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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Conclusions • Multimaterial and isotopically-labeled specimens were successfully fabricated via FFF-AM • Raman spectroscopy, atomic force microscopy, and neutron scattering show promise for direct measurements of interlayer diffusion in the multimaterial and isotopically-labeled specimens • Although isotopically-labeled specimens offer the greatest potential for experimentally verifying FFF-AM process models, substituting hydrogen with deuterium alters the thermal and rheological properties of the HDPE polymer

Multimaterial and Isotopically Labeled Specimen Fabrication via Material Extrusion Additive Manufacturing for Interlayer Diffusion Analysis

Jones, Haley W. [Savannah River National Laborator↗
NASA NTRS2004

Integrating Carbon Nanotubes For Atomic Force Microscopy Imaging Applications

Carbon nanotube (CNT) related nanostructures possess remarkable electrical, mechanical, and thermal properties. To produce these nanostructures for real world applications, a large-scale controlled growth of carbon nanotubes is crucial for the integration and fabrication of nanodevices and nanosensors. We have taken the approach of integrating nanopatterning and nanomaterials synthesis with traditional silicon micro fabrication techniques. This integration requires a catalyst or nanomaterial protection scheme. In this paper, we report our recent work on fabricating wafer-scale carbon nanotube AFM cantilever probe tips. We will address the design and fabrication considerations in detail, and present the preliminary scanning probe test results. This work may serve as an example of rational design, fabrication, and integration of nanomaterials for advanced nanodevice and nanosensor applications.

Ye, Qi↗
NASA NTRS1996

Technique to Predict Ultraviolet Radiation Embrittlement of Polymers in Space

In the low-Earth-orbit environment, solar ultraviolet (UV) radiation embrittles polymer materials through bond breaking and crosslinking. This UV embrittlement increases the surface hardness of the polymer. Before the durability of polymer materials in the low- Earth-orbit environment can be predicted, the extent of UV embrittlement needs to be determined. However, traditional techniques for measuring the microhardness of materials cannot be employed to measure changes in the hardness of UV-embrittled surfaces because traditional techniques measure bulk hardness and are not sensitive enough to surface changes. A unique technique was used at the NASA Lewis Research Center to quantify polymer surface damage that had been induced by UV radiation. The technique uses an atomic force microscope (AFM) to measure surface microhardness. An atomic force microscope measures the repulsive forces between the atoms in a microscopic cantilevered tip and the atoms on the surface of a sample. Typically, an atomic force microscope produces a topographic image of a surface by monitoring the movement of the tip over features of the surface. The force applied to the cantilevered tip, and the indention of the tip into the surface, can be measured. The relationship between force and distance of indentation, the quantity force/distance (newtons/meter), provides a measure of the surface hardness. Under identical operating conditions, direct comparisons of surface hardness values can be made.

Source record↗
DOE OSTI2025

Multi-fidelity learning for interatomic potentials: low-level forces and high-level energies are all you need

The promise of machine learning interatomic potentials (MLIPs) has led to an abundance of public quantum mechanical (QM) training datasets. The quality of an MLIP is directly limited by the accuracy of the energies and atomic forces in the training dataset. Unfortunately, most of these datasets are computed with relatively low-accuracy QM methods, e.g. density functional theory with a moderate basis set. Due to the increased computational cost of more accurate QM methods, e.g. coupled-cluster theory with a complete basis set (CBS) extrapolation, most high-accuracy datasets are much smaller and often do not contain atomic forces. The lack of high-accuracy atomic forces is quite troubling, as training with force data greatly improves the stability and quality of the MLIP compared to training to energy alone. Because most datasets are computed with a unique level of theory, traditional single-fidelity (SF) learning is not capable of leveraging the vast amounts of published QM data. In this study, we apply multi-fidelity learning (MFL) to train an MLIP to multiple QM datasets of different levels of accuracy, i.e. levels of fidelity. Specifically, we perform three test cases to demonstrate that MFL with both low-level forces and high-level energies yields an extremely accurate MLIP—far more accurate than a SF MLIP trained solely to high-level energies and almost as accurate as a SF MLIP trained directly to high-level energies and forces. Therefore, MFL greatly alleviates the need for generating large and expensive datasets containing high-accuracy atomic forces and allows for more effective training to existing high-accuracy energy-only datasets. Indeed, low-accuracy atomic forces and high-accuracy energies are all that are needed to achieve a high-accuracy MLIP with MFL.

