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      A Novel Metal Dielectric Metal Based GAA-Junction-Less TFET Structure for Low Loss SRAM Design

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          Tunnel field-effect transistors as energy-efficient electronic switches.

          Power dissipation is a fundamental problem for nanoelectronic circuits. Scaling the supply voltage reduces the energy needed for switching, but the field-effect transistors (FETs) in today's integrated circuits require at least 60 mV of gate voltage to increase the current by one order of magnitude at room temperature. Tunnel FETs avoid this limit by using quantum-mechanical band-to-band tunnelling, rather than thermal injection, to inject charge carriers into the device channel. Tunnel FETs based on ultrathin semiconducting films or nanowires could achieve a 100-fold power reduction over complementary metal-oxide-semiconductor (CMOS) transistors, so integrating tunnel FETs with CMOS technology could improve low-power integrated circuits. © 2011 Macmillan Publishers Limited. All rights reserved
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            Physics of Semiconductor Devices

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              Nanowire transistors without junctions.

              All existing transistors are based on the use of semiconductor junctions formed by introducing dopant atoms into the semiconductor material. As the distance between junctions in modern devices drops below 10 nm, extraordinarily high doping concentration gradients become necessary. Because of the laws of diffusion and the statistical nature of the distribution of the doping atoms, such junctions represent an increasingly difficult fabrication challenge for the semiconductor industry. Here, we propose and demonstrate a new type of transistor in which there are no junctions and no doping concentration gradients. These devices have full CMOS functionality and are made using silicon nanowires. They have near-ideal subthreshold slope, extremely low leakage currents, and less degradation of mobility with gate voltage and temperature than classical transistors.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Silicon
                Silicon
                Springer Science and Business Media LLC
                1876-990X
                1876-9918
                May 2023
                November 19 2022
                May 2023
                : 15
                : 7
                : 2989-3001
                Article
                10.1007/s12633-022-02218-0
                3bc8f624-843b-4fab-8645-8a849f79ff41
                © 2023

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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