Carbon Nanotube Field-effect Transistors Research Articles

Opto-Electrical Decoupled Phototransistor for Starlight Detection.

Highly sensitive shortwave infrared (SWIR) detectors are essential for detecting weak radiation (typically below 10-8 W·Sr-1·cm-2·µm-1) with high-end passive image sensors. However, mainstream SWIR detection based on epitaxial photodiodes cannot effectively detect ultraweak infrared radiation due to the lack of inherent gain. Here, we develop a heterojunction-gated field-effect transistor (HGFET) consisting of a colloidal quantum dot (CQD)-based p-i-n heterojunction and a carbon nanotube (CNT) field-effect transistor, which achieves a high inherent gain based on an opto-electric decoupling mechanism for suppressing noise. The stacked heterojunction absorbs infrared radiation and separates electron-hole pairs. Then, the generated photovoltage tunes the drain current of the CNT FET through an Y2O3 gate insulator. As a result, the HGFET significantly detects and amplifies SWIR signals with a high inherent gain while minimally amplifying noise, leading to a recorded specific detectivity above 1014 Jones at 1300nm and a recorded maximum gain-bandwidth product of 69.2 THz. Direct comparative testing indicates that the HGFET can detect weak infrared radiation at 0.46 nWcm-2 levels; thus, compared to commercial and reported SWIR detectors, this detector is much more sensitive and enables starlight detection or vision. As the fabrication process is very compatible with CMOS readout integrated circuits, the HGFET is a promising SWIR detector for realizing passive night vision imaging sensors with high resolutions that are high-end, highly sensitive, and inexpensive.

A review of carbon nanotube field effect transistor from structure and properties to applications

Abstract. In the pursuit of next-generation electronic devices that overweigh the limitations of traditional silicon-based technologies, Carbon Nano Tube Field Effect Transistors (CNTFETs) have garnered significant attention. Unlike conventional Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs), CNTFETs utilize the exceptional properties of Carbon Nanotubes (CNTs) as the channel material, promising substantial improvements in performance, power consumption, and scalability. This paper presents a comprehensive overview of CNTFETs, delving into their fundamental structures and underlying principles. It critically examines the unique characteristics that make CNTFETs an attractive alternative, including their superior carrier mobility, reduced leakage currents, and compatibility with nanoscale fabrication techniques. This review explores the application prospects of CNTFETs, spanning from high-speed digital circuits to energy-efficient sensors and beyond. Despite their promising potential, the paper also acknowledges recent challenges associated with CNTFETs, such as challenges in material synthesis, integration with existing semiconductor processes, and cost considerations. By addressing these challenges and fostering interdisciplinary research collaborations, the widespread adoption of CNTFETs in integrated circuits could revolutionize the electronics industry, enabling the development of more efficient, powerful, and sustainable devices for the future.

Energy-efficient design and CNFET implementation of GDI-based ternary prefix adders

Abstract Ternary adders have produced more benefits compared to binary adders i.e., the ternary adder occupies less amount of area as well as produces less interconnect complexity. However, the CMOS implementation of the ternary adders failed to perform the process when the channel length was taken as 32 nm. At 32 nm technology, the CMOS transistors exhibit undesired effects such as Short Channel Effects (SCEs), mobility degradation, high leakage current, etc. Multi-gate devices are preferred to overcome these issues. Carbon Nano-tube Field Effect Transistors (CNFETs) are one of the technologies to work efficiently when the channel length is 32 nm. In this paper, CNFET-based ternary prefix adders are designed. Power consumption is the most critical requirement for the VLSI system, as it enhances energy efficiency and reduces heat dissipation. One way to achieve this power reduction is by minimizing the number of transistors employed in the adder circuits. This study employed a reduction technique known as Gate Diffusion Input (GDI) logic included in the proposed prefix adder design. The overall experimental investigation is done with the help of the HSPICE supporting platform. The proposed adder improved by reducing the power by up to 83%, energy by up to 83%, current by up to 78%, and delay by up to 96%. Finally, the Power Delay product (PDP) was also reduced by 84% compared to existing ternary adders. The proposed design proves to be highly effective in implementing the neuron structure, with the corresponding parameters thoroughly analysed and well-documented in this study.

