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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

ELECTRIC FIELD-ASSISTED DIFFUSION WELDING TO FABRICATE ALLOY 617 COMPACT HEAT EXCHANGERS

Compact heat exchangers are of interest for a number of applications including advanced reactors. Alloy 617 is one of the top candidate materials for the gas-cooled reactor intermediate heat exchanger. Previous endeavors to diffusion weld Alloy 617 utilized hot pressing (HP). It was reported that grain boundary migration across the interface was hindered by extensive precipitation. Bonds of this nature have been observed to reduce the elevated-temperature mechanical properties compared to the wrought-product form. It was hypothesized that the electric current applied during electric-field-assisted sintering (EFAS) can overcome these challenges, resulting in improved diffusion welding (DW). This study investigated DW of Alloy 617 via EFAS. Stacks composed of three sheets that were 20 mm in diameter were welded using EFAS. Specimens were welded with an applied electric current, a pressure of 30 MPa, hold time of 30 min, and temperatures of 1050°C, 1100°C, and 1150°C. DW using HP as the zero-current analog of EFAS was also performed at the most promising EFAS conditions. Results revealed that both the applied electric current and temperature played a key role in precipitation and grain boundary migration in diffusion-welded Alloy 617. Precipitates were observed at the interface of the hot-pressed samples which limited grain boundary migration. Electric current was found to prevent precipitate formation along the interface at 1150°C. The electric current coupled with a temperature of 1150°C during EFAS resulted in significant grain boundary migration across the interface.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

A Guideline to Mitigate Interfacial Degradation Processes in Solid‐State Batteries Caused by Cross Diffusion

Abstract Diffusion of transition metals across the cathode–electrolyte interface is identified as a key challenge for the practical realization of solid‐state batteries. This is related to the formation of highly resistive interphases impeding the charge transport across the materials. Herein, the hypothesis that formation of interphases is associated with the incorporation of Co into the Li 7 La 3 Zr 2 O 12 lattice representing the starting point of a cascade of degradation processes is investigated. It is shown that Co incorporates into the garnet structure preferably four‐fold coordinated as Co 2+ or Co 3+ depending on oxygen fugacity. The solubility limit of Co is determined to be around 0.16 per formula unit, whereby concentrations beyond this limit causes a cubic‐to‐tetragonal phase transition. Moreover, the temperature‐dependent Co diffusion coefficient is determined, for example, D 700 °C = 9.46 × 10 −14 cm 2 s −1 and an activation energy E a = 1.65 eV, suggesting that detrimental cross diffusion will take place at any relevant process condition. Additionally, the optimal protective Al 2 O 3 coating thickness for relevant temperatures is studied, which allows to create a process diagram to mitigate any degradation with a minimum compromise on electrochemical performance. This study provides a tool to optimize processing conditions toward developing high energy density solid‐state batteries.

Chemistry↗
DOE OSTI2020

Accelerated Modeling of Lithium Diffusion in Solid State Electrolytes using Artificial Neural Networks

Abstract Previous efforts to understand structure‐function relationships in high ionic conductivity materials for solid state batteries have predominantly relied on density functional theory (DFT‐) based ab initio molecular dynamics (MD). Such simulations, however, are computationally demanding and cannot be reasonably applied to large systems containing more than a hundred atoms. Here, an artificial neural network (ANN) is trained to accelerate the calculation of high accuracy atomic forces and energies used during such MD simulations. After carefully training a robust ANN for four and five element systems, nearly identical lithium ion diffusivities are obtained for Li 10 GeP 2 S 12 (LGPS) when benchmarking the ANN‐MD results with DFT‐MD. Applying the ANN‐MD approach, the effect of chlorine doping on the lithium diffusivity is calculated in an LGPS‐like structure and it is found that a dopant concentration of 1.3% maximizes ionic conductivity. The optimal concentration balances the competing consequences of effective atomic radii and dielectric constants on lithium diffusion and agrees with the experimental composition. Performing simulations at the resolution necessary to model experimentally relevant and optimal concentrations would be infeasible with traditional DFT‐MD. Systems that require a large number of simulated atoms can be studied more efficiently while maintaining high accuracy with the proposed ANN‐MD framework.