36 MATERIALS SCIENCE↗
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗
DOE OSTI2022

Laser-induced forces on atoms during ultrafast demagnetization

Laser-induced femtosecond demagnetization has attracted a broad attention as a possible candidate for information storage technology. However, whether or not lattice vibration directly participates in demagnetization has been highly controversial over a decade. A recent electron diffraction experiment attributed the demagnetization to the polarized phonon effect, but a similar x-ray diffraction experiment attributed it to the Einstein–de Haas effect. Common to both experiments is that neither the angular momentum of the lattice nor the rotation of the sample was directly probed. Here, we report our first first-principles calculation of forces on atoms induced by an ultrafast laser during ultrafast demagnetization. We employ two complementary methods: (i) the frozen lattice with electronic excitation and (ii) frozen excitation but moving the lattice. We find that the forces on atoms start at –50 fs and peak around 30 fs. The magnitude of the force is far smaller than the empirical estimates. Within the limit of our theory, our results suggest that the polarized phonon effect and the Einstein–de Haas effect are unlikely to be the main course of demagnetization. As a result, we expect that our finding has a profound impact on the future direction of laser-induced dynamics in magnetic and quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2004

The force exerted by the membrane potential during protein import into the mitochondrial matrix

The force exerted on a targeting sequence by the electrical potential across the inner mitochondrial membrane is calculated on the basis of continuum electrostatics. The force is found to vary from 3.0 pN to 2.2 pN (per unit elementary charge) as the radius of the inner membrane pore (assumed aqueous) is varied from 6.5 to 12 A, its measured range. In the present model, the decrease in force with increasing pore width arises from the shielding effect of water. Since the pore is not very much wider than the distance between water molecules, the full shielding effect of water may not be present; the extreme case of a purely membranous pore without water gives a force of 3.2 pN per unit charge, which should represent an upper limit. When applied to mitochondrial import experiments on the protein barnase, these results imply that forces between 11 +/- 2 pN and 13.5 +/- 2.5 pN catalyze the unfolding of barnase in those experiments. A comparison of these results with unfolding forces measured using atomic force microscopy is made.

Models, Molecular↗
DOE OSTI2024

Multiparametric AFM Insights into Electron Transport Mechanisms in Biomemristors

Biomemristors have attracted significant attention due to their applications in biodegradable and flexible electronic devices, and their prospective functions in information storage, neural synapses, and neuromorphic computation. Hence, understanding biomaterials' resistive switching (RS) mechanism is essential to design novel biomemristors with enhanced performance. In the last decade, various atomic force microscopy (AFM) modes, such as Kelvin probe force microscopy (KPFM) and conductive atomic force microscopy (cAFM), in situ/operando visualize the electron transport behaviors within biomemristors at the nanoscale. This review provides a comprehensive discussion of multiparametric AFM techniques to characterize biomemristors and inspire new ideas in developing next-generation consumer electronics. We also summarize the progress of revealing the internal mechanism of biomemristors with functional AFM to visualize and understand the switching behavior. Finally, the opportunities and challenges of further utilizing multiparametric AFM to explore the electron transport mechanisms in biomemristors are presented.

Shi, Chenyang↗
DOE OSTI2023

Effect of Flexibility in Molecular Simulations of Carbon Dioxide Adsorption and Diffusion in a Cuprous Triazolate Framework