Static Approximate Modified Mirror—Full Adder for High Speed and Low Power Operations Using 32 nm CNTFET Technology

ABSTRACTThe error tolerance nature of the digital multimedia applications enables the implementation of approximate digital circuits to achieve the benefits of high speed of operation and low power consumption. This paper proposes a static approximate modified mirror full adder (SAMM‐FA) circuit designed using logic level approximation to reduce the number of transistors in the circuit. Owing to the balanced electrical characteristics, better stability and higher on‐current to off‐current ratio (Ion/Ioff), 32 nm carbon nanotube field effect transistor (CNTFET) technology has been used for implementing the proposed circuit in the Cadence Virtuoso tool. Featuring only 10 transistors and operating at a supply voltage of 0.5 V, the proposed SAMM‐FA has a low power dissipation of just 4.14 nW, and propagation delay of just 3.82 ps. The power delay product and energy delay product figure of merits of the proposed circuit are found to be excellent when compared with the contemporary designs.

Single Ended Read Decoupled High Stable 9T CNTFET SRAM for Low Power Applications

ABSTRACTIn wireless sensor networks, conserving power is vital for prolonging battery life. This research introduces a groundbreaking solution: a 9T carbon nanotube‐field effect transistor (CNTFET) based SRAM cell (9T SRAM) designed to optimize power consumption and stability. Through meticulous analysis, the performance of this 9T SRAM cell is quantified. Power consumption metrics reveal impressive figures: the write, hold, read, and dynamic power are measured at 0.21 nW, 0.32 nW, 15.28 μW, and 8.09 μW, respectively. Furthermore, the Write SNM (WSNM), Hold SNM (HSNM), and Read SNM (RSNM) are found to be 380.11, 390.22, and 390.31 mV, respectively, indicating robust stability. The proposed bit cell has a write and read delay of 95.1 and 39.6 pS, respectively. Incorporating stacked transistors diminishes power consumption, while the decoupled read technique boosts the stability of the proposed bit cell. By comparing these results with existing SRAM cells, the superiority of the proposed 9T SRAM cell in terms of power efficiency becomes evident. Notably, it outperforms earlier models, making it an ideal candidate for integration into wireless sensor networks. These findings are supported by simulations conducted using HSPICE, alongside a 32 nm CNTFET model sourced from Stanford University.

Improving the ON/OFF Current Ratio and Ambipolarity of Doping-Less Tunneling Carbon-Nanotube FET Using Drain Engineering Technique

This paper presents a novel structure utilizing a doping-less (DL) tunneling carbon nanotube field-effect transistor (T-CNTFET) with dual drain work functionality aimed at enhancing the ON/OFF current ratio. The proposed design features a zigzag carbon nanotube (CNT) of type (13, 0) with a diameter of 1 nm. It employs HfO2 as the gate oxide, which is 2 nm thick and has a dielectric constant of 16. The CNT serves as an intrinsic semiconductor for the source and drain regions, which are composed of metals with appropriate work functions. By selecting appropriate metals for the source and drain regions, the necessity for doping as a fabrication step is avoided, simplifying construction and reducing costs for the nanoscale device. This design includes two drain electrodes, each measuring 15 nm in length and having different work functions (DWFs). The work function of the drain positioned closest to the channel (DWFAC) is set at 3.9 eV, which is 0.5 eV lower than that of the CNT, while the other drain section has a work function of 3.4 eV, 1 eV lower than the CNT. The electrical properties of the device were examined through quantum numerical simulations using the non-equilibrium Green's function (NEGF) method. The results indicate that the proposed structure significantly decreases the OFF-state current and improves the ON/OFF current ratio. Additionally, the leakage current is substantially lowered, resulting in favorable changes to the device's ambipolarity, along with a reduction in hot carrier effects and subthreshold swing (SS).

