Effects of Breakup of Weakly Bound Projectile and Neutron Transfer on Fusion Reactions

Lin, C.J.; Zhang, H.Q.; Yang, F.; Ruan, M.; Liu, Z.H.; Wu, X.K.; Zhou, P.; Zhang, C.L.; Zhang, G.L.; An, G.P.

doi:10.1063/1.2398820

Effects of Breakup of Weakly Bound Projectile and Neutron Transfer on Fusion Reactions

Nov 15, 2006

Part of Nuclear physics trends. Proceedings, 6th China-Japan Joint Nuclear Physics Symposium, Shanghai, China, May 16-20, 2006, 1

Published in:

AIP Conf.Proc. 865 (2006) 1, 1

Contribution to:

6th China Japan Joint Nuclear Physics Symposium, 1

Published: Nov 15, 2006

DOI:

10.1063/1.2398820

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Abstract: (AIP)

The excitation functions of elastic and quasielastic scattering at backward angles are measured for the systems 16O + 152Sm , 6,7Li + 208Pb. The barrier distributions are extracted from these measured excitation functions and compared with the corresponding fusion barrier distributions. Except some details, the barrier distributions derived from the data of fusion and elastic/quasielastic scattering are almost the same for the tightly bound reaction systems. For the reaction systems with weakly bound projectile, the barrier distributions extracted from quasielastic scattering are obviously different the fusion barrier distributions. However, the barrier distributions extracted from the excitation functions of the quasielastic scattering plus breakup are almost the same as the one extracted from the complete fusion data. This result means that barrier distribution not only bears the information of nuclear structures but also contains the knowledge of reaction mechanisms. In addition, the measured barrier distribution of 32S + 96Zr is flat and extends to lower energy due to the coupling of neutron transfer with positive Q‐values, which will result in a significant enhancement effusion cross sections at the subbarrier energies. However, our results show that the complete fusion of the weakly bound projectile with heavy target is suppressed at the above barrier energies as compared with the model predictions.

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