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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cost and Time Effective Lithography of Reusable Millimeter Size Bone Tissue Replicas With Sub‐15 nm Feature Size on A Biocompatible Polymer

Abstract The ability to replicate the microenvironment of biological tissues creates unique biomedical possibilities for stem cell applications. Current fabrication methods are limited by either the control on feature size and shape, or by the throughput and size of the replicas. Here, a novel platform is reported that combines thermal scanning probe lithography (tSPL) with innovative methodologies for the low‐cost and high‐throughput nanofabrication of large area quasi‐3D bone tissue replicas with high fidelity, sub‐15 nm lateral precision, and sub‐2 nm vertical resolution. This bio‐tSPL platform features a biocompatible polymer resist that withstands multiple cell culture cycles, allowing the reuse of the replicas, further decreasing costs and fabrication times. The as‐fabricated replicas support the culture and proliferation of human induced mesenchymal stem cells, which display broad therapeutic and biomedical potential. Furthermore, it is demonstrated that bio‐tSPL can be used to nanopattern the bone tissue replicas with amine groups, for subsequent tissue‐mimetic biofunctionalization. The achieved level of time and cost‐effectiveness, as well as the cell compatibility of the replicas, make bio‐tSPL a promising platform for the production of tissue‐mimetic replicas to study stem cell‐tissue microenvironment interactions, test drugs, and ultimately harness the regenerative capacity of stem cells and tissues for biomedical applications.

Liu, Xiangyu↗
DOE OSTI2021

Opening band gaps of low-dimensional materials at the meta-GGA level of density functional approximations

The quasiparticle band structure can be properly described by Hedin's GW approximation (GW), at a high computational cost. For band gaps, semilocal density functionals up to the generalized gradient approximation (GGA) level cannot compete with the accuracy of hybrid-based approximations or GW. Meta-GGA density functionals with a strong dependence on the kinetic energy density ingredient can potentially give wider band gaps compared with GGAs. The recent TASK meta-GGA density functional from Aschebrock and Kümmel [ Phys. Rev. Research 1 , 033082 (2019) ], is constructed with an enhanced nonlocality in the generalized Kohn-Sham scheme and therefore harbors great opportunities for band gap prediction. Although this approximation was found to yield excellent band gaps of bulk solids, this accuracy cannot be straightforwardly transferred to low-dimensional materials. Additionally, the reduced screening of these materials results in larger band gaps compared with their bulk counterparts, as an additional barrier to overcome. In this paper we demonstrate how the alteration of this functional affects the band gaps of monolayers and nanoribbons and present accurate band gaps competing with the revised Heyd-Scuseria-Ernzerhof (HSE06) approximation. In order to achieve this goal, we have modified the TASK functional (a) by changing the tight upper bound for one- or two-electron systems ( h X 0 ) from 1.174 to 1.29 and (b) by changing the limit of the interpolation function f X ( α → ∞ ) of the TASK functional that interpolates the exchange enhancement factor F X ( s , α ) from α = 0 to 1. The resulting modified TASK (mTASK) was tested for various materials from three dimensions to two dimensions to one dimension (nanoribbons) and was compared with the results of the higher-level hybrid functional HSE06 or with the G 0 W 0 approximation within many-body perturbation theory. We find that mTASK systematically improves the band gaps and band structures of two-dimensional (2D) and 1D systems, without significantly affecting the accuracy of the original TASK for the bulk 3D materials, when compared with the Perdew-Burke-Ernzerhof (PBE) GGA and the strongly constrained and appropriately normed (SCAN) meta-GGA. We further demonstrate the applicability of mTASK by assessing the band structures of transition metal dichalcogenide nanoribbons with respect to various bending curvatures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simurgh: A Framework for Cad-Driven Deep Learning Based X-Ray CT Reconstruction

High-resolution X-ray computed tomography (XCT) is an important technique for the inspection of additively manufactured (AM) parts. While XCT is typically used off-line to inspect a subset of manufactured parts, significantly accelerating measurement speed while retaining accuracy would enable use of XCT for in-line inspection to rapidly identify defects in each part as it is manufactured. Here, we propose a deep learning (DL) based approach that uses computer aided design (CAD) models of the AM parts and physics-based information to rapidly produce high-quality reconstructions from sparse XCT measurements without high quality ground truth data. Our approach uses a generative adversarial neural network (GAN) to produced realistic training data from the CAD-based simulations and a deep neural network that is trained using data from the first stage to produce accurate 3D reconstructions. Using experimental XCT data of metal parts, we demonstrate enhanced defect detection capabilities while dramatically reducing the scan time.