Rao, Karun K.↗
DOE OSTI2020

An Atomic View of Cation Diffusion Pathways from Single‐Crystal Topochemical Transformations

Abstract The diffusion pathways of Li‐ions as they traverse cathode structures in the course of insertion reactions underpin many questions fundamental to the functionality of Li‐ion batteries. Much current knowledge derives from computational models or the imaging of lithiation behavior at larger length scales; however, it remains difficult to experimentally image Li‐ion diffusion at the atomistic level. Here, by using topochemical Li‐ion insertion and extraction to induce single‐crystal‐to‐single‐crystal transformations in a tunnel‐structured V 2 O 5 polymorph, coupled with operando powder X‐ray diffraction, we leverage single‐crystal X‐ray diffraction to identify the sequence of lattice interstitial sites preferred by Li‐ions to high depths of discharge, and use electron density maps to create a snapshot of ion diffusion in a metastable phase. Our methods enable the atomistic imaging of Li‐ions in this cathode material in kinetic states and provide an experimentally validated angstrom‐level 3D picture of atomic pathways thus far only conjectured through DFT calculations.

Handy, Joseph V.↗
DOE OSTI2026

Effect of Magnetic Islands on Neoclassical Heat Diffusivity in a Global Tokamak Simulation

Resonant magnetic perturbations (RMPs) alter magnetic field topology via island formation and can modify core transport in toroidal fusion devices. Using the global gyrokinetic particle‐in‐cell code XGC‐S, originally developed for stellarator geometries, we quantify how island topology affects neoclassical heat transport in a circular tokamak with ($m,n$) = (5,2) RMP‐induced islands. Electron radial heat diffusivity exhibits a two‐peak structure with a dominant enhancement near the O/X‐point region and a secondary peak at the outer island boundary, whereas ion transport remains close to the neoclassical prediction. The observed electron diffusivity is strongly enhanced over the neoclassical baseline but remains well below the Rechester–Rosenbluth estimate, consistent with the non‐ergodic character of the island topology. The density dependence of diffusivity is weaker inside the islands than outside, indicating the presence of topology‐driven transport channels that do not depend strongly on collisionality. Two‐dimensional heat flux maps reveal an up–down antisymmetric structure at the island separatrices consistent with magnetic gradient and curvature drift effects, in contrast to the symmetric temperature flattening inside the islands. These results identify topology‐dependent avenues for electron heat transport in RMP‐perturbed cores and suggest regimes in which island geometry, rather than collisions alone, governs radial transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Fast Exciton Diffusion in Monolayer PtSe2

Recently, 2D noble metal dichalcogenides have drawn considerable attention due to their thickness-tunable electronic and optical properties. However, the dynamical properties of photocarriers in these materials are less studied. In this report photocarrier dynamics in monolayer and bilayer PtSe 2 samples prepared by chemical vapor deposition are studied by transient absorption microscopy. Spatially and temporally resolved differential reflectance measurements yield room-temperature exciton lifetimes of 25 and 50 ps for monolayer and bilayer samples, respectively. The exciton diffusion coefficient in monolayer PtSe 2 is found to be as large as 48 cm 2 s -1 . This value is higher than exciton diffusion coefficients of most known monolayer semiconductors. The deduced exciton mobility is close to the theoretical limit of charge carrier mobility of monolayer PtSe 2 . The superior exciton transport property is unique to monolayers, as the exciton diffusion coefficient drops to 6.7 cm 2 s -1 in bilayers PtSe 2 . The novel exciton transport properties, along with its high air stability, make monolayer PtSe 2 an attractive material for ultrathin excitonic devices. These results provide insights on the exciton dynamic properties of 2D PtSe 2 and help develop fundamental understanding on the performance of various optoelectronic devices based on 2D PtSe 2 . .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model

