Search Results (53)

As transistor dimensions continue to scale below 10 nm, traditional MOSFET architectures face increasing limitations from short-channel effects, gate leakage, and variability. FinFETs, especially junctionless FinFETs on silicon-on-insulator (SOI) substrates, offer improved electrostatic control and simplified fabrication, making them attractive for deeply scaled nodes. In this work, we propose a novel Stepped-Spacer Structured FinFET (S³-FinFET) that incorporates a three-layer HfO₂/Si₃N₄/HfO₂ spacer configuration designed to enhance electrostatics and suppress parasitic effects. Using 2D TCAD simulations, the S³-FinFET is evaluated in terms of key performance metrics, including transfer/output characteristics, ON/OFF current ratio, subthreshold swing (SS), drain-induced barrier lowering (DIBL), gate capacitance, and cut-off frequency. The results show significant improvements in leakage control and high-frequency behavior. These enhancements make the S³-FinFET particularly well-suited for Field-Programmable Gate Arrays (FPGAs), where power efficiency, speed, and signal integrity are critical to performance in reconfigurable logic environments. Full article

Despite the advantages of fin field-effect transistors (FinFETs), there are hidden issues such as electric field enhancement and exacerbated self-heating effects, which will intensify device aging effects. Due to the escalating costs associated with aging protection at the device process level, there is an urgent need to reduce the impact of aging on circuit performance from the circuit design perspective. This study focuses on the specific structure of the strong-arm latch comparator and conducts a detailed aging analysis. Based on the quasi-static approximation (QSA) model, the threshold voltage shift under operational stress is simulated. It is concluded that both the hot carrier injection (HCI) effect and negative bias temperature instability (NBTI) effect play equally non-negligible roles. Furthermore, aging tests were conducted based on 14 nm FinFET devices, validating the substantial HCI effects induced by short-duration pulses. Simultaneously, the test results suggest that the aging effect becomes more remarkable with increasing current. An improved circuit is proposed to reduce the HCI effect by reducing the current pulse by the way of pre-charging, which effectively reduces the threshold voltage shift of the latch comparator input transistors. Full article

The continuous scaling down of MOSFETs is one of the present trends in semiconductor devices to increase device performance. Nevertheless, with scaling down beyond 22 nm technology, the performance of even the newer nanodevices with multi-gate architecture declines with an increase in short channel effects (SCEs). Consequently, to facilitate further increases in the drain current, the use of strained silicon technology provides a better solution. Thus, the development of a novel Gate-All-Around Field-Effect Transistor (GAAFET) incorporating a strained silicon channel with a 10 nm gate length is initiated and discussed. In this device, strain is incorporated in the channel, where a strained silicon germanium layer is wedged between two strained silicon layers. The GAAFET device has four gates that surround the channel to provide improved control of the gate over the strained channel region and also reduce the short channel effects in the devices. The electrical properties, such as the on current, off current, threshold voltage (V_TH), subthreshold slope, drain-induced barrier lowering (DIBL), and I_on/I_off current ratio, of the 10 nm channel length GAAFET are compared with the 22 nm strained silicon channel GAAFET, the existing SOI FinFET device on 10 nm gate length, and IRDS 2022 specifications device. The developed 10 nm channel length GAAFET, having an ultrathin strained silicon channel, delivers enriched device performance, being augmented in contrast to the IRDS 2022 specifications device, showing improved characteristics along with amended SCEs. Full article

FinFET transistors with fin channel lengths of 160 nm and 2000 nm and a planar MOSFET transistor with channel lengths of 180 nm and 90 nm are presented with characteristic curves at various Gate biases. A finalized algorithm with kink effects was effectively responsible for addressing the field effect transistors. The algorithm included the modified conventional current–voltage formula and a nonlinear heat-associated kink solution which was simplified as a Gaussian form. Three parameters in the modified model included k_N (which was related with channel width, channel length, and gate oxide capacitor, and was proportional to the mobility of carriers), Vth (threshold voltage), and λ (the inverse of early voltage). Those parameters were determined to minimize the discrepancies between the measured data and the fitting values, but left kinks located at around (V_GS-Vth), which were deliberately eliminated by the Gaussian form because of the agitation of thermal kink effects. The whole fitting was made to be as close as possible to the as-measured I_DS-V_DS. In the meantime, those determined parameters were physically meaningful after the analysis had been performed. Full article

