A potential energy function for the water dimer has been developed with an artificial neural network (back propagation of error algorithm). The potential energy surface was obtained with 6s3p3d/3s3p MP2 ab initio MO calculations. The trained neural network reproduced the potential energy surface of the water dimer very well, not only in the low-energy region but also in the high-energy region.
All Science Journal Classification (ASJC) codes
- Physics and Astronomy(all)
- Physical and Theoretical Chemistry