Graphene Transistors Research Articles

Dielectric engineered graphene transistors for high-performance near-infrared photodetection

Graphene, known for its ultrahigh carrier mobility and broadband optical absorption, holds significant potential in optoelectronics. However, the carrier mobility of graphene on silicon substrates experienced a marked decrease due to surface roughness, phonon scattering affects. Here we report carrier mobility enhancement of graphene dielectric engineering. Through the fabrication of devices utilizing Si/SiO2/Al2O3/graphene layers and subsequent electrical characterization, our findings illustrate the navigable nature of the Al2O3 dielectric layer is navigable for reducing the SiO2 phonon scattering and increasing graphene's carrier mobility by up to ∼8000cm2V-1s-1. Furthermore, the improvement in carrier mobility of graphene has been utilized in the hybrid near-infrared photodetector, resulting in outstanding responsivity of ∼400 AW-1, detectivity of ∼2.2 ✕ 1011 Jones in the graphene/Ag2Te detector. Our study establishes pathways for the seamless integration of graphene or other 2D materials within the standard CMOS processes, thereby facilitating the fabrication of advanced optoelectronic devices.

Facial Expression Realization of Humanoid Robot Head and Strain-Based Anthropomorphic Evaluation of Robot Facial Expressions.

The facial expressions of humanoid robots play a crucial role in human-computer information interactions. However, there is a lack of quantitative evaluation methods for the anthropomorphism of robot facial expressions. In this study, we designed and manufactured a humanoid robot head that was capable of successfully realizing six basic facial expressions. The driving force behind the mechanism was efficiently transmitted to the silicone skin through a rigid linkage drive and snap button connection, which improves both the driving efficiency and the lifespan of the silicone skin. We used human facial expressions as a basis for simulating and acquiring the movement parameters. Subsequently, we designed a control system for the humanoid robot head in order to achieve these facial expressions. Moreover, we used a flexible vertical graphene sensor to measure strain on both the human face and the silicone skin of the humanoid robot head. We then proposed a method to evaluate the anthropomorphic degree of the robot's facial expressions by using the difference rate of strain. The feasibility of this method was confirmed through experiments in facial expression recognition. The evaluation results indicated a high degree of anthropomorphism for the six basic facial expressions which were achieved by the humanoid robot head. Moreover, this study also investigates factors affecting the reproduction of expressions. Finally, the impulse was calculated based on the strain curves of the energy consumption of the humanoid robot head to complete different facial expressions. This offers a reference for fellow researchers when designing humanoid robot heads, based on energy consumption ratios. To conclude, this paper offers data references for optimizing the mechanisms and selecting the drive components of the humanoid robot head. This was realized by considering the anthropomorphic degree and energy consumption of each part. Additionally, a new method for evaluating robot facial expressions is proposed.

Facile, cost-effective NO2 gas sensors based on polymer intercalated graphene/ reduced graphene oxide materials

BackgroundThe increasing severity of air pollution has driven the demand for efficient and cost-effective NO2 gas sensors. This report aims to develop a miniaturized NO2 gas sensor based on polymer intercalated graphene and reduced graphene oxide and investigate their adsorption mechanisms. MethodsThe fabrication of sensors is realized by depositing the graphene materials via a surfactant assisted two-step dipping onto laser-patterned interdigitated electrodes. The characterization of the graphene materials is carried out using various microscopic/spectroscopic techniques and the sensing performance is evaluated using a potentiostat. Significant findingsThe study reveals that the sensor based on reduced graphene oxide outperforms the graphene sensor, exhibiting a doubled response. Moreover, Langmuir adsorption isotherm also suggests the enhanced performance is attributable to the additional adsorption sites created by oxygen defects.

Two-Step Relaxation of Non-Equilibrium Electrons in Graphene: The Key to Understanding Pump–Probe Experiments

In the majority of experiments targeting nonlinear optical phenomena, the application of high-intensity pulses drives electrons in graphene into a strongly non-equilibrium state. Under these conditions, conventional perturbation theory falls short in explaining graphene’s intricate optical response because of significant deviations in electron distribution over energy states from the equilibrium Fermi-Dirac one. In this work, we present a two-step relaxation model capable of predicting the transient dynamics of graphene’s carriers out of equilibrium, from the generation of spectrally narrow populations of non-thermalized electrons and holes to the establishment of a hot-electron gas and its subsequent cooling toward equilibrium with the crystal lattice. By comparing our model calculations to experimental results, we demonstrate its reliability and relevance to pump–probe experiments, providing insights into the pivotal role of hot electrons in comprehending ultrafast dynamics in graphene.