Low power process tolerant nano cache memory for military applications

ABSTRACT Rapid growth in high-performance battery-powered computing applications, Internet of Things (IoT) and artificial intelligence (AI), has raised the need for low-power integrated circuits. Particularly in military applications, wireless sensor nodes are used to detect border intrusion, weapon attacks, biometric wearables, internet of battlefield things (IoBT), etc. The computing and security devices utilised by the soldiers are powered by batteries. To increase the life and performance of these devices, the integrated circuits (IC) used within these devices need careful design. Particularly, an appropriate memory needs more attention because the design of memory has a substantial impact on IC performance as it occupies most of the chip space. In this article, a novel 8T transistor low-power cache memory cell is proposed and simulations for nominal chirality and dual chirality are done using HSPICE-compatible CNFET (carbon nanotube field effect transistor) technology. The power consumption is minimized in dual chirality case than nominal chirality. But still the power saving percentage of the proposed cache memory cell remains good compared to conventional memory structures. Thus the proposed cache memory cell provides low power, delay and energy apart from being process tolerant, thus proving that it is compatible for warfare and military applications.

Accelerating Linear Congruential Generators with Carbon Nanotube Field-Effect Transistors

Abstract In the era of technological advancements, safeguarding information privacy has become paramount across sectors like defense, finance, healthcare, and more. At the heart of these security measures lies cryptography, a field that necessitates the efficient processing and secure storage of data. Our project focuses on the optimization of Linear Congruential Generators (LCG), pivotal for cryptographic applications and pseudorandom number generation. Here it has been pioneered the implementation of LCG using Carbon Nanotube Field-Effect Transistor (CNTFET) technology, targeting the reduction of leakage power through the innovative application of sleep techniques. This advanced approach not only embodies a leap towards minimizing energy consumption but also enhances the overall performance and reliability of cryptographic systems. By integrating sleep modes into the CNTFET-based LCG design, our methodology significantly curtails leakage power without compromising the generator’s efficiency or output quality. The successful implementation and synthesis of this design, employing cutting-edge CNTFET technology, underscore the potential for substantial improvements in power efficiency while maintaining high standards of security and randomness essential for cryptographic algorithms.

Reconfigurable Five-In-One Carbon Nanotube Optoelectronic Transistor for Intelligent Computing and Communication.

Advances in artificial general intelligence (AGI) necessitate the integration of diverse functionalities to address complex tasks. Carbon nanotubes (CNTs), with their unique physical properties, have broad applications in emerging research fields, providing a foundation for next-generation devices that could overcome the limits of Moore's Law. This work demonstrates a novel intelligent device that integrates five functions─sensors, memory, neuromorphic computing, logic, and communication─using CNT field-effect transistors (CNFETs) compatible with CMOS processes. Through passivation and annealing techniques, we have significantly enhanced the optoelectronic performance of CNFETs, leading to the development of multifunctional optoelectronic synaptic transistors. These optimized CNFETs enable dual-mode weight-tunable synaptic functions, including long-term plasticity and multilevel storage. Additionally, a CNT-based neural network has achieved high recognition accuracy on the MNIST data set, showcasing the potential of in-memory computing. This research also innovates by integrating logic functions with optoelectronic communication capabilities, paving the way for next-generation intelligent computing and communication integrated systems.

