Data-driven simulations for training AI-based segmentation of neutron images.

Neutron interferometry uniquely combines neutron imaging and scattering methods to enable characterization of multiple length scales from 1 nm to 10 µm. However, building, operating, and using such neutron imaging instruments poses constraints on the acquisition time and on the number of measured images per sample. Experiment time-constraints yield small quantities of measured images that are insufficient for automating image analyses using supervised artificial intelligence (AI) models. One approach alleviates this problem by supplementing annotated measured images with synthetic images. To this end, we create a data-driven simulation framework that supplements training data beyond typical data-driven augmentations by leveraging statistical intensity models, such as the Johnson family of probability density functions (PDFs). We follow the simulation framework steps for an image segmentation task including Estimate PDFs → Validate PDFs → Design Image Masks → Generate Intensities → Train AI Model for Segmentation. Our goal is to minimize the manual labor needed to execute the steps and maximize our confidence in simulations and segmentation accuracy. We report results for a set of nine known materials (calibration phantoms) that were imaged using a neutron interferometer acquiring four-dimensional images and segmented by AI models trained with synthetic and measured images and their masks.

Simultaneous multimaterial operando tomography of electrochemical devices.

The performance of electrochemical energy devices, such as fuel cells and batteries, is dictated by intricate physiochemical processes within. To better understand and rationally engineer these processes, we need robust operando characterization tools that detect and distinguish multiple interacting components/interfaces in high contrast. Here, we uniquely combine dual-modality tomography (simultaneous neutron and x-ray tomography) and advanced image processing (iterative reconstruction and metal artifact reduction) for high-contrast multimaterial imaging, with signal and contrast enhancements of up to 10 and 48 times, respectively, compared to conventional single-modality imaging. Targeted development and application of these methods to electrochemical devices allow us to resolve operando distributions of six interacting fuel cell components (including void space) with the highest reported pairwise contrast for simultaneous yet decoupled spatiotemporal characterization of component morphology and hydration. Such high-contrast tomography ushers in key gold standards for operando electrochemical characterization, with broader applicability to numerous multimaterial systems.

Data from cryo-neutron phase change experiments with LH2 and LCH4.

Cryogenic Propellant management is a critical roadblock to enable long term space missions. Commonly used propellants (liquid hydrogen and methane) undergo constant vaporization but there is limited knowledge on the phase change rate and its implications on long term storage stability. This is, in part, due to the inability to image the liquid-vapor mixture inside opaque metallic containers at cryogenic temperatures. Here, neutron imaging is used as a visualization technique to track the liquid-vapor interface inside Al 6061 and SS 316 test cells. The data contains first known images of steady evaporation/condensation in cryogenic propellants. The experiments were conducted at the NIST Center for Neutron Research using the BT-2 Neutron Imaging facility. The test cells were instrumented with temperature sensors and inserted into a 70-mm liquid helium cryostat before being placed into the neutron beam. Temperatures and pressures were altered to achieve condensation/evaporation and Neutron images were captured during the entire phase change process. Phase change rates were obtained through image processing. The data contains raw images and processed phase change rates along with experimental temperature and pressure. The one-of-a-kind data could be used for model validation, correlation development or serve as a benchmark for future experiments.

Fabrication of Black Body Grids by Thick Film Printing for Quantitative Neutron Imaging.

Neutron imaging offers deep penetration through many high-Z materials while also having high sensitivity to certain low-Z isotopes such as 1H, 6Li, and 10B. This unique combination of properties has made neutron imaging an attractive tool for a wide range of material science and engineering applications. However, measurements made by neutron imaging or tomography are generally qualitative in nature due to the inability of detectors to discriminate between neutrons which have been transmitted through the sample and neutrons which are scattered by the sample or within the detector. Recent works have demonstrated that deploying a grid of small black bodies (BBs) in front of the sample can allow for the scattered neutrons to be measured at the BB locations and subsequently subtracted from the total measured intensity to yield a quantitative transmission measurement. While this method can be very effective, factors such as the scale and composition of the sample, the beam divergence, and the resolution and construction of the detector may require optimization of the grid design to remove all measurement biases within a given experimental setup. Therefore, it is desirable to have a method by which BB grids may be rapidly and inexpensively produced such that they can easily be tailored to specific applications. In this work, we present a method for fabricating BB patterns by thick film printing of Gd2O3 and evaluate the performance with variation in feature size and number of print layers with cold and thermal neutrons.

