Constraints on the symmetry energy from neutron star observations

The modeling of many neutron star observables incorporates the microphysics of both the stellar crust and core, which is tied intimately to the properties of the nuclear matter equation of state (EoS). We explore the predictions of such models over the range of experimentally constrained nuclear matter parameters, focusing on the slope of the symmetry energy at nuclear saturation density $L$. We use a consistent model of the composition and EoS of neutron star crust and core matter to model the binding energy of pulsar B of the double pulsar system J0737-3039, the frequencies of torsional oscillations of the neutron star crust and the instability region for r-modes in the neutron star core damped by electron-electron viscosity at the crust-core interface. By confronting these models with observations, we illustrate the potential of astrophysical observables to offer constraints on poorly known nuclear matter parameters complementary to terrestrial experiments, and demonstrate that our models consistently predict $L<70$ MeV.

Enhancement of Spin Injection into Graphene by Water Dipping

We immerse single layer graphene spin valves into purified water for a short duration (<1 min) and investigate the effect on spin transport. Following water immersion, we observe an enhancement in nonlocal magnetoresistance. Additionally, the enhancement of spin signal is correlated with an increase in junction resistance, which produces an increase in spin injection efficiency. This study provides a simple way to improve the signal magnitude and establishes the robustness of graphene spin valves to water exposure, which enables future studies involving chemical functionalization in aqueous solution.