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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 OSTI2024

Unveiling the nanoscale architectures and dynamics of protein assembly with in situ atomic force microscopy

Proteins play a vital role in different biological processes by forming complexes through precise folding with exclusive inter- and intra-molecular interactions. Understanding the structural and regulatory mechanisms underlying protein complex formation provides insights into biophysical processes. Furthermore, the principle of protein assembly gives guidelines for new biomimetic materials with potential applications in medicine, energy, and nanotechnology. Atomic force microscopy (AFM) is a powerful tool for investigating protein assembly and interactions across spatial scales (single molecules to cells) and temporal scales (milliseconds to days). It has significantly contributed to understanding nanoscale architectures, inter- and intra-molecular interactions, and regulatory elements that determine protein structures, assemblies, and functions. This review describes recent advancements in elucidating protein assemblies with in situ AFM. We discuss the structures, diffusions, interactions, and assembly dynamics of proteins captured by conventional and high-speed AFM in near-native environments and recent AFM developments in the multimodal high-resolution imaging, bimodal imaging, live cell imaging, and machine-learning-enhanced data analysis. These approaches show the significance of broadening the horizons of AFM and enable unprecedented explorations of protein assembly for biomaterial design and biomedical research.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Global warming potential estimates of mass timber constructions beyond the first life: A dynamic radiative forcing modeling approach

In the face of a warming planet, steps must be taken to reduce the greenhouse gas emissions (GHG) associated with our building industry, which is a significant contributor to global emissions. Large, prefabricated wood elements such as mass timber panels (MTP) have great potential to achieve these reductions as they help displace high-embodied‑carbon materials like concrete and steel. Furthermore, storing the wood's biogenic carbon in buildings benefits the climate because it delays the eventual release of the carbon into the atmosphere. While these climate impacts have been assessed for the construction phase of mass timber buildings, relatively few life cycle assessment (LCA) studies have evaluated the climate impacts for the buildings' end-of-life (EOL) phase. This research estimates the climate impacts of four EOL scenarios for MTP: reusing as MTP, recycling into particleboard, incinerating, and landfilling. Using dynamic radiative forcing modeling and factoring in temporal GHG emissions and biogenic carbon storage, the global warming potential impacts are calculated for construction, deconstruction, and EOL processing of hybrid mass timber buildings in the U.S. Pacific Northwest for 160 years (GWP 160 ). The 160-year temporal scale used in this paper is an arbitrary scale, with the first 80 years being the assumed life of the building, followed by a series of reuse, recycle, or disposal scenarios over the second 80 years of that temporal scale. Of the four EOL scenarios considered in this paper, the ‘reuse’ scenario has the lowest net GWP 160 impact (calculated by summing the GWP 160 and carbon storage benefits, i.e., GWP$^{bioCS}_{160}$ ), emerging as a climate-preferred scenario, followed by ‘landfill’, ‘incinerate’, and ‘recycle’ scenarios. The lower net GWP 160 impact associated with the reuse scenario is due to the low fossil carbon emissions during EOL processing, as well as the biogenic carbon storage benefits. The results of this study also highlight the importance of efficient reuse and recycling strategies for wood in MTP.

42 ENGINEERING↗
DOE OSTI2024

Atomic force microscopy monitoring of subcritical slow crack growth in soda lime silicate glass

Prediction of brittle fracture in silicate glasses requires a fundamental understanding of slow crack growth rates, far below the critical stress intensity (K IC ) of the material. Here, in this study, atomic force microscopy (AFM) was used to characterize slow crack propagation in soda lime silicate glasses. Using large-sample AFM systems with specialized tips and scanners, fractures less than 20 nm wide were measured as a function of relative humidity (RH). The results were found to be sensitive to the type of AFM tip used and to the dryness of the surface. Continuous scanning and image capture over several days allowed the determination of the crack tip velocity. The dependance of crack tip velocity on RH was measured by enclosing the sample and AFM head in a humidity-controlled chamber. The crack tip velocity was measured as low 4.0×10 -12 m/s at 15 % RH and as high as 3.7×10 -10 m/s at 40 % RH. Overall crack growth was smooth during the AFM scan. Additionally, recession of the crack tip was noted as the sample dried, indicating crack tip closure may be occurring. Further studies on alternative compositions will provide details on subcritical fracture processes in a range of different environmental conditions.

