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DOE OSTI2024

Synchrotron micro-computed tomography analysis of neutron-irradiated U-Mo fuel

The three-dimensional (3D) microstructure of neutron-irradiated uranium-10 wt.% molybdenum (U-10Mo) fuel with a burn-up of 9.8 × 10 21 fissions/cm 3 was characterized using a novel, multi-modal synchrotron micro-computed tomography approach combining propagation-based phase-contrast enhanced and absorption contrast techniques. The porosity development, porosity interconnectedness, swelling, composition, local thickness of the zirconium (Zr) diffusion barrier, and the influence of the fuel–cladding interaction on the local composition and pore morphology, were uniquely determined in 3D. Two cuboids were produced using a focused ion beam-scanning electron microscope at the Zr diffusion barrier–fuel interface and in the bulk fuel. The bulk fuel sample swelled by 53.3 [+9.7/−3.1]%, while the fuel near the Zr–fuel interface swelled by 63.3 [+14.7/−7.2]%. The average local thickness of the Zr diffusion barrier decreased by 53 %, compared to the expected pre-irradiated thickness. Four pore morphology regions were identified initiating parallel to the fuel–Zr interaction region: (1) an interaction layer of suppressed porosity, (2) a layer of elongated and interconnected porosity, (3) a transition zone of low porosity, and (4) a layer of unoriented porosity representative of the bulk fuel behavior. The increase in porosity near the diffusion barrier corresponded to a higher U concentration compared to that in the bulk fuel. The interconnected porosity in the fuel near the diffusion barrier was extensive and oriented parallel to the diffusion barrier, while the bulk fuel had more compact and isolated pore networks. The interaction layer, despite having suppressed porosity, was nearly 100 wt.% U. Porosity suppression at the diffusion barrier corresponds to the expected reduction in radiation-driven diffusion of Xe at the interface despite the anticipated increase in fission product nucleation originating from a higher U concentration. In conclusion, the novel 3D insights of the porosity, swelling, and compositional variations characterized herein can improve the fidelity of fuel performance codes for proliferation-resistant fuels for research and test reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Laser strengthening of additive manufactured edge seal for vacuum insulated glazing with micro-size glass frit

Sealing of glass edge is a key step in developing cost-effective and durable vacuum insulated glazing for the drive towards net-zero energy buildings. In this study, to achieve a high-strength sealing with scalable and low-cost processing, we investigated a novel sealing method based on additive manufacturing and laser process and reported quantitative analysis of the laser assisted method sealing strength and the requirement of vacuum insulation glazing. Micro-size glass frits in printing ink and a continuous-wave laser curing were employed to allow the formation of a hermetic bonding layer with low thermal budget. Controlling various sealing parameters including laser traveling speed, spot diameter, and laser power, the water seepage and mechanical strength of the resulting glass-to-glass bonding were examined. Through the response surface methodology, we identified the optimized sealing condition where the bonding strength reached 5.68 MPa. A comparation of the bonding strength between thermal sealing method and laser-assisted method has been analyzed as well.

42 ENGINEERING↗

DOE OSTI2020

Microstructural and micro-mechanical analysis of 14YWT nanostructured Ferritic alloy after varying thermo-mechanical processing paths into tubing

Microstructural analyses and micro-pillar compression were conducted on 14YWT nanostructured ferritic alloy (NFA) to compare different processing pathways: hydrostatic extrusion and Pilger processing with varying annealing temperatures into thin walled tubing, and after hot extrusion and cross-rolling into a plate. Hydrostatic extrusion at 815 °C resulted in the smallest grain sizes and highest yield strength of 1.20 GPa. Pilger processing with annealing at 800 °C had fine grained regions and bands of coarse grains, leading to a large variation in yield strength of 0.9–1.40 GPa. Higher annealing temperatures of 1200 °C after pilger processing significantly increased the grain size and lowered the yield strength to 1.01 GPa. These tubes showed a stronger (111) crystallographic texture in the normal direction and elongated grains in the extrusion direction. Characterization of the nano-oxides using TEM reveals more numerous, smaller oxides present in tubing processed at lower temperatures. Overall, this work shows NFA tubing after hydrostatic extrusion and pilger processing can lead to fine grained microstructures and texturing leading to higher yield strengths at lower annealing temperatures (e.g. 800 °C).

