Manipulation of microstructure and mechanical properties during dehydrogenation of hydrogen-sintered Ti–6Al–4V
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Here, this study investigates the fabrication of oxide dispersion strengthened (ODS) Fe-Cr-Al alloys via laser powder bed fusion (LPBF) with strategic additions of 0.3 wt% Zr and 0.3 wt% Y 2 O 3 for enhanced mechanical performance in nuclear applications. Systematic processing parameter optimization yielded three distinct conditions: one low-density product with significant defects and two near-full-density materials with improved consolidation. Comprehensive characterization confirmed single-phase α-ferrite matrix formation with successful incorporation of Y-, Zr-, O-, and C-rich precipitates characteristic of ODS alloys. However, precipitate density remained low (∼10 7 cm −3 ), resulting in sink strength values substantially below optimal levels for radiation resistance. Microhardness values (mid-200s HV) correlated inversely with grain size following the Hall-Petch relationship, indicating grain boundary strengthening as the dominant mechanism rather than precipitation strengthening. The optimized processing conditions achieved excellent mechanical properties with room temperature yield strength of approximately 500 MPa and 30 % elongation, demonstrating superior strength-ductility synergy compared to other additively manufactured ODS materials and performance consistent with literature values for LPBF-processed ODS-FeCrAl alloys. This investigation reveals both the potential and limitations of LPBF processing for ODS Fe-Cr-Al alloys. While successful defect-free fabrication was achieved, results highlight the critical need for systematic optimization of processing parameters and post-processing heat treatments to enhance precipitate density for effective dispersion strengthening and radiation resistance while maintaining additive manufacturing advantages.
The effort to develop metallic alloys with increased structural strength and improved radiation performance has focused on the incorporation of either solute elements or microstructural inhomogeneities to mitigate damage. The recent discovery and development of single-phase concentrated solid-solution alloys (SP-CSAs) has prompted fundamental questions that challenge established theories and models currently applicable to conventional alloys. Here, the current understanding of electronic and atomic effects, defect evolution, and microstructure progression suggests that radiation energy dissipates in SP-CSAs at different interaction strengths via energy carriers (electrons, phonons, and magnons). Modification of electronic- and atomic-level heterogeneities and tailoring of atomic transport processes can be realized through tuning of the chemical complexity of SP-CSAs by the selection of appropriate elements and their concentrations. Fundamental understanding of controlling energy dissipation via site-to-site chemical complexity reveals new design principles for predictive discovery and guided synthesis of new alloys with targeted functionalities, including radiation tolerance.
This project provides an initial assessment and research recommendations of U-50 wt.%Zr (U-50Zr) for its use as a light water reactor (LWR) fuel. This work based on the outcome of a recently funded exercise on the failure mode effects and analysis (FMEA) and the phenomena identification and ranking table (PIRT) to investigate high level nuclear fuel qualification metrics as derived by the United States Nuclear Regulatory Commission.
In this work the processability and properties of AM alloy ABD900 processed via laser and electron beam powder bed fusion are investigated. Both AM modalities are suitable for processing and the material exhibits good high temperature creep properties. This phase I CRADA demonstrates that ABD900 is a suitable allow for potential blade repair work using powder bed fusional AM technology.
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As part of the US Department of Energy’s Advanced Materials and Manufacturing Technologies program’s mission to accelerate qualification of advanced manufacturing pathways for nuclear applications, laser powder bed fusion (LPBF) 316H stainless steel (SS) has been selected as a model system to develop a rapid code case framework. This effort directly addresses the grand challenges of (1)expanding the limited portfolio of materials currently codified for elevated-temperature nuclear structural service under Section III, Division 5of the American Society of Mechanical Engineers’ Boiler and Pressure Vessel Code; and (2) significantly reducing qualification timelines that traditionally exceed a decade. The strategic importance of LPBF 316H lies in its immediate industrial relevance, existing data foundation from wrought 316H, and alignment with ongoing code case development for LPBF 316L.Prior work revealed accelerated precipitation of deleterious secondary phases and reduced creep ductility in as-printed LPBF 316H. Building on that prior research, FY2025activities focused on establishing an understanding of the key failure mechanisms of crept 316H specimens to aid in code case development and on evaluating stress relief (SR) parameters on the high-temperature performance and thermal aging-induced degradation of tensile and fracture behavior in LPBF316H.
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Explore the source record for details and available documents.
Explore the source record for details and available documents.
Evaluating the mechanical response of fiber-reinforced composites can be extremely time-consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input–output pairs and have exhibited success in composite research. This paper explores a fully convolutional neural network modified from StressNet, which was originally used for linear elastic materials, and extended here for a non-linear finite element (FE) simulation to predict the stress field in 2D slices of segmented tomography images of a fiber-reinforced polymer specimen. The network was trained and evaluated on data generated from the FE simulations of the exact microstructure. The testing results show that the trained network accurately captures the characteristics of the stress distribution, especially on fibers, solely from the segmented microstructure images. The trained model can make predictions within seconds in a single forward pass on an ordinary laptop, given the input microstructure, compared to 92.5 h to run the full FE simulation on a high-performance computing cluster. These results show promise in using ML techniques to conduct fast structural analysis for fiber-reinforced composites and suggest a corollary that the trained model can be used to identify the location of potential damage sites in fiber-reinforced polymers.
Commercially-produced, pressureless sintered Si3N4, SiC, and SiAlON were characterized with respect to density, phases present, bend strength, and oxidation resistance. The room-temperature bend strengths of sintered Si3N4, SiC, and SiAlON are comparable. However, the room-temperature strengths are much lower (approximately 40 to 50%) than the room-temperature strength of hot-pressed Si3N4 (NC-132). The strength loss in Si3N4 and SiAlON materials at high temperature was attributed to a viscous grain-boundary phase, retained during cooling from the sintering temperature. The oxidation resistance of sintered alpha-SiC was the best of any materials tested.
Since the first reports on superconducting thin films obtained by evaporating BaF2, Cu and Y(sup 1), or Yb or Er(sup 2), several others have followed. All these reports describe thin films prepared by means of molecular beam cells or electron guns. Researchers show that films with similar properties can be obtained by radio frequency sputtering of a single mosaic target composed by Y-Er, BaF2 and Cu. Process steps are described.