Abstract Background Accurate delineation of the clinical target volume (CTV) is essential in the radiotherapy treatment of soft tissue sarcomas. However, this process is subject to inter‐reader variability due to the need for clinical assessment of risk and extent of potential microscopic spread. This can lead to inconsistencies in treatment planning, potentially impacting treatment outcomes. Most existing automatic CTV delineation methods do not account for this variability and can only generate a single CTV for each case. Purpose This study aims to develop a deep learning‐based technique to generate multiple CTV contours for each case, simulating the inter‐reader variability in the clinical practice. Methods We employed a publicly available dataset consisting of fluorodeoxyglucose positron emission tomography (FDG‐PET), x‐ray computed tomography (CT), and pre‐contrast T1‐weighted magnetic resonance imaging (MRI) scans from 51 patients with soft tissue sarcoma, along with an independent validation set containing five additional patients. An experienced reader drew a contour of the gross tumor volume (GTV) for each patient based on multi‐modality images. Subsequently, two additional readers, together with the first one, were responsible for contouring three CTVs in total based on the GTV. We developed a diffusion model‐based deep learning method that is capable of generating arbitrary number of different and plausible CTVs to mimic the inter‐reader variability in CTV delineation. The proposed model incorporates a separate encoder to extract features from the GTV masks, leveraging the critical role of GTV information in accurate CTV delineation. Results The proposed diffusion model demonstrated superior performance with the highest Dice Index (0.902 compared to values below 0.881 for state‐of‐the‐art models) and the best generalized energy distance (GED) (0.209 compared to values exceeding 0.221 for state‐of‐the‐art models). It also achieved the second‐highest recall and precision metrics among the compared ambiguous image segmentation models. Results from both datasets exhibited consistent trends, reinforcing the reliability of our findings. Additionally, ablation studies exploring different model structures and input configurations highlighted the significance of incorporating prior GTV information for accurate CTV delineation. Conclusions The proposed diffusion model successfully generates multiple plausible CTV contours for soft tissue sarcomas, effectively capturing inter‐reader variability in CTV delineation.

Dong, Yafei [Yale Biomedical Imaging Institute Yal↗
DOE OSTI2021

IMEX Runge-Kutta Parareal for Non-diffusive Equations

Parareal is a widely studied parallel-in-time method that can achieve meaningful speedup on certain problems. However, it is well known that the method typically performs poorly on non-diffusive equations. This paper analyzes linear stability and convergence for IMEX Runge-Kutta Parareal methods on non-diffusive equations. By combining standard linear stability analysis with a simple convergence analysis, we find that certain Parareal configurations can achieve parallel speedup on non-diffusive equations. These stable configurations all posses low iteration counts, large block sizes, and a large number of processors. Numerical examples using the nonlinear Schrodinger equation demonstrate the analytical conclusions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Effective field theory of stochastic diffusion from gravity

Planar black holes in AdS have long-lived quasinormal modes which capture the physics of charge and momentum diffusion in the dual field theory. How should we characterize the effective dynamics of a probe system coupled to the conserved currents of the dual field theory? Specifically, how would such a probe record the long-lived memory of the black hole and its Hawking fluctuations? We address this question by exhibiting a universal gauge invariant framework which captures the physics of stochastic diffusion in holography: a designer scalar with a gravitational coupling governed by a single parameter, the Markovianity index. We argue that the physics of gauge and gravitational perturbations of a planar Schwarzschild-AdS black hole can be efficiently captured by such designer scalars. We demonstrate that this framework allows one to decouple, at the quadratic order, the long-lived quasinormal and Hawking modes from the short-lived ones. It furthermore provides a template for analyzing fluctuating open quantum field theories with memory. In particular, we use this set-up to analyze the diffusive Hawking photons and gravitons about a planar Schwarzschild-AdS black hole and derive the quadratic effective action that governs fluctuating hydrodynamics of the dual CFT. Along the way we also derive results relevant for probes of hyperscaling violating backgrounds at finite temperature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

The utility of diffusion-weighted imaging in improving the sensitivity of LI-RADS classification of small hepatic observations suspected of malignancy