Effect of Fluid Properties on Contact Angles in the Eagle Ford Shale Measured with Spontaneous Imbibition.

Models of fluid flow are used to improve the efficiency of oil and gas extraction and to estimate the storage and leakage of carbon dioxide in geologic reservoirs. Therefore, a quantitative understanding of key parameters of rock-fluid interactions, such as contact angles, wetting, and the rate of spontaneous imbibition, is necessary if these models are to predict reservoir behavior accurately. In this study, aqueous fluid imbibition rates were measured in fractures in samples of the Eagle Ford Shale using neutron imaging. Several liquids, including pure water and aqueous solutions containing sodium bicarbonate and sodium chloride, were used to determine the impact of solution chemistry on uptake rates. Uptake rate analysis provided dynamic contact angles for the Eagle Ford Shale that ranged from 51 to 90° using the Schwiebert-Leong equation, suggesting moderately hydrophilic mineralogy. When corrected for hydrostatic pressure, the average contact angle was calculated as 76 ± 7°, with higher values at the fracture inlet. Differences in imbibition arising from differing fracture widths, physical liquid properties, and wetting front height were investigated. For example, bicarbonate-contacted samples had average contact angles that varied between 62 ± 10° and ∼84 ± 6° as the fluid rose in the column, likely reflecting a convergence-divergence structure within the fracture. Secondary imbibitions into the same samples showed a much more rapid uptake for water and sodium chloride solutions that suggested alteration of the clay in contact with the solution producing a water-wet environment. The same effect was not observed for sodium bicarbonate, which suggested that the bicarbonate ion prevented shale hydration. This study demonstrates how the imbibition rate measured by neutron imaging can be used to determine contact angles for solutions in contact with shale or other materials and that wetting properties can vary on a relatively fine scale during imbibition, requiring detailed descriptions of wetting for accurate reservoir modeling.

Effect of Membrane Properties on the Carbonation of Anion Exchange Membrane Fuel Cells.

Anion exchange membrane fuel cells (AEMFC) are potentially very low-cost replacements for proton exchange membrane fuel cells. However, AEMFCs suffer from one very serious drawback: significant performance loss when CO2 is present in the reacting oxidant gas (e.g., air) due to carbonation. Although the chemical mechanisms for how carbonation leads to voltage loss in operating AEMFCs are known, the way those mechanisms are affected by the properties of the anion exchange membrane (AEM) has not been elucidated. Therefore, this work studies AEMFC carbonation using numerous high-functioning AEMs from the literature and it was found that the ionic conductivity of the AEM plays the most critical role in the CO2-related voltage loss from carbonation, with the degree of AEM crystallinity playing a minor role. In short, higher conductivity-resulting either from a reduction in the membrane thickness or a change in the polymer chemistry-results in faster CO2 migration and emission from the anode side. Although this does lead to a lower overall degree of carbonation in the polymer, it also increases CO2-related voltage loss. Additionally, an operando neutron imaging cell is used to show that as AEMFCs become increasingly carbonated their water content is reduced, which further drives down cell performance.

Boosting Membrane Hydration for High Current Densities in Membrane Electrode Assembly CO2 Electrolysis.

