NSUF 18-1198: Extension and Validation of Rate Theory Model of Nanocluster Irradiation Evolution: An Atom Probe Tomography Study
The objective of this study is to extend a nanocluster irradiation evolution rate theory model to a wider variety of nuclear-relevant alloys, using atom probe tomography (APT) based validation. Nanoclusters play a critical role in the structure-property-performance relationships of metallic alloys used in nuclear power reactors. Irradiation, however, can induce coarsening or dissolution of these nanoclusters, until a steady-state cluster morphology is achieved. Such changes to the nanocluster size and number density can have profound consequences on the mechanical integrity of alloys under irradiation, thus there is a critical need to understand the irradiation evolution of nanoclusters. To address this need, work overseen by the PI has recently demonstrated a rate theory model that reliably predicts nanocluster evolution in bcc Fe-Cr alloys. The model considers recoil dissolution, disordering dissolution, and diffusion-driven growth. Thus far, the model has been validated against an extensive APT dataset from neutron, proton, and self-ion irradiated model Fe-9Cr oxide dispersion strengthened (ODS) alloy containing Y-Ti-O nanoclusters, and ferritic/martensitic (F/M) alloys HCM12A and HT9, containing Cu-rich, and Si-Ni-Mn-rich (i.e. G-phase) nanoclusters, all irradiated using neutrons, protons, or self-ions; this validation data has been obtained through a series of previous NSUF projects since 2014. However, since irradiation-induced nanocluster evolution is a technical challenge in nearly all nuclear alloys, there is value in extending this model to additional classes of alloys.
In this project, we hypothesize that our same rate theory model can be extended to a wider range of alloys by adjusting for the relevant alloying components’ diffusivities. We now propose to collect the requisite APT data against which this model can be validated. We select four crosscutting, nuclear-relevant alloys that enable us to test the versatility of the model for variations in: (a) composition of ODS oxide nanoclusters, tested using proton irradiated Fe-Cr ODS alloy containing Zr-O nanoclusters, (b) minor alloying species, tested using proton irradiated SA508 pressure vessel steel containing irradiation-induced G-phase nanoclusters, (c) crystal structure, tested using neutron irradiated 304 stainless steel containing irradiation-induced G-phase nanoclusters, and (d) major alloying elements and clustered species, tested using proton irradiated Cu-10Ta containing Ta-rich nanoclusters. Scientifically, this work will demonstrate the efficacy of a rate theory model to meaningfully predict nanocluster irradiation evolution across a wide spectrum of nuclear alloys. More broadly, this work will enable alloy designers to better account for these nanoclusters and design more irradiation-stable nano/microstructures in future nuclear alloys.
Additional Info
| Field | Value |
|---|---|
| Abstract | The objective of this study is to extend a nanocluster irradiation evolution rate theory model to a wider variety of nuclear-relevant alloys, using atom probe tomography (APT) based validation. Nanoclusters play a critical role in the structure-property-performance relationships of metallic alloys used in nuclear power reactors. Irradiation, however, can induce coarsening or dissolution of these nanoclusters, until a steady-state cluster morphology is achieved. Such changes to the nanocluster size and number density can have profound consequences on the mechanical integrity of alloys under irradiation, thus there is a critical need to understand the irradiation evolution of nanoclusters. To address this need, work overseen by the PI has recently demonstrated a rate theory model that reliably predicts nanocluster evolution in bcc Fe-Cr alloys. The model considers recoil dissolution, disordering dissolution, and diffusion-driven growth. Thus far, the model has been validated against an extensive APT dataset from neutron, proton, and self-ion irradiated model Fe-9Cr oxide dispersion strengthened (ODS) alloy containing Y-Ti-O nanoclusters, and ferritic/martensitic (F/M) alloys HCM12A and HT9, containing Cu-rich, and Si-Ni-Mn-rich (i.e. G-phase) nanoclusters, all irradiated using neutrons, protons, or self-ions; this validation data has been obtained through a series of previous NSUF projects since 2014. However, since irradiation-induced nanocluster evolution is a technical challenge in nearly all nuclear alloys, there is value in extending this model to additional classes of alloys. In this project, we hypothesize that our same rate theory model can be extended to a wider range of alloys by adjusting for the relevant alloying components’ diffusivities. We now propose to collect the requisite APT data against which this model can be validated. We select four crosscutting, nuclear-relevant alloys that enable us to test the versatility of the model for variations in: (a) composition of ODS oxide nanoclusters, tested using proton irradiated Fe-Cr ODS alloy containing Zr-O nanoclusters, (b) minor alloying species, tested using proton irradiated SA508 pressure vessel steel containing irradiation-induced G-phase nanoclusters, (c) crystal structure, tested using neutron irradiated 304 stainless steel containing irradiation-induced G-phase nanoclusters, and (d) major alloying elements and clustered species, tested using proton irradiated Cu-10Ta containing Ta-rich nanoclusters. Scientifically, this work will demonstrate the efficacy of a rate theory model to meaningfully predict nanocluster irradiation evolution across a wide spectrum of nuclear alloys. More broadly, this work will enable alloy designers to better account for these nanoclusters and design more irradiation-stable nano/microstructures in future nuclear alloys. |
| Award Announced Date | 2018-02-01T14:14:33.79 |
| Awarded Institution | None |
| Facility | None |
| Facility Tech Lead | Yaqiao Wu |
| Irradiation Facility | None |
| PI | Janelle Wharry |
| PI Email | [email protected] |
| Project Type | RTE |
| RTE Number | 1198 |