Nonlinear Landau Fan Diagram for Graphene Electrons Exposed to a Moiré Potential.

Due to Landau quantization, the conductance of two-dimensional electrons exposed to a perpendicular magnetic field exhibits oscillations that generate a fan of linear trajectories when plotted in the parameter space spanned by density and field. This fan looks identical, irrespective of the dispersion and field dependence of the Landau level energy. This is no surprise because the position of conductance minima depends solely on the level degeneracy that is linear in flux. The fractal energy spectrum that emerges within each Landau band when electrons are also exposed to a two-dimensional superlattice potential produces numerous additional oscillations, but they also create just linear fans for identical reasons. Here, we report conductance oscillations of graphene electrons exposed to a moiré potential that defy this general rule and form nonlinear trajectories in the density-field plane. We attribute this anomalous behavior to the simultaneous occupation of multiple minibands and magnetic breakdown-induced open orbits.

Aqueous chemimemristor based on proton-permeable graphene membranes

Memristive devices, electrical elements whose resistance depends on the history of applied electrical signals, are leading candidates for future data storage and neuromorphic computing. Memristive devices typically rely on solid-state technology, while aqueous memristive devices are crucial for biology-related applications such as next-generation brain-machine interfaces. Here, we report a simple graphene-based aqueous memristive device with long-term and tunable memory regulated by reversible voltage-induced interfacial acid-base equilibria enabled by selective proton permeation through the graphene. Surface-specific vibrational spectroscopy verifies that the memory of the graphene resistivity arises from the hysteretic proton permeation through the graphene, apparent from the reorganization of interfacial water at the graphene/water interface. The proton permeation alters the surface charge density on the CaF2 substrate of the graphene, affecting graphene's electron mobility, and giving rise to synapse-like resistivity dynamics. The results pave the way for developing experimentally straightforward and conceptually simple aqueous electrolyte-based neuromorphic iontronics using two-dimensional (2D) materials.

Graphene and nanocomposites—Imprints on environmentally sustainable production and applications based on ecological aspects

Graphene, an innovative nanocarbon, has been discovered as a significant technological material. Increasing utilization of graphene has moved research towards the development of sustainable green techniques to synthesize graphene and related nanomaterials. This review article is basically designed to highlight the significant sustainability aspects of graphene. Consequently, the sustainability vision is presented for graphene and graphene nanocomposites. Environmentally sustainable production of graphene and ensuing nanomaterials has been studied. The formation of graphene, graphene oxide, reduced graphene oxide, and other derivatives has been synthesized using ecological carbon and green sources, green solvents, non-toxic reagents, and green routes. Furthermore, the utilization of graphene for the conversion of industrial polymers to sustainable recycled polymers has been studied. In addition, the recycled polymers have also been used to form graphene as a sustainable method. The implication of graphene in the sustainable energy systems has been investigated. Specifically, high specific capacitance and capacitance retention were observed for graphene-based supercapacitor systems. Subsequently, graphene may act as a multi-functional, high performance, green nanomaterial with low weight, low price, and environmental friendliness for sustainable engineering and green energy storage applications. However, existing challenges regarding advanced material design, processing, recyclability, and commercial scale production need to be overcome to unveil the true sustainability aspects of graphene in the environmental and energy sectors.

Using Machine Learning to Overcome Interfering Oxygen Effects in a Graphene Volatile Organic Compound Sensor.

Discriminating between volatile organic compounds (VOCs) for applications including disease diagnosis and environmental monitoring, is often complicated by the presence of interfering compounds such as oxygen. Graphene sensors are effective at detecting VOCs; however, they are also known to be highly sensitive to oxygen. Therefore, the combined effects of each of these gases on graphene sensors must be understood. In this work, we use graphene variable capacitor (varactor) sensors to examine the cross-selectivity of oxygen at 3 concentrations and 3 VOCs (ethanol, methanol, and methyl ethyl ketone) at 5 concentrations each. The sensor responses exhibit distinct shapes dependent on the relative concentrations in mixtures of oxygen and VOCs. Because the entire response shape is therefore informative for distinguishing between each gas mixture, a classification algorithm that utilizes entire sequences of data is needed. Accordingly, a long short-term memory (LSTM) network is used to classify the mixtures and VOC concentrations. The model achieves 100% accurate classification of the VOC type, even in the presence of varying levels of oxygen. When the VOC type and VOC concentration are classified, we show that the sensors can provide VOC concentration resolution within approximately 200 ppm. Throughout this work, we also demonstrate that an effective gas mixture classification can be achieved, even while the sensors exhibit varied drift patterns typical of graphene sensors. This is made possible due to the data analysis and machine learning methods employed.