Ziabari, Amir↗
DOE OSTI2026

X-ray tomography of damage dynamics in advanced materials using a laser wakefield accelerator

Additively manufactured (AM) metals offer the potential for customizable, cost-effective components, but qualification and certification are crucial. Key to this process is understanding pore dynamics under stress, typically analyzed using micro-computed tomography. This study introduces laboratory-scale “betatron” x-rays from laser wakefield acceleration as a high-throughput alternative for x-ray tomography of advanced materials, such as AM AlSi10Mg alloys. Coupled with 3D finite element modeling, this method provides detailed insights into stress-porosity interactions. The approach delivers high-resolution scans, revealing that pore shape and local triaxiality significantly influence fracture dynamics, supporting advanced material characterization. This work also demonstrates the potential and versatility of laser-betatron x-ray μCT for generating large datasets to accelerate our understanding of the stochastic, process-specific nature of pore formation in AM alloys.

Senthilkumaran, Vigneshvar↗
DOE OSTI2023

Electrochemical polymer pen lithography

Disclosed herein is a massively parallel patterning tool for the deposition of single metals or metal alloys with size and composition control. Methods of the disclosure use a hydrogel array of pyramidal pen tips as a medium for localized electrodeposition, in conjunction with a scanning probe lithography platform and a three-electrode cell. This versatile technique can be used for high-throughput 3D printing, biomolecule patterning, or screening of catalyst nanoparticles or thin films.

Mirkin, Chad A.↗
DOE OSTI2023

Multi-Task Learning of Scanning Electron Microscopy and Synthetic Thermal Tomography Images for Detection of Defects in Additively Manufactured Metals

One of the key challenges in laser powder bed fusion (LPBF) additive manufacturing of metals is the appearance of microscopic pores in 3D-printed metallic structures. Quality control in LPBF can be accomplished with non-destructive imaging of the actual 3D-printed structures. Thermal tomography (TT) is a promising non-contact, non-destructive imaging method, which allows for the visualization of subsurface defects in arbitrary-sized metallic structures. However, because imaging is based on heat diffusion, TT images suffer from blurring, which increases with depth. We have been investigating the enhancement of TT imaging capability using machine learning. In this work, we introduce a novel multi-task learning (MTL) approach, which simultaneously performs the classification of synthetic TT images, and segmentation of experimental scanning electron microscopy (SEM) images. Synthetic TT images are obtained from computer simulations of metallic structures with subsurface elliptical-shaped defects, while experimental SEM images are obtained from imaging of LPBF-printed stainless-steel coupons. MTL network is implemented as a shared U-net encoder between the classification and the segmentation tasks. Results of this study show that the MTL network performs better in both the classification of synthetic TT images and the segmentation of SEM images tasks, as compared to the conventional approach when the individual tasks are performed independently of each other.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Joint iterative reconstruction and 3D rigid alignment for X-ray tomography

X-ray tomography is widely used for three-dimensional structure determination in many areas of science, from the millimeter to the nanometer scale. The resolution and quality of the 3D reconstruction is limited by the availability of alignment parameters that correct for the mechanical shifts of the sample or sample stage for the images that constitute a scan. In this paper we describe an algorithm for marker-free, fully automated and accurately aligned and reconstructed X-ray tomography data. Our approach solves the tomographic reconstruction jointly with projection data alignment based on a rigid-body deformation model. We demonstrate the robustness of our method on both synthetic phantom and experimental data and show that our method is highly efficient in recovering relatively large alignment errors without prior knowledge of a low resolution approximation of the 3D structure or a reasonable estimate of alignment parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Pushing the limits: Resolving paleoseawater signatures in nanoscale fluid inclusions by atom probe tomography

