The mass and binding energy of atomic nuclei are the keys to the understanding of
many physical processes. For this reason, it is important to construct reliable theoretical
models for the values of the nuclear mass and binding energy of a nucleus as a function of mass A and atomic number Z. Generally, the binding energy is, to a first approximation, a
fairly smooth function of `macroscopic' degrees of freedom that pertain to the nucleus as
a whole. If we are willing to ignore small local departures, it is possible to develop
simple formulae that express the binding energy EB, or equivalently mass M (Z,N) of a nucleus in terms of these bulk coordinates. In order to keep the formulae simple, we may not wish,
for instance, to make complicated calculations to relate various terms in the expression to
the underlying nucleon-nucleon interactions. One of the more popular approaches to
obtain nuclear binding energies is based on the analogy of a nucleus to a drop of
incompressible fluid.
The Weizacker mass formula does not always give good results for the binding
energy differences of nearby nuclei that are important in many applications. For this purpose
the Kelson-Garvey approach (Janecke, 1988, p. 285 and Basu, 2004) is more useful. This
method is a microscopic model that nuclear binding energy is considered to be the result of a sum
of one and two-nucleon interaction terms. The value of these terms may vary from one
mass region to another but in a small region differing only by a few nucleons, they must
essentially be constant. The known binding energies of nuclei may be used to extract the values
of these terms and results may then be used to predict the unknown binding energies in
the same region. We illustrate this method below by considering the one and two
nucleon interactions and then develop a method to calculate the binding energy with the
considering three nucleon interactions. Finally, we calculate the binding energy for some nuclei
and compare the obtained results with available experimental and theoretical data. |