Resistive switching random access memory data storage gadgets are attracting a great deal of attention in the field of non-volatile memory owing to their superior attributes, for example, fast switching speed, low operation voltage, simple structure, long retention time, non-destructive readout, and high packing density. The memory cells are made of elementary 3-D stacking structure with a dielectric material positioned between two electrodes. Flexibility, mechanical stiffness, feasible cross-bar structure, and transparency are of ultimate importance when it comes to resistive switching random access memory.
High transparent and excellently flexible ultrathin 2-D nanomaterials are potential building blocks of the wearable electronic non-volatile memory gadgets. Graphene oxide has appeared to be a promising candidate for devices with long retention time, and high ON/OFF ratio due to its ultrathin thickness, excellent solubility in water, and unique physical and chemical properties. However, graphene oxide-based memories face a few challenges with regards to chemical composition, flexibility, size, thermal stability, and transparency.
Therefore, researchers led by professor Dong Ha Kim at Ewha Womans University in South Korea developed a new approach to synthesize high-performance graphene oxide 2-D nanomaterial-based resistive memory devices with enhanced chemical composition as well as transparency. They further focused on doping graphene oxide implementing layer-by-layer self-assembly method to synthesize uniform thin layers. Their work is now published in Small.
The authors prepared negatively charged graphene oxide via the Hummer’s method. Positively charged nitrogen-doped graphene oxide was prepared by decorating the negatively charge graphene oxide surface with amine functional group. Positively charged sulfur and nitrogen co-doped graphene oxide was prepared by decorating negatively charged graphene oxide surface with amine and thiol functional groups.
Different types of about 40nm thick graphene oxide-based 2-D nanomaterials were prepared on the bottom aluminum electrode implementing the layer-by-layer self-assembly approach. A 50 nm thick gold top electrode was thermally deposited on the graphene oxide. The top electrode lines were aligned perpendicularly to the bottom aluminum electrode lines. This gave an arrangement of memory cells with 100×100 mm2 active area.
Layer by layer deposition of the various graphene oxide-based nanomaterials was realized through the sequential adsorption of components that were negatively charged by electrostatic interactions. The authors observed that the samples recorded decreasing transmittance values with an increase in the multilayers. This implied a regular growth of the deposited films upon adsorption of every graphene oxide-based layer. 75% transmittance value in the range of 400-550nm wavelength was realized after the deposition of approximately 30 bilayer films.
The multicomponent system gadget displayed nonvolatile bipolar switching characteristics with about 105 ON/OFF ratios, good endurance cycles, approximately 104 s retention time, and high memory cells stability of about 95%. High graphene oxide concentrations were pointed to favor high memory cell stability. Manganese oxide inclusion in the graphene oxide matrix was declared ineffective in enhancing the retention time, ON/OFF ratios, endurance, and stability of metal-free gadgets.
The developed methodology and the resulting graphene oxide-based 2D Nanosheets are therefore invaluable for future applications in electronics.
1) Synthesis of different GO based nanomaterials with positive and negative charges
2) Deposition of multilayers on Al-coated substrate by LBL assembly (spin coating) method
3) Device fabrication
4) ReRAM nonvolatile memory characteristics
Adila Rani, Dhinesh Babu Velusamy, Richard Hahnkee Kim, Kyungwha Chung, Filipe Marques Mota, Cheolmin Park, and Dong Ha Kim. Non-Volatile ReRAM Devices Based on Self-Assembled Multilayers of Modified Graphene Oxide 2D Nanosheets. Small 2016, 12, No. 44, 6167–6174.Go To Small