This paper introduces a novel technology for the monolithic integration of GaN-based vertical and lateral devices. This approach is groundbreaking as it facilitates the drive of high-power GaN vertical switching devices through lateral GaN HEMTs with minimal losses and enhanced stability. A significant challenge in this technology is ensuring electrical isolation between the two types of devices. We propose a new isolation method designed to prevent any degradation of the lateral transistor’s performance. Specifically, high voltage applied to the drain of the vertical GaN power FinFET can adversely affect the lateral GaN HEMT’s performance, leading to a shift in the threshold voltage and potentially compromising device stability and driver performance. To address this issue, we introduce a highly doped n⁺ GaN layer positioned between the epitaxial layers of the two devices. This approach is validated using the TCAD-Sentaurus simulator, demonstrating that the n⁺ GaN layer effectively blocks the vertical electric field and prevents any depletion or enhancement of the 2D electron gas (2DEG) in the lateral GaN HEMT. To our knowledge, this represents the first publication of such an innovative isolation strategy between vertical and lateral GaN devices. Full article

The scaling of bulk Si-based transistors has reached its limits, while novel architectures such as FinFETs and GAAFETs face challenges in sub-10 nm nodes due to complex fabrication processes and severe drain-induced barrier lowering (DIBL) effects. An effective strategy to avoid short-channel effects (SCEs) is the integration of low-dimensional materials into novel device architectures, leveraging the coupling between multiple gates to achieve efficient electrostatic control of the channel. We employed TCAD simulations to model multi-gate FETs based on various dimensional systems and comprehensively investigated electric fields, potentials, current densities, and electron densities within the devices. Through continuous parameter scaling and extracting the sub-threshold swing (SS) and DIBL from the electrical outputs, we offered optimal MoS₂ layer numbers and single-walled carbon nanotube (SWCNT) diameters, as well as designed structures for multi-gate FETs based on monolayer MoS₂, identifying dual-gate transistors as suitable for high-speed switching applications. Comparing the switching performance of two device types at the same node revealed CNT’s advantages as a channel material in mitigating SCEs at sub-3 nm nodes. We validated the performance enhancement of 2D materials in the novel device architecture and reduced the complexity of the related experimental processes. Consequently, our research provides crucial insights for designing next-generation high-performance transistors based on low-dimensional materials at the scaling limit. Full article

Software-Defined Networking (SDN) revolutionizes network management by decoupling control plane functionality from data plane devices, enabling the centralized control and programmability of network behavior. This paper uses the ternary system to improve the Central Processing Unit (CPU) inside the SDN controller to enhance network management. The Multiple-Valued Logic (MVL) circuit shows remarkable improvement compared to the binary circuit regarding the chip area, propagation delay, and energy consumption. Moreover, the Carbon Nanotube Field-Effect Transistor (CNTFET) shows improvement compared to other transistor technologies regarding energy efficiency and circuit speed. To the best of our knowledge, this is the first time that a ternary design has been applied inside the CPU of an SDN controller. Earlier studies focused on Ternary Content-Addressable Memory (TCAM) in SDN. This paper proposes a new 1-trit Ternary Full Adder (TFA) to decrease the propagation delay and the Power–Delay Product (PDP). The proposed design is compared to the latest 17 designs, including 15 designs that are 1-trit TFA CNTFET-based, 2-bit binary FA FinFET-based, and 2-bit binary FA CMOS-based, using the HSPICE simulator, to optimize the CPU utilization in SDN environments, thereby enhancing programmability. The results show the success of the proposed design in reducing the propagation delays by over 99% compared to the 2-bit binary FA CMOS-based design, over 78% compared to the 2-bit binary FA FinFET-based design, over 91% compared to the worst-case TFA, and over 49% compared to the best-case TFAs. Full article

