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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 109 records · Page 6

Nanoscale Mass Spectrometry Multimodal Imaging via Tip-Enhanced Photothermal Desorption

Materials ranging from adhesives, pharmaceuticals, lubricants, and personal care products are traditionally studied using macroscopic characterization techniques. However, their functionality is in reality defined by details of chemical organization on often noncrystalline matter with characteristic length scales on the order of microns to nanometers. Additionally, these materials are traditionally difficult to analyze using standard vacuum-based approaches that provide nanoscale chemical characterization due to their volatile and beam-sensitive nature. Therefore, approaches that operate under ambient conditions need to be developed that allow probing of nanoscale chemical phenomena and correlated functionality. Here, we demonstrate a tool for probing and visualizing local chemical environments and correlating them to material structure and functionality using advanced multimodal chemical imaging on a combined atomic force microscopy (AFM) and mass spectrometry (MS) system using tip-enhanced photothermal desorption with atmospheric pressure chemical ionization (APCI). We demonstrate enhanced performance metrics of the technique for correlated imaging and point sampling and illustrate the applicability for the analysis of trace chemicals on a human hair, additives in adhesives on paper, and pharmaceuticals samples notoriously difficult to analyze in a vacuum environment. Overall, this approach of correlating local chemical environments to structure and functionality is key to advancing research in many fields ranging from biology, to medicine, to material science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resolving Nanoscopic and Mesoscopic Heterogeneity of Fluorinated Species in Battery Solid-Electrolyte Interphases by Cryogenic Electron Microscopy

The stability of lithium batteries is tied to the physicochemical properties of the solid-electrolyte interphase (SEI). Owing to the difficulty in characterizing this sensitive interphase, the nanoscale distribution of SEI components is poorly understood. Here, we use cryogenic scanning transmission electron microscopy (cryo-STEM) to map the spatial distribution of SEI components across the metallic Li anode. We reveal that LiF, an SEI component widely believed to play an important role in battery passivation, is absent within the compact SEI film (~15 nm); instead, LiF particles (100–400 nm) precipitate across the electrode surface. We term this larger length scale as the indirect SEI regime. On the basis of these observations, we conclude that LiF cannot be a dominant contribution to anode passivation nor does it influence Li+ transport across the compact SEI film. We refine the traditional SEI structure derived from ensemble-averaged characterizations and nuance the role of SEI components on battery performance.

25 ENERGY STORAGE↗

A machine-learning approach to measure 3D sample properties from 2D Transmission Electron Microscopy images

Transmission Electron Microscopy (TEM) is a powerful tool for the characterization of materials at the nanoscale; however, its inherent two-dimensional (2D) nature poses significant challenges to accurately measure three-dimensional (3D) properties. We introduce a supervised machine-learning model that predicts 3D structural information, such as sample thickness and curvature, from a series of conventional 2D TEM images. The model, a U-Net convolutional neural network, is trained on a large synthetic dataset generated from dynamical diffraction simulations that model TEM’s complex, nonlinear image formation, accounting for sample thickness and curvature. This physically realistic framework enables exploration of a broad parameter space impractical to sample experimentally. We demonstrate that the trained model has accurate predictions for experimental single-crystal silicon samples, achieving performance comparable to established measurement techniques. This work highlights the critical role of robust, simulation-based training in overcoming the limitations of real-world imaging artifacts and inconsistent sample geometries. By integrating machine learning with numerical simulations, we offer an efficient and scalable framework for quantitative TEM analysis, paving the way for more sophisticated 3D characterization of complex materials.

Dynamical diffraction↗

Operando Infrared Nanospectroscopy of the Silicon/Electrolyte Interface during Initial Stages of Solid-Electrolyte-Interphase Layer Formation

The solid electrolyte interphase (SEI) is a critical component in Li-ion batteries; however, its nanoscale structure and composition and unstable nature make it difficult to characterize and ascertain primary functional mechanisms. We use operando nanoscale Fourier transform infrared spectroscopy (nano-FTIR) with a broadband synchrotron IR source to study the SEI formation on a thin-film Si electrode at nanometer-scale spatial resolution as a function of time and voltage. By probing the Si/carbonate electrolyte interface through a 25 nm-thick amorphous Si window/electrode, we detect molecular vibrational modes within a 10s of nanometers region adjacent to the Si surface and observe that PF6 – anions react to form LiF at 0.5 V. Spatially resolved nano-FTIR spectra showcase subtle nanoscale heterogeneities in the initial solid/liquid interface and the resulting deposited LiF. With its nanoscale resolution and high chemical specificity, operando nano-FTIR provides unique insights into the dynamics and heterogeneous formation of SEIs and opens opportunities for connecting nanoscale interfacial properties to bulk performance metrics.

