ACS Nano · 2022 · 107 citations · 51 references
EngineeringComputer EngineeringElectrical EngineeringMemoryMicroelectronicsSemiconductor DevicesComplementary Metal-oxide-semiconductor TechnologyMemory DevicesMetal-oxide-semiconductor Field-effect TransistorsNanoelectronicsTwo-dimensional SemiconductorsComplementary Metal-oxide-semiconductor DevicesData-intensive ComputingDual-gate Field-effect TransistorsFerroelectric Field-effect TransistorsFerroelectric SemiconductorsLogic GatesMemory CircuitsVon Neumann Architecture
In-memory computing featuring a radical departure from the von Neumann architecture is promising to substantially reduce the energy and time consumption for data-intensive computation. With the increasing challenges facing silicon complementary metal-oxide-semiconductor (CMOS) technology, developing in-memory computing hardware would require a different platform to deliver significantly enhanced functionalities at the material and device level. Here, we explore a dual-gate two-dimensional ferroelectric field-effect transistor (2D FeFET) as a basic device to form both nonvolatile logic gates and artificial synapses, addressing in-memory computing simultaneously in digital and analog spaces. Through diversifying the electrostatic behaviors in 2D transistors with the dual-ferroelectric-coupling effect, rich logic functionalities including linear (AND, OR) and nonlinear (XNOR) gates were obtained in unipolar (MoS2) and ambipolar (MoTe2) FeFETs. Combining both types of 2D FeFETs in a heterogeneous platform, an important computation circuit, i.e., a half-adder, was successfully constructed with an area-efficient two-transistor structure. Furthermore, with the same device structure, several key synaptic functions are shown at the device level, and an artificial neural network is simulated at the system level, manifesting its potential for neuromorphic computing. These findings highlight the prospects of dual-gate 2D FeFETs for the development of multifunctional in-memory computing hardware capable of both digital and analog computation.
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