Improving the Electrical Performance of Large-area Graphene Transistors Through Vacuum-assisted Annealing

Improving the Electrical Performance of Large-area Graphene Transistors Through Vacuum-assisted Annealing

Gate-Controlled Neuromorphic Functional Transition in an Electrochemical Graphene Transistor.

Neuromorphic devices have attracted significant attention as potential building blocks for the next generation of computing technologies owing to their ability to emulate the functionalities of biological nervous systems. The essential components in artificial neural networks such as synapses and neurons are predominantly implemented by dedicated devices with specific functionalities. In this work, we present a gate-controlled transition of neuromorphic functions between artificial neurons and synapses in monolayer graphene transistors that can be employed as memtransistors or synaptic transistors as required. By harnessing the reliability of reversible electrochemical reactions between carbon atoms and hydrogen ions, we can effectively manipulate the electric conductivity of graphene transistors, resulting in a high on/off resistance ratio, a well-defined set/reset voltage, and a prolonged retention time. Overall, the on-demand switching of neuromorphic functions in a single graphene transistor provides a promising opportunity for developing adaptive neural networks for the upcoming era of artificial intelligence and machine learning.

Parafilm Enabled Rapid and Scalable Delamination/Integration of Graphene for High‐Performance Capacitive Touch Sensor

The high electrical conductivity and bendability of graphene makes it versatile for flexible electronic sensor applications. The fabrication of such flexible sensors necessitates two important prerequisites: defect‐free transfer of graphene to a flexible substrate and creating appropriate patterns without altering graphene's inherent properties. Here, a potentially rapid and scalable method to delaminate graphene non‐destructively from a metal substrate by using flexible parafilm is reported. This method allows not only the scalable transfer of continuous graphene, but also the realization of graphene patterns on the parafilm substrate. Graphene on parafilm showed negligible doping effect with high room temperature carrier mobility exceeding 6 × 103 cm2 V−1 s−1 for a centimeter‐scale sample. Using parafilm as a substrate‐cum‐dielectric medium, a proof‐of‐concept capacitive touch sensor (CTS) arrays is demonstrated without the use of lithography, by simple cross‐assembling and mild heating. The graphene sensor thus realized in its simplistic device configuration had an enhanced sensitivity of 43% when touch and release cycles are performed on the device. The nearly non‐destructive and user‐friendly route for directly integrating graphene with a flexible substrate is expected to play a potential role in the design of graphene‐based flexible electronics.

Visible-frequency plasmonic enhancement at the edge of graphene/h-BN heterostructures on silicon substrate

Heterostructures of graphene and hexagonal boron nitride (G/h-BN) have been widely studied for controlling and utilizing graphene electronic properties. Here we characterize specific optical and electronic properties of G/h-BN heterostructures made of a high-quality single layer chemical vapor deposition (CVD) graphene laid over h-BN flakes, with focus on plasmonic effects. We compare the G/h-BN properties on Si and SiO2 substrates by micro-Raman spectroscopy mapping, Kelvin probe force microscopy, optical and atomic force microscopy. We observe highly enhanced Raman intensity (up to 280 %) from Si as well as graphene along the G/h-BN edge. It is attributed to localized concentration of electrons in graphene and suitable perpendicular orientation of plasmonic vibrations at the edge. The plasmonic Raman enhancement occurs under a visible light excitation (532 nm) and the effect can be tuned by the h-BN flake thickness (10–150 nm). The enhancement is specific to G/h-BN/Si structures, on G/h-BN/SiO2 structures the Raman signal is suppressed while I2D/IG ratio is increased. Vice versa, change of surface potential under visible light illumination (photovoltage) is on G/h-BN/Si negligible (within 10 mV) compared to the G/h-BN/SiO2 structures. These results open new prospects for broad utilization of localized visible plasmonic effects in graphene.

Subthreshold slope below 60 mV/decade in graphene transistors induced by channel geometry at the wafer-scale

In this paper, we demonstrate experimentally that field-effect transistors with nanoconstricted graphene monolayer channels have a subthreshold swing (SS) below 60 mV/dec, which is slightly dependent on temperature. Two shapes of nanoconstricted graphene monolayers are considered: (i) a bow-tie shape, representative for a symmetric channel, and (ii) a trapezoidal shape, which illustrates an asymmetric channel. While both types of nonuniform channels are opening a bandgap in graphene, thus showing an on/off ratio of 105, the SS in the graphene bow-tie channel is below 60 mV/dec in the temperature range 25 °C–44 °C.

