Improved resistive switching characteristics of a multi-stacked HfO2/Al2O3/HfO2 RRAM structure for neuromorphic and synaptic applications: experimental and computational study

Enhancing Charge Trapping Performance of Hafnia Thin Films Using Sequential Plasma Atomic Layer Deposition

We aimed to fabricate reliable memory devices using HfO2, which is gaining attention as a charge-trapping layer material for next-generation NAND flash memory. To this end, a new atomic layer deposition process using sequential remote plasma (RP) and direct plasma (DP) was designed to create charge-trapping memory devices. Subsequently, the operational characteristics of the devices were analyzed based on the thickness ratio of thin films deposited using the sequential RP and DP processes. As the thickness of the initially RP-deposited thin film increased, the memory window and retention also increased, while the interface defect density and leakage current decreased. When the thickness of the RP-deposited thin film was 7 nm, a maximum memory window of 10.1 V was achieved at an operating voltage of ±10 V, and the interface trap density (Dit) reached a minimum value of 1.0 × 1012 eV-1cm-2. Once the RP-deposited thin film reaches a certain thickness, the ion bombardment effect from DP on the substrate is expected to decrease, improving the Si/SiO2/HfO2 interface and thereby enhancing device endurance and reliability. This study confirmed that the proposed sequential RP and DP deposition processes could resolve issues related to unstable interface layers, improve device performance, and enhance process throughput.

Comprehensive first principles to investigate optoelectronic and transport phenomenon of lead-free double perovskites Ba2AsBO6 (B[bond, double bond]Nb, Ta) compounds

In the current work we studied the structural, elastics, electrical, optical, thermoelectric, as well as spectroscopic limited maximum efficiency (SLME) of oxide based Ba2AsBO6 (B[bond, double bond]Nb, Ta) materials. All the calculations were performed using first-principles calculation by employing the WIEN2k code. We checked the stability in diverse forms such as optimization, phonon dispersion, mechanical, formation energy, cohesive energy, and thermal stability is computed. The semiconducting nature of these Ba2AsBO6 (B[bond, double bond]Nb, Ta) systems is revealed by calculating the direct band gap values are 1.97 eV and 1.49 eV respectively. Additionally, we determined the optical properties which analyze the utmost absorption and transition of carriers versus photon energy (eV). Moreover, Ba2AsNbO6 has an estimated SLME of 32 %, making it an encouraging alternative for single-junction solar cells. Lastly, we studied the transport properties against temperature, the chemical potential for p-type and n-type charge carriers at various temperatures. At 300 K, the zT values are found to be 0.757 and 0.751 for Ba2AsBO6 (B[bond, double bond]Nb, Ta) compounds respectively. Both materials were examined as having strong absorption patterns and an excellent figure of merit (ZT), indicating that materials are appropriate for daily life applications.

Volatile threshold switching and synaptic properties controlled by Ag diffusion using Schottky defects

We investigated diffusion memristors in the structure of Ag/Ta2O5/HfO2/Pt, in which active Ag ions control active metal ion diffusion and mimic biological brain functions. The CMOS compatible high-k metal oxide could control an Ag electrode that was ionized by applying an appropriate voltage to form a conductive filament, and the movement of Ag ions was chemically and electrically controlled due to oxygen density. This diffusion memristor exhibited diffused characteristics with a selectivity of 109, and achieved a low power consumption of 2 mW at a SET voltage of 0.2 V. The threshold transitions were reliably repeatable over 20 cycles for compliance currents of 10-6 A, 10-4 A, and no compliance current, with the largest standard deviation value of SET variation being 0.028. Upon filament formation, Ag ions readily diffused into the interface of the Ta2O5 and HfO2 layer, which was verified by investigating the Ag atomic percentage using XPS and vertical EDX and by measuring the relaxation time of 0.8 ms. Verified volatile switching device demonstrated the biological synaptic properties of quantum conductance, short-term memory, and long-term memory due to controlling the Ag. Diffusion memristors using designed control and switching layers as following film density and oxygen vacancy have improved results as low-power devices and neuromorphic devices compared to other diffusion-based devices, and these properties can be used for various applications such as selectors, synapses, and neuromorphic devices.

Challenges to Optimize Charge Trapping Non-Volatile Flash Memory Cells: A Case Study of HfO2/Al2O3 Nanolaminated Stacks

The requirements for ever-increasing volumes of data storage have urged intensive studies to find feasible means to satisfy them. In the long run, new device concepts and technologies that overcome the limitations of traditional CMOS-based memory cells will be needed and adopted. In the meantime, there are still innovations within the current CMOS technology, which could be implemented to improve the data storage ability of memory cells-e.g., replacement of the current dominant floating gate non-volatile memory (NVM) by a charge trapping memory. The latter offers better operation characteristics, e.g., improved retention and endurance, lower power consumption, higher program/erase (P/E) speed and allows vertical stacking. This work provides an overview of our systematic studies of charge-trapping memory cells with a HfO2/Al2O3-based charge-trapping layer prepared by atomic layer deposition (ALD). The possibility to tailor density, energy, and spatial distributions of charge storage traps by the introduction of Al in HfO2 is demonstrated. The impact of the charge trapping layer composition, annealing process, material and thickness of tunneling oxide on the memory windows, and retention and endurance characteristics of the structures are considered. Challenges to optimizing the composition and technology of charge-trapping memory cells toward meeting the requirements for high density of trapped charge and reliable storage with a negligible loss of charges in the CTF memory cell are discussed. We also outline the perspectives and opportunities for further research and innovations enabled by charge-trapping HfO2/Al2O3-based stacks.

Improved Performance of the Al2O3-Protected HfO2-TiO2 Base Layer with a Self-Assembled CH3NH3PbI3 Heterostructure for Extremely Low Operating Voltage and Stable Filament Formation in Nonvolatile Resistive Switching Memory

Herein, we report intriguing observations of an extremely stable nonvolatile bipolar resistive switching (NVBRS) memory device fabricated using HfO₂-TiO₂ topologically protected by Al₂O₃ as a stacked base layer for a CH₃NH₃PbI₃ (MAPI) electrolyte layer sandwiched between Ag and fluorine-doped tin oxide (FTO) electrodes. MAPI has been successfully synthesized by a rapid microwave-solvothermal (MW-ST) method within 10 min at 120 °C without requiring any inert gas atmosphere using low-cost precursors and solvents. Subsequently, MAPI powders are dissolved in aprotic solvents (DMF/DMSO = 8:2), and a spin-coated thin film is allowed to recrystallize upon annealing at 120 °C via a solution-based nanoscale self-assembly process. The fabricated memory device with the Ag/MAPI/Al₂O₃/TiO₂-HfO₂/FTO configuration shows an enhanced resistance ratio of 10⁵ for >10⁴ s at an extremely lower operating voltage (SET +0.2 V, RESET -0.2 V) when compared to that of the pristine MAPI device (±1 V, 10², 10⁴ s). We show that the memory device also exhibits a remarkable endurance of ≥3500 cycles due to the Al₂O₃ robust coating on the HfO₂-TiO₂ layer, facilitating prompt heterojunction formation. Thus, the adopted innovative strategies to prepare structurally and optically stable (∼1.5 years) MAPI under high-humid conditions could offer enhanced performance of NVBRS memory devices for medical, security, internet of things (IoT), and artificial intelligence (AI) applications.