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Additions of solute that trap vacancies slow down vacancy diffusion and promote point-defect recombination in alloys subjected to irradiation. Such selective alloying can thus help to minimize the detrimental consequences resulting from point defect fluxes. The current work investigates the effect of solute additions on the recombi- nation rate using kinetic Monte Carlo simulations for a model alloy system, which was parametrized to Cu-Ag in the dilute limit, but with an increased solubility limit, ≈0.86 at.% at 300 K. As the solute concentration was increased above 0.1 at.%, solute clustering was observed and led to a strong increase in recombination rate. The beneficial effects of solute clustering on reducing vacancy mobility, and reducing solute drag, were analyzed by calculating relevant transport coefficients using the KineCluE code (Schuler et al., Computational Materials Science (2020) 172,109,191). Moreover, it was observed in the KMC simulations that large recombination rates resulted in a shift of steady-state distributions of solute cluster sizes to smaller clusters compared to equilibrium distributions in the solid solution. This shift is rationalized as resulting from the irreversible character of the interstitial-vacancy recombination reaction. These results suggest a novel irradiation effect on phase stability where a high recombination rate increases the solubility limit of a solute at steady state over its equilibrium value. 

Computational methods have become increasingly used in both academia and industry. At the University of Illinois Urbana Champaign, the Department of Materials Science and Engineering (MSE), as part of a university-funded educational innovation program, has integrated computation throughout its undergraduate courses since 2014. Within this curriculum, students are asked to solve practical problems related to their coursework using computational tools in all required courses and some electives. Partly in response to feedback from students, we have expanded our current curriculum to include more computational modules. A computational module was added to the freshman Introduction to Materials Science and Engineering class; thus, students will be expected to use computational tools from their first year onwards. In this paper, we survey students who are currently taking courses with integrated computation to explore the effects of gradually introducing students to programming as well as both macro- and micro-scale simulations over multiple years. We investigate the improving confidence level of students, their attitude towards computational tools, and their satisfaction with our curriculum reform. We also updated our survey to be more detailed and consistent between classes to aid in further improvements of our MSE curriculum. 

A computational approach has become an indispensable tool in materials science research and related industry. At the University of Illinois, Urbana-Champaign, our team at the Department of Materials Science and Engineering (MSE), as part of a Strategic Instructional Initiatives Program (SIIP), has integrated computation into multiple MSE undergraduate courses over the last years. This has established a stable environment for computational education in MSE undergraduate courses through the duration of the program. To date, all MSE students are expected to have multiple experiences of solving practical problems using computational modules before graduation. In addition, computer-based techniques have been integrated into course instruction through iClicker, lecture recording, and online homework and testing. In this paper, we seek to identify the impact of these changes beyond courses participating in the original SIIP project. We continue to keep track of students' perception of the computational curriculum within participating courses. Furthermore, we investigate the influence of the computational exposure on students' perspective in research and during job search. Finally, we collect and analyze feedback from department faculty regarding their experience with teaching techniques involving computation.