Since the first report of ferroelectricity in a Si-doped HfO2 film in 2011, HfO2-based materials
have attracted much interest from the ferroelectric materials and devices community …

Ferroelectric materials, the charge equivalent of magnets, have been the subject of
continued research interest since their discovery more than 100 years ago. The …

The growing computational demand in artificial intelligence calls for hardware solutions that
are capable of in situ machine learning, where both training and inference are performed by …

Compute-in-memory (CIM) is a new computing paradigm that addresses the memory-wall
problem in hardware accelerator design for deep learning. The input vector and weight …

Ferroelectrics are a class of materials that possess a variety of interactions between
electrical, mechanical, and thermal properties that have enabled a wealth of functionalities …

In this article, we review the recent progress of ferroelectric field-effect transistors (FeFETs)
based on ferroelectric hafnium oxide (HfO 2), ten years after the first report on such a device …

Ferroelectric materials are characterized by two stable polarization states that can be
switched from one to another by applying an electrical field. As one of the most promising …

In the past five decades, the semiconductor industry has gone through two distinct eras of
scaling: the geometric (or classical) scaling era and the equivalent (or effective) scaling era …

Deep neural networks are efficient at learning from large sets of labelled data, but struggle to
adapt to previously unseen data. In pursuit of generalized artificial intelligence, one …

Ferroelectric field-effect transistors employ a ferroelectric material as a gate insulator, the
polarization state of which can be detected using the channel conductance of the device. As …