Atomic force microscopy↗
DOE OSTI2025

High-fidelity forced convection simulations of the University of Wisconsin–Madison air-cooled reactor cavity cooling system

Among the various types of advanced nuclear technologies that exist, high-temperature gas-cooled reactors (HTGRs) stand out for their co-generation capabilities and exceptional passive safety systems. HTGRs rely on a reactor cavity cooling system (RCCS) to remove decay heat from the reactor pressure vessel (RPV) during the course of long-term transients. Several studies have focused on experimental and numerical modeling of the RCCS; however, the literature reveals a notable gap when it comes to high-fidelity simulations such as direct numerical simulations (DNS) or large eddy simulation (LES) models of the RCCS. An LES model was developed for forced convection inside the RCCS so as to obtain a high-fidelity representation of the RCCS at a scale never before attempted. Furthermore, the LES model was compared against three different Reynolds-averaged Navier–Stokes (RANS) models (Realizable k − ϵ, k − ω SST, and Reynolds stress model [RSM]). This comparison verified the robustness and accuracy of the turbulence modeling approach of the RANS models for the RCCS. Finally, based on the comparison between the LES and the RANS models, the k − ω SST RANS model of the experimental facility was developed and compared against the available experimental data.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Characterization of Polyamide Thin Films by Atomic Force Microscopy

This study directly compares the mechanical behavior of novel molecular layer deposition (MLD) and analogous interfacial polymerization (IP) polyamide thin films in environments relevant to reverse osmosis (RO) membrane operation. The elastic modulus of the films was determined using atomic force microscopy (AFM) in dry, hydrated, and chlorinated states. Surface roughness characteristics were also obtained given their potential influence on AFM modulus measurements. The much smoother MLD films demonstrated a statistically higher modulus in all states as compared to their IP counterparts. The MLD films maintained a modulus ~3X and ~5X greater than that of IP films after hydration and chlorination, respectively. Such differences in behavior may be due to the higher density and correspondingly lower void content of the MLD films. Results from this study provide a rationale for future development of MLD for fabrication of polyamide films for incorporation in RO membranes.

atomic force microscopy↗
DOE OSTI2026

A Transferable Force Field for Simulating Adsorption in Metal–Organic Frameworks with Open Metal Sites Based on the 12–6–4 Lennard-Jones Potential

Metal−organic frameworks (MOFs) that contain coordinatively unsaturated open metal sites (OMSs) provide strong host− guest interactions, making them promising sorbents for low-concentration gas adsorption applications such as direct air capture and atmospheric water harvesting. However, accurately modeling host−guest interactions involving OMSs remains challenging for classical force fields (FFs) based on the 12−6 Lennard−Jones (LJ) potential, as the polarization effect of the guest molecule induced by the positively charged OMS is not considered. Here, we introduce an FF based on the 12−6−4 LJ potential, which incorporates charge−induced dipole interactions and is parametrized against a diverse set of host−guest potential energy surfaces (PESs) obtained from density functional theory (DFT). The resulting FF, trained on a generic trimetallic cluster, performs well in both host−guest binding energetics and gas adsorption isotherms across different OMS-containing MOFs, including MOF-74 series and Cu-BTC. These results highlight the excellent transferability of our approach and its potential to enhance the accuracy and robustness of high-throughput MOF discovery workflows, particularly for gas adsorption and separation in large and diverse MOF databases.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ReaxFF Reactive Force Field for Exploring Electronically Switchable Polarization in Zn 1– x Mg x O Ferroelectric Semiconductors

Cation misfit in traditional ferroelectric crystals offers a new material platform that can drive electronic components toward structural miniaturization and high-density integration, enabling deviation from von-Neumann architectures. Here, we explore ferroelectricity in Zn 1–x Mg x O, a nontraditional ferroelectric material with tunable properties. Using data from density-functional theory calculations, we have developed a ReaxFF reactive force field to explore the ferroelectric properties of Zn 1–x Mg x O and reveal the hysteresis behavior. We discover that ferroelectric switching can be observed at a critical thickness of 10 nm with a residual polarization of ~100 μC/cm 2 . Our analysis indicates that an increase in Mg-substitution correlates with a decrease in the coercive field. We also observe a strong temperature dependence of the coercive field in Zn 1–x Mg x O, with values decreasing as the temperature increases. Additionally, we find that the distribution of Mg atoms significantly impacts the coercive field, with a clustered distribution leading to a substantial increase. In particular, a decrease in coercive field values is observed when Mg atoms are randomly distributed, compared to uniform distribution. Furthermore, leveraging tunable hysteresis behavior offered by varied percentages and distribution of Mg-substitution provides valuable insights into the design of next-generation functional devices and will inspire further investigations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Kelvin Probe Force Microscopy Imaging of Plasticity in Hydrogenated Perovskite Nickelate Multilevel Neuromorphic Devices

