Versatile Sol–Gel and Inkjet Printing Route for Low-Cost Fabrication of Mesoporous SiO<sub>2</sub>-Based Conductive Bridge Memristors

The growing demand for cost-effective nonvolatile memory has driven research into emerging resistive random-access memory (ReRAM) technologies, including conductive bridge random-access memories (CBRAMs). In this work, we investigate the electrical performance of CBRAMs based on mesoporous sol-gel SiO<sub>2</sub> electrolytes, fabricated using a cost-effective process combining sol-gel deposition, evaporation-induced self-assembly, and inkjet printing. By varying key fabrication parameters, namely, porosity and electrolyte thickness, we analyze their impact on switching behavior, retention, and endurance. Our findings reveal that mesoporous SiO<sub>2</sub> significantly enhances CBRAM performance, offering well-controlled ionic pathways for filament formation and dissolution while keeping the deposition process flexible in terms of deposition parameters. Among the tested configurations, the memory cells based on a moderately porous (20%) and thick (280 nm) SiO<sub>2</sub> layer demonstrate the best stability, with minimal SET/RESET voltage variability, strong retention over 28 h, and reliable endurance over 1000 cycles. In contrast, highly porous electrolyte layers lead to greater variability in resistive states due to unstable filament dissolution. These results highlight the potential of mesoporous SiO<sub>2</sub>-based CBRAMs for next-generation memory applications, particularly in flexible electronics and neuromorphic computing. The study provides key insights into optimizing memory design through electrolyte engineering and scalable, low-cost manufacturing processes.

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Publication Details

Journal
ACS Omega
Published
2025-09-04
DOI
https://doi.org/10.1021/acsomega.5c06969
Primary Topic
Advanced Memory and Neural Computing
Type
article
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article

Versatile Sol–Gel and Inkjet Printing Route for Low-Cost Fabrication of Mesoporous SiO2-Based Conductive Bridge Memristors

David Grosso, Cédric Djaou, Magali Putero, Minh Anh Luong et al.
ACS Omega
Advanced Memory and Neural Computing
article

Versatile Sol–Gel and Inkjet Printing Route for Low-Cost Fabrication of Mesoporous SiO2-Based Conductive Bridge Memristors

David Grosso, Cédric Djaou, Magali Putero, Minh Anh Luong, Marc Bocquet, Roxane Mamberti, Evangéline Bènevent
article en

Abstract

The growing demand for cost-effective nonvolatile memory has driven research into emerging resistive random-access memory (ReRAM) technologies, including conductive bridge random-access memories (CBRAMs). In this work, we investigate the electrical performance of CBRAMs based on mesoporous sol-gel SiO<sub>2</sub> electrolytes, fabricated using a cost-effective process combining sol-gel deposition, evaporation-induced self-assembly, and inkjet printing. By varying key fabrication parameters, namely, porosity and electrolyte thickness, we analyze their impact on switching behavior, retention, and endurance. Our findings reveal that mesoporous SiO<sub>2</sub> significantly enhances CBRAM performance, offering well-controlled ionic pathways for filament formation and dissolution while keeping the deposition process flexible in terms of deposition parameters. Among the tested configurations, the memory cells based on a moderately porous (20%) and thick (280 nm) SiO<sub>2</sub> layer demonstrate the best stability, with minimal SET/RESET voltage variability, strong retention over 28 h, and reliable endurance over 1000 cycles. In contrast, highly porous electrolyte layers lead to greater variability in resistive states due to unstable filament dissolution. These results highlight the potential of mesoporous SiO<sub>2</sub>-based CBRAMs for next-generation memory applications, particularly in flexible electronics and neuromorphic computing. The study provides key insights into optimizing memory design through electrolyte engineering and scalable, low-cost manufacturing processes.

ACS OmegaVol. 10(36)
Centre National de la Recherche Scientifique (FR), Université de Toulon (FR), Université Fédérale de Toulouse Midi-Pyrénées (FR), Centre d’Élaboration de Matériaux et d’Études Structurales (FR), OZ Biosciences (France) (FR), Centre d’Immunologie de Marseille-Luminy (FR), Centre Interdisciplinaire de Nanoscience de Marseille (FR)
Openalex Percentile: Top 77%
Advanced Memory and Neural Computing
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