In this work, fluctuation patterns of ReRAM current are classified automatically by proposed fluctuation pattern classifier (FPC). FPC is trained with artificially created dataset to overcome the difficulties of measured current signals, including the annotation cost and imbalanced data amount. Using FPC, fluctuation occurrence under different write conditions is analyzed for both HRS and LRS current. Based on the measurement and classification results, physical models of fluctuations are established.

Minimizing the residual impurity gases is a key factor for reducing temporal dark image sticking. Therefore, this paper uses a vacuum-sealing method that minimizes the residual impurity gases by enhancing the base vacuum level, and the resultant change in temporal dark image sticking is then examined in comparison to that with the conventional sealing method using 42-in. ac-PDPs with a high Xe (11%) content. As a result of monitoring the difference in the display luminance, infrared emission, and perceived luminance between the cells with and without temporal dark image sticking, the vacuum-sealing method is demonstrated to reduce temporal dark image sticking by decreasing the residual impurity gases and increasing the oxygen vacancy in the MgO layer. Furthermore, the use of a modified driving waveform along with the vacuum-sealing method is even more effective in reducing temporal dark image sticking.