Ion drift in nanoscale electronically inhomogeneous semiconductors is among the most important mechanisms being studied for designing neuromorphic computing hardware. However, nondestructive imaging of the ion drift in operando devices directly responsible for multiresistance states and synaptic memory represents a formidable challenge. Here, we present Kelvin probe force microscopy imaging of hydrogen-doped perovskite nickelate device channels subject to high-speed electric field pulses to directly visualize proton distribution by monitoring surface potential changes spatially, which is also supported with finite element-based electric field distribution studies. First-principles calculations provide mechanistic insights into the origin of surface potential changes as a function of hydrogen donor doping that serves as the contrast mechanism. We demonstrate 128 (7-bit) nonvolatile conductance levels in such devices relevant to in-memory computing applications. The synaptic plasticity measurements are implemented in spiking neural networks and show promising results for classification (SciKit Learn’s Iris and Wine data sets) and control (OpenAI’s CartPole-v1 and BipedalWalker-v3) simulation tasks.

Kelvin probe force microscopy↗
DOE OSTI2024

Impacts of Topography-Based Subgrid Scheme and Downscaling of Atmospheric Forcing on Modeling Land Surface Processes in the Conterminous US

The effects of small-scale topography-induced land surface heterogeneity are not well represented in current Earth System Models (ESMs). In this study, a new topography-based subgrid structure referred to as topographic units (TGU) designed to better capture subgrid topographic effects, and methods to downscale atmospheric forcing to the land TGUs have been implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM). Effects of the subgrid scheme and downscaling methods on ELM simulated land surface processes are evaluated over the conterminous United States (CONUS). For this purpose, ELM simulations are performed using two configurations without (NoD ELM) and with (D ELM) downscaling, both using TGUs derived for the 0.5-degree grids and the same land surface parameters. Simulations using the two ELM configurations are compared over the CONUS domain, regional levels, and at observational sites (e.g., SNOTEL). The CONUS-level results suggest that D ELM simulates more snowfall and snow water equivalent (SWE), higher runoff, and less ET during spring and summer. Regional-level results suggest more pronounced impacts of downscaling over regions dominated by higher elevation TGUs and regions with maximum precipitation occurring during cool seasons. Results at the SNOTEL sites suggest that D ELM has superior capability of reproducing the observed SWE at 83% of the sites, with more pronounced performance over topographically heterogeneous TGUs with their maximum precipitation occurring during cool seasons. The results highlight the importance of improving representation of small-scale surface heterogeneity in ESMs and motivate future research to understand their effects on land-atmosphere interactions, streamflow, and water resources management over mountainous regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Seasonality and Albedo Dependence of Cloud Radiative Forcing in the Upper Colorado River Basin

Mountains create and enhance their own clouds, which both scatter and absorb shortwave radiation from the sun and absorb and re-emit land surface and atmospheric longwave radiation. However, the impacts of clouds on the surface radiation balance in high elevation snowy mountain terrain are poorly explored. In this study, we use data collected by the SAIL field campaign and partner organizations in the upper elevations (2,880 m.a.s.l) of the Upper Colorado River Basin (UCRB) over a 21-month period from September 2021 to June 2023 to estimate Cloud Radiative Forcing (CRF) in the shortwave, longwave, and the net effect. Longwave warming effects dominate during the winter when snow albedos are high (0.8–0.9) and the background atmospheric precipitable water vapor is low (<0.5 cm), yielding a maximum monthly average net CRF of +34.7 W·m -2 , meaning that clouds increase the net radiation relative to clear skies during this time period. The sign of net CRF switches in the warm season as snow recedes, sun-angles increase, and the North American monsoon arrives, yielding a minimum monthly average net CRF of -47.6 W·m -2 with hourly minima of -600 W·m -2 . The sign of net CRF is typically positive, even at solar noon, when the surface is snow covered, except for a brief period over melting, low-albedo snow (0.5–0.6) impacted by dust impurities. Sensitivity tests elucidate the role of the surface albedo on the net CRF. The results suggest that net CRF will increase in magnitude and lead to a more persistent cooling effect on the surface net radiation budget as the snow cover declines.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Deep generative learning of magnetic frustration in artificial spin ice from magnetic force microscopy images