New insight into the geochemistry of ancient environments can be gained through structural and chemical analyses of nanometer-scale features within minerals. Here, we present recent developments using atom probe tomography (APT) enabling direct visualization of nanoscale fluid inclusions trapped within pyrite (FeS 2 ) and thereby chemical characterization of remnant seawater. Pyrite framboids (spherical clusters of nanocrystals) were sampled from the Middle Devonian Leicester Pyrite Member (New York). Scanning transmission electron microscopy shows low density regions distributed within the pyrite consistent with nanoscale pores (<4 nm in size). APT 3D visualization and compositional mapping reveals that the nanopores are filled with water. The inclusions appear to preserve the elemental signature of the water column in which the framboids formed, specifically seawater components including Na, K, Mg, and Ca. Mg/Ca ratios within the pyrite were generally measured to be within 0.6±0.2 – consistent with calcite-dominated seawater conditions existing in the Middle Devonian. Furthermore, this study demonstrates the potential for a novel approach to reconstruct paleoenvironmental conditions from coupled elemental and structural analyses of nanoscale fluid inclusions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Bridging microscopy with molecular dynamics and quantum simulations: an atomAI based pipeline

Recent advances in (scanning) transmission electron microscopy have enabled a routine generation of large volumes of high-veracity structural data on 2D and 3D materials, naturally offering the challenge of using these as starting inputs for atomistic simulations. In this fashion, the theory will address experimentally emerging structures, as opposed to the full range of theoretically possible atomic configurations. However, this challenge is highly nontrivial due to the extreme disparity between intrinsic timescales accessible to modern simulations and microscopy, as well as latencies of microscopy and simulations per se. Addressing this issue requires as a first step bridging the instrumental data flow and physics-based simulation environment, to enable the selection of regions of interest and exploring them using physical simulations. Here we report the development of the machine learning workflow that directly bridges the instrument data stream into Python-based molecular dynamics and density functional theory environments using pre-trained neural networks to convert imaging data to physical descriptors. Additionally, the pathways to ensure structural stability and compensate for the observational biases universally present in the data are identified in the workflow. This approach is used for a graphene system to reconstruct optimized geometry and simulate temperature-dependent dynamics including adsorption of Cr as an ad-atom and graphene healing effects. However, it is universal and can be used for other material systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Rotational Millimeter-Wave Shoe Scanner Using the Discrete Fourier Transform for Backprojection-Based Image Reconstruction

An active 3D microwave / millimeter-wave shoe scanner was previously developed at the Pacific Northwest National Laboratory (PNNL) using two linear arrays scanned over a rectilinear aperture. The radar system chirps a frequency sweep from 10-40 GHz. These frequencies allow imaging through optically opaque material such as leather, rubber, plastics, and other dielectrics. The system was designed to detect concealed items in the soles of shoes while allowing people to leave their shoes on through a security checkpoint. To shrink the footprint of the system, a new iteration of the design has been developed that scans the two linear arrays over a circular aperture. This new footprint opens the possibility of it being installed in the floor of a cylindrical millimeter-wave body scanner. The backprojection-based multilayer dielectric image reconstruction developed at PNNL can easily handle arbitrary spatial sampling, accommodating the new rotational shoe scanner design. Commonly, the fast Fourier transform (FFT) is used to efficiently compute the range response from the data collected by the system as a preprocessing step to the backprojection algorithm. It was found that converting to range using the discrete Fourier transform (DFT) directly has some advantages over the FFT. For example, nonlinear and non-uniform frequency sweeps can easily be compensated for during the computation of the DFT and only the range bins of interest need to be computed and their spacing can be chosen arbitrarily. Because the range conversion step of the image reconstruction is the fastest part of the process there is very little speed penalty for using the DFT over the FFT and it can even increase the speed of image reconstruction when the ranges of interest are fewer than the total span that is calculated in the FFT.