Tunable quantum interferometer for correlated moiré electrons

Magic-angle twisted bilayer graphene can host a variety of gate-tunable correlated states – including superconducting and correlated insulator states. Recently, junction-based superconducting moiré devices have been introduced, enabling the study of the charge, spin and orbital nature of superconductivity, as well as the coherence of moiré electrons in magic-angle twisted bilayer graphene. Complementary fundamental coherence effects—in particular, the Little–Parks effect in a superconducting ring and the Aharonov–Bohm effect in a normally conducting ring – have not yet been reported in moiré devices. Here, we observe both phenomena in a single gate-defined ring device, where we can embed a superconducting or normally conducting ring in a correlated or band insulator. The Little–Parks effect is seen in the superconducting phase diagram as a function of density and magnetic field, confirming the effective charge of 2e. We also find that the coherence length of conducting moiré electrons exceeds several microns at 50 mK. In addition, we identify a regime characterized by h/e-periodic oscillations but with superconductor-like nonlinear transport.

Alloy/Perovskite Compounds Modified by Plasma Treatment and their Role in Enhancing the Capacitance of Sustainable Graphene Supercapacitors

AbstractGraphene electrodes were firstly printed on recycled single‐use‐packets. Later, the Ni50Mn35In15 (NMI) alloy or Ca2.9Nd0.1Co3.9Cu0.1O9, (CNCCO) misfit perovskite was deposited on the graphene electrodes to enhance their capacitive performance. Next, flexible supercapacitors (SCs) were assembled by using such electrodes. The SCs made with NMI and CNCCO powders were named as GNMI‐SC, and GCNCCO‐SC, respectively. Those ones produced capacitances/energy‐densities of 761.8 F g−1/152.6 Wh kg−1 and 207.7 F g−1/41.6 Wh kg−1, respectively. Subsequently, a mixture 1 : 1 of NMI and CNCCO powders was melted/coalesced at 1700 °C by using a plasma treatment in argon atmosphere and obtained in this way a NMI/CNCCO composite powder. The SC made with this last composite generated a capacitance/energy‐density of 1235.2 F g−1/247.3 Wh kg−1. Those last values are 62–500 % higher than these for the GNMI‐SC, and GCNCCO‐SC devices. Other benefits obtained after the introduction of the NMI/CNCCO powders into the SCs were: 1) the formation of additional Cu2+, Mn4+, Nd2+ and In3+ species, which enhanced the capacitance; 2) the capacitance retention was maintained above 93 % after 500 cycles of charge discharge; and 3) the lowest values of series and charge transfer resistances were obtained, which favored the ion diffusion/storage in the SC electrodes.

Laser fabrication of epidermal paper-based graphene sensors

There is an increasing demand for epidermal sensors that can adapt to the contours and the movements of the human body, but the fabrication of prevalent polymer-based epidermal sensors often involves costly materials and complex procedures. Paper has emerged as a cost-effective substrate for next-generation epidermal sensors, featuring such advantages as bendability, breathability, biocompatibility, and environment-friendliness. However, transducing materials are commonly introduced to paper substrates in post hoc manners or through time-consuming syntheses, in addition to the direct manufacturing of paper. Here we report an integrative method to fabricate epidermal paper-based graphene sensors, where graphene induction and paper cutting can be achieved in a single lasing procedure to generate both transducing components and overall sensor formats. Lasing conditions are systematically explored, mainly to control the multifaceted properties of the obtained graphene transducers. The resultant paper-based graphene structures exhibit sufficient reliability in various scenarios regarding storage, lighting, and deformation. Paper-based graphene sensors are strategically designed in terms of overall formats, geometric patterns, hydrophilicity/hydrophobicity, surface functionalization, and readouts for measuring biophysical and biochemical information relevant to human health. The sensor performance can be optimized by adjusting laser power, and the calibrated sensitivities for mechanical strain, temperature, humidity, pH, and glucose are 76.93, –0.15% °C–1, 37.06 μA %–1, 28.13 mV pH–1, and 1.26 μA mM–1, respectively. Multimodal health monitoring is demonstrated with paper-based graphene sensors. Our approach can facilitate the generation of epidermal paper-based sensors and meet diverse requirements of health monitoring.

