4.6 Article

Investigations on resistive switching effect and time series statistical analysis of solution combustion synthesized ZnTiO3 memristive device

Journal

JOURNAL OF MATERIALS SCIENCE-MATERIALS IN ELECTRONICS
Volume 33, Issue 30, Pages 23390-23403

Publisher

SPRINGER
DOI: 10.1007/s10854-022-09100-0

Keywords

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Funding

  1. 'RUSA-Industry Sponsored Centre for VLSI System Design', Maharashtra state

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In this research, zinc titanium oxide (ZnTiO3) was synthesized using the solution combustion synthesis technique for resistive memory application. The synthesized material was characterized and a fabricated device demonstrated good resistive switching property and memristive effect. Time series analysis was used to model the switching voltages, and the non-volatile memory measurements showed the device's endurance cycles and data retention capabilities. The study highlights the advantages of solution-processable resistive memory devices and the use of statistical time series analysis for understanding their dynamics.
In this work, a facile approach has been adopted to synthesize zinc titanium oxide (ZnTiO3) using the solution combustion synthesis technique for resistive memory application. The synthesized ZnTiO3 has been thoroughly characterized using different analytical tools. The fabricated Al/ZnTiO3/FTO device demonstrates good bipolar resistive switching property and a non-ideal memristive effect. Furthermore, switching voltages dynamics were modeled using time series analysis based on autoregressive integrated moving average (ARIMA) and Holt-Winter's exponential smoothing (HWES) techniques. The non-volatile memory measurements suggested that the Al/ZnTiO3/FTO memristive device can switch between 10(3) endurance cycles and can retain data up to 10(4) s. The conduction analysis and plausible filamentary type RS mechanism are investigated for the fabricated memristive device. The present work demonstrates the benefits of the solution-processable RS device for non-volatile memory application and the use of statistical time series analysis for understanding the switching voltage dynamics.

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