Related papers: A Dual-Memory Ferroelectric Transistor Emulating S…

The growing use of ferroelectric-based technology, extending beyond conventional memory storage applications, necessitates the development of compact models that can be easily integrated into circuit simulation environments. These models…

Silicon ferroelectric field-effect transistors (FeFETs) with low-k interfacial layer (IL) between ferroelectric gate stack and silicon channel suffers from high write voltage, limited write endurance and large read-after-write latency due…

Compute-in-memory (CiM) is a promising approach to alleviating the memory wall problem for domain-specific applications. Compared to current-domain CiM solutions, charge-domain CiM shows the opportunity for higher energy efficiency and…

Memristive systems emerge as strong candidates for the implementation of Resistive Random Access Memories (RRAM) and neuromorphic computing devices, as they can mimic the electrical analog behavior or biological synapses. In addition,…

Wurtzite nitride ferroelectric materials have emerged as promising candidates for next-generation memory applications due to their exceptional polarization properties and compatibility with conventional semiconductor processing techniques.…

An atomistic effective Hamiltonian technique is used to investigate the finite-temperature energy storage properties of a ferroelectric nanocomposite consisting of an array of BaTiO$_{3}$ nanowires embedded in a SrTiO$_{3}$ matrix, for…

Ferroelectric field-effect transistors (Fe-FETs) with ferroelectric hafnium oxide (FE HfO2) as gate insulator are being extensively explored as a promising device candidate for three-dimensional (3D) NAND memory application. FE HfO2…

We have fabricated a variety of "PZT-PFW" (PbZr0.52Ti0.48O3)1-x(PbFe2/3W1/3O3)x [PZTFWx; 0.2 < x < 0.4] single-phase tetragonal ferroelectrics via chemical solution deposition (CSD) [polycrystalline] and pulsed laser deposition (PLD)…

Ferroelectrics offer a promising materials platform to realize energy-efficient non-volatile memory technology with the FeFET-based implementations being one of the most area-efficient ferroelectric memory architectures. However, the FeFET…

HfO$_2$-based ferroelectrics are one of the most actively developed functional materials for memory devices. However, in HfO$_2$-based ferroelectric devices, dielectric breakdown is a main failure mechanism during repeated polarization…

Breaking the memory wall in advanced computing architectures will require complex 3D integration of emerging memory materials such as ferroelectrics-either within the back-end-of-line (BEOL) of CMOS front-end processes or through advanced…

In hafnia-based thin-film ferroelectric devices, chemical phenomena during growth and processing such as oxygen vacancy formation and interfacial reactions appear to strongly affect device performance. However, the nanoscale structure,…

Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor-based circuits are particularly promising for RC, as…

Two-dimensional ferroelectric materials are beneficial for power-efficient memory devices and transistor applications. Here, we predict out-of-plane ferroelectricity in a new family of buckled metal oxide (MO; M: Ge, Sn, Pb) monolayers with…

A numerical analysis on the computational capability of physical reservoir computing utilizing a spin-torque oscillator with two free layers is reported. Conventional spintronics devices usually consist of two ferromagnets, where the…

Usually, resistive switching (RS) devices show digital RS memory (sharp SET and RESET process), which is most suitable for digital data storage applications. Some RS devices also manifest ideal memristive behavior or analog memory…

The demand for efficient data processing motivates a shift toward in-memory computing architectures. Ferroelectric materials, particularly AlScN, show great promise for next-generation memory devices. However, their widespread application…

The fields of machine learning and artificial intelligence drive researchers to explore energy-efficient, brain-inspired new hardware. Reservoir computing encompasses recurrent neural networks for sequential data processing and matches the…

Reservoir computing has been considered as a promising intelligent computing paradigm for effectively processing complex temporal information. Exploiting tunable and reproducible dynamics in the single electronic device have been desired to…

Ferroelectric memories have attracted significant interest due to their non-volatile storage, energy efficiency, and fast operation, making them prime candidates for future memory technologies. As commercial Dynamic Random Access Memory…