As AI models grow in complexity to enhance accuracy, supporting hardware encounters challenges such as heightened power consumption and diminished processing speed due to high throughput demands. Compute-in-memory (CIM) technology emerges as a promising solution. Furthermore, carbon nanotube field-effect transistors (CNFETs) show significant potential in bolstering CIM technology. Despite advancements in silicon semiconductor technology, CNFETs pose as formidable competitors, offering advantages in reliability, performance, and power efficiency. This is particularly pertinent given the ongoing challenges posed by the reduction in silicon feature size. We proposed an ultra-low-power architecture leveraging CNFETs for Binary Neural Networks (BNNs), featuring an advanced state-of-the-art 8T SRAM bit cell and CNFET model to optimize performance in intricate AI computations. Through meticulous optimization, we fine-tune the CNFET model by adjusting tube counts and chiral vectors, as well as optimizing transistor ratios for SRAM transistors and nanotube diameters. SPICE simulation in 32 nm CNFET technology facilitates the determination of optimal transistor ratios and chiral vectors across various nanotube diameters under a 0.9 V supply voltage. Comparative analysis with conventional FinFET-based CIM structures underscores the superior performance of our CNFET SRAM-based CIM design, boasting a 99% reduction in power consumption and a 91.2% decrease in delay compared to state-of-the-art designs. Full article

To mimic the homeostatic functionality of biological neurons, a split-gate field-effect transistor (S-G FET) with a charge trap layer is proposed within a neuron circuit. By adjusting the number of charges trapped in the Si₃N₄ layer, the threshold voltage (V_th) of the S-G FET changes. To prevent degradation of the gate dielectric due to program/erase pulses, the gates for read operation and V_th control were separated through the fin structure. A circuit that modulates the width and amplitude of the pulse was constructed to generate a Program/Erase pulse for the S-G FET as the output pulse of the neuron circuit. By adjusting the V_th of the neuron circuit, the firing rate can be lowered by increasing the V_th of the neuron circuit with a high firing rate. To verify the performance of the neural network based on S-G FET, a simulation of online unsupervised learning and classification in a 2-layer SNN is performed. The results show that the recognition rate was improved by 8% by increasing the threshold of the neuron circuit fired. Full article

Since its invention in the 1960s, one of the most significant evolutions of metal-oxide semiconductor field effect transistors (MOSFETs) would be the 3D version that makes the semiconducting channel vertically wrapped by conformal gate electrodes, also recognized as FinFET. During recent decades, the width of fin (W_fin) and the neighboring gate oxide width (t_ox) in FinFETs has shrunk from about 150 nm to a few nanometers. However, both widths seem to have been leveling off in recent years, owing to the limitation of lithography precision. Here, we show that by adapting the Penn model and Maxwell–Garnett mixing formula for a dielectric constant (κ) calculation for nanolaminate structures, FinFETs with two- and three-stage κ-graded stacked combinations of gate dielectrics with SiO₂, Si₃N₄, Al₂O₃, HfO₂, La₂O₃, and TiO₂ perform better against the same structures with their single-layer dielectrics counterparts. Based on this, FinFETs simulated with κ-graded gate oxides achieved an off-state drain current (I_OFF) reduced down to 6.45 × 10⁻¹⁵ A for the Al₂O₃: TiO₂ combination and a gate leakage current (I_G) reaching down to 2.04 × 10⁻¹¹ A for the Al₂O₃: HfO₂: La₂O₃ combination. While our findings push the individual dielectric laminates to the sub 1 nm limit, the effects of dielectric permittivity matching and κ-grading for gate oxides remain to have the potential to shed light on the next generation of nanoelectronics for higher integration and lower power consumption opportunities. Full article

The gate-all-around (GAA) nanosheet (NS) field-effect-transistor (FET) is poised to replace FinFET in the 3 nm CMOS technology node and beyond, marking the second seminal shift in device architecture across the extensive 60-plus-year history of MOSFET. The introduction of a new device structure, coupled with aggressive pitch scaling, can give rise to reliability challenges. In this article, we present a review of the key reliability mechanisms in GAA NS FET, including bias temperature instability (BTI), hot carrier injection (HCI), gate oxide (Gox) time-dependent dielectric breakdown (TDDB), and middle-of-line (MOL) TDDB. We aim to not only underscore the unique reliability attributes inherent to NS architecture but also provide a holistic view of the status and prospects of NS reliability, taking into account the challenges posed by future scaling. Full article