Millimeter-wave imaging, microwave imaging, shoe s↗
DOE OSTI2020

3D Printing with Mixed Powders of Boron Carbide and Al Alloy

Laser additive manufacturing with mixed powders of boron carbide and aluminum alloy is investigated. Parameters such as laser power, scan speed, scan pattern, and hatching space are systematically evaluated and optimized to obtain the desired density and porosity. These results show that the AM part contains 20 wt% boron carbide and 80 wt% aluminum alloy, which are well mixed and synthesized during the melting process. Its mechanical properties are close to those of aluminum. A thin-wall structure based two dimensional and three dimensional radial collimators were fabricated with well-controlled geometry for neutron scattering measurement.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Additively Manufactured Carbon Fiber-Reinforced Siliconized Silicon Carbide Composites Using Carbon Fiber-Reinforced Poly-Ether-Ether-Ketone (PEEK) as a Precursor

Herein, we report a method to additively manufacture carbon fiber-reinforced siliconized silicon carbide composites. The process involves the pyrolysis of a 3D-printed carbon fiber-reinforced poly-ether-ether-ketone (PEEK) composite to produce a porous carbon fiber-reinforced carbon matrix composite preform, which is subsequently infiltrated with molten silicon to obtain a carbon fiber-reinforced siliconized silicon carbide composite. A key aspect of the method is limiting polymer melt flow during pyrolysis of PEEK, which is achieved by thermally annealing the 3D-printed carbon fiber-reinforced PEEK preform in air at a temperature below PEEK’s melting temperature. Rheological and differential scanning calorimetry (DSC) measurements demonstrate that the thermal annealing treatment altered the melting behavior of PEEK, while NMR and FTIR measurements provided a mechanistic explanation for the structural changes responsible for the behavior. It was also found that dimensional changes during pyrolysis were anisotropic with greater shrinkage in the stacking direction of the material.

Yoon, Bola [ORNL] (ORCID:0000000260875373)↗
DOE OSTI2020

High-speed volumetric two-photon fluorescence imaging of neurovascular dynamics

Abstract Understanding the structure and function of vasculature in the brain requires us to monitor distributed hemodynamics at high spatial and temporal resolution in three-dimensional (3D) volumes in vivo. Currently, a volumetric vasculature imaging method with sub-capillary spatial resolution and blood flow-resolving speed is lacking. Here, using two-photon laser scanning microscopy (TPLSM) with an axially extended Bessel focus, we capture volumetric hemodynamics in the awake mouse brain at a spatiotemporal resolution sufficient for measuring capillary size and blood flow. With Bessel TPLSM, the fluorescence signal of a vessel becomes proportional to its size, which enables convenient intensity-based analysis of vessel dilation and constriction dynamics in large volumes. We observe entrainment of vasodilation and vasoconstriction with pupil diameter and measure 3D blood flow at 99 volumes/second. Demonstrating high-throughput monitoring of hemodynamics in the awake brain, we expect Bessel TPLSM to make broad impacts on neurovasculature research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Effect of printing parameters on 3D-printed carbon fiber-reinforced polymer composites under magnetic field control

Magnetic field controlled (MFC) 3D printing is a promising method for realizing the intelligent control of the structural performance of carbon fiber-reinforced plastic (CFRP) composites by adjusting the fiber orientation during the printing process. However, few studies have focused on the influence of the printing parameters on the magnetic control of the fiber direction. Therefore, in this study, the mechanical properties and internal fiber distributions of MFC 3D-printed samples of CFRP composites with 10 wt% fiber content, which were printed at different speeds and layer thicknesses, were investigated. Subsequently, the effects of the fiber content on the mechanical properties and fiber distribution of the MFC 3D-printed samples were studied. Furthermore, the origin of fiber fracture was evaluated through observation and analysis of the fracture section using scanning electron microscopy. The fiber orientation could be well adjusted under the action of a magnetic field and adjustment of printing parameters, thereby improving the tensile strength, young's modulus significantly with slightly decrease of fracture elongation. The recommended parameter combinations (printing speed and layer thickness) were 40 mm/s and 0.2 mm for 10 wt% fiber content CFRP composites.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Mesoscale atomic engineering in a crystal lattice

