Hydrogen embrittlement of Ni-based superalloys modeled at the atomic scale
Abstract
The present two-year project will develop an information-efficient scheme to carry out atomistic simulations on structural materials systems, and will apply the scheme to study the embrittlement and mechanical failure of alloys, primarily Ni-based, due to hydrogen impurities. Specifically, a first “Methods” part of the project will use Machine Learning (ML) techniques to speed up multi-scale “QM/MM” atomistic simulations in which quantum-mechanical (QM) calculations are embedded in molecular-mechanics (MM) calculations to simulate model materials systems in the million-atom size range. A second “Applications” part of the project will use the QM/MM scheme to elucidate hydrogen-induced stress-shielding effects, and fracture-related phenomena such as embrittlement and failure of nickel systems. Both project parts are of direct interest for ONR. Namely, developing novel “big data” methodologies enabling the simulation of chemo- mechanical processes in materials (e.g., catastrophic brittle fracture, fatigue cracking, stress corrosion, friction, …) is of clear strategic value for a large range of applications. When used in conjunction with High Performance Computing (HPC), these simulation approaches have a great potential to offer an increasingly attractive and cost-saving alternative to full physical testing. Meanwhile, nickel-based superalloys are the main material components of turbine blades used in jet engines, whose safe operation is of obvious strategic interest for the US Navy planes. In particular, the stress shielding phenomena that will be investigated here have been conjectured to occur even at extremely low hydrogen background concentrations [1], potentially enabling enhanced dislocation pileup up, and failure in operation. The main expected outcomes of the project will be (1) devising an efficient ML scheme for this class of applications, in particular novel representations of atomic configurations, to be used in machine learning databases for QM-based structural materials simulations, and (2) new knowledge on the failure mechanism of the Ni/Ni3Al interfaces system, elucidating any role of H in promoting the process. The project results will be implemented in state of the art software and will be disseminated in conference presentations and scientific papers.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 03, 2017
- Source ID
- N62909151N079
Entities
People
- Alessandro De Vita
Organizations
- Office of Naval Research
- United States Navy