A Low-Power, High-Resolution Analog Front-End Circuit for Carbon-Based SWIR Photodetector

Carbon nanotube field-effect transistors (CNT-FETs) have shown great promise in infrared image detection due to their high mobility, low cost, and compatibility with silicon-based technologies. This paper presents the design and simulation of a column-level analog front-end (AFE) circuit tailored for carbon-based short-wave infrared (SWIR) photodetectors. The AFE integrates a Capacitor Trans-impedance Amplifier (CTIA) for current-to-voltage conversion, coupled with Correlated Double Sampling (CDS) for noise reduction and operational amplifier offset suppression. A 10-bit/125 kHz Successive Approximation analog-to-digital converter (SAR ADC) completes the signal processing chain, achieving rail-to-rail input/output with minimized component count. Fabricated using 0.18 μm CMOS technology, the AFE demonstrates a high signal-to-noise ratio (SNR) of 59.27 dB and an Effective Number of Bits (ENOB) of 9.35, with a detectable current range from 500 pA to 100.5 nA and a total power consumption of 7.5 mW. These results confirm the suitability of the proposed AFE for high-precision, low-power SWIR detection systems, with potential applications in medical imaging, night vision, and autonomous driving systems.

Reproducible, Accurate, and Sensitive Food Toxin On-Site Detection with Carbon Nanotube Transistor Biosensors.

Field-effect transistor (FET) biosensors based on nanomaterials are promising in the areas of food safety and early disease diagnosis due to their ultrahigh sensitivity and rapid response. However, most academically developed FET biosensors lack real-world reproducibility and comprehensive methodological validation to meet the standards of regulatory bodies. Here, highly uniform and well-packaged semiconducting carbon nanotube (CNT) FET biosensor chips were developed and assessed for the plug-and-play sensing for the rapid and highly sensitive detection of aflatoxin B1 (AFB1) in real food samples to meet international standards. In order to meet the requirements for reproducibility and stability, a scalable residual-free passivation and packaging process was developed for CNT FET biosensors. Portable detection systems were then constructed for on-site detection. The resulting packaged chips were functionalized with nucleic aptamers to enable highly selective detection of AFB1 in food samples with a detection limit (LOD) of 0.55 fg/mL (standard) for AFB1 and cross-reactivity coefficients to interferences as low as 1.8 × 10-7 in simulated solutions. Utilizing the portable detection system, on-site real food detection was achieved with a rapid response time less than 60 s, and LOD of 0.25 pg/kg (standard) in complex corn sample matrices. Single-blind tests demonstrated the ability of the chips to detect AFB1-positive food with 100% accuracy, using a set of 30 peanut samples. Validation experiments confirmed that the detection range, stability, and repeatability met international standards. This study showcased the accuracy, reliability, and potential practical applications of CNT FET biosensor chips in areas such as food safety and rapid biomedical testing.

Realization of a high-efficient GDI-based 4:2 compressor for sum of absolute difference detection in image and signal processing

A new 4:2 approximate compressor is designed based on gate diffusion input (GDI), which has 14 transistors and only 6 errors in its outputs. The integration of the GDI with the dynamic threshold (DT) overcomes the body effect by the selection of carbon nanotube field-effect transistors (CNTFET) technology. By embedding the proposed compressor in the 8-bit sum of absolute difference (SAD) system, an area of 284.6 µm2 is occupied and a reliable system for difference detection between two images and electrocardiogram (ECG) results. Considering the fair conditions of comparison, the proposed circuit has significant performance in terms of circuitry parameters such as power, delay, and figure of merits (FoMs). In terms of power-delay-product (PDP) and power-delay-area-product (PDAP) the proposed cell shows a saving of 27 % and 47 %, respectively. A 40 % improvement in terms of a FoM containing PDP and power signal-to-noise ratio (PSNR) compared to the closest competitor qualifies the proposed circuit over the other counterparts. The proposed cell has a high performance under the difference detection in images and ECGs.

