We present a semi-empirical scaling law for non-resonant ion-atom single charge exchange cross sections for collisions with velocities from 10 to 10 cm s 7 9 1and ions with positive charge q 8 < . Non-resonant cross sections tend to have a velocity peak at collision velocities v 1 au with exponential decay around this peak. We construct a scaling formula for the location of this peak then choose a functional form for the cross section curve and scale it. The velocity at which the cross section peaks, v m , is proportional to the energy defect of the collision, E D , which we predict with the decay approximation. The value of the cross section maximum is proportional to the charge state q, inversely proportional to the target ionization energy I T , and inversely proportional to v m . For the shape of the cross section curve, we use a function that decays exponentially asymptotically at high and low velocities. We scale this function with parameters v I Z Z , , , and m T T P , where the Z T,P are the target and projectile atomic numbers. For the more than 100 cross section curves that we use to find the scaling rules, the scaling law predicts cross sections within a little over a factor of 2 on average.
We present an extension of the classical overbarrier model [F. Sattin, Phys. Rev. A 62, 042711 (2000)] to include the effect of electron back-capture. Back-capture is the process by which an electron that has already been captured by the projectile ion is recaptured by the target atom. Back-capture reduces the electron capture cross section at low impact velocities when the projectile ionization energy is less than that of the target. This creates a cross section peak. We alter the location of this peak to correspond to that predicted by an adiabatic criterion by using a free parameter of the model. These extensions bring the overbarrier model more in line with experimental data, especially at low impact velocity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.