A strategy to improve fatigue performance of oil-grade nickel-based alloy 718: Low-temperature arc-enhanced glow discharge nitriding
Source abstract
Abstract
Aging hardening nickel-based alloy 718 is a key material for oil and gas applications, but it is susceptible to fatigue failure under the combined effects of cyclic loading and corrosive media. This study focused on exploring low-temperature Arc-Enhanced Glow Discharge (AEGD) nitriding as a strategy to form an expanded austenite (γ N ) nitrided layer, aiming to enhance the fatigue performance of alloy 718. This study aimed to investigate the effects of AEGD nitriding on the fatigue performance of alloy 718. The alloy underwent AEGD nitriding at a low temperature of 400°C for 4 hours, and its characteristics were analyzed using SEM, TEM, XRD, microhardness testing, and residual stress analysis. Fatigue testing was subsequently carried out in both air and a sulfur-containing environment. The results showed that the AEGD nitriding treatment successfully formed a dense nitrided layer, approximately 6 μm thick, dominated by γ N with no obvious nitride formation such as CrN. This nitrided layer increased the surface hardness by approximately 50% and, crucially, transformed the original tensile stress into a residual compressive stress of -474 MPa. As a consequence, the fatigue life of alloy 718 was significantly improved, with increases of 43% in air and 48% in the sulfur-containing environment. Fracture analysis revealed that after nitriding, fatigue crack initiation shifted from the surface to the subsurface region. These findings confirm that low-temperature AEGD nitriding is an effective method for improving the fatigue resistance of alloy 718, offering a promising solution for components subjected to harsh service conditions.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Metal and Thin Film Mechanics · Surface Treatment and Residual Stress · Diamond and Carbon-based Materials Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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