Purpose: We investigated the added value of diffusion-weighted imaging (DWI)/apparent diffusion coefficient (ADC) in the categorization of small hepatic observation (≤ 20 mm) detected in patients with chronic liver disease in reference to LI-RADS (liver imaging reporting and data system) classification system. Methods: We prospectively evaluated 165 patients with chronic liver disease with small hepatic observations (≤ 20 mm) which were previously categorized as LI-RADS grade 3–5 on dynamic contrast-enhanced CT (DCE-CT). All patients were submitted to a functional MRI including DCE and DWI. Using LI-RADS v2017, two radiologists independently evaluated the observations and assigned a LI-RADS category to each observation using DCE-MRI alone and combined DCE-MRI and DWI/ADC. In the combined technique, the radiologists assigned a LI-RADS category based on a modified LI-RADS criteria in which restricted diffusion on DWI was considered a major feature of HCC. We evaluated the inter-reader agreement with Kappa statistics and compared the diagnostic performance of the LI-RADS with two imaging techniques by Fisher’s exact test using histopathology as the reference standard. Results: Combined technique in LI-RADS yielded better sensitivities (reader 1, 97% [65/67]; reader 2, 95.5% [64/67]) for HCC diagnosis than DCE-MRI alone (reader 1, 80.6% [54/67], p = 0.005; reader 2, 83.6% [56/67], p = 0.04). The specificities were insignificantly lower in combined technique (reader 1, 88.4% [107/121]; reader 2, 77.7% [94/121]) than in DCE-MRI alone (reader 1, 90.9% [110/121], p = 0.67; reader 2, 79.3% [96/121], p = 0.88). The inter-reader agreement of the LI-RADS scores between combined technique and DCE-MRI was good (κ = 0.765). Conclusion: The use of DWI/ADC as an additional major criterion, improved the sensitivity of LI-RADS in the diagnosis of HCC while keeping high specificity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Diffusion tensor imaging of the kidney in healthy controls and in children and young adults with autosomal recessive polycystic kidney disease

Objective: To compare diffusion tensor imaging (DTI) of the kidneys and its derived parameters in children with autosomal recessive polycystic kidney disease (ARPKD) versus healthy controls. Methods: In a prospective IRB-approved study, we evaluated the use of DTI to compare kidney parenchyma FA values in healthy controls (age-matched children with no history of renal disease) versus patients with ARPKD. A 20-direction DTI with b-values of b = 0 s/mm{sup 2} and b = 400 s/mm{sup 2} was used to acquire data in coronal direction using a fat-suppressed spin-echo echo-planar sequence. Diffusion Toolkit and TrackVis were used for analysis and segmentation. TrackVis was used to draw regions of interest (ROIs) covering the entire volume of the renal parenchyma, excluding the collecting system. Fibers were reconstructed using a deterministic fiber tracking algorithm. The FA values based on the ROI data, mean length, and volume of the tracks based on the fiber tracking data were recorded. Results: Eight healthy controls (mean age = 12.9 years ± 4.0; 1/8 males) and six ARPKD participants (mean age = 13.8 years ± 8.5; 5/6 males) were included in the study. Compared to healthy controls, patients with ARPKD had significantly lower FA values (0.33 ± 0.03 vs. 0.25 ± 0.02, p = 0.002) and mean track length (16.73 ± 3.43 vs. 11.61 ± 1.29 mm, p = 0.005). Conclusion: DTI of the kidneys shows significantly lower FA values and mean track length in children and young adults with ARPKD compared to normal subjects. DTI of the kidney offers a novel approach for characterizing renal disease based on changes in diffusion anisotropy and kidney structure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

The Hot Bending and Diffusion Bonding of TiAl-Based Alloy for Corrugated-Core Sandwich Structure