Controlling individual atoms using lasers, ion traps and scanning probe tips has transformed our understanding of matter and enabled breakthroughs in quantum science. Extending this control into three-dimensional (3D) solids and across mesoscopic scales, however, remains a foundational challenge. Electron irradiation in electron microscopes is known to induce atomic displacements, and atomic manipulation has been proposed and demonstrated. Yet repeated and deterministic control has remained elusive. Here, in this study, we demonstrate deterministic atomic engineering in a 3D crystal, creating ordered arrangements of more than 40,000 user-defined defects within minutes across a 150 nm × 100 nm × 13 nm volume. By steering individual Cr atoms in the magnetic semiconductor CrSBr into selected interstitial sites using an electron beam directed with sub-20-pm-scale accuracy, we create vacancy–interstitial complexes. The resulting impurity array forms a mesoscale crystal embedded within the host lattice, a new form of engineered artificial matter that remains stable at room temperature and outside the microscope. By tracking Cr atom displacements, we identify conditions under which the defect structures are predictable. Our calculations suggest that these defects form correlated impurity states with intra-defect optical transitions and inter-defect kinetic and Coulomb interactions. This establishes a generalizable platform for atomic defect engineering at mesoscopic, and potentially macroscopic, scales, opening opportunities for scalable quantum technologies, including deterministic colour-centre placement, quantum simulation of many-body lattice models and atomic-scale manufacturing.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Finite density QCD equation of state: Critical point and lattice-based 𝑇′ expansion

Here, we present a novel construction of the QCD equation of state (EoS) at finite baryon density. Our work combines a recently proposed resummation scheme for lattice QCD results with the universal critical behavior at the QCD critical point. This allows us to obtain a family of equations of state in the range 0 ≤ 𝜇 𝐵 ≤ 700 MeV and 25 MeV ≤ 𝑇 ≤ 800 MeV, which match lattice QCD results near 𝜇 𝐵 =0 while featuring a critical point in the 3D Ising model universality class. The position of the critical point can be chosen within the range accessible to beam-energy scan heavy-ion collision experiments. The strength of the singularity and the shape of the critical region are parametrized using a standard parameter set. We impose stability and causality constraints and discuss the available ranges of critical point parameter choices, finding that they extend beyond earlier parametric QCD EoS proposals. We present thermodynamic observables, including baryon density, pressure, entropy density, energy density, baryon susceptibility and speed of sound, that cover a wide range in the QCD phase diagram relevant for experimental exploration.

Astronomy & Astrophysics↗
DOE OSTI2020

Intra- and Intermolecular Self-Assembly of a 20-nm-Wide Supramolecular Hexagonal Grid.

For the past three decades, the coordination-driven self-assembly of three-dimensional structures has undergone rapid progress; however, parallel efforts to create large discrete two-dimensional architectures-as opposed to polymers-have met with limited success. The synthesis of metallo-supramolecular systems with well-defined shapes and sizes in the range of 10-100 nm remains challenging. Here we report the construction of a series of giant supramolecular hexagonal grids, with diameters on the order of 20 nm and molecular weights greater than 65 kDa, through a combination of intra- and intermolecular metal-mediated self-assembly steps. The hexagonal intermediates and the resulting self-assembled grid architectures were imaged at submolecular resolution by scanning tunnelling microscopy. Characterization (including by scanning tunnelling spectroscopy) enabled the unambiguous atomic-scale determination of fourteen hexagonal grid isomers.

Zhang, Zhe↗
DOE OSTI2025

Atomic ionization: sd energy imbalance and Perdew–Zunger self-interaction correction energy penalty in 3d atoms

To accurately describe the energetics of transition metal systems, density functional approximations (DFAs) must provide a balanced description of s- and d- electrons. One measure of this is the sd transfer error, which has previously been defined as E ( 3 d n − 1 4 s 1 ) − E ( 3 d n − 2 4 s 2 ) . Theoretical concerns have been raised about this definition due to its evaluation of excited-state energies using ground-state DFAs. A more serious concern appears to be strong correlation in the 4s 2 configuration. Here, we define a ground-state measure of the sd energy imbalance, based on the errors of s- and d-electron second ionization energies of the 3d atoms, that effectively circumvents the aforementioned problems. We find an improved performance as we move from the local spin density approximation (LSDA) to the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA) to the regularized and restored Strongly Constrained and Appropriately Normed (r 2 SCAN) meta-GGA for first-row transition metal atoms. However, we find large (∼2 eV) ground-state sd energy imbalances when applying a Perdew–Zunger 1981 self-interaction correction. This is attributed to an “energy penalty” associated with the noded 3d orbitals. A local scaling of the self-interaction correction to LSDA results in a balance of s- and d-errors.

Science & Technology - Other Topics↗