Optimising CNT-FET biosensor design through modelling of biomolecular electrostatic gating and its application to β-lactamase detection

Carbon nanotube field effect transistors (CNT-FET) hold great promise as next generation miniaturised biosensors. One bottleneck is modelling how proteins, with their distinctive electrostatic surfaces, interact with the CNT-FET to modulate conductance. Using advanced sampling molecular dynamics combined with non-canonical amino acid chemistry, we model protein electrostatic potential imparted on single walled CNTs (SWCNTs). We focus on using β-lactamase binding protein (BLIP2) as the receptor as it binds the antibiotic degrading enzymes, β-lactamases (BLs). BLIP2 is attached via the single selected residue to SWCNTs using genetically encoded phenyl azide photochemistry. Our devices detect two different BLs, TEM-1 and KPC-2, with each BL generating distinct conductance profiles due to their differing surface electrostatic profiles. Changes in conductance match the model electrostatic profile sampled by the SWCNTs on BL binding. Thus, our modelling approach combined with residue-specific receptor attachment could provide a general approach for systematic CNT-FET biosensor construction.

Mass Production of Carbon Nanotube Transistor Biosensors for Point-of-Care Tests.

Low-dimensional semiconductor-based field-effect transistor (FET) biosensors are promising for label-free detection of biotargets while facing challenges in mass fabrication of devices and reliable reading of small signals. Here, we construct a reliable technology for mass production of semiconducting carbon nanotube (CNT) film and FET biosensors. High-uniformity randomly oriented CNT films were prepared through an improved immersion coating technique, and then, CNT FETs were fabricated with coefficient of performance variations within 6% on 4-in. wafers (within 9% interwafer) based on an industrial standard-level process. The CNT FET-based ion sensors demonstrated threshold voltage standard deviations within 5.1 mV at each ion concentration, enabling direct reading of the concentration information based on the drain current. By integrating bioprobes, we achieved detection of biosignals as low as 100 aM through a plug-and-play portable detection system. The reliable technology will contribute to commercial applications of CNT FET biosensors, especially in point-of-care tests.

Bioelectronic sensing platform emulating the human endocannabinoid system for assessing and modulating of cannabinoid activity

Cannabinoids are involved in physiological and neuromodulatory processes through their interactions with the human cannabinoid receptor-based endocannabinoid system. Their association with neurodegenerative diseases and brain reward pathways underscores the importance of evaluating and modulating cannabinoid activity for both understanding physiological mechanisms and developing therapeutic drugs. The use of agonists and antagonists could be strategic approaches for modulation. In this study, we introduce a bioelectronic sensor designed to monitor cannabinoid binding to receptors and assess their agonistic and antagonistic properties. We produced human cannabinoid receptor 1 (hCB1R) via an Escherichia coli expression system and incorporated it into nanodiscs (NDs). These hCB1R-NDs were then immobilized on a single-walled carbon nanotube field-effect transistor (swCNT-FET) to construct a bioelectronic sensing platform. This novel system can sensitively detect the cannabinoid ligand anandamide (AEA) at concentrations as low as 1 fM, demonstrating high selectivity and real-time response. It also successfully identified the hCB1R agonist Δ9-tetrahydrocannabinol and observed that the hCB1R antagonist rimonabant diminished the sensor signal upon AEA binding, indicating the antagonism-based modulation of ligand interaction. Consequently, our bioelectronic sensing platform holds potential for ligand detection and analysis of agonism and antagonism.

Gate all around carbon nanotube field effect transistor espoused discrepancy cascode pass transistor adiabatic logic for ultra-low power application

Advances in wearable technology, IoT, and mobile applications have increased the demand for ultra-low-power electronic devices. Adiabatic Logic Circuit (ALC) is a design technique utilized in digital circuits to decrease the power consumption by decreasing the dynamic power dissipation. Current technologies face challenges in achieving both high performance and ultra-low power consumption. This research work introduces a novel approach in digital circuit design, specifically the Gate All-around Carbon Nanotube Field Effect Transistor with Discrepancy Cascode Pass Transistor Adiabatic Logic (GAA-CNTFET-DCPTAL), tailored for ultra-low power applications. This design operates efficiently with a four-phase Power Clock (PC) and demonstrates remarkable performance by achieving operation frequencies of up to 1 GHz while minimizing energy dissipation. GAA-CNTFET provides superior electrostatic control and high carrier mobility, reducing leakage currents and enhancing switching speeds. Simultaneously, Discrepancy Cascode Pass Transistor Adiabatic Logic (DCPTAL) uses adiabatic logic principles and a cascode structure to minimize energy dissipation during switching events. The technology node of proposed model is 10 nm. The software used for assessment is HSPICE is used for the simulation and validation of the proposed design. The proposed GAA-design attains 25.36 %, 14.28 %, and 16.06 % lower average power analyzed with existing techniques, such as Design with Evaluation of Clocked Differential Adiabatic Logic Families for the applications of low Power (DE-CDAL-LPA), Adiabatic logic-base strong ARM comparator for ultra-low power applications (AL-SARM-ULPA) and Analysis of 2PADCL Energy Recovery Logic for Ultra Low Power VLSI Design for SOC with Embedded Applications (2PADCL-ULP-VLSI) respectively.