Dopilka, Andrew↗

Thermal Gradient Effects on Redox Evolution and Volatility-Driven Fractionation in Ternary U/Ce/Cs Condensates

Understanding how thermal history influences redox evolution and chemical fractionation is essential for characterizing high-temperature condensation in complex materials, including nuclear debris. Here, we tested the hypothesis that distinct thermal regimes in a plasma flow reactor influence redox pathways and elemental partitioning in ternary U/Ce/Cs systems. A configurable plasma flow reactor was modified with an external tube furnace to impose two distinct thermal gradients: continuous ambient cooling and a furnace-assisted thermal hold-up near 1400 K followed by rapid cooling. Transmission electron microscopy characterized phase identity, morphology, and nanoscale element distributions, while inductively coupled plasma-mass spectrometry quantified bulk elemental ratios. Across both thermal regimes, uranium and cerium condensed as UO 2 and CeO 2 as dominant refractory oxide products. Uranium partially oxidized to α-UO 3 during extended ambient cooling, while furnace-assisted hold-up preserved UO 2 and produced partial reduction of cerium to Ce 2 O 3 . Cesium remained volatile upstream and condensed later in the reactor, forming Cs 2 O and Cs-uranate phases with the highest incorporation after thermal hold-up. Bulk ICP-MS measurements supported these observations. U/Ce ratios remained comparatively stable and Cs displayed delayed and apparent transient enrichment that matched the nanoscale measurements. This integrated approach provides a quantitative method for linking thermal gradients to redox evolution and volatility-driven fractionation. These results show how the plasma flow reactor can identify where equilibrium descriptions remain adequate and where kinetic effects from residence time and temperature history must be considered when interpreting condensation behavior in multicomponent systems.

and nuclear chemistry↗

Atomic-Scale Tracking of Topological Defect Motion and Incommensurate Charge Order Melting

Charge order pervades the phase diagrams of quantum materials where it competes with superconducting and magnetic phases, hosts electronic phase transitions and topological defects, and couples to the lattice generating intricate structural distortions. Incommensurate charge order is readily stabilized in manganese oxides, where it is associated with anomalous electronic and magnetic properties, but its nanoscale structural inhomogeneity complicates precise characterization and understanding of its relationship with competing phases. Leveraging atomic-resolution variable-temperature cryogenic scanning transmission electron microscopy, we characterize the thermal evolution of charge order as it transforms from its ground state in a model manganite system. We find that mobile networks of discommensurations and dislocations generate phase inhomogeneity and induce global incommensurability in an otherwise lattice-locked modulation. Driving the order to melt at high temperatures, the discommensuration density grows, and regions of order locally decouple from the lattice periodicity. Published by the American Physical Society 2025

Schnitzer, Noah (ORCID:0000000210421146)↗

Carbon-Binder Weight Loading Optimization for Improved Lithium-Ion Battery Rate Capability

Battery performance is strongly correlated with electrode microstructure and weight loading of the electrode components. Among them are the carbon-black and binder additives that enhance effective conductivity and provide mechanical integrity. However, these both reduce effective ionic transport in the electrolyte phase and reduce energy density. Therefore, an optimal additive loading is required to maximize performance, especially for fast charging where ionic transport is essential. Such optimization analysis is however challenging due to the nanoscale imaging limitations that prevent characterizing this additive phase and thus quantifying its impact on performance. Herein, an additive-phase generation algorithm has been developed to remedy this limitation and identify percolation threshold used to define a minimal additive loading. Improved ionic transport coefficients from reducing additive loading has been then quantified through homogenization calculation, macroscale model fitting, and experimental symmetric cell measurement, with good agreement between the methods. Rate capability test demonstrates capacity improvement at fast charge at the beginning of life, from 37% to 55%, respectively for high and low additive loading during 6C CC charging, in agreement with macroscale model, and attributed to a combination of lower cathode impedance, reduced electrode tortuosity and cathode thickness.