14YWT↗

DOE OSTI2024

Engineered MXene quantum dots for micro-supercapacitors with excellent capacitive behaviors

Micro-supercapacitors (MSCs) have drawn tremendous attention as promising candidates to power miniaturized portable/wearable electronics, but they still suffer from unsatisfactory electrochemical performance (e.g., insufficient energy density, mediocre rate capability), thus impeding their widespread applications. Here, a synergistic surface and structure engineering strategy achieved by downsizing to quantum dot scale, doping of heteroatoms, and introducing defects and functional groups is proposed to regulate the physicochemical properties of Ti 3 C 2 T x MXene. Encouragingly, the resulting MSCs based on defect-rich nitrogen-doped Ti 3 C 2 T x quantum dots (QDs) possess excellent electrochemical performance as demonstrated by large operating voltage (3.0 V in ionic liquid and 1.0 V in aqueous electrolyte), perfect rectangular CV shape even at 1000 V·s -1 , high volumetric capacitance of 33.1 F·cm -3 , and superior cycling stability after 10000 cycles. By employing experimental characterizations and density functional theory calculations, the remarkable performance of the MSCs is mainly due to the special chemical states as well as the unique surface and structural features of Ti 3 C 2 T x QDs, which offer abundant active sites, shorten ion diffusion pathways, promote ion/electron transports, and provide enhanced capacitance. Finally, this work provides a new strategy for the design of high-performance MSCs and a reference for the applications of MXene QDs in other energy-related fields.

42 ENGINEERING↗

DOE OSTI2020

Electron-positron pair creation in the electric fields generated by micro-bubble implosions

Here, we show that electron-positron pair production from the vacuum is possible via the strong Coulomb fields generated by micro-bubble implosions induced by ultra-high intensity lasers. Even in the case where the Coulomb fields are lower than the pair creation threshold, externally injected high energy electrons or photons could be used to generate pairs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Effects of dilution and pressure on combustion characteristics within externally heated micro-tubes

Here this study investigates the impact of pressure and dilution on combustion behavior of of C 2H6/air/N2 mixtures within an externally heated micro-tube using both experimental and analytical techniques. Experiments are conducted for pressures up to 10 bar at multiple dilution levels and document three flame regimes, i.e. weak flames, FREI and normal flames. Characteristic temperatures for flame stabilization, as well as and ignition and extinction are obtained by applying a novel thin filament pyrometry method (TFP), which uses a thin silicon carbide (SiC) filament that enables temperature measurements for both reacting and non-reacting cases. Results show a decrease of characteristic temperatures with increasing pressure, which can be which can be partially compensated by a decrease of O2 content. Further, regime transitions occur at lower velocity as the pressure increases, whereas weak flame positions are insensitive to dilution at a given pressure. Predictions from the analytical model compare favorably with experimental results. The most prominent finding is that as dilution increases, the transition from weak flame to FREI becomes less abrupt and is completely lost for high dilution levels (i.e. low O2 content). Both experimental and analytical results indicate that the unstable FREI combustion regime does not exist at high dilution levels, i.e. weak flame and normal flame regimes are no longer clearly separated. As FREI are interpreted as a cyclic transition from an ignition zone to a propagating flame, results for highly diluted conditions are interpreted as a combustion regime where classical flame propagation ceases to exist.

42 ENGINEERING↗

DOE OSTI2022

Porosity evolution under increasing tension in wire-arc additively manufactured aluminum using in-situ micro-computed tomography and convolutional neural network

Internal defects such as porosities are often formed in additively manufactured metal components. The pores nucleate, grow, and coalesce to form cracks under loads, leading to eventual catastrophic failure. Here, in this paper, the full-field porosity evolution, including pore growth and coalescence in a wire-arc additively manufactured (WAAM) aluminum alloy cylinder under tension is observed with in-situ X-ray micro-computed tomography (μCT). The pore size distribution, density, and tensile stress are calculated from the volumetric images analyzed by a convolutional neural network (CNN) algorithm, which provides rapid analysis of 12,950 slice images from μCT volumetric images at the reference state and 13 tensile strains. The results show the quantitative evolution of the growth and coalescence of macropores under tension. A strong correlation is found between the local pore volume fraction and the true tensile stress when the tensile strain is larger than 5%.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Investigation of Coupled Processes in Fractures and the Bordering Matrix via a Micro‐Continuum Reactive Transport Model