Increasingly large datasets of microscopic images with nanoscale resolution facilitate the development of machine learning methods to identify and analyze subtle physical phenomena embedded within the images. In this work, microscopic images of honeycomb lattice spin-ice samples serve as datasets from which we automate the calculation of net magnetic moments and directional orientations of spin-ice configurations. In the first stage of our workflow, machine learning models are trained to accurately predict magnetic moments and directions within spin-ice structures. Variational Autoencoders (VAEs), an emergent unsupervised deep learning technique, are employed to generate high-quality synthetic magnetic force microscopy (MFM) images and extract latent feature representations, thereby reducing experimental and segmentation errors. The second stage of proposed methodology enables precise identification and prediction of frustrated vertices and nanomagnetic segments, effectively correlating structural and functional aspects of microscopic images. This facilitates the design of optimized spin-ice configurations with controlled frustration patterns, enabling potential on-demand synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A bi-channel aided stitching of atomic force microscopy images

Microscopy is an essential tool in scientific research, enabling the visualization of structures at micro- and nanoscale resolutions. However, the field of microscopy often encounters limitations in field-of-view (FOV), restricting the amount of sample that can be imaged in a single capture. To overcome this limitation, image stitching techniques have been developed to seamlessly merge multiple overlapping images into a single, high-resolution composite. The images collected from microscope need to be optimally stitched before accurate physical information can be extracted from post analysis. However, the existing stitching tools either struggle to stitch images together when the microscopy images are feature sparse or cannot address all the transformations of images when performing image stitching. To address these issues, we propose a bi-channel aided feature-based image stitching method and demonstrate its use on Atomic Force Microscopy (AFM) generated Pantoea sp. YR343 biofilm and PTO thin film sample images as experimental data. The topographical channel image of AFM data captures the morphological details of the sample, and a stitched topographical image is desired for researchers. We utilize the amplitude and phase channels of AFM data to maximize the matching features and to estimate the position of the original topographical images and show that the proposed bi-channel aided stitching method outperforms the traditional direct stitching approach in AFM topographical image stitching task. Here, we demonstrated the application on AFM, but similar approaches could be employed of optical microscopy with brightfield and fluorescence channels. We believe this proposed workflow can serve as a valuable augmentation strategy for microscopy image stitching tasks and will benefit the experimentalist to avoid erroneous analysis and discovery due to incorrect stitching.

Atomic force microscopy↗
DOE OSTI2024

Coriolis forces modify magnetostatic ponderomotive potentials

It is possible to produce a ponderomotive effect in a plasma system without time-varying fields, if the plasma flows over spatial oscillations in the field. This can be achieved by superimposing a spatially oscillatory perturbation on a guide field, then setting up an electric field perpendicular to the guide field to drive flow over the perturbation. However, subtle distinctions in the structure of the resulting electric field can entirely change the behavior of the resulting ponderomotive force. Previous work has shown that, in slab models, these distinctions can be explained in terms of the polarization of the effective wave that appears in the co-moving frame. Here, we consider what happens to this picture in a cylindrical system, where the transformation to the co-moving (rotating) frame is not inertial. It turns out that the non-inertial nature of this frame transformation can lead to counterintuitive behavior, partly due to the appearance of parallel (magnetic-field-aligned) electric fields in the rotating frame even in cases where none existed in the laboratory frame. Apart from the academic interest of this study, the practical impact lies in being better able to anticipate the antenna configuration on the plasma periphery of a cylindrical plasma that will lead to optimal ponderomotive barrier formation in the interior plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Morphological Characterization of Uranyl Fluoride Particles via Atomic Force Microscopy

