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Results for “Post-annealing”

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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41 records · Page 3

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DOE OSTI2021

Perspectives of Open-Air Processing to Enable Perovskite Solar Cell Manufacturing

We report high throughput open-air processing techniques for the scalable production of all device and barrier layers for perovskite photovoltaics (PV). This work discusses and resolves some of the most formidable barriers to module-level scaling that the perovskite community has been facing. Our advanced technoeconomic manufacturing analysis indicates that vacuum-based processes with high capital expenditures (CapEx) and low throughputs dominate the cost of production. Open-air fabrication methods offer low CapEx routes to manufacturing, but achieving reproducibility in ambient conditions with varying relative humidity has been a persistent challenge. The use of rapid processing methods with plasma curing to convert films from the solution-state enables reproducibility, moisture immunity, and the highest perovskite PV efficiency produced in open-air. These methods are readily translatable to in-line processing where layers are sequentially deposited without the need for lengthy post-annealing steps that reduce throughput and involve additional equipment. Significant progress is demonstrated in reduced manufacturing costs as perovskites contend as a commercially viable next-generation thin film PV technology.

14 SOLAR ENERGY↗

DOE OSTI2021

Stable, Ductile and Strong Ultrafine HT-9 Steels via Large Strain Machining

Beyond the current commercial materials, refining the grain size is among the proposed strategies to manufacture resilient materials for industrial applications demanding high resistance to severe environments. Here, large strain machining (LSM) was used to manufacture nanostructured HT-9 steel with enhanced thermal stability, mechanical properties, and ductility. Nanocrystalline HT-9 steels with different aspect rations are achieved. In-situ transmission electron microscopy annealing experiments demonstrated that the nanocrystalline grains have excellent thermal stability up to 700 °C with no additional elemental segregation on the grain boundaries other than the initial carbides, attributing the thermal stability of the LSM materials to the low dislocation densities and strains in the final microstructure. Nano-indentation and micro-tensile testing performed on the LSM material pre- and post-annealing demonstrated the possibility of tuning the material’s strength and ductility. The results expound on the possibility of manufacturing controlled nanocrystalline materials via a scalable and cost-effective method, albeit with additional fundamental understanding of the resultant morphology dependence on the LSM conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Iron nitride permanent magnet and technique for forming iron nitride permanent magnet

A bulk permanent magnetic material may include between about 5 volume percent and about 40 volume percent Fe16N2 phase domains, a plurality of nonmagnetic atoms or molecules forming domain wall pinning sites, and a balance soft magnetic material, wherein at least some of the soft magnetic material is magnetically coupled to the Fe16N2 phase domains via exchange spring coupling. In some examples, a bulk permanent magnetic material may be formed by implanting N+ ions in an iron workpiece using ion implantation to form an iron nitride workpiece, pre-annealing the iron nitride workpiece to attach the iron nitride workpiece to a substrate, and post-annealing the iron nitride workpiece to form Fe16N2 phase domains within the iron nitride workpiece.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Iron nitride permanent magnet and technique for forming iron nitride permanent magnet

Wang, Jian-Ping↗

DOE OSTI2026

Virtual Growth of SRF Materials: A Machine Learning Approach to Predict the Crystalline Structural Ordering in Nb Surface Oxides

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Unlisted, US, IL; Fermilab]↗