Related papers: A back-end, CMOS compatible ferroelectric Field Ef…

TiO2 ferroelectric field effect transistors (FeFETs) with HfZrO2 (HZO) ferroelectric dielectric layers and bottom gate topology are fabricated for applications in neuromorphic systems. Two sets of devices are fabricated with different gate…

Online training of deep neural networks (DNN) can be significantly accelerated by performing in-situ vector matrix multiplication in a crossbar array of analog memories. However, training accuracies often suffer due to device non-idealities…

The persistent and switchable polarization of ferroelectric materials based on HfO$_2$-based ferroelectric compounds, compatible with large-scale integration, are attractive synaptic elements for neuromorphic computing. To achieve a record…

Neuromorphic systems seek to replicate the functionalities of biological neural networks to attain significant improvements in performance and efficiency of AI computing platforms. However, these systems have generally remained limited to…

Achieving brain-like density and performance in neuromorphic computers necessitates scaling down the size of nanodevices emulating neuro-synaptic functionalities. However, scaling nanodevices results in reduction of programming resolution…

Ferroelectric field-effect transistors (FeFET) with two-dimensional (2D) semiconductor channels are promising low-power, embedded non-volatile memory (NVM) candidates for next-generation in-memory computing. However, the performance of…

Neuromorphic in-memory computing requires area-efficient architecture for seamless and low latency parallel processing of large volumes of data. Here, we report a compact, vertically integrated/stratified field-effect transistor (VSFET)…

A multi-bit digital weight cell for high-performance, inference-only non-GPU-like neuromorphic accelerators is presented. The cell is designed with simplicity of peripheral circuitry in mind. Non-volatile storage of weights which eliminates…

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…

Heavy computational demands from artificial intelligence (AI) leads the research community to explore the design space for functional materials that can be used for high performance memory and neuromorphic computing hardware. Novel device…

In this paper, we demonstrate low-thermal-budget ferroelectric field-effect transistors (FeFETs) based on two-dimensional ferroelectric CuInP2S6 (CIPS) and oxide semiconductor InZnO (IZO). The CIPS/IZO FeFETs exhibit non-volatile memory…

Neuromorphic computing, inspired by biological intelligence, offers a pathway to revolutionize artificial intelligence (AI) by unifying memory and processing in an energy-efficient, sustainable framework for data-intensive tasks.…

We demonstrate ferroelectric (FE) memory transistors on a crystalline silicon channel with endurance exceeding $10^{10}$ cycles. The ferroelectric transistors (FeFETs) incorporate a high-$\kappa$ interfacial layer (IL) of thermally grown…

Neuromorphic computing demands synaptic elements that can store and update weights with high precision while being read non-destructively. Conventional ferroelectric synapses store weights in remnant polarization states and might require…

The continued evolution of CMOS technology demands materials and architectures that emphasize low power consumption, particularly for computations involving large scale data processing and multivariable optimization. Ferroelectric materials…

HfO2-based Ferroelectric field-effect transistor (FeFET) has become a center of attraction for non-volatile memory applications because of their low power, fast switching speed, high scalability, and CMOS compatibility. In this work, we…

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…

A Ferroelectric Analog Non-Volatile Memory based on a WOx electrode and ferroelectric HfZrO4 layer is fabricated at a low thermal budget (~375C), enabling BEOL processes and CMOS integration. The devices show suitable properties for…

Reconfigurable devices have garnered significant attention for alleviating the scaling requirements of conventional CMOS technology, as they require fewer components to construct circuits with similar function. Prior works required…

Intimate integration of memory devices with logic transistors is a frontier challenge in computer hardware. This integration is essential for augmenting computational power concurrently with enhanced energy efficiency in big-data…