Abstract In multi‐mineral fractured rocks, the altered porous layer on the fracture surface resulting from preferential dissolution of the fast‐reacting minerals can have profound impacts on subsequent chemical‐physical alteration of the fractures. This study adopts the micro‐continuum approach to provide further understanding of reactive transport processes in the altered layer (AL), and mass exchanges with the bordering matrix and fracture. The modeling framework couples the Darcy‐Brinkman‐Stokes (DBS) solver in COMSOL Multiphysics and the geochemical modeling capability of CrunchFlow. Three‐dimensional steady state simulations with systematically varied chemical‐physical parameters of the AL were performed to examine the impacts of individual factors and processes. Our simulation results confirm previous observations that dissolution of the fast‐reacting mineral (i.e., calcite) is largely controlled by diffusion across the AL. We also show that dissolution of the slow‐reacting mineral (i.e., dolomite), which controls AL development and fracture enlargement, increases with surface area and has a complex dependence on different local rate‐limiting processes. In particular, advection can result in evident spatial variations in the local dissolution rates of dolomite, although it does not affect the bulk chemistry significantly. The difference in the spatial patterns between simulations with and without advection in the AL is more noticeable in the locations with smaller apertures, with up to 20% difference in local reaction rates. Therefore, it is important to include a full depiction of advection, diffusion, and reactions for accurately capturing local dynamics that control long‐term fracture evolution.

58 GEOSCIENCES↗

DOE OSTI2021

Simulated Performance of the Micro-Pocket Fission Detector in the Advanced Test Reactor Critical Facility

The Micro-Pocket Fission Detector (MPFD) is a small-form–factor real-time fission chamber. MPFD performance has been simulated in the Advanced Test Reactor Critical Facility (ATRC), located at Idaho National Laboratory (INL). Here, the neutron and gamma-ray flux profiles and magnitudes were simulated using Monte Carlo N-Particle (MCNP) in the near-core B-8 irradiation position. These simulations were performed at 69 discrete axial locations inside the B-8 position for three separate orientations of the nearby hafnium outer shim control cylinders and at a power level of 700 Wth. The resulting neutron and gamma-ray flux values were used to determine the MPFD response for various fissile masses and detector gas pressures. The optimal gas-operating pressure was determined to be between 30 and 60 psig. The required fissile-layer mass was determined to be between 1–2 µg of 235 U. Additionally, the gamma-ray to fission-fragment interaction rate was determined to be 4.42 × 10 -3 with average energy deposition for gamma rays and fission fragments in 30 psig argon gas to be 1 keV and 9.5 MeV, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Equilibrium Core Model for Micro Pebble Bed Reactors Using OpenMC

Estimating the equilibrium state for pebble bed reactors (PBRs) presents complex challenges as it requires simultaneous consideration of changes in the pebbles’ movement as well as their fuel compositions. Whereas traditional approaches use multigroup diffusion codes for neutronics calculations of PBRs’ equilibrium state, the double-heterogeneity of PBRs complicates neutron cross-section generation. Continuous-energy Monte Carlo (MC) methods are better suited for detailed PBR analysis because of their natural handling of double-heterogeneity, but they demand substantially more computational resources. Here, this study introduces a novel method for efficiently estimating the equilibrium state in small and micro PBRs with reduced computational cost. The method is anticipated to accelerate the processes of core design and performing parametric studies for utilizing advanced fuel and structural materials. The HTR-10 reactor design was used for validating the method’s predictions and evaluating its computational efficiency. When compared to reference calculation values from the literature, criticality (k-effective) was predicted to be approximately within the margin of error of the MC transport calculation, average core power density (in megawatts per cubic meter) was predicted within 2.5% relative error, and maximum thermal flux (10 13 n/cm 2 .s −1 ) was predicted within 1.8% relative error. The calculated inventory of fission products and fuel composition in the equilibrium core were within 15% and 16.6%, respectively, when compared to reported values from the literature. The difference is attributed to variance in the considered values of the core temperature, which was found to significantly affect the depletion analyses.