Foldy-Wouthuysen transformation and multiwave states of a graphene electron in external fields and free (2+1)-space

The relativistic Foldy-Wouthuysen transformation is used for an advanced description of planar graphene electrons in external fields and free (2+1)-space. It is shown that the initial Dirac equation should by based on the usual (4 × 4) Dirac matrices but not on the reduction of matrix dimensions and the use of (2 × 2) Pauli matrices. Nevertheless, the both approaches agree with the experimental data on graphene electrons in a uniform magnetic field. The pseudospin of graphene electrons is not the one-value spin and takes the values ±1/2. The exact Foldy-Wouthuysen Hamiltonian of a graphene electron in uniform and nonuniform magnetic fields is derived. The exact energy spectrum agreeing with the experiment and exact Foldy-Wouthuysen wave eigenfunctions are obtained. These eigenfunctions describe multiwave (structured) states in the (2+1)-space. It is proven that the Hermite-Gauss beams exist even in the free space. In the multiwave Hermite-Gauss states, graphene electrons acquire nonzero effective masses dependent on a quantum number and move with group velocities which are less than the Fermi velocity. Graphene electrons in a static electric field also can exist in the multiwave Hermite-Gauss states defining non-spreading coherent beams. These beams can be accelerated and decelerated.

A flexible transparent graphene/metal–organic framework complex hybrid chemical sensor for highly sensitive ethanol detection

AbstractHigh‐performance flexible and transparent chemical sensors are key to achieving wearable electronics. Graphene with high transmittance and electrical properties is a suitable material for flexible and transparent chemical sensors. However, graphene has low detectivity to chemical substances. Here, we report hybrid chemical sensors fabricated by introducing a highly flat and smooth metal–organic framework (MOF) on graphene. The graphene chemical sensors functionalized with MOF on SiO2/Si wafer exhibit 22 times higher sensitivity of 6.07 μA ppm−1 in detecting ethanol than that of pristine graphene transistors of 0.28 μA ppm−1 and a low detection limit of 1 ppm. Furthermore, a flexible transparent 7 × 7 chemical sensor array exhibits great driving stability after the bending cycles of 105 at a bending radius of 1.0 mm and shows sensitivity of 0.11 μA ppm−1. Our findings demonstrate an efficient way to improve the chemical sensing ability of graphene for application in wearable chemical sensors.image

The rational design of poly (inoic liquid) for 4.0 V graphene-based supercapacitors

The rational design of poly (inoic liquid) for 4.0 V graphene-based supercapacitors

Laser-Guided, Self-Confined Graphitization for High-Conductivity Embedded Electronics.

Facile fabrication of highly conductive and self-encapsulated graphene electronics is in urgent demand for carbon-based integrated circuits, field effect transistors, optoelectronic devices, and flexible sensors. The current fabrication of these electronic devices is mainly based on layer-by-layer techniques (separate circuit preparation and encapsulation procedures), which show multistep fabrication procedures, complicated renovation/repair procedures, and poor electrical property due to graphene oxidation and exfoliation. Here, we propose a laser-guided interfacial writing (LaserIW) technique based on self-confined, nickel-catalyzed graphitization to directly fabricate highly conductive, embedded graphene electronics inside multilayer structures. The doped nickel is used to induce chain carbonization, which firstly enhances the photothermal effect to increase the confined temperature for initial carbonization, and the generated carbon further increases the light-absorption capacity to fabricate high-quality graphene. Meanwhile, the nickel atoms contribute to the accelerated connection of carbon atoms. This interfacial carbonization inherently avoids the exfoliation and oxidation of the as-formed graphene, resulting in an 8-fold improvement in electrical conductivity (~20,000 S/m at 7,958 W/cm2 and 2 mm/s for 20% nickel content). The LaserIW technique shows excellent stability and reproducibility, with ±2.5% variations in the same batch and ±2% variations in different batches. Component-level wireless light sensors and flexible strain sensors exhibit excellent sensitivity (665 kHz/(W/cm2) for passive wireless light sensors) and self-encapsulation (<1% variations in terms of waterproof, antifriction, and antithermal shock). Additionally, the LaserIW technique allows for one-step renovation of in-service electronics and nondestructive repair of damaged circuits without the need to disassemble encapsulation layers. This technique reverses the layer-by-layer processing mode and provides a powerful manufacturing tool for the fabrication, modification, and repair of multilayer, multifunctional embedded electronics, especially demonstrating the immense potential for in-space manufacturing.