25 ENERGY STORAGE↗

Carbon-Binder Optimization for Lithium-Ion Battery Extreme Fast Charge

Battery performance is strongly correlated with electrode microstructure and weight loading of the electrode components. Among them are the carbon-black and binder additives that enhance effective conductivity and provide mechanical integrity. However, these both reduce effective ionic transport in the electrolyte phase and reduce energy density. Therefore, an optimal additive loading is required to maximize performance, especially for fast charging where ionic transport is essential. Such optimization analysis is however challenging due to the nanoscale imaging limitations that prevent characterizing this additive phase and thus quantifying its impact on performance. Herein, an additive-phase generation algorithm has been developed to remedy this limitation and identify percolation threshold used to define a minimal additive loading. Improved ionic transport coefficients from reducing additive loading has been then quantified through homogenization calculation, macroscale model fitting, and experimental symmetric cell measurement, with good agreement between the methods. Rate capability test demonstrates capacity improvement at fast charge at the beginning of life, from 37% to 55%, respectively for high and low additive loading during 6C CC charging, in agreement with macroscale model, and attributed to a combination of lower cathode impedance, reduced electrode tortuosity and cathode thickness.

carbon-binder additives↗

Atomistic Simulations of the Elastic Compression of Platinum Nanoparticles

Abstract The elastic behavior of nanoparticles depends strongly on particle shape, size, and crystallographic orientation. Many prior investigations have characterized the elastic modulus of nanoscale particles using experiments or simulations; however their reported values vary widely depending on the methods for measurement and calculation. To understand these discrepancies, we used classical molecular dynamics simulation to model the compression of platinum nanoparticles with two different polyhedral shapes and a range of sizes from 4 to 20 nm, loaded in two different crystal orientations. Multiple standard methods were used to calculate the elastic modulus from stress-vs-strain data for each nanoparticle. The magnitudes and particle-size dependence of the resulting moduli varied with calculation method and, even for larger nanoparticles where bulk-like behavior may be expected, the effective elastic modulus depended strongly on shape and orientation. Analysis of per-atom stress distributions indicated that the shape- and orientation-dependence arise due to stress triaxiality and inhomogeneity across the particle. When the effective elastic modulus was recalculated using a representative volume element in the center of a large nanoparticle, the elastic modulus had the expected value for each orientation and was shape independent. It is only for single-digit nanoparticles that meaningful differences emerged, where even the very center of the particle had a lower modulus due to the effect of the surface. These findings provide better understanding of the elastic properties of nanoparticles and disentangle geometric contributions (such as stress triaxiality and spatial inhomogeneity) from true changes in elastic properties of the nanoscale material.

36 MATERIALS SCIENCE↗

Nano-compositional imaging of the lanthanum silicide system at THz wavelengths

Terahertz scattering-type scanning near-field optical microscopy (THz-sSNOM) provides a noninvasive way to probe the low frequency conductivity of materials and to characterize material compositions at the nanoscale. However, the potential capability of atomic compositional analysis with THz nanoscopy remains largely unexplored. Here, we perform THz near-field imaging and spectroscopy on a model rare-earth alloy of lanthanum silicide (La–Si) which is known to exhibit diverse compositional and structural phases. We identify subwavelength spatial variations in conductivity that is manifested as alloy microstructures down to much less than 1 μ m in size and is remarkably distinct from the surface topography of the material. Signal contrasts from the near-field scattering responses enable mapping the local silicon/lanthanum content differences. These observations demonstrate that THz-sSNOM offers a new avenue to investigate the compositional heterogeneity of material phases and their related nanoscale electrical as well as optical properties.