Equilibrium core↗

DOE OSTI2024

Measurement of atomic oxygen densities using TALIF on a dielectric barrier discharge: insights into the volume above a micro cavity plasma array

Dielectric barrier discharges, particularly micro cavity plasma arrays, offer significant potential for plasma-catalytic research due to their ability to ignite plasma in direct contact with a catalytic surface, enabling the observation of plasma-surface interactions. A key factor in their application is the generation of reactive species, such as atomic oxygen, within the cavities. These species can interact with both the surface (e.g. for activation or cleaning) and the gas being treated (e.g. for oxidation). Given the central role of oxygen atoms in plasma catalysis and their use as a model for more complex species, this work investigates the transport of these atoms out of the cavities. Two-photon absorption laser-induced fluorescence spectroscopy with picosecond laser excitation is performed in the volume above the cavities. The results are compared with a basic diffusion model. The reactor operates with a He/O 2 mixture at a flow rate of 1 slm and atmospheric pressure. Densities of up to 10 16 cm -3 are measured near the surface. Time-dependent measurements show that, at a distance of 350 µm from the surface, a density equilibrium is reached within less than 3 ms of reactor operation. Decay times due to ozone formation after the reactor is turned off are on a similar scale. Spatially resolved measurements show that the oxygen density decreases exponentially from the surface but remains detectable up to approximately 1 mm above the surface, indicating significant application potential. Variations in the O 2 admixture show a density maximum at 0.4%, confirming previous helium state enhanced actinometry measurements within the cavities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Micro-tearing mode dominated electron heat transport in DIII-D H-mode pedestal

Abstract A new, comprehensive set of evidence reveals that Micro-Tearing Modes (MTMs) dominate pedestal electron heat transport in an H-mode experiment in the DIII-D tokamak. The experiment investigates the role of MTMs by scanning pedestal collisionality, a main drive of MTM instability, from 0.43 to 0.84 on the pedestal top. Broadband (150–800 kHz) magnetic and density fluctuations originating from the pedestal gradient region and highly consistent with MTMs are observed, with amplitude increasing during the scan. The higher magnetic fluctuation amplitude correlates with a lower pedestal electron temperature gradient, implying MTMs may regulate the pedestal electron heat transport. The collisionality scan results in profile and transport changes consistent with predicted transport capability of MTMs: (1) experimentally-determined electron heat diffusivity increases ∼40% at the location where the broadband density fluctuations peak; (2) ion heat diffusivity has less increase (<20%); and (3) a locally flattened region in the electron temperature pedestal is observed at high collisionality. A local, linear gyrokinetic simulation finds MTMs as the most unstable mode in the pedestal gradient region. In addition, local, nonlinear simulations suggest MTMs can dominate and drive experimentally-relevant, megawatt-level electron heat flux. This result establishes MTMs as an effective transport mechanism in the H-mode pedestal, in particular at high collisionality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

XtalCAMP: a comprehensive program for the analysis and visualization of scanning Laue X-ray micro-/nanodiffraction data

XtalCAMP is a software package based on the MATLAB platform, which is suitable for, but not limited to, the analysis and visualization of scanning Laue X-ray micro-/nanodiffraction data. The main objective of the software is to provide complementary functionalities to the Laue indexing software packages used at several synchrotron beamlines. Here, the graphical user interfaces allow the easy analysis of characteristic microstructure features, including real-time intensity mapping for a quick examination of phase, grain and defect distribution, 2D color-coded mapping of microstructural properties from the output of other Laue indexing software, crystal orientation visualization, grain boundary characterization based on orientation/misorientation calculation, principal strain/stress analysis, and strain ellipsoid representation, as well as a series of additional toolkits. As an example, XtalCAMP is applied to the microstructural investigation of a solution-heat-treated Ni-based superalloy manufactured using a laser 3D-printing technique, and a deformed natural quartzite from Val Bregaglia in the Central Alps.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Secure and Cost-Effective Micro Phasor Measurement Unit (PMU)-Like Metering for Behind-the-Meter (BTM) Solar Systems using Blockchain-Assisted Smart Inverters

