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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 145 records · Page 8

Illuminating the Material World: Autonomous Microscopy to Understand Order, Disorder, and Everything In Between

Artificial intelligence (AI) holds immense promise for revolutionizing microscopy, yet its widespread adoption has been hindered by challenges ranging from user inexperience to limited model transferability and difficulties in operationalizing machine learning. This presentation showcases our approach to developing practical autonomy for materials discovery, aiming to accelerate the integration of AI into everyday microscopy workflows. As shown in Fig. 1, I will focus on three key areas: understanding order-disorder transitions, quantifying point defects, and achieving truly device-scale microscopy. First, I will demonstrate the power of multi-modal knowledge graphs for integrating diverse microscopy data. By combining imaging, spectroscopy, and diffraction data, these graphs provide a holistic view of material behavior, capturing the intricate relationships between different modalities [1,2]. I will present a case study on how these models illuminate the structural and chemical changes associated with irradiation in oxide thin films, revealing critical insights for designing materials for extreme environments like spaceflight and nuclear energy. Specifically, I will show how multi-modal analysis clarifies the evolution of order-disorder transitions under irradiation, a key factor influencing material performance in these applications. Next, I will address the challenge of quantifying point defects in 2D materials. We demonstrate the application of computer vision and transfer learning to accurately identify and classify various defect types, such as vacancies and substitutional atoms, and to quantify their concentrations. This information is crucial for understanding and tailoring the properties of 2D materials for applications in electronics, optoelectronics, and catalysis. For example, I will show how our models can characterize the topological distribution of point defects in MXene transition metal carbides, providing valuable insights for optimizing their performance in energy storage and separation science. Finally, I will discuss our progress toward autonomous device-scale microscopy [3,4]. We are fundamentally redesigning electron microscopes around the principles of machine reasoning, enabling automation beyond basic tasks like sample navigation and data acquisition to include sophisticated experimental design. This approach paves the way for truly reproducible and massively scaled analysis campaigns. I will emphasize the importance of autonomous microscopy platforms for high-throughput materials discovery and characterization, facilitating the rapid screening of materials for a broad range of applications and accelerating the development of next-generation technologies.

36 MATERIALS SCIENCE↗

Correlating Superconducting Qubit Performance Losses to Sidewall Near-Field Scattering via Terahertz Nanophotonics

Elucidating dielectric losses, structural heterogeneity, and interface imperfections is critical for improving coherence in superconducting qubits. However, most diagnostics rely on destructive electron microscopy or low-throughput millikelvin quantum measurements. Here, we demonstrate noninvasive terahertz (THz) nano-imaging/-spectroscopy of encapsulated niobium transmon qubits, revealing sidewall near-field scattering that correlates with qubit coherence. We further employ a THz hyperspectral line scan to probe dielectric responses and field participation at Al junction interfaces. These findings highlight the promise of THz near-field methods as a high-throughput proxy characterization tool for guiding material selection and optimizing processing protocols to improve qubit and quantum circuit performance.

Kim, Richard H.J. [Ames Lab]↗

Comprehensive single-shot biophysical cytometry using simultaneous quantitative phase imaging and Brillouin spectroscopy

Abstract Single-cell analysis, or cytometry, is a ubiquitous tool in the biomedical sciences. Whereas most cytometers use fluorescent probes to ascertain the presence or absence of targeted molecules, biophysical parameters such as the cell density, refractive index, and viscosity are difficult to obtain. In this work, we combine two complementary techniques—quantitative phase imaging and Brillouin spectroscopy—into a label-free image cytometry platform capable of measuring more than a dozen biophysical properties of individual cells simultaneously. Using a geometric simplification linked to freshly plated cells, we can acquire the cellular diameter, volume, refractive index, mass density, non-aqueous mass, fluid volume, dry volume, the fractional water content of cells, both by mass and by volume, the Brillouin shift, Brillouin linewidth, longitudinal modulus, longitudinal viscosity, the loss modulus, and the loss tangent, all from a single acquisition, and with no assumptions of underlying parameters. Our methods are validated across three cell populations, including a control population of CHO-K1 cells, cells exposed to tubulin-disrupting nocodazole, and cells under hypoosmotic shock. Our system will unlock new avenues of research in biophysics, cell biology, and medicine.