Single-Walled Carbon Nanotube Based Field-Effect Transistors Functionalized with Odorant Receptors for Biosensing Applications

Bioelectronic detection of volatile organic compounds (VOC) has been demonstrated in a wide range of applications, with early reports focusing on environmental exogenous VOCs due to their adverse effects on human health; bacterial VOC signatures used as disease biomarkers, etc. Carbon nanotube field-effect transistors (CNT-FETs) are considered promising devices for bioelectronic detection due to their sensitivity, robustness and compatibility with microelectronic fabrication technologies. However, implementation of CNT-FETs still faces many challenges. Current VOCs detection approaches rely on separation techniques coupled with mass spectrometry, necessitating expensive equipment, labor-intensive preparation steps and trained personnel, and are not suitable for field use. Overcoming the challenges in the development of bioelectronic CNT-FET sensors holds great promise for high-throughput screening of VOCs.The natural insect odorant receptors (ORs) are highly attractive probes, potentially allowing ultrahigh specificity for VOC biosensing. Insect ORs exhibit remarkable sensitivities and the ability to selectively detect a vast number of VOCs. We have recently developed OR-functionalized carbon nanotube field-effect transistor (FET) devices. These FET devices comprise an isolated single-walled carbon nanotube (SWCNT), serving as the conducting channel material, functionalized with multiple insect ORs. These hybrid devices are capable of transducing ligand binding into an electronic current, without amplification. The insect OR-functionalized CNT FET were applied for the detection of several markers of environmental and clinical importance including Indole, Skatole, Octen-3-ol and Nonyl-aldehyde.We have developed a bioelectronic assay platform that contains a chip with 61 ORs-functionalized CNT-FET devices. Our unique functionalization method is based on directing the attachment of a native ORs-containing nanovesicles (which we have exogenously expressed and functionally characterized) to a generated CNT-FET point defect. Target binding-induced ionic current and conformational changes of ORs affect an electric field that modulates the device conductance.

GPU-Enabled Exascale Quantum Transport Modeling of Carbon Nanotube Devices

The work will describe our efforts to develop an exascale electrostatic-quantum transport framework, Quantum-eXstatic (https://github.com/AMReX-Microelectronics/eXstatic), currently supporting the modeling of carbon nanotube field-effect transistors (CNTFETs). The framework is capable of modeling realistic three-dimensional structures, efficiently, using CPU/GPU heterogeneous architectures of state-of-the-art supercomputers. It is built on top of the AMReX library, which is a GPU-enabled software library containing functionality for writing particle-mesh applications on structured grids. The Quantum-eXstatic framework comprises three major components: the electrostatic module, the quantum transport module, and the part that self-consistently couples the two modules. The electrostatic module using a finite-volume multigrid solver to compute the electrostatic potential induced by charges on the surface of carbon nanotubes, as well as by source, drain, and gate terminals, which can be modeled using an embedded boundary approach to allow for intricate shapes. The quantum transport module uses the Nonequilibrium Green's Function (NEGF) method to model induced charge. Currently, it supports coherent (ballistic) transport, mode-space approximation for subbands of nanotube, contacts modeled as semi-infinite leads, and Hamiltonian representation using the tight-binding approximation. Special features are being included for accurate modeling of long nanotubes, such as adaptive refinement of integration contours to resolve van Hove singularities in long channels. Particular attention is paid to overlap computations with communication to optimize GPU performance. The self-consistency between the two modules is achieved using Broyden's modified second algorithm, which is parallelized using CPUs and GPUs. Preliminary scaling studies show that the code exhibits ~77% weak-scaling efficiency on 512 NVIDIA A100 GPUs of Perlmutter supercomputer for modeling gate-all-around CNTFETs with a channel length of 13.5 microns at equilibrium conditions. This case involved computations of electrostatic potential in 14.5 billion computational cells and Green’s function computation for a Hamiltonian of size 131,072 x 131,072. For problems of this large size, the code takes about 5 min to reach self-consistency. Figure 1

