Method to evaluate LINAC dataset efficiency on the Axcelis GSD/HE class high energy implanters

The Axcelis GSD/HE class of Ion Implanters uses a radio frequency (RF) linear accelerator (LINAC) to provide the final acceleration to the extracted ions. The process of recipe creation on this tool often requires the modification of LINAC datasets which specify the RF voltage amplitude and phase as well as the focusing quadrupole lens voltage of the 10 to 14 RF cavities and lens assemblies. LINAC datasets are uniquely specified by the ion species, ion charge, extraction voltage, final energy, and beam current. The creation of a new dataset for a new final energy can be difficult because a change to the amplitude or phase of any given resonator changes the interaction of the beam with all subsequent downstream resonators. LINAC datasets are often created which make inefficient use of the RF voltage, with phase and amplitude combinations which can result in both acceleration and deceleration at various stages in the LINAC. Poor datasets can result in poor beam transmission efficiency and shorten the life of RF amplifiers which are being driven at unnecessarily high RF voltages. The FEM spectrum tool sweeps the magnetic field of the final energy magnet (FEM) and records the beam current exiting the FEM as a function of the magnet current. We have developed a method to evaluate the efficiency of LINAC datasets by utilizing the built in FEM spectrum capabilities of the tool. By turning off RF resonators starting at the end of the LINAC and using the FEM spectrum tool the energy evolution of the beam as it passes from one resonator to another can be directly measured. The effectiveness of a given RF cavity is then evaluated by computing the acceleration efficiency defined as the energy gain produced by the resonator divided by the resonator Rf. By dissecting the dataset in this manner resonators are often found to add no additional energy, or in some instances decelerate the beam. The characteristics of efficient datasets such as phase shifts from resonator to resonator can be identified which aid in creation of new datasets and the improvement of existing datasets.