Steelman, Zachary A.↗

Ultrafast nano-imaging and nano-spectroscopy

Ultrafast pump–probe nano-imaging combines scanning probe-based optical near-field microscopy with ultrafast spectroscopy to enable imaging with deep sub-wavelength spatial resolution, femtosecond temporal resolution and simultaneous spectral resolution. Ultrafast nano-imaging has gained increased attention for its ability to provide far-from-equilibrium excitation and excited-state contrast. With coherent and nonlinear probing, coupled electron, spin and lattice dynamics on elementary timescale and length scale can be resolved. Through nano-movies, ultrafast nano-imaging visualizes correlated quantum dynamics underlying the properties of solid-state materials, semiconductors, molecular electronic, photonic, photovoltaic and other functional materials. With nanometre spatial resolution, this method probes elementary dynamic processes across multiple length scales that are otherwise obscured in conventional ultrafast spectroscopy in which heterogeneities are spatially averaged. Furthermore, this Primer describes the theoretical background and experimental implementation of ultrafast nano-imaging; signal interpretation and modelling; representative examples and a perspective for the future development of the field.

Microscopy↗

Bayesian Active Learning for Scanning Probe Microscopy: From Gaussian Processes to Hypothesis Learning

Recent progress in machine learning methods and the emerging availability of programmable interfaces for scanning probe microscopes (SPMs) have propelled automated and autonomous microscopies to the forefront of attention of the scientific community. However, enabling automated microscopy requires the development of task-specific machine learning methods, understanding the interplay between physics discovery and machine learning, and fully defined discovery workflows. This, in turn, requires balancing the physical intuition and prior knowledge of the domain scientist with rewards that define experimental goals and machine learning algorithms that can translate these to specific experimental protocols. Here, we discuss the basic principles of Bayesian active learning and illustrate its applications for SPM. We progress from the Gaussian process as a simple data-driven method and Bayesian inference for physical models as an extension of physics-based functional fits to more complex deep kernel learning methods, structured Gaussian processes, and hypothesis learning. These frameworks allow for the use of prior data, the discovery of specific functionalities as encoded in spectral data, and exploration of physical laws manifesting during the experiment. Here, the discussed framework can be universally applied to all techniques combining imaging and spectroscopy, SPM methods, nanoindentation, electron microscopy and spectroscopy, and chemical imaging methods and can be particularly impactful for destructive or irreversible measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic Force Microscopy-Based Force Spectroscopy and Multiparametric Imaging of Biomolecular and Cellular Systems

During the last three decades, a series of key technological improvements turned atomic force microscopy (AFM) into a nanoscopic laboratory to directly observe and chemically characterize molecular and cell biological systems under physiological conditions. In this work, we review key technological improvements that have established AFM as an analytical tool to observe and quantify native biological systems from the micro- to the nanoscale. Native biological systems include living tissues, cells, and cellular components such as single or complexed proteins, nucleic acids, lipids, or sugars. We showcase the procedures to customize nanoscopic chemical laboratories by functionalizing AFM tips and outline the advantages and limitations in applying different AFM modes to chemically image, sense, and manipulate biosystems at (sub)nanometer spatial and millisecond temporal resolution. We further discuss theoretical approaches to extract the kinetic and thermodynamic parameters of specific biomolecular interactions detected by AFM for single bonds and extend the discussion to multiple bonds. Finally, we highlight the potential of combining AFM with optical microscopy and spectroscopy to address the full complexity of biological systems and to tackle fundamental challenges in life sciences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Five-second STEM dislocation tomography for 300 nm thick specimen assisted by deep-learning-based noise filtering

Scanning transmission electron microscopy (STEM) is suitable for visualizing the inside of a relatively thick specimen than the conventional transmission electron microscopy, whose resolution is limited by the chromatic aberration of image forming lenses, and thus, the STEM mode has been employed frequently for computed electron tomography based three-dimensional (3D) structural characterization and combined with analytical methods such as annular dark field imaging or spectroscopies. However, the image quality of STEM is severely suffered by noise or artifacts especially when rapid imaging, in the order of millisecond per frame or faster, is pursued. Here we demonstrate a deep-learning-assisted rapid STEM tomography, which visualizes 3D dislocation arrangement only within five-second acquisition of all the tilt-series images even in a 300 nm thick steel specimen. The developed method offers a new platform for various in situ or operando 3D microanalyses in which dealing with relatively thick specimens or covering media like liquid cells are required.

