TY - JOUR
T1 - Holistic Variability Analysis in Resistive Switching Memories Using a Two-Dimensional Variability Coefficient
AU - Acal, Christian
AU - Maldonado, David
AU - Aguilera, Ana M.
AU - Zhu, Kaichen
AU - Lanza, Mario
AU - Roldán, Juan Bautista
N1 - KAUST Repository Item: Exported on 2023-04-10
Acknowledgements: The authors thank the support of the Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain), and the FEDER program for Projects B-TIC-624-UGR20, PID2020-113961GB-I00, A-FQM-66-UGR20, and FQM-307. Additionally, the authors acknowledge financial support by the IMAG María de Maeztu Grant CEX2020-001105-M/AEI/10.13039/501100011033. M.L. acknowledges generous support from the King Abdullah University of Science and Technology.
PY - 2023/4/7
Y1 - 2023/4/7
N2 - We present a new methodology to quantify the variability of resistive switching memories. Instead of statistically analyzing few data points extracted from current versus voltage (I-V) plots, such as switching voltages or state resistances, we take into account the whole I-V curve measured in each RS cycle. This means going from a one-dimensional data set to a two-dimensional data set, in which every point of each I-V curve measured is included in the variability calculation. We introduce a new coefficient (named two-dimensional variability coefficient, 2DVC) that reveals additional variability information to which traditional one-dimensional analytical methods (such as the coefficient of variation) are blind. This novel approach provides a holistic variability metric for a better understanding of the functioning of resistive switching memories.
AB - We present a new methodology to quantify the variability of resistive switching memories. Instead of statistically analyzing few data points extracted from current versus voltage (I-V) plots, such as switching voltages or state resistances, we take into account the whole I-V curve measured in each RS cycle. This means going from a one-dimensional data set to a two-dimensional data set, in which every point of each I-V curve measured is included in the variability calculation. We introduce a new coefficient (named two-dimensional variability coefficient, 2DVC) that reveals additional variability information to which traditional one-dimensional analytical methods (such as the coefficient of variation) are blind. This novel approach provides a holistic variability metric for a better understanding of the functioning of resistive switching memories.
UR - http://hdl.handle.net/10754/690910
UR - https://pubs.acs.org/doi/10.1021/acsami.2c22617
U2 - 10.1021/acsami.2c22617
DO - 10.1021/acsami.2c22617
M3 - Article
C2 - 37027783
SN - 1944-8244
JO - ACS Applied Materials & Interfaces
JF - ACS Applied Materials & Interfaces
ER -