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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

4D-STEM Coupled with Unsupervised Machine Learning to Reveal at Large-Scale the Microstructural Evolution in Li- and Mn-Rich Cathodes

Li- and Mn-rich (LMR) layered oxides are known to exhibit a thin surface reconstruction layer, which grows during electrochemical cycling in a manner that depends on exposed crystallographic facets, cycling conditions, and electrolyte chemistry. Direct characterization of this layer has traditionally relied on high-resolution electron microscopy, which is inherently limited to small fields of view. Here, we employ four-dimensional scanning transmission electron microscopy (4D-STEM) combined with unsupervised machine-learning clustering to quantitatively map phase distributions over large areas and track their evolution in LMR cathodes during electrochemical aging. Our results show that the surface reconstruction layer consists predominantly of a rocksalt phase, whose thickness varies across different facets following activation cycling and becomes substantially thicker and more uniform during calendar aging. In contrast, a spinel-like phase is observed within the particle bulk. Large-area phase mapping and correlative high-resolution imaging reveal that this spinel-like phase preferentially nucleates at bulk crystallographic defects, including boundaries between 60°-rotated layered domains and associated mixed-phase regions, rather than exclusively at the particle surface. Our findings establish a mechanistic distinction between surface-driven rocksalt formation and bulk-defect-mediated spinel nucleation while demonstrating the unique capability of 4D-STEM to provide statistically robust, mesoscale insight into complex phase-evolution processes in LMR cathodes.

4D-STEM↗
DOE OSTI2019

Relating Structural and Microstructural Evolution to the Reactivity of Cellulose and Lignin during Alkaline Thermal Treatment with Ca(OH) 2 for Sustainable Energy Production Integrated with CO 2 Capture

The transition toward a low carbon economy necessitates the implementation of a wide range of negative emissions technologies, including bioenergy integrated with CO 2 capture and storage. Advancing large-scale or modular technologies for bioenergy with carbon capture and storage requires a fundamental understanding of chemo-morphological coupling in these material systems. In this context, integrated chemical pathways such as alkaline thermal treatment (ATT) of biomass which involves the production of bio-H 2 while converting and storing CO 2 as solid carbonates provides promising potential for integrating bioenergy with carbon capture and storage. We elucidate the structural and morphological changes when biomass feedstocks such as cellulose and lignin are reacted with calcium hydroxide to capture, convert, and store CO 2 as calcium carbonate while producing energy carrier such as H 2 . These structural and morphological changes were monitored using synchrotron based in operando multiscale X-ray scattering measurements. Enhanced CO 2 capture at temperatures above 375 °C was evident from the significant growth of the calcium carbonate phase at these conditions. Increase in the surface area and porosity of cellulose was noted compared to lignin due to the relatively fast decomposition of cellulose. Pore–solid interfaces in Ca(OH) 2 + cellulose system became smoother in the temperature range of 500–700 °C compared to Ca(OH) 2 + lignin system, where the interfaces became rougher. Enhanced roughness of the pore–solid interfaces in the presence of lignin is attributed to the simultaneous slow decomposition of lignin and formation of calcium carbonate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Investigating microstructure evolution in block copolymer membranes

Block copolymer self-assembly in conjunction with nonsolvent-induced phase separation (SNIPS) has been increasingly leveraged to fabricate integral-asymmetric membranes. The large number of formulation and processing parameters associated with SNIPS, however, has prevented the reliable construction of high performance membranes. In this study, we apply dynamical self-consistent field theory to model the SNIPS process and investigate the effect of various parameters on the membrane morphology: solvent selectivity, nonsolvent selectivity, initial film composition, and glass transition composition. We examine how solvent selectivity and concentration of polymers in the film impact the structure of micelles that connect to form the membrane matrix. In particular, we find that preserving the order in the surface layer and forming a connection between the supporting and surface layer are nontrivial and sensitive to each parameter studied. Furthermore, the effect of each parameter is discussed, and suggestions are made for successfully fabricating viable block copolymer membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

How relative defect migration energies drive contrasting temperature-dependent microstructural evolution in irradiated ceramics