Uranium hexafluoride (UF 6 ) undergoes a rapid hydrolysis reaction when exposed to atmospheric water. In addition to producing hazardous HF gas, the hydrolysis reaction produces uranyl fluoride (UO 2 F 2 ), a radioactive solid phase particulate material. Because of the technological utility of UF 6 in the nuclear fuel cycle, understanding the transport properties of UO 2 F 2 aerosol produced via UF 6 hydrolysis is important for accident scenarios. Moreover, the fundamental chemical and physical properties of the UF 6 hydrolysis reaction are not completely understood. Recently, several experiments on the aerosol phase properties of UO 2 F 2 produced in this way have shown that under most relevant conditions, the particle size distribution (PSD) of UO 2 F 2 can be extremely small, approximately 3 to 5 nm, which is well below the threshold that can be routinely observed via scanning electron microscopy (SEM). Although readily observable in the aerosol phase, observation of nanometer-sized particles in the condensed phase (i.e. deposited on surfaces) remains a challenge. Here, in this study, we have used atomic force microscopy (AFM) to study the PSD and morphological characteristics of UO 2 F 2 deposited at low and high concentrations under different humidity conditions, a primary variable in the hydrolysis reaction. Here, we find strong agreement between PSD measured in the aerosol phase via scanning mobility particle sizing and PSD measured via AFM, with particle sizes peaked below 4 nm for low-humidity conditions. At higher humidity, the distribution is centered around 5 to 10 nm but extends up to 20 nm. These results are in stark contrast to previous measurements using SEM that show PSD on the order of 300- to 1000-nm particle sizes; moreover, these are the first direct measurements of individual particles of UO 2 F 2 having been produced via UF 6 hydrolysis deposited on surfaces. These measurements, therefore, open a new avenue for collecting and detecting UO 2 F 2 in the condensed phase and further refine the PSD, which is critical for environmental transport determinations.

Uranium hexafluoride↗
DOE OSTI2024

Searching for axion forces with spin precession in atoms and molecules

We propose to use atoms and molecules as quantum sensors of axion-mediated monopole-dipole forces. We show that electron spin precession experiments using atomic and molecular beams are well-suited for axion searches thanks to the presence of co-magnetometer states and single-shot temporal resolution. Experimental strategies to detect axion gradients from localised sources and the earth are presented, taking ACME III as a prototype example. Other possibilities including atomic beams, and laser-cooled atoms and molecules are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Assessment of critical flaw sizes and crack driving forces during additive manufacturing of metallic materials

Additive manufacturing (AM) of complex engineering components is often plagued by a high susceptibility to cracking, particularly in high-strength metallic materials. While alloy design efforts have made progress in mitigating solidification defects, there remains a need for mechanistic guidelines to predict susceptibility to solid-state cracking. To address this gap, driving forces for the growth of melt pool cracks are calculated across a wide range of alloys using an efficient computational framework. Calculations are coupled with rapid single track laser experiments to elucidate trends in cracking from laser melting. The analyses conducted here highlight the important role of material properties in susceptibility to cracking, notably fracture toughness and elastic modulus. An important finding is that residual stresses that are limited in magnitude to the yield stress of the material are likely insufficient to drive cracking during cooling. Furthermore, the implications of these results are discussed in the context of alloy design for AM and residual stress accumulation during AM.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Entropy-based feature selection for capturing impacts in Earth system models with abrupt forcing

This paper presents the development of a new entropy-based feature selection method for identifying and quantifying impacts. Here, impacts are defined as statistically significant differences in spatio-temporal fields when comparing datasets with and without an external forcing in an Earth system model. Temporal feature selection is performed by first computing the cross-fuzzy entropy to quantify similarity of patterns between two datasets and then applying changepoint detection to identify regions of statistically constant entropy. The method is used to capture temperate north surface cooling from a 9-member simulation ensemble of the Mt. Pinatubo volcanic eruption, which injected 10 Tg of SO 2 into the stratosphere. The results estimate a mean difference decrease in near surface air temperature of -0.560 K with a 99% confidence interval between -0.864 K and -0.257 K between April and November of 1992, one year following the eruption. A sensitivity analysis with decreasing SO 2 injection revealed that the impact is statistically significant at 5 Tg but not at 3 Tg. Using identified features, a dependency graph model based on a 9-day lag had significantly fewer nodes than a graph based on monthly means. Furthermore, this demonstrates our method’s ability to perform dimension reduction while still uncovering source-to-impact pathways.

Changepoint detection↗