47 OTHER INSTRUMENTATION↗

Reducing Artifacts in BF and HAADF-STEM Images of Pt/C Fuel Cells using MBIR-ARAR

Electron tomography is a powerful tool for characterization of three-dimensional (3D) nanoscale materials and devices. Bright-field (BF) and high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) are two widely used imaging modes in electron tomography. These imaging modalities have proven to be useful for characterizing the structure of carbon-supported platinum (Pt/C) electrocatalysts used in fuel cells, which are an important class of clean energy conversion systems. BF and HAADF-STEM images are typically simultaneously acquired due to the complementary information they contain, as BF-STEM is more suitable for characterizing carbon due to its ability to detect lighter elements, while HAADF-STEM is more suitable for characterizing platinum due to its sensitivity to atomic number. However, the quality of BF- and HAADF-STEM images is often compromised by various artifacts, such as local blurring due to abrupt contrast changes as well as missing wedge artifacts which can severely impact the accuracy of the reconstructed 3D images. The traditional methods of reconstruction, such as Filtered Back-projection (FBP), Simultaneous Iterative Reconstruction Technique (SIRT), and Model-Based Iterative Reconstruction (MBIR), are often not suitable for removing these artifacts effectively. Here, to address this challenge, we present a novel approach called MBIR with Artifact Reduction and Adaptive Regularization (MBIR-ARAR).

25 ENERGY STORAGE↗

Precision Calcination Mechanism of CaCO 3 to High-Porosity Nanoscale CaO CO 2 Sorbent Revealed by Direct In Situ Observations

Deploying energy storage and carbon capture at scale is hindered by the substantial endothermic penalty of decomposing CaCO 3 to CaO and CO 2 , and the rapid loss of CO 2 absorption capacity by CaO sorbent particles due to sintering at the high requisite decomposition temperatures. The decomposition reaction mechanism underlying sorbent deactivation remains unclear at the atomic level and nanoscale due to past reliance on postmortem characterization methods with insufficient spatial and temporal resolution. Thus, elucidating the important CaCO 3 decomposition reaction pathway requires direct observation by time-resolved (sub-)nanoscale methods. Here, chemical and structural dynamics during the decomposition of CaCO 3 nanoparticles to nanoporous CaO particles comprising high-surface-area CaO nanocrystallites are examined. Comparing in situ transmission electron microscopy (TEM) and synchrotron X-ray diffraction experiments gives key insights into the dynamics of nanoparticle calcination, involving anisotropic CaCO 3 thermal distortion before conversion to thermally dilated energetically stable CaO crystallites. Time-resolved TEM uncovered a novel CaO formation mechanism involving heterogeneous nucleation at extended CaCO 3 defects followed by sweeping reaction front motion across the initial CaCO 3 particle. These observations clarify longstanding, yet incomplete, reaction mechanisms and kinetic models lacking accurate information about (sub-)nanoscale dynamics, while also demonstrating calcination of CaCO 3 without sintering through rapid heating and precise temperature control.

36 MATERIALS SCIENCE↗

Two–Photon Polymerized Shape Memory Microfibers: A New Mechanical Characterization Method in Liquid

Two-photon polymerization (TPP) is widely used to create 3D micro- and nanoscale scaffolds for biological and mechanobiological studies, which often require the mechanical characterization of the TPP fabricated structures. To satisfy physiological requirements, most of the mechanical characterizations need to be conducted in liquid. However, previous characterizations of TPP fabricated structures are all conducted in air due to the limitation of conventional micro- and nanoscale mechanical testing methods. In this study, a new experimental method is reported for testing the mechanical properties of TPP-printed microfibers in liquid. The experiments show that the mechanical behaviors of the microfibers tested in liquid are significantly different from those tested in air. By controlling the TPP writing parameters, the mechanical properties of the microfibers can be tailored over a wide range to meet a variety of mechanobiology applications. In addition, it is found that, in water, the plasticly deformed microfibers can return to their predeformed shape after tensile strain is released. The shape recovery time is dependent on the size of microfibers. The experimental method represents a significant advancement in mechanical testing of TPP fabricated structures and may help release the full potential of TPP fabricated 3D tissue scaffolds for mechanobiological studies.