Despite the advantages of CO2 electrolyzers, efficiency losses due to mass and ionic transport across the membrane electrode assembly (MEA) are critical bottlenecks for commercial-scale implementation. In this study, more efficient electrolysis of CO2 was achieved by increasing cation exchange membrane (CEM) hydration via the humidification of the CO2 reactant inlet stream. A high current density of 755 mA/cm2 was reached by humidifying the reactant CO2 in a MEA electrolyzer cell featuring a CEM. The power density was reduced by up to 30% when the fully humidified reactant CO2 was introduced while operating at a current density of 575 mA/cm2. We reduced the ohmic losses of the electrolyzer by fourfold at 575 mA/cm2 by fully humidifying the reactant CO2. A semiempirical CEM water uptake model was developed and used to attribute the improved performance to 11% increases in membrane water uptake and ionic conductivity. Our CEM water uptake model showed that the increase in ohmic losses and the limitation of ionic transport were the result of significant dehydration at the central region of the CEM and the anode gas diffusion electrode-CEM interface region, which exhibited a 2.5% drop in water uptake.

Using operando techniques to understand and design high performance and stable alkaline membrane fuel cells.

There is a need to understand the water dynamics of alkaline membrane fuel cells under various operating conditions to create electrodes that enable high performance and stable, long-term operation. Here we show, via operando neutron imaging and operando micro X-ray computed tomography, visualizations of the spatial and temporal distribution of liquid water in operating cells. We provide direct evidence for liquid water accumulation at the anode, which causes severe ionomer swelling and performance loss, as well as cell dryout from undesirably low water content in the cathode. We observe that the operating conditions leading to the highest power density during polarization are not generally the conditions that allow for long-term stable operation. This observation leads to new catalyst layer designs and gas diffusion layers. This study reports alkaline membrane fuel cells that can be operated continuously for over 1000 h at 600 mA cm-2 with voltage decay rate of only 32-µV h-1 - the best-reported durability to date.

Reconciling temperature-dependent factors affecting mass transport losses in polymer electrolyte membrane electrolyzers.

In this work, we investigated the impact of temperature on two-phase transport in low temperature (LT)-polymer electrolyte membrane (PEM) electrolyzer anode flow channels via in operando neutron imaging and observed a decrease in mass transport overpotential with increasing temperature. We observed an increase in anode oxygen gas content with increasing temperature, which was counter-intu.itive to the trends in mass transport overpotential. We attributed this counterintuitive decrease in mass transport overpotential to the enhanced reactant distribution in the flow channels as a result of the temperature increase, determined via a one-dimensional analytical model. We further determined that gas accumulation and fluid property changes are competing, temperature-dependent contributors to mass transport overpotential; however, liquid water viscosity changes led to the dominate enhancement of reactant water distributions in the anode. We present this temperature-dependent mass transport overpotential as a great opportunity for further increasing the voltage efficiency of PEM electrolyzers.

Thick Sintered Electrode Lithium-Ion Battery Discharge Simulations: Incorporating Lithiation-Dependent Electronic Conductivity and Lithiation Gradient Due to Charge Cycle.

In efforts to increase the energy density of lithium-ion batteries, researchers have attempted to both increase the thickness of battery electrodes and increase the relative fractions of active material. One system that has both of these attributes are sintered thick electrodes comprised of only active material. Such electrodes have high areal capacities, however, detailed understanding is needed of their transport properties, both electronic and ionic, to better quantify their limitations to cycling at higher current densities. In this report, efforts to improve models of the electrochemical cycling of sintered electrodes are described, in particular incorporation of matrix electronic conductivity which is dependent on the extent of lithiation of the active material and accounting for initial gradients in lithiation of active material in the electrode that develop as a consequence of transport limitations during charging cycles. Adding in these additional considerations to a model of sintered electrode discharge resulted in improved matching of experimental cell measurements.

Probing transport limitations in thick sintered battery electrodes with neutron imaging.

