DIFFERENTIAL SCATTERING CROSS-SECTIONS FOR HECL2, NECL2, AND ARCL2 - MULTIPROPERTY FITS OF THE POTENTIAL-ENERGY SURFACES

Differential scattering cross section measurements are reported for th e Ne and Ar scattering from Cl-2. This new data, along with previously published data and ab initio quantum calculations, are used to determ ine potential energy surfaces for HeCl2, NeCl2, and ArCl2 via multipro perty fits. The starting point of the fitting procedure was fitting a one-center Morse-spline-van der Waals potential to a set of ab initio points for each molecule. Because the resulting ab initio potential is highly anisotropic, this fit required the use of up to nine anisotrop y parameters, many more than could independently be fitted with experi mental data alone. Therefore the ab initio potential was adjusted to f it the data by varying as few of the parameters as possible. The fit t o the scattering data was carried out within the infinite order sudden approximation. The fits were also constrained by spectroscopically de termined rotational constants and experimental dissociation energies ( except for HeCl2 for which no measurement of D-0 is available). These were calculated from the potentials via a J-dependent variational meth od. The ab initio surfaces can be brought into good accord with the da ta by an overall deepening of the potentials and a slight shift to sho rter distances. In the case of NeCl2, for which the best data is avail able, no changes in the anisotropy parameters were necessary to achiev e an excellent fit. For HeCl2 and ArCl2 the fitting required slightly more adjustments, and there are more uncertainties inherent in the fit ting method, but very good agreement is still achieved. The present mu ltiproperty analysis confirms that the highly anisotropic ab initio su rfaces, with similar well depths for the linear and perpendicular conf igurations, are consistent with the experimental data. We believe that these are the best available surfaces for the ground states of these molecules, and that new data or much higher level calculations will be required to achieve significant improvements.