Nonvolatile Latch Designs With Node-Upset Tolerance and Recovery Using Magnetic Tunnel Junctions and CMOS

Yan, Aibin; Wang, Litao; Cui, Jie; Huang, Zhengfeng; Ni, Tianming; Girard, Patrick; Wen, Xiaoqing

doi:10.1109/tvlsi.2023.3323562

Cited by 34 publications

(3 citation statements)

References 24 publications

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“…Since the vacuum gate dielectric degrades the coupling capacitance, leading to worse carrier control, leveraging negative capacitance ferroelectric materials [ 68 , 69 , 70 ] to improve such carbon nanodevices can be a matter for further investigation. Furthermore, very interesting results are presented in [ 71 , 72 , 73 ]. Self-powered application presented in [ 74 , 75 ].…”

Section: Resultsmentioning

confidence: 99%

Performance Projection of Vacuum Gate Dielectric Doping-Free Carbon Nanoribbon/Nanotube Field-Effect Transistors for Radiation-Immune Nanoelectronics

Tamersit,

Kouzou,

Rodriguez

et al. 2024

Nanomaterials

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This paper investigates the performance of vacuum gate dielectric doping-free carbon nanotube/nanoribbon field-effect transistors (VGD-DL CNT/GNRFETs) via computational analysis employing a quantum simulation approach. The methodology integrates the self-consistent solution of the Poisson solver with the mode space non-equilibrium Green’s function (NEGF) in the ballistic limit. Adopting the vacuum gate dielectric (VGD) paradigm ensures radiation-hardened functionality while avoiding radiation-induced trapped charge mechanisms, while the doping-free paradigm facilitates fabrication flexibility by avoiding the realization of a sharp doping gradient in the nanoscale regime. Electrostatic doping of the nanodevices is achieved via source and drain doping gates. The simulations encompass MOSFET and tunnel FET (TFET) modes. The numerical investigation comprehensively examines potential distribution, transfer characteristics, subthreshold swing, leakage current, on-state current, current ratio, and scaling capability. Results demonstrate the robustness of vacuum nanodevices for high-performance, radiation-hardened switching applications. Furthermore, a proposal for extrinsic enhancement via doping gate voltage adjustment to optimize band diagrams and improve switching performance at ultra-scaled regimes is successfully presented. These findings underscore the potential of vacuum gate dielectric carbon-based nanotransistors for ultrascaled, high-performance, energy-efficient, and radiation-immune nanoelectronics.

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Section: Resultsmentioning

confidence: 99%

Performance Projection of Vacuum Gate Dielectric Doping-Free Carbon Nanoribbon/Nanotube Field-Effect Transistors for Radiation-Immune Nanoelectronics

Tamersit,

Kouzou,

Rodriguez

et al. 2024

Nanomaterials

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“…The carbon nanotubes (CNT) offer some astonishing advantages which include high I ON /I OFF [7], absence of mobility degradation [8], and ballistic transport [9,10]. Other exceptional benefits include less sensitivity to process variations [11], ultra-thin body [12,13] and variation of bandgap within a single material [14]. The use of CNT in channels and as interconnects makes the CNTFET a promising substitute at 32 nm and below nodes.…”

Section: Introductionmentioning

confidence: 99%

Low-power and robust ternary SRAM cell with improved noise margin in CNTFET technology

Haq,

Abbasian,

Khurshid

et al. 2024

Phys. Scr.

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In this paper, a carbon nanotube field-effect transistor (CNTFET) based low power and robust ternary SRAM (TSRAM) cell with enhanced static noise margin (SNM) has been proposed. The proposed cell uses a low-power cell core and a stack of 2 CNTFETs to discharge the read bit line (RBL) to ground, unlike the previous SRAM designs which use read buffers or transmission gates (TG) to alter the voltage levels on the RBL. The proposed TSRAM cell has been simulated relentlessly, using the Stanford 32 nm CNTFET technology mode file with Synopsis HSPICE tool under various operating conditions. Unlike other designs, the cross-coupled ternary inverters used as the cell core in the proposed TSRAM show higher gain and steep curves in the transition region mitigating the static power of the cell. The simulation results exhibit improvements in performance parameters like power consumption, energy, noise margins, and reliability. At 0.9 V supply voltage, the proposed TSRAM cell offers 52.44% and 43.17% reduction in write and read static power, a PDP reduction of 35.29% in comparison, and a 36.36% improvement in SNM compared to best designs under investigation. Also, the proposed TSRAM design shows higher robustness compared to other designs.

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“…This EMS is responsible for the optimal planning of energy resources and ESS devices to provide power to subscribers [ [8] , [9] , [10] ]. EMS activities aimed at ensuring security, stability [ [11] , [12] , [13] ], and optimal economic and environmental exploitation of microgrids can be presented in a hierarchical control framework [ 14 , 15 ]. Therefore, EMS is obliged to manage energy and storage resources in the microgrid in such a way that the requirements related to load management and economic and environmental exploitation are provided simultaneously [ [16] , [17] , [18] , [19] , [20] ].…”

Section: Introductionmentioning

confidence: 99%

Designing a multi-objective energy management system in multiple interconnected water and power microgrids based on the MOPSO algorithm

Alkuhayli,

Dashtdar,

Flah

et al. 2024

Heliyon

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Nonvolatile Latch Designs With Node-Upset Tolerance and Recovery Using Magnetic Tunnel Junctions and CMOS

Cited by 34 publications

References 24 publications

Performance Projection of Vacuum Gate Dielectric Doping-Free Carbon Nanoribbon/Nanotube Field-Effect Transistors for Radiation-Immune Nanoelectronics

Performance Projection of Vacuum Gate Dielectric Doping-Free Carbon Nanoribbon/Nanotube Field-Effect Transistors for Radiation-Immune Nanoelectronics

Low-power and robust ternary SRAM cell with improved noise margin in CNTFET technology

Designing a multi-objective energy management system in multiple interconnected water and power microgrids based on the MOPSO algorithm

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