An estimation for EUV radiation energy using FLN

Recently, a Z-pinch GDPP light source as EUV for next generation lithography has being developed in our lab. However, the physics of the processes, plasma and surface discharges produced, magneto-hydrodynamic, photon radiation transport, and plasma-electrode interactions, which lead to EUV emission, is intrinsically complex. Many simplifying assumption are inevitable with numerical simulations, resulting in low-credibility outcomes. A FLN with GI learning algorithm has been first employed to construct a predictive model of EUV radiation energy and to overcome the uncertainty of the operational parameters. The research shows that EUV radiation energy can be effectively estimated by using FLN.