Recently, there is increasing interest in using behind-the-meter (BTM) solar systems for grid services. However, providing visibility and operational situational awareness of BTM solar systems mainly operated by small-scale solar inverters is challenging due to the requirement of relatively expansive networked observation tools (e.g., micro phasor measurement units (µPMUs)) and consequent cybersecurity threats through networks. This paper presents a secure, cost-effective, µPMUs-like metering method using a blockchain-assisted smart (BAS) inverters for a BTM solar system. The proposed BAS inverter consisting of an internet of things device as a node of a local blockchain network enables the secure provision of inverter measurement data for grid services. The BAS inverter sends the encrypted local measurement data with a timestamp to a local blockchain miner. Once the blockchain miner generates a tamper-resistant metering ledger including the measurements, it is used to assess the situational awareness of the BTM solar system. The concept of the proposed metering using the BAS inverters is validated by experimental studies.

behind the meter↗

DOE OSTI2021

Event-Based Analysis of Solar Power Distribution Feeder Using Micro-PMU Measurements

Solar distribution feeders are commonly used in solar farms that are integrated into distribution substations. In this paper, we focus on a real-world solar distribution feeder and conduct an event-based analysis by using micro-PMU measurements. The solar distribution feeder of interest is a behind-the-meter solar farm with a generation capacity of over 4 MW that has about 200 low-voltage distributed photovoltaic (PV) inverters. The event-based analysis in this study seeks to address the following practical matters. First, we conduct event detection by using an unsupervised machine learning approach. For each event, we determine the event’s source region by an impedancebased analysis, coupled with a descriptive analytic method. We segregate the events that are caused by the solar farm, i.e., locallyinduced events, versus the events that are initiated in the grid, i.e., grid-induced events, which caused a response by the solar farm. Second, for the locally-induced events, we examine the impact of solar production level and other significant parameters to make statistical conclusions. Third, for the grid-induced events, we characterize the response of the solar farm; and make comparisons with the response of an auxiliary neighboring feeder to the same events. Fourth, we scrutinize multiple specific events; such as by revealing the dynamics to the control system of the solar distribution feeder. The results and discoveries in this study are informative to utilities and solar power industry.

14 SOLAR ENERGY↗

DOE OSTI2025

On High-Order/Low-Order and Micro-Macro Methods for Implicit Time-Stepping of the BGK Model

In this paper, a high-order/low-order (HOLO) method is combined with a micro-macro (MM) decomposition to accelerate iterative solvers in fully implicit time-stepping of the Bhatnagar–Gross–Krook (BGK) equation for gas dynamics. The MM formulation represents a kinetic distribution as the sum of a local Maxwellian and a perturbation. In highly collisional regimes, the perturbation away from initial and boundary layers is small and can be compressed to reduce the overall storage cost of the distribution. The convergence behavior of the MM methods, the usual HOLO method, and the standard source iteration method is analyzed on a linear BGK model. Both the HOLO and MM methods are implemented using a discontinuous Galerkin (DG) discretization in phase space, which naturally preserves the consistency between high- and low-order models required by the HOLO approach. Furthermore, the accuracy and performance of these methods are compared on the Sod shock tube problem and a sudden wall heating boundary layer problem. Overall, the results demonstrate the robustness of the MM and HOLO approaches and illustrate the compression benefits enabled by the MM formulation when the kinetic distribution is near equilibrium.

