Review on role of nanoscale HfO2 switching material in resistive random access memory device
S NM, NN, AN - Emergent Materials, 2022 - Springer
Typical semiconductor data storage devices reach a breaking point in terms of their physical
dimension and storage capacity. Among various upcoming high-density non-volatile …
dimension and storage capacity. Among various upcoming high-density non-volatile …
SPICE implementation of the dynamic memdiode model for bipolar resistive switching devices
This paper reports the fundamentals and the SPICE implementation of the Dynamic
Memdiode Model (DMM) for the conduction characteristics of bipolar-type resistive switching …
Memdiode Model (DMM) for the conduction characteristics of bipolar-type resistive switching …
Spikesim: An end-to-end compute-in-memory hardware evaluation tool for benchmarking spiking neural networks
Spiking neural networks (SNNs) are an active research domain toward energy-efficient
machine intelligence. Compared to conventional artificial neural networks (ANNs), SNNs …
machine intelligence. Compared to conventional artificial neural networks (ANNs), SNNs …
Linearity improvement of HfOx-based memristor with multilayer structure
Y Jiang, K Zhang, K Hu, Y Zhang, A Liang… - Materials Science in …, 2021 - Elsevier
The limitation of traditional Von Neumann architecture could be resolved by machine
learning training in neuromorphic computing. However, the nonlinearity characteristic during …
learning training in neuromorphic computing. However, the nonlinearity characteristic during …
Incorporating variability of resistive RAM in circuit simulations using the Stanford–PKU model
J Reuben, M Biglari, D Fey - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Intrinsic variability observed in resistive-switching devices (cycle-to-cycle and device-to-
device) is widely recognised as a major hurdle for widespread adoption of Resistive RAM …
device) is widely recognised as a major hurdle for widespread adoption of Resistive RAM …
RRAM-based non-volatile SRAM cell architectures for ultra-low-power applications
Abstract Static Random-Access Memories (SRAMs) have flourished in the memory market
relying on their speed, power consumption and compatibility with standard CMOS process …
relying on their speed, power consumption and compatibility with standard CMOS process …
Fabrication and modeling of flexible high-performance resistive switching devices with biomaterial gelatin/ultrathin HfOx hybrid bilayer
Flexible resistive random access memory (RRAM) devices with biomaterial gelatin and
ultrathin HfOx hybrid bilayer dielectric exhibiting excellent resistive switching (RS) behavior …
ultrathin HfOx hybrid bilayer dielectric exhibiting excellent resistive switching (RS) behavior …
Complete stability of neural networks with extended memristors
The article considers a large class of delayed neural networks (NNs) with extended
memristors obeying the Stanford model. This is a widely used and popular model that …
memristors obeying the Stanford model. This is a widely used and popular model that …
Data-driven RRAM device models using Kriging interpolation
A two-tier Kriging interpolation approach is proposed to model jump tables for resistive
switches. Originally developed for mining and geostatistics, its locality of the calculation …
switches. Originally developed for mining and geostatistics, its locality of the calculation …
A flexible and reliable RRAM-based in-memory computing architecture for data-intensive applications
This article proposes a practical, flexible, and reliable in-memory computing architecture for
resistive-memory-based logic designs. Our design uses a new RRAM-based polymorphic in …
resistive-memory-based logic designs. Our design uses a new RRAM-based polymorphic in …