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The lack of an engaging pedagogy and the highly competitive atmosphere in introductory science courses tend to discourage students from pursuing science, technology, engineering, and mathematics (STEM) majors. Once in a STEM field, academic and social integration has been long thought to be important for students’ persistence. Yet, it is rarely investigated. In particular, the relative impact of in-class and out-of-class interactions remains an open issue. Here, we demonstrate that, surprisingly, for students whose grades fall in the “middle of the pack,” the out-of-class network is the most significant predictor of persistence. To do so, we use logistic regression combined with Akaike’s information criterion to assess in- and out-of-class networks, grades, and other factors. For students with grades at the very top (and bottom), final grade, unsurprisingly, is the best predictor of persistence—these students are likely already committed (or simply restricted from continuing) so they persist (or drop out). For intermediate grades, though, only out-of-class closeness—a measure of one’s immersion in the network—helps predict persistence. This does not negate the need for in-class ties. However, it suggests that, in this cohort, only students that get past the convenient in-class interactions and start forming strong bonds outside of class are or become committed to their studies. Since many students are lost through attrition, our results suggest practical routes for increasing students’ persistence in STEM majors.

The ability to use common computational thermodynamic and kinetic tools to study the microstructure evolution in Inconel 625 (IN625) manufactured using the additive manufacturing (AM) technique of laser powder-bed fusion is evaluated. Solidification simulations indicate that laser melting and re-melting during printing produce highly segregated interdendritic regions. Precipitation simulations for different degrees of segregation show that the larger the segregation, i.e., the richer the interdendritic regions are in Nb and Mo, the faster the d-phase (Ni 3 Nb) precipitation. This is in accordance with the accelerated d precipitation observed experimentally during post-build heat treatments of AM IN625 compared to wrought IN625. The d-phase may be undesirable since it can lead to detrimental effects on the mechanical properties. The results are presented in the form of a TTT diagram and agreement between the simulated diagram and the experimental TTT diagram demonstrate how these computational tools can be used to guide and optimize post-build treatments of AM materials.

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Ultra-small-angle X-ray scattering-X-ray photon correlation spectroscopy (USAXS-XPCS) is a new measurement technique for the study of equilibrium and slow nonequilibrium dynamics in disordered materials. Taking advantage of Bonse-Hart crystal optics, this technique fills a gap between the accessible scattering vector ranges of dynamic light scattering and conventional X-ray photon correlation spectroscopy. It also overcomes the limits of visible light scattering techniques imposed by multiple scattering and is suitable for the study of optically opaque materials containing near-micrometer sized structures. USAXS-XPCS has been applied to study the equilibrium dynamics of micrometer-sized colloidal dispersions and nonequilibrium dynamics of polymer composites and alloy steels. We anticipate that this technique will be important in the understanding of thermallyinduced equilibrium dynamics of soft materials and nonequilibrium behavior of both soft and hard materials, and lead to technical payoffs in a wide range of areas such as the manufacture of advanced ceramic and metallurgical materials and self-repairing biologically critical materials.

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