Ceramic materials have become widely used in various fields of material science, and ceramic oxides such as cubic zirconia (c- ZrO 2 ) and magnesia (MgO) are candidate materials for nuclear energy applications. For the corresponding in-service conditions of these materials, there is a crucial need in studies at moderate or high temperatures of the physical phenomena underlying the damage buildup under irradiation. Here in the present work, we show, using x-ray diffraction, that these two materials exhibit a similar damage accumulation process under ion irradiation at fixed temperature. However, they display an unexpected opposite damaging rate to changes in the irradiation temperature. In fact, as the temperature is increased, the final damage state is reached earlier in c- ZrO 2 while it is delayed in MgO. Rate equation cluster dynamics simulations show that defect clustering is favored over defect recombination in c- ZrO 2 , but the situation is reversed for MgO, explaining the observed opposite response to temperature of the two materials. This contrasting behavior can be rationalized in terms of nonequivalent interstitial versus vacancy defect migration energies in MgO. We finally demonstrate that these results allow for a qualitative prediction of the evolution of the experimental irradiation-induced disorder with temperature, henceforth potentially reducing the cost in selecting and developing ad hoc materials.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Experimental Validation of UO 2 Microstructural Evolutions for NEAMS Tool MARMOT (Final Report)

The project was aimed at experimentally validating the NEAMS tool MARMOT for predicting the GB migration and pore and GB interaction in UO 2 oxide fuel under the driving forces of high temperatures and large temperature gradient anticipated in a LWR fuels. By performing the well-aligned experiments and simulations simultaneously using precisely defined initial conditions, the high-quality experiment data will provide a direct benchmarking of the MARMOT code by evaluating the fidelity of physics, materials science principles and models, and the coupling of multi-physics solutions. A bottom up approach will be used by studying each specific behavior while the code will be statistically validated again the overall structural evolution. The GB energy, specific GB mobility, grain growth kinetic, GB interaction with pores, and effects of large temperature gradients will be specifically studied using experiments. The isothermal grain growth, grain growth under large temperature gradient, and pore and GB interactions will be modeled using 2-D or 3-D simulations. Four questions will be answered at the conclusion of this project: Is the anisotropic grain boundary energy model able to better represent a real view the grain property and would it have a significant impact on the grain growth behavior? Is the classical Zener pinning model in MARMOT sufficient for representing the retarding effect on grain gain boundary migration from pores? Does the temperature gradient have a minimum impact on the average grain growth behavior at varied average temperatures and temperature gradients? Does the pore migrate towards the high temperature domain at the velocities predicted by MARMOT code?

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

The Effect of Process History on Grain Boundaries and Dislocation Substructures on Functional Properties of Nb for SRF Cavities: Plastic Formability and Microstructural Evolution. Final report

While much progress has been made in improving the performance of cavities in the past decade, reproducible performance remains elusive. This renewal of “The cost of grain boundaries on the performance of superconducting cavities” examines in further depth the interactions between forming and annealing processes and functional performance at the scale of dislocation substructure and grain boundaries. There are five tasks identified in the renewal, which are: Characterization / analysis of current cavity technology: Effect of deformation, heat treatment, surface treatments, and residual damage on cavity function (Lee and Bieler) Characterization of dislocation mechanisms in single and bicrystals (Bieler) Quantifying effects of impurities and deformation mechanisms in Nb using density functional theory calculations (Solanki) Crystal plasticity constitutive model development (Pourboghrat and Eisenlohr) Modeling and measuring thermal conductivity in thin layers (Wright)

36 MATERIALS SCIENCE↗
DOE OSTI2024

Chapter 4: Physically informed deep learning networks for simulating microstructure evolution of 3D polycrystals

As discussed in the previous chapter, high energy diffraction microscopy (HEDM) is used to study the micromechanical evolution of a material during in situ loading. HEDM experiments have been used to verify crystal plasticity (CP) simulations [119, 91, 90, 120], for experimental planning, material design, and to further analyze experimental results. However, Fast Fourier transform-based CP (CP-FFT) or finite element-based CP (CP-FE) methods are often too slow to be used in real-time during an experiment. CP-FFT is faster than CP-FE simulations due to the absence of meshing, but can still take hours to simulate the response of a single volume depending on the size and number of strain steps [127]. Reducing computation time would create a larger exploration space in planning and design, and enable faster analysis of experimental results and real-time feedback during an experiment. This research expands upon previous works to develop a workflow for predicting the full-field evolution of a 3D polycrystal. The workflow is simplified from previous works to predict only orientation and elastic strain tensors (from which stress tensors are calculated). The network is physically informed through loss functions and network architecture for a more robust model. The orientation predictions are informed about the cubic crystal symmetry of the material by incorporating disorientation and misorientation information into the network architecture and loss. The Von Mises stress is used to enforce the correct stress-strain trends in the strain tensor predictions. Additional total strain steps from the elastic and elastoplastic region are included to better capture the stress-strain evolution at smaller total strain steps. Material and hardening parameters are additional inputs into the networks to further inform the network and to study the network’s ability to predict different materials other than those used for training.

36 MATERIALS SCIENCE↗