Results 81 to 90 of about 15,744,307 (196)

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Tunable threshold voltage of an n-type Si nanowire ferroelectric-gate field effect transistor for high-performance nonvolatile memory applications.

, 2014
We successfully fabricated ferroelectric-gate field effect transistor (FEFET)-based nonvolatile memory devices using an n-type Si nanowire coated with omega-shaped-gate organic ferroelectric poly(vinylidene fluoride-trifluoroethylene) via a low ...
Kang, DJ, Van, NH, Kim, JM, Whang, D, Lee, J-H, Lee, JH, Cha, S, Sohn, JI, ,   +8 more
core   +1 more source

Parametric Analysis of Spiking Neurons in 16 nm Fin Field‐Effect Transistor Technology

Advanced Intelligent Discovery, EarlyView.
Energy efficient computing has driven a shift toward brain‐inspired neuromorphic hardware. This study explores the design of three distinct silicon neuron topologies implemented in 16 nm fin field‐Effect transistor technology. While the Axon‐Hillock design achieves gigahertz throughput, its functional fragility persists. The Morris–Lecar model captures
Logan Larsh, Raiyan Siddique, Sarah S. Sharif, Yaser Mike Banad   +3 more
wiley   +1 more source

Enhancement of Ion-Sensitive Field-Effect Transistors through Sol-Gel Processed Lead Zirconate Titanate Ferroelectric Film Integration and Coplanar Gate Sensing Paradigm

Chemosensors
To facilitate the utility of field effect transistor (FET)-type sensors, achieving sensitivity enhancement beyond the Nernst limit is crucial. Thus, this study proposed a novel approach for the development of ferroelectric FETs (FeFETs) using lead ...
Dong-Gyun Mah, Seong-Moo Oh, Jongwan Jung, Won-Ju Cho   +3 more
doaj   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

Advanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison, Kevin Nadaud, Josquin Harrison, Guillaume F. Nataf, Laura Bégon‐Lours   +4 more
wiley   +1 more source

Neuromorphic Computing with 28nm High-K-Metal Gate Ferroelectric Field Effect Transistors Based Artificial Synapses

, 2022
This paper presents a comprehensive overview of 28 nm high-k-metal gate-based ferroelectric field effect transistor devices for synaptic applications. The device under test was fabricated on 300mm wafers at GlobalFoundries.
Yannick Raffel (12758051), Franz Müller (13271700), Thomas Kaempfe (12758118), Maximilian Lederer (13271703), Bhaswar Chakrabarti (14431645), Masud S K Rana (14431639), Sourav De (12294287), Konrad Seidel (13271706), Luca Pirro (12758112), Sunanda Thunder (12758097)   +9 more
core   +1 more source

Two‐Dimensional Layered Oxides and the Two‐Dimensionalization of Bulk Oxides for Post‐Moore Information Devices

Information &Functional Materials, EarlyView.
This review systematically summarizes two‐dimensional layered and nonlayered oxides, focusing on their synthesis, properties, and post‐Moore applications in transistors, gate dielectrics, optoelectronics, and ferroelectric/magnetic devices. It also discusses challenges including scalable growth and interface engineering, along with future industrial ...
Xinjie Hou, Yanchang Zhou, Yushan Zhu, Xiao Zhang, Ruiqing Cheng, Jun He   +5 more
wiley   +1 more source

Scaling of the ferroelectric field effect transistor and programming concepts for non-volatile memory applications [PDF]

, 2005
The importance of non-volatile memory for storage of digital information is without question. Research over the years has led to many different types of memory, each tailored to a specific need.
Fitsilis, Michael
core