This paper presents robotic manipulation methods for rapid high-arc object transfer using dynamic, non-prehensile interactions. Two complementary techniques are introduced, two-fingered scoop-and-flick and one-fingered topple-and-flick, designed for objects with low and high centers of mass, respectively. Both methods enable a robot to retrieve objects resting on a surface and launch them into controlled projectile trajectories without requiring stable grasp formation. To support these maneuvers, we develop physics-based models of object acquisition and release, and combine them with a data-driven framework. While analytical modeling guides the acquisition phase, the highly nonlinear flicking dynamics are captured using learned predictive models that enable accurate selection of control parameters for desired trajectories. The proposed techniques enable dynamic object transfer, reduced grasp planning complexity, and adaptability to environmental constraints. Experiments conducted on a custom robotic platform demonstrate reliable and accurate high-arc object transfer, in which the majority of object displacement is achieved through projectile motion.