The multi-layer structure of TiAl-based alloys can meet the demand of having lightweight and high-strength properties at elevated temperature. In this paper, the corrugated-core sandwich structure of a TiAl-based alloy was fabricated by the hot bending/diffusion bonding process. In order to fabricate this structure, the high-temperature tensile property, hot bending behavior, and vacuum diffusion bonding of a Ti-47.5Al-Cr-V alloy were investigated. The flow behavior was evaluated by uniaxial tensile experiment, and the results showed that the alloy exhibited good plasticity at the given conditions, and the maximum elongation reached 200% at 1000 °C at strain rate of 3 × 10{sup −4} s{sup −1}. The bending experiments were also performed at temperatures of 950, 1000, and 1050 °C with fillet radii of R = 0, 0.5, and 1 mm, respectively. No micro-/macro-defects developed. The vacuum diffusion bonding of this alloy was also carried out, and the shear bonding strength of bonding joints was measured at room temperature. The maximum shear strength was 398 MPa, and the joint was obtained at 1000 °C/30 MPa/3 h. Combining the bonding interface with the shear strength of different joints, the appropriate bonding pressure and bonding time for diffusion bonding of the TiAl alloy at 1000 °C were 20 MPa and 2 h, respectively. Then, the forming process of the corrugated-core sheet was conducted at 1000 °C with a fillet radius of 1 mm. Finally, the corrugated-core sandwich structure was manufactured under vacuum atmosphere, and the mechanical properties and the interface microstructure were investigated.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Ultrahigh temperature in situ transmission electron microscopy based bicrystal coble creep in zirconia I: Nanowire growth and interfacial diffusivity

This study demonstrates novel in situ transmission electron microscopy-based microscale single grain boundary Coble creep experiments used to grow nanowires through a solid-state process in cubic ZrO 2 between ≈ 1200 °C and ≈ 2100 °C. Experiments indicate Coble creep drives the formation of nanowires from asperity contacts during tensile displacement, which is confirmed by phase field simulations. The experiments also facilitate efficient measurement of grain boundary diffusivity and surface diffusivity. 10 mol% Sc 2 O 3 doped ZrO 2 is found to have a cation grain boundary diffusivity of $D_{gb} = (0.056 ± 0.05)exp (\frac{-380,000±41,000}{RT})m^2 s^{-1}$, and $D_s = (0.10 ± 0.27)exp(\frac{-380,000 ± 28,000}{RT}) m^2 s^{-1}$.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Chloride diffusivity, chloride threshold, and corrosion initiation in reinforced alkali-activated mortars: Role of calcium, alkali, and silicate content

The aim of this study is to investigate systematically the chloride diffusivity and chloride threshold of a wide range of calcium-rich and fly ash-dominated alkali-activated samples in light of their compositional differences. To this end, the effects of various fly ash (FA)-to-slag ratios, of alkali concentrations and of silicate content in the activator were investigated. The electrochemical aspects of the passive samples were also assessed. Results show the prominent role of calcium in the matrix to reduce the chloride diffusivity. While higher alkali concentration increased the porosity and chloride diffusivities in general, lower modulus ratios provided considerably better performance in the FA-dominated samples. Chloride threshold values range between 0.19 (wt% binder mass) for calcium-rich mortars fabricated at low levels of alkalinities and 0.69 for FA-dominated mortars fabricated with highly alkaline activators. Half-cell potential and polarization resistance of alkali-activated samples were in general lower than their Portland cement counterparts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Integration of hydrophobic gas diffusion layers for zero-gap electrolyzers to enable highly energy-efficient CO 2 electrolysis to C 2 products

Electrochemical CO 2 reduction (eCO2R) is an attractive route for mitigating global CO 2 emissions while producing value-added chemicals. Ethylene is one product of eCO2R and is an essential industrial precursor with a global market of $230 billion. The large-scale implementation of C 2 H 4 -selective CO 2 electrolyzers remains challenging because of low energy efficiencies. In this work, we develop the design principles necessary for incorporating an expanded polytetrafluoroethylene (ePTFE) electrode into a zero-gap electrolyzer while simultaneously developing an integrated electrical front contact that reduces the ohmic resistances inherent to electrically insulating gas diffusion layers. By co-designing the catalyst layer, gas diffusion medium, and operating conditions for a zero-gap ePTFE gas diffusion electrode (GDE), we achieved a full-cell voltage of 2.5 V at 200 mA cm −2 at 25 cm 2 geometric area cell with Faradaic efficiencies of 48% for ethylene and 40% for ethanol. This work highlights strategies for developing a scalable, stable, and highly energy-efficient eCO2R for C 2 products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Discovering a reaction–diffusion model for Alzheimer’s disease by combining PINNs with symbolic regression

