the lack of established code ecosystems, standardized benchmarks, and integration strategies. Correspondingly, the efficiency of data usage is very low, and time expenditures at the analysis stage are enormous. In addition to post-acquisition data analysis, the emergence of application programming interfaces by major microscope manufacturers now creates opportunities for real-time ML-based data analytics to enable automated decision making, and particularly ML-agent controlled real-time microscope operation. Despite these opportunities, there is a significant gap in integrating the ML community with the broader microscopy community, limiting the value that these methods bring to physics and materials discovery and materials optimization. Hackathons address these challenges by fostering collaboration between ML experts and microscopy professionals, encouraging the development of innovative solutions that leverage ML for microscopy and preparing the workforce of the future both for microscopy-intensive domains areas, instrument manufacturers, and ML scientists interested in real world applications for fundamental research, materials optimization, and manufacturing. The hackathon generated benchmark datasets and digital twins of microscopes that further contribute to the development of the field and establish data analysis ecosystems. All the codes can be found at GitHub(https://github.com/KalininGroup/Mic-hackathon-2024-codes-publication/tree/1.0.0.1) and Zenodo (https://zenodo.org/records/15579940).

97 MATHEMATICS AND COMPUTING↗