47 OTHER INSTRUMENTATION↗

Thermal Stability of Quasi-1D NbS 3 Nanoribbons and Their Transformation to 2D NbS 2 : Insights from in Situ Electron Microscopy and Spectroscopy

Here in situ electron microscopy imaging and spectroscopy enabled us to study the evolution of quasi-1D NbS 3 -IV nanoribbons with respect to morphology and chemical structure at temperatures between room temperature and 1000 °C. Scanning transmission electron microscopy (STEM) experiments included imaging in the secondary electron, (transmitted) bright field, and high-angle annular dark-field modes while operating in the low kV regime. The results showed that NbS 3 -IV samples transform dramatically from smooth nanoribbons into highly textured configurations featuring polyhedral divots and steps. Similar in situ heating experiments conducted with aberration-corrected STEM revealed that bilayers of NbS 3 -IV chains convert topotactically into aligned 2H-NbS 2 sheets upon loss of sulfur. Atomic resolution imaging, fast Fourier transform analysis, and electron energy loss spectroscopy confirmed these chemical changes, from which we propose an atomistic mechanism for the NbS 3 -IV → 2H-NbS 2 conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photodetachment spectroscopy and resonant photoelectron imaging of cryogenically cooled 1-pyrenolate

We report an investigation of the 1-pyrenolate anion (PyO - ) and the 1-pyrenoxy radical (PyO) using photodetachment spectroscopy and resonant photoelectron imaging of cryogenically-cooled anions. The electron affinity of PyO is measured to be 2.4772(4) eV (19,980 ± 3 cm -1 ) from high-resolution photoelectron spectroscopy. Photodetachment spectroscopy reveals a dipole-bound state (DBS) for PyO - 280 cm-1 below the detachment threshold, as well as a broad and intense valence excited state (shape resonance) 1,077 cm-1 above the detachment threshold. The shape resonance with an excitation energy of 21,055 cm -1 is due to excitation of an electron from the highest occupied molecular orbital of PyO - to its lowest unoccupied molecular orbital in the continuum. Twenty-nine vibrational levels of the DBS are observed, including twenty-seven above-threshold vibrational levels (vibrational Feshbach resonances). Twenty-seven resonant photoelectron spectra are obtained by tuning the detachment laser to the vibrational Feshbach resonances, resulting in highly non-Franck-Condon photoelectron spectra and rich vibrational information. In total, the frequencies of twenty-one vibrational modes are obtained for the PyO radical by the combination of the photodetachment and resonant photoelectron spectroscopy, including thirteen out-of-plane bending modes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photodetachment spectroscopy and resonant photoelectron imaging of the 2-naphthoxide anion via dipole-bound excited states

We report a photodetachment spectroscopy and high-resolution resonant photoelectron imaging study of cryogenically-cooled 2-naphthoxide anions (C 10 H 7 O - ). The photodetachment spectrum revealed a dipole-bound state (DBS) 202(4) cm -1 below the detachment threshold and thirty-eight resonances corresponding to the vibrational levels of the DBS. By tuning the detachment laser to these above-threshold resonances, we obtained thirty-eight resonantly-enhanced photoelectron spectra, which were highly non-Franck-Condon as a result of mode-selective vibrational auto-detachment from the DBS. The resonances were assigned by comparing the resonant and non-resonant photoelectron spectra, assisted by the computed vibrational frequencies. Specifically, vibrational features with low Franck-Condon factors or from Franck-Condon-forbidden vibrational modes were significantly enhanced in the resonant photoelectron spectra, resulting in much richer spectroscopic information. The electron affinity of the 2-naphthoxy radical was measured accurately to be 19,387(4) cm -1 or 2.4037(5) eV. In addition, a total of seventeen vibrational frequencies were obtained for the 2-naphthoxy radical. In particular, seven Franck-Condon-forbidden out-of-plane bending modes, including the two lowest frequency modes (ν 48 at 102 cm -1 and ν47 at 171 cm -1 ), were observed, demonstrating the advantages of combining photodetachment spectroscopy and resonant photoelectron spectroscopy in obtaining vibrational information for polar radical species via DBS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the redistribution of charge in La 0.7 Sr 0.3 CrO 3 /La 0.7 Sr 0.3 MnO 3 multilayer thin films