Lithium-ion batteries have received significant research interest due to their advantages in energy and power density, which are important to enabling many devices. One route to further increase energy density is to fabricate thicker electrodes in the battery cell; however, careful consideration must be taken when designing electrodes as to how increasing the thickness impacts the multiscale and multiphase molecular transport processes, which can limit the overall battery operating power. Design of these electrodes necessitates probing the molecular processes when the battery cell undergoes electrochemical charge/discharge. One tool for in situ insights into the cell is neutron imaging, because neutron imaging can provide information of where electrochemical processes occur within the electrodes. In this manuscript, neutron imaging is applied to track the lithiation/delithiation processes within electrodes at different current densities for a full cell with a thick sintered Li4Ti5O12 anode and LiCoO2 cathode. The neutron imaging reveals that the molecular distribution of Li+ during discharge within the electrode is sensitive to the current density, or equivalently discharge rate. An electrochemical model provides additional insights into the limiting processes occurring within the electrodes. In particular, the impact of tortuosity and molecular transport in the liquid phase within the interstitial regions in the electrodes are considered, and the influence of tortuosity was shown to be highly sensitive to the current density. Qualitatively, the experimental results suggest that the electrodes behave consistent with the packed hard sphere approximation of Bruggeman tortuosity scaling, which indicates that the electrodes are largely mechanically intact but also that a design that incorporates tunable tortuosity could improve the performance of these types of electrodes.

Influence of Substrate Moisture State and Roughness on Interface Microstructure and Bond Strength: Slant Shear vs. Pull-Off Testing.

There are conflicting views in the literature concerning the optimum moisture state for an existing substrate prior to the application of a repair material. Both saturated-surface-dry (SSD) and dry substrates have been found to be preferable in a variety of studies. One confounding factor is that some studies evaluate bonding of the repair material to the substrate via pull-off (direct tension) testing, while others have employed some form of shear specimens as their preferred testing configuration. Available evidence suggests that dry substrate specimens usually perform equivalently or better in shear testing, while SSD ones generally exhibit higher bond strengths when a pull-off test is performed, although exceptions to these trends have been observed. This paper applies a variety of microstructural characterization tools to investigate the interfacial microstructure that develops when a fresh repair material is applied to either a dry or SSD substrate. Simultaneous neutron and X-ray radiography are employed to observe the dynamic microstructural rearrangements that occur at this interface during the first 4 h of curing. Based on the differences in water movement and densification (particle compaction) that occur for the dry and SSD specimens, respectively, a hypothesis is formulated as to why different bond tests may favor one moisture state over the other, also dependent on their surface roughness. It is suggested that the compaction of particles at a dry substrate surface may increase the frictional resistance when tested under slant shear loading, but contribute relatively little to the bonding when the interface is submitted to pull-off forces. For maximizing bond performance, the fluidity of the repair material and the roughness and moisture state of the substrate must all be given adequate consideration.

Studying water and solute transport through desalination membranes via neutron radiography.

Neutron radiography, a non-destructive imaging technique, is applied to study water and solute transport through desalination membranes. Specifically, we use neutron radiography to quantify lithium chloride draw solute concentrations across a thin-film composite membrane during forward osmosis permeation. This measurement provides direct visual confirmation of incomplete support layer wetting and reveals significant dilutive external concentration polarization of the draw solution outside of the membrane support layer. These transport-limiting phenomena have been hypothesized in previous work and are not accounted for in the standard thin-film model of forward osmosis permeation, resulting in inaccurate estimations of membrane transport properties. Our work demonstrates neutron radiography as a powerful measurement tool for studying membrane transport and emphasizes the need for direct experimental measurements to refine the forward osmosis transport model.

Neutron imaging detector with 2 µm spatial resolution based on event reconstruction of neutron capture in gadolinium oxysulfide scintillators.

We report on efforts to improve the achievable spatial resolution in neutron imaging by centroiding the scintillation light from gadolinium oxysulfide scintillators. The current state-of-the-art neutron imaging spatial resolution is about 10 µm, and many applications of neutron imaging would benefit from at least an order of magnitude improvement in the spatial resolution. The detector scheme that we have developed magnifies the scintillation light from a gadolinium oxysulfide scintillator, calculates the center of mass of the scintillation event, resulting in an event-based imaging detector with spatial resolution of about 2 µm.