BGK model↗

DOE OSTI2026

ML-based Micro-CT SOFC Microstructure Models (from Kent 2026 Microstructural Augmentation paper)

Overview -------------------------- This repository contains datasets from the manuscript **"Enhanced Generalizability to Deep-Learning Quantification of 3D Microstructural Characteristics through Microstructurally Aware Augmentation of Scarce Data"** (*William F. Kent, Rochan Bajpai, Rachel C. Kurchin, William K. Epting, Harry W. Abernathy, Paul A. Salvador. Submitted 2026*). The methods are also described in the dissertation **Data Intensive Analysis of Solid Oxide Cell Microstructures** (*Doctoral dissertation, Carnegie Mellon University, 2025*). The datasets here are trained convolutional neural network (CNN) models for predicting key microstructural properties of solid oxide cell (SOC) electrodes from low-res, 2-channel 3D images, as well as some helpful code. The parameters for input images are provided in the paper. Sample data is provided in the file `Combined_anode_aug_dual_1k_examples` - that particular data was used to train `anode_all_aug.pth` and will work most accurately with that model. Please familiarize yourself with all caveats on accuracy and applicability, as detailed in the associated paper. Usage -------------------------- The basic usage is as follows, assuming `model_fn` is the path to the .pth file, and `X` is 2-channel input image(s) of the proper dimensions (either one image of shape `[2,12,24,24]`, or a batch of N input images of shape `[N,2,12,24,24]`): from CNN_inferencer import load_model_for_inference model = load_model_for_inference(model_fn) y_predicted = model(X) The model object automatically handles input scaling and output de-scaling based on the way the models were trained - in other words, pass in a 2-channel micro-CT image, and it will output microstructural property values in real units. ## Other model object attributes Note that model has useful attributes other than its forward pass model(X). * `model.output_descaler` - returns the output descaler object. Model does the de-scaling when generating inferences, but you may want to re-use this de-scaler on other values to e.g. compare predictions to ground truth from already-scaled training data. * `model.prop_names` - Gives the property names of the predicted y values, in order. Only exists if there's an output scaler as part of the model object, which there will be in the models provided here. ## Usage with sample data Here is a short script to use with the included sample data. from CNN_inferencer import display_predictions, load_model_for_inference, calculate_mape, parity_plot import h5py import numpy as np model_fn = 'anode_all_aug.pth' data_fn = 'Combined_anode_aug_dual_1k_examples.h5' N_samples = 200 figure_outdir = '.' model = load_model_for_inference(model_fn) with h5py.File(data_fn,'r') as f: XX = f['X'] #These are the 2-channel 3D images yy = f['y'] #These are the ground-truth microstructural properties, but they have been scaled for training - need to de-scale below N = XX.shape[0] #How many images total in the input data file #Run inferences on N_samples random samples from XX. #Run in a batch, much more efficient than one at a time. ii = np.random.choice(N,N_samples,replace=False) ii.sort() y_pred = model(XX[ii]) #Get the original/true (but normalized/scaled) values from the training dataset... #Because they were normalized, they are not in real units yet. So let's also de-scale them using model.output_scaler. y_true = model.output_scaler.transform(yy[ii]) #Let's display actual values for just 5 random ones for i in np.random.choice(N_samples,5,replace=False): display_predictions(y_true[i], y_pred[i], model.prop_names) #Make parity plots for each property (ground truth vs predicted values) #Also label each plot with the mean abs. percent error (MAPE) of the predicted values for i,key in enumerate(model.prop_names): mape = calculate_mape(y_true[:,i], y_pred[:,i]) parity_plot(y_true[:,i], y_pred[:,i], figure_outdir, key, extra_title=f' ({mape:.2f}% MAPE)')

3D microstructure↗

DOE OSTI2020

High BMEP and High Efficiency Micro-Pilot Ignition Natural Gas Engine (Final Project Report)

The project objectives were to develop demonstrate a high-efficiency high-output natural gas diesel micro-pilot stoichiometric engine operating with diesel pilot contribution of less than 5% on a medium duty engine. The program’s outcomes achieve in a partnership between Michigan Technological University and Westport Power Inc. were very successful. The engine platform was a 6.7L I6 engine with a compression ratio of 15:1 and achieved 24 bar BMEP and 41% brake thermal efficiency at lambda. Simulation and modeling with an improved turbocharger and combustion chamber improvements demonstrated a clear path to 43% BTE. The operational stoichiometric range was from 5 to 24 bar with minimal throttling. Diesel contribution over the cycle was 4.6%. The results achieved in this program are well above the best in-class baseline natural gas spark ignition engines of 19.5 bar BMEP and 40% BTE.

33 ADVANCED PROPULSION SYSTEMS↗