[SY-B5] Using computational modeling to understand radiation damage tolerance in complex oxides both from the bottom-up and the top-down
Meeting the ever-increasing demand for energy is a key challenge for the 21st century. Nuclear energy is a proven and green energy source that will be a key component of the world’s energy profile. However, maximizing the efficiency of nuclear energy systems requires materials that have significantly increased tolerance against radiation damage. Computational modeling has an important role in understanding and discovering new materials for next-generation nuclear energy systems.
In this talk, we will describe research efforts that apply computational modeling to understand the response of materials to radiation damage. We will focus on a class of complex oxides, pyrochlores, that have been proposed for nuclear waste encapsulation. Pyrochlores, with the chemical formula A2B2O7, are related to the simpler fluorite structure, with the added complication of having two cation species and oxygen structural vacancies. Past work by numerous groups has shown that the radiation tolerance of these materials is sensitive to the nature of the A and B cations and, in particular, their propensity to disorder. However, these observations are empirical at best and there is still a lack of understanding on the factors that govern the radiation response of these materials.
We have tackled this problem from two different perspectives. First, using accelerated molecular dynamics, we have studied how cation disorder, often created during radiation damage, impacts defect kinetics and thus the transport mechanisms that dictate damage recovery. This bottom-up approach has revealed that a percolation transition occurs as disorder is introduced that leads to higher defect mobilities, which in turn promotes self-healing of the damage. On the other hand, we have used materials informatics to analyze the role of pyrochlore chemistry on radiation tolerance. In this case, divorced from the complexities of making true predictions of performance, we instead use machine learning to take a top-down perspective and discover heuristic relationships between the material composition and the susceptibility of the material to amorphization. While neither study provides a complete understanding of radiation damage in these materials, together they provide a more complete picture of the factors that dictate their response to irradiation.
In this talk, we will describe research efforts that apply computational modeling to understand the response of materials to radiation damage. We will focus on a class of complex oxides, pyrochlores, that have been proposed for nuclear waste encapsulation. Pyrochlores, with the chemical formula A2B2O7, are related to the simpler fluorite structure, with the added complication of having two cation species and oxygen structural vacancies. Past work by numerous groups has shown that the radiation tolerance of these materials is sensitive to the nature of the A and B cations and, in particular, their propensity to disorder. However, these observations are empirical at best and there is still a lack of understanding on the factors that govern the radiation response of these materials.
We have tackled this problem from two different perspectives. First, using accelerated molecular dynamics, we have studied how cation disorder, often created during radiation damage, impacts defect kinetics and thus the transport mechanisms that dictate damage recovery. This bottom-up approach has revealed that a percolation transition occurs as disorder is introduced that leads to higher defect mobilities, which in turn promotes self-healing of the damage. On the other hand, we have used materials informatics to analyze the role of pyrochlore chemistry on radiation tolerance. In this case, divorced from the complexities of making true predictions of performance, we instead use machine learning to take a top-down perspective and discover heuristic relationships between the material composition and the susceptibility of the material to amorphization. While neither study provides a complete understanding of radiation damage in these materials, together they provide a more complete picture of the factors that dictate their response to irradiation.