Using fixed atom force fields to model gas adsorption in flexible metal organic frameworks (MOFs) is known to pose difficulties in accurately reproducing and predicting experimental results. This paper studies the difference in accuracy between flexible and fixed atom force fields in reproducing CO 2 adsorption measurements in MAF-2 ([Cu(etz)]∞ (MAF-2, Hetz) 3,5-diethyl-1,2,4-triazole), an NbO-type triazolate scaffold with a bcu cavity system and attached ethyl groups. The flexible force field used to run the hybrid molecular dynamics and grand canonical Monte Carlo calculations were generated using the QuickFF software incorporating van der Waals parameters from the Universal Force Field (UFF) and density derived electrostatic and chemical (DDEC) charges. The fixed atom force field used was composed of UFF van der Waals parameters together with DDEC charges. The calculations were run at 298 K and at pressures of 0.1, 0.3, 0.5, 0.8, and 1 bar. It was observed that for this MOF the rigid force field overpredicted gas adsorption, whereas the flexible force field values closely matched experimental data. In the flexible structure, the freely moving ethyl groups of MAF-2 hindered adsorption, reducing the interaction energy between CO 2 and the N atoms of the triazolate framework as well as reducing the size of the largest cavity diameter. Here, the combination of these factors led to improved prediction of adsorption values with the flexible forcefield as compared to the rigid forcefield, demonstrating the need for modeling MOFs in a way more indicative of their behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Breaking a dative bond with mechanical forces

Bond breaking and forming are essential components of chemical reactions. Recently, the structure and formation of covalent bonds in single molecules have been studied by non-contact atomic force microscopy (AFM). Here, we report the details of a single dative bond breaking process using non-contact AFM. The dative bond between carbon monoxide and ferrous phthalocyanine was ruptured via mechanical forces applied by atomic force microscope tips; the process was quantitatively measured and characterized both experimentally and via quantum-based simulations. Our results show that the bond can be ruptured either by applying an attractive force of ~150 pN or by a repulsive force of ~220 pN with a significant contribution of shear forces, accompanied by changes of the spin state of the system. Our combined experimental and computational studies provide a deeper understanding of the chemical bond breaking process.

36 MATERIALS SCIENCE↗
NASA NTRS1999

The MSP 2001 Mars Environmental Compatibility Assessment (MECA)

The Mars Environmental Compatibility Assessment (MECA) will evaluate the Martian environment for soil and dust-related hazards to human exploration as part of the Mars Surveyor Program 2001 Lander. Sponsored by the Human Exploration and Development of Space (HEDS) enterprise, MECA's goal is to evaluate potential geochemical and environmental hazards that may confront future Martian explorers, and to guide HEDS scientists in the development of high fidelity Mars soil simulants. The integrated MECA payload contains a wet-chemistry laboratory, a microscopy station, an electrometer to characterize the electrostatics of the soil and its environment, and arrays of material patches to study the abrasive and adhesive properties of soil grains. The instrument will acquire soil samples with a robotic arm equipped with a camera. MECA will examine surface and subsurface soil and dust in order to characterize particle size, shape, hardness, and also physical characteristics that may provide clues to mineralogy. MECA will characterize soil/water mixtures with respect to pH, redox potential, total dissolved ions, and trace toxins. MECA will determine the nature of electrostatic charging associated with excavation of soil, and the influence of ionizing radiation on material properties. It will also observe natural dust accumulation on engineering materials. To accomplish these objectives, MECA is allocated a mass of 10 kg within an enclosure of 35 x 25 x 15 cm. The Wet Chemistry Laboratory (WCL) consists of four identical cells that will accept samples from surface and subsurface regions accessible to the Lander's robotic arm, mix them with water, and perform extensive analysis of the solution. Ion-selective electrodes and related sensors will evaluate total dissolved solids, redox potential, pH, and the concentration of many soluble ions and gases in wet Martian soil. These electrodes can detect potentially dangerous heavy-metal ions, emitted pathogenic gases, and the soil's corrosive potential. Experiments will include cyclic voltammetry and anodic stripping voltammetry. Complementary to the Viking experiments, the chemical laboratory will characterize the water-soil solution rather than emitted gases. Nonetheless, through analysis of dissolved gases it will be able to replicate many of the Viking observations related to oxidants. MECA's microscopy station combines optical and atomic-force microscopy (AFM) in an actively focused, controlled illumination environment to image particles from millimeters to nanometers in size. Careful selection of substrates allows controlled experiments in adhesion, abrasion, hardness, aggregation, magnetic and other properties. Special tools allow primitive manipulation (brushing and scraping) of samples. Soil particle properties including size, shape, color, hardness, adhesive potential (electrostatic and magnetic), will be determined using an array of sample receptacles and collection substrates. The simple, rugged atomic-force microscope will image in the submicron size range and has the capability of performing a particle-by-particle analysis of the dust and soil. On Earth, the earliest forms of life are preserved as microfossils. The atomic-force microscope will have the required resolution to image down to the scale of terrestrial microfossils and beyond. Mounted on the end of the robot arm, MECA's electrometer actually consists of four types of sensors: an electric field meter, several triboelectricity monitors, an ion gauge, and a thermometer. Tempered only by ultraviolet-light-induced ions and a low-voltage breakdown threshold, the dry, cold, dusty martian environment presents an imposing electrostatic hazard to both robots and humans. The field meter will measure the ambient field on nearby objects while the triboelectric sensors, using identical circuitry, will measure the charge accumulated on test substances as they are dragged through the soil by the arm. The ion chamber, open to the environment, will sense both charged dust and free ions in the air. Over and above the potential threat to electronics, the electrostatic environment holds one of the keys to transport of dust and, consequently, Martian meteorology. Viewed with the robot arm camera, the abrasion and adhesion plates are strategically placed to allow direct observation of the interaction between materials and soils on a macroscopic scale. Materials of graded hardness are placed directly under the robot arm scoop to sense wear and soil hardness. A second array, placed on the lander deck, is deployed after the dust plume of landing has settled. It can be manipulated in a primitive fashion by the arm, first having dirt deposited on it from the scoop and subsequently shaken clean. A third array will passively collect dust from the atmosphere. In addition to objectives related to human exploration, the MECA data set will be rich in information relevant to basic geology, paleoclimate, and exobiology issues. To understand both contemporaneous and ancient processes on Mars, the mineralogy, petrology, and reactivity of Martian surface materials should be constrained. The MECA experiment will shed light on these quantities through its combination of chemistry and microscopy. MECA will be capable of measuring the composition of ancient surface water environments, observing microscopic evidence of geological (and biological?) processes, inferring soil and dust transport, comminution and weathering mechanisms, and characterizing soil horizons that might be encountered during excavation.