Characterization and Control of Carbon Nanotube Doping

Carbon nanotube FETs show great promise for beyond-Si and monolithic 3D electronics, however there are still fundamental questions to explore. In particular, controlled N- and P- doping is a fundamental process module which can be used to engineer semiconductor resistance in un-gated regions such as the contact or extension, as well as optimize band-to-band tunneling leakage [1-4]. To-date both N- and P- doping has been demonstrated for CNT, but the optimal strategies for doping control and carrier density quantification have not been determined. In this work, we present a study of N- and P- doping using solid-state dopants and doping control strategy using a dielectric barrier of tunable thickness. A TCAD evaluation reveals the tradeoffs between carrier density and mobility for increasing dielectric barrier thickness, and reveals the critical role of dielectric constant in optimizing performance of spacer doping [5]. Multiple characterization approaches under evaluation help to correlate doping strength to experimentally measurable quantities with insight into the doping mechanisms. Finally, we will summarize potential approaches for improving doping control and quantification, and progress towards integration of the doping in highly-scaled high-performance carbon nanotube FETs [6].[1] Z. Zhang, et al., “Complementary carbon nanotube metal-oxide-semiconductor field-effect transistors with localized solid-state extension doping,” Nature Electronics, 2023.[2] Q. Lin, et al., “Band-to-band Tunneling Leakage Current Characterization and Projection in Carbon Nanotube Transistors,” ACS Nano, 2023.[3] G. Zeevi, et al., “PN Junction and band to band tunneling in carbon nanotube transistors at room temperature,” Nanotechnology, 2021.[4] L. Liyanage, et al., “VLSI-compatible carbon nanotube doping technique with low work-function metal oxides,” Nano Letters, 2014.[5] C. Gilardi et al., “Barrier Booster for Remote Extension Doping and its DTCO for 1D & 2D FETs”, IEDM 2023[6] S.Li, et al., “High-performance and low parasitic capacitance CNT MOSFET: 1.2 mA/μm at VDS of 0.75 V by self-aligned doping in sub-20 nm spacer,” IEDM 2023.

(Invited) Correlation Measurements for Carbon Nanotubes with Quantum Defects

Single-photon sources are one of the essential building blocks for the development of photonic quantum technology. In terms of potential practical application, an on-demand electrically driven quantum-light emitter on a chip is notably crucial for integrating photonic integrated circuits. Here, we propose functionalized single-walled carbon nanotube field-effect transistors as a promising solid-state quantum-light source by demonstrating photon antibunching behavior via electrical excitation. The sp3 quantum defects were formed on the surface of (7, 5) carbon nanotubes by 3,5-dichlorophenyl functionalization, and individual carbon nanotubes were wired to graphene electrode pairs. Filtered electroluminescent defect-state emission at 77 K was coupled into a Hanbury Brown and Twiss experiment setup, and single-photon emission was observed by performing second-order correlation function measurements. We discuss the dependence of the intensity correlation measurement on excitation power and emission wavelength highlighting the challenges of performing such measurements while simultaneously analyzing acquired data. Our results indicate a route toward room-temperature electrically-triggered single-photon emission.