Misfolded tau proteins play a critical role in the progression and pathology of Alzheimer's disease. Recent studies suggest that the spatio-temporal pattern of misfolded tau follows a reaction-diffusion type equation. However, the precise mathematical model and parameters that characterize the progression of misfolded protein across the brain remain incompletely understood. Here, we use deep learning and artificial intelligence to discover a mathematical model for the progression of Alzheimer's disease using longitudinal tau positron emission tomography from the Alzheimer's Disease Neuroimaging Initiative database. Specifically, we integrate physics informed neural networks (PINNs) and symbolic regression to discover a reaction-diffusion type partial differential equation for tau protein misfolding and spreading. First, we demonstrate the potential of our model and parameter discovery on synthetic data. Then, we apply our method to discover the best model and parameters to explain tau imaging data from 46 individuals who are likely to develop Alzheimer's disease and 30 healthy controls. Our symbolic regression discovers different misfolding models f(c) for two groups, with a faster misfolding for the Alzheimer's group, f(c) = 0.23c 3 – 1.34c 2 + 1.11c, than for the healthy control group, f(c) = –c 3 + 0.62c 2 + 0.39c. Our results suggest that PINNs, supplemented by symbolic regression, can discover a reaction-diffusion type model to explain misfolded tau protein concentrations in Alzheimer's disease. Furthermore, we expect our study to be the starting point for a more holistic analysis to provide image-based technologies for early diagnosis, and ideally early treatment of neurodegeneration in Alzheimer's disease and possibly other misfolding-protein based neurodegenerative disorders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Diffusion of point defects in ordered and disordered Ni–Fe alloys

We present how the ordered and disordered arrangement of elements can affect the transport properties of point defects in Ni–Fe metallic alloys using atomistic simulations. With molecular dynamics (MD) based on both first-principles calculations and empirical potentials, we show that defect diffusion slows down in the ordered Ni–Fe phases due to the decrease of effective coordination number for nearest-neighbor defect jumps. Thus, the disorder-order transition influences defect migration by changing the local atomic environment. We further elucidate that the defect diffusion in ordered and disordered phases is a result of the interplay between preferential defect diffusion and defect stability that relate to the defect energetics. These results indicate that defect evolution may be significantly delayed by embedding certain ordered structures into bulk disordered alloys, which are important to the understanding of the role of disorder in metallic alloys and provide insights on materials engineering by tuning the disorder/order level.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Stable low diffusion flux splitting schemes on unstructured meshes

Shock instabilities are shown to manifest in modern low-diffusion flux-vector splitting (FVS) schemes when used on unstructured meshes, or situations where shocks do not align with the mesh lines. These instabilities occur irrespective of the Mach number of the shock. Three types of dissipative mechanisms that suppress these instabilities are presented. These mechanisms are carefully designed in order to affect only problematic regions of the flux-splittings. The AUSM + and LDFSS schemes are stabilized using the proposed modifications. It is shown that the added dissipation improves the shock behavior of AUSM and LDFSS on unstructured meshes. It is also shown that the AUSM + -up scheme is prone to the “carbuncle” instability, a specific type of shock instability, when used on unstructured meshes. The modifications proposed in this work do not lead to carbuncle instabilities for the problems considered here. Furthermore, the modified schemes are shown to satisfy certain properties that are crucial for accurate shear layer computations, such as stationary contact preservation. Using benchmark problems, it is demonstrated that despite the diffusion added for stabilization, these schemes are not overly diffusive. Furthermore, due to these advantages, the modified FVS schemes presented here are promising candidates for high-speed compressible flow computations on unstructured meshes.

97 MATHEMATICS AND COMPUTING↗