Hecht, M. H.↗
NASA NTRS1999

Mars Environmental Compatibility Assessment (MECA): Identifying the Hazards of the Martian Soil

Sometime in the next decade NASA will decide whether to send a human expedition to explore the planet Mars. The Mars Environmental Compatibility Assessment (MECA) has been selected by NASA to evaluate the Martian environment for soil and dust hazards to human exploration. The integrated MECA payload contains three elements: a wet-chemistry laboratory, a microscopy station, and enhancements to a lander robot-arm system incorporating arrays of material patches and an electrometer to identify triboelectric charging during soil excavation. The wet-chemistry laboratory will evaluate samples of Martian soil in water to determine the total dissolved solids, redox potential, pH, and quantify the concentration of many soluble ions using ion-selective electrodes. These electrodes can detect potentially dangerous heavy-metal ions, emitted pathogenic gases, and the soil's corrosive potential. MECA's microscopy station combines optical and atomic-force microscopy with a robot-arm camera to provide imaging over nine orders of magnitude, from meters to nanometers. Soil particle properties including size, shape, color, hardness, adhesive potential (electrostatic and magnetic), will be determined on the microscope stage using an ar-ray of sample receptacles and collection substrates, and an abrasion tool,. The simple, rugged atomic-force microscope will image in the submicron size range and has the capability of performing a particle-by-particle analysis of the dust and soil. Although selected by NASA's Human Exploration and Development of Space Enterprise, the MECA instrument suite also has the capability to address basic geology, paleoclimate, and exobiology issues. To understand both contemporaneous and ancient processes on Mars, the mineralogical, petrological, and reactivity of Martian surface materials should be constrained: the NMCA experiment will shed light on these quantities through its combination of chemistry and microscopy. On Earth, the earliest forms of life are preserved as microfossils. The atomic-force microscope will have the required resolution to image down to the scale of terrestrial microfossils and beyond.

Meloy, T. P.↗