36 MATERIALS SCIENCE↗

Probing phonon softening in ferroelectrics by scanning probe microwave spectroscopy

Microwave measurements have recently been successfully applied to measure ferroelectric materials on the nanoscale, including detection of polarization switching and ferroelectric domain walls. In this study we discuss the question of whether scanning probe microscopy operating at microwave frequency can identify the changes associated with the soft phonon dynamics in a ferroic. The analytical expressions for the electric potential, complex impedance, and dielectric losses are derived and analyzed, since these physical quantities are linked to experimentally measurable properties of the ferroic. As a ferroic we consider virtual or proper ferroelectric with an optic phonon mode that softens at a Curie point. We also consider a decay mechanism linked to the conductance of the ferroic, thus manifesting itself as the dielectric loss in the material. Our key finding is that the influence of the soft phonon dispersion on the surface potential distribution, complex impedance, and dielectric losses are evidently strong in the vicinity (~10–30 K) of the Curie temperature. Additionally, we quantified how the spatial distribution and frequency spectra of the complex impedance and the dielectric losses react on the dynamics of the soft phonons near the Curie point. These results set the stage for characterization of polar phase transitions with nanoscale microwave measurements, providing a complementary approach to well established electromechanical measurements for fundamental understanding of ferroelectric properties as well as their applications in telecommunication and computing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Fracture resistance of hierarchical Cu–Mo nanocomposite thin films

We report the fracture behavior of high-temperature co-sputtered Cu/Mo nanocomposite thin films was investigated through in situ 3-point bend testing of pre-notched microbeams in SEM. The as-synthesized nanocomposites present hierarchical nano/microstructures composed of a matrix of phase-separated Cu–Mo with nanoscale ligaments dispersed with sub-micron scale Cu-rich islands containing Mo nano-precipitates. Results show a significant crack growth resistance in the hierarchical nanocomposite, several times higher than that measured in Cu/Mo nanoscale multilayers. Based on electron microscopy characterization, three mechanisms of crack growth resistance in the hierarchical structures are proposed: crack bridging by the Cu-rich layer, crack deflection via shear along the Cu/Mo interface, and multiple cracking. This work demonstrates an approach to increase toughness in high strength nanocomposites through interface micro-structure design.

36 MATERIALS SCIENCE↗

Carbon nanotube (CNT) reinforced 316L stainless steel composites made by laser powder bed fusion: Microstructure and wear response

Carbon nanotube (CNT) reinforced 316L stainless steel (SS) composites were fabricated by laser powder bed fusion (LPBF) additive manufacturing (AM). This study focuses on microstructure evolution, hardness, and wear behavior. The wear behavior for AM 316L SS and 1 wt% CNT/316L SS was studied by a dry sliding test under normal loads of 10, 15, and 25 N. The addition of CNT to 316L SS led to the change of solidification mode from cellular/columnar to dendritic growth, producing grain refinement. Nanoscale dendrites were observed. Although TEM characterization confirmed the existence of CNT in cell interior, most CNT were damaged, resulting in carbon material segregation along cellular/dendritic boundaries. The wear rate was found dramatically decreased due to the improved hardness. Compared to the adhesive and abrasive wear in AM 316L SS, the wear mechanism of CNT/316L composite was adhesion and oxidative wear. Furthermore, enhanced cellular/dendritic boundary strengthening by carbon segregation was the main strengthening mechanism of CNT/316L composite.

36 MATERIALS SCIENCE↗

Multimodal hard X-ray nanoprobe techniques for operando investigations of photovoltaic devices

Compared with conventional laboratory-scale X-ray techniques, synchrotron based X-rays with higher brilliance and higher coherence allow for the investigation of various material properties with high spatial resolution. The microscopic behaviours of materials can be examined using the Hard X-ray Nanoprobe beamline (I14) at Diamond Light Source, which provides a 50 nm focused beam and has been successfully employed to identify nanoscale optoelectronic features in energy-harvesting materials such as halide perovskites that exhibit local heterogeneity. We have developed X-ray beam-induced current (XBIC) measurement capability at I14 to address the growing demand for operando analysis in energy-harvesting research. Here, we demonstrate that X-ray fluorescence (XRF)/XBIC multimodal measurements are feasible at I14 and apply these newly implemented techniques to study perovskite solar cells with various additive concentrations to understand the effect of the additive on nanoscale optoelectronic performance. This expanded operando characterization capability offers the possibility of monitoring nanometre-scale compositional variations and corresponding optoelectronic features of actual solar cell configurations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