The atomic and electronic structures of La 0.7 Sr 0.3 MnO 3 (LSMO)/La 0.7 Sr 0.3 CrO 3 (LSCO) multilayer thin films are investigated using aberration corrected scanning transmission electron microscopy (STEM) imaging and spectroscopy. Atomic resolution high angle annular dark-field reveals that LSMO layers have an expanded out-of-plane lattice parameter compared to compressed LSCO layers, contrasting with x-ray diffraction measurements. The expansion is found to result from preferential oxygen vacancy formation in LSMO during STEM sample preparation as determined by electron energy-loss spectroscopy. The La/Sr atom column intensity is also found to oscillate by about 4% between the LSMO and LSCO layers, indicative of La/Sr concentration variation. Using energy-dispersive x-ray spectroscopy in combination with image simulations, we confirm the La/Sr inhomogeneity and elucidate the origin of charge redistribution within the multilayer. These results illuminate the sensitivity of the technique to subtle structural, chemical, and electronic features that can arise to compensate charge imbalances in complex oxide heterostructures.

36 MATERIALS SCIENCE↗

Enhanced spatial resolution of Eljen-204 plastic scintillators for use in rep-rated proton diagnostics

A pixelated scintillator has been designed, fabricated, and tested using a laser-accelerated proton source for use in proton diagnostics at rep-rated laser facilities. The work presented here demonstrates the enhanced spatial resolution of thin, organic scintillators through a novel pixelation technique. Furthermore, experimental measurements using laser-generated protons incident onto 130 μm-thick scintillators indicate a >20% reduction in the scintillator point spread function (PSF) for the detectors tested. The best performing pixelated detector reduced the ~200 μm PSF of the stock material to ~150 μm. The fabrication technique may be tailored to reduce the pixel size and achieve higher spatial resolutions.

47 OTHER INSTRUMENTATION↗

Ultrafast method for scanning tunneling spectroscopy

A scanning tunneling microscope (STM) combines unique capabilities in imaging and spectroscopy with atomic precision, and it can obtain energy-resolved spectroscopic data with atomic resolution. In this paper, we utilize a recently proposed modification to the STM feedback control loop to acquire high quality d 2 I/dV 2 images. We have developed a constant differential conductance imaging method by closing the STM feedback loop with a high precision dI/dV measurement. In this mode, the tip’s vertical position is adjusted so as to keep the differential conductance constant during raster scanning of the surface. Based on this imaging mode, we propose a new technique to acquire fast and reliable scanning tunneling spectroscopy (STS) data simultaneously with the imaging.

47 OTHER INSTRUMENTATION↗

RapidEELS: machine learning for denoising and classification in rapid acquisition electron energy loss spectroscopy

Recent advances in detectors for imaging and spectroscopy have afforded in situ, rapid acquisition of hyperspectral data. While electron energy loss spectroscopy (EELS) data acquisition speeds with electron counting are regularly reaching 400 frames per second with near-zero read noise, signal to noise ratio (SNR) remains a challenge owing to fundamental counting statistics. In order to advance understanding of transient materials phenomena during rapid acquisition EELS, trustworthy analysis of noisy spectra must be demonstrated. In this study, we applied machine learning techniques to denoise high frame rate spectra, benchmarking with slower frame rate “ground truths”. The results provide a foundation for reliable use of low SNR data acquired in rapid, in-situ spectroscopy experiments. Such a tool-set is a first step toward both automation in microscopy as well as use of these methods to interrogate otherwise poorly understood transformations.

36 MATERIALS SCIENCE↗