In recent years, graphene has received so much attention because of its superlative properties and its potential to revolutionize electronics, especially in VLSI. This study analyzes the effect of single-event upset (SEU) in an SRAM cell, which employs a metal-oxide semiconductor type graphene nano-ribbon field effect transistor (MOS-GNRFET) and compares the results with another SRAM cell designed using a PTM 10 nm FinFET node. Our simulations show that there is a change in the data stored in the SRAM after a heavy ion strike. However, it recovers from radiation effects after 0.46 ns for GNRFET and 0.51 ns for FinFET. Since the degradation observed in Q and Qb of GNRFET SRAM are 2.7X and 2.16X as compared to PTM nano-MOSFET, we can conclude that GNRFET is less robust to single effect upset. In addition, the stability of SRAM is improved by increasing the supply voltage V_DD. Full article

At sub-3 nm nodes, the scaling of lateral devices represented by a fin field-effect transistor (FinFET) and gate-all-around field effect transistors (GAAFET) faces increasing technical challenges. At the same time, the development of vertical devices in the three-dimensional direction has excellent potential for scaling. However, existing vertical devices face two technical challenges: “self-alignment of gate and channel” and “precise gate length control”. A recrystallization-based vertical C-shaped-channel nanosheet field effect transistor (RC-VCNFET) was proposed, and related process modules were developed. The vertical nanosheet with an “exposed top” structure was successfully fabricated. Moreover, through physical characterization methods such as scanning electron microscopy (SEM), atomic force microscopy (AFM), conductive atomic force microscopy (C-AFM) and transmission electron microscopy (TEM), the influencing factors of the crystal structure of the vertical nanosheet were analyzed. This lays the foundation for fabricating high-performance and low-cost RC-VCNFETs devices in the future. Full article

We comprehensively investigate displacement-defect-induced current and static noise margin variations in six-transistor (6T) static random access memory (SRAM) based on a 10 nm node fin field-effect transistor (FinFET) using technology computer-aided design (TCAD). Various defect cluster conditions and fin structures are considered as variables to estimate the worst-case scenario for displacement defects. The rectangular defect clusters capture more widely distributed charges at the fin top, reducing the on- and off-current. The read static noise margin (RSNM) is the most degraded in the pull-down transistor during the read operation. The increased fin width decreases the RSNM due to the gate field. The current per cross-sectional area increases when the fin height decreases, but the energy barrier lowering by the gate field is similar. Therefore, the reduced fin width and increased fin height structure suit the 10 nm node FinFET 6T SRAMs with high radiation hardness. Full article

Multi-gate field effect transistors (FETs) such as FinFETs are severely affected by short-channel effects (SCEs) below 14 nm technology nodes, with even taller fins incurring fringing capacitances. This leads to performance degradation of the devices, which inhibits further scaling of nanoFETs, deterring the progress of semiconductor industries. Therefore, research has not kept pace with the technological requirements of the International Roadmap for Devices and Systems (IRDS). Thus, the development of newer devices with superior performances in terms of higher ON currents, acceptable leakage currents and improved SCEs is needed to enable the continuance of integrated circuit (IC) technologies. The literature has advocated integration of strained-silicon technology in existing FinFETs, which is highly effective in enhancing ON currents through the strain effect. However, the ON currents can also be amplified by intensifying the number of fins in trigate (TG) FinFETs. Thus, three-fin TG quantum (Q)-FinFETs, using a novel tri-layered strained-silicon channel, are deployed here at 10 nm and 8 nm channel lengths. Threshold voltage is calculated analytically to validate the designs. The electrical parameters and quantum effects of both devices are explored, analysed and compared with respect to existing heterostructure-on-insulator (HOI) FinFETs and the proposed existing standard requirement of IRDS 2022 for a 3 nm technology node. The comparisons demonstrated a significant increase in the drive currents upon employing three fins of the same dimensions (8 nm gate length) and specifications in a device-based system. The performance is augmented in contrast to the 3 nm technology node device of IRDS 2022, with SCEs within the limits. Thus, employing a tri-layered strained-silicon channel system in each fin allowed for forming a three-fin Q-FinFET that, in our opinion, is the technique for consolidating the performance of the devices and enabling future generation device for faster switching operation in a sub-nano regime. Full article