Decade of 2D-materials-based RRAM devices: a review

Low Power Volatile and Nonvolatile Memristive Devices from 1D MoO2-MoS2 Core-Shell Heterostructures for Future Bio-Inspired Computing

Memristors-based integrated circuits for emerging bio-inspired computing paradigms require an integrated approach utilizing both volatile and nonvolatile memristive devices. Here, an innovative architecture comprising of 1D CVD-grown core-shell heterostructures (CSHSs) of MoO2-MoS2 is employed as memristors manifesting both volatile switching (with high selectivity of 107 and steep slope of 0.6 mV decade-1) and nonvolatile switching phenomena (with Ion/Ioff ≈103 and switching speed of 60 ns). In these CSHSs, the metallic core MoO2 with high current carrying capacity provides a conformal and immaculate interface with semiconducting MoS2 shells and therefore it acts as a bottom electrode for the memristors. The power consumption in volatile devices is as low as 50 pW per set transition and 0.1 fW in standby mode. Voltage-driven current spikes are observed for volatile devices while with nonvolatile memristors, key features of a biological synapse such as short/long-term plasticity and paired pulse facilitation are emulated suggesting their potential for the development of neuromorphic circuits. These CSHSs offer an unprecedented solution for the interfacial issues between metallic electrodes and the layered materials-based switching element with the prospects of developing smaller footprint memristive devices for future integrated circuits.

Emulating biological synaptic characteristics of HfOx/AlN-based 3D vertical resistive memory for neuromorphic systems

Here, we demonstrate double-layer 3D vertical resistive random-access memory with a hole-type structure embedding Pt/HfOx/AlN/TiN memory cells, conduct analog resistive switching, and examine the potential of memristors for use in neuromorphic systems. The electrical characteristics, including resistive switching, retention, and endurance, of each layer are also obtained. Additionally, we investigate various synaptic characteristics, such as spike-timing dependent plasticity, spike-amplitude dependent plasticity, spike-rate dependent plasticity, spike-duration dependent plasticity, and spike-number dependent plasticity. This synapse emulation holds great potential for neuromorphic computing applications. Furthermore, potentiation and depression are manifested through identical pulses based on DC resistive switching. The pattern recognition rates within the neural network are evaluated, and based on the conductance changing linearly with incremental pulses, we achieve a pattern recognition accuracy of over 95%. Finally, the device's stability and synapse characteristics exhibit excellent potential for use in neuromorphic systems.

Tweaking the Non-Volatile Write-Once-Read-Many-Times (WORM) Memory using Donor-Acceptor Architecture with Isatin as Core Acceptor

Organic memory devices have attracted attention because they promise flexible electronics, low manufacturing costs, and compatibility with large-scale integration. A series of new D-A architectures were synthesized employing different donor groups and the isatin moiety as the acceptor through Suzuki-Miyaura coupling reactions. Strong intramolecular interactions were observed in the synthesized compounds, further corroborated by an optimal bandgap. The SEM investigation confirmed good molecular ordering and superior thin film surface coverage. All the compounds demonstrated notable binary Write-Once-Read-Many-Times (WORM) memory behaviour. The threshold switching voltage for these D-A systems ranged from -0.79 to -2.37 V, with the compound having isobutyl substituent showing the lowest threshold voltage and maximum ON/OFF ratio of 102, thus outperforming others. The combined effects of charge transfer and charge trapping are responsible for the resistive switching mechanism prevailing in these systems. The alterations in D-A molecules that affect molecular packing, thin film morphology, and, finally, the memory performance of the active layer are highlighted in this work.

Design and synthesis of a solution-processed redox-active bis(formazanate) zinc complex for resistive switching applications

In this paper, we report the synthesis and characterization of a mononuclear zinc complex (1) containing a redox-active bis(4-antipyrinyl) derivative of the 3-cyanoformazanate ligand. Complex 1 was readily obtained by refluxing zinc acetate with 3-cyano-1,5-(4-antipyrinyl)formazan (LH) in a methanolic solution. Single-crystal X-ray diffraction analysis of complex 1 shows that the formazanate ligands bind to the zinc center in a five-member chelate "open" form via the 1- and 4-positions of the 1,2,4,5-tetraazapentadienyl formazanate backbone leading to the formation of the mononuclear bis(formazanate) zinc complex exhibiting a distorted octahedral geometry. We also report the study of resistive-switching random access memory application of this solution-processable bis(formazanate) Zn(II) complex to facilitate the practical implementation of transition metal complex-based molecular memory devices. The complex demonstrated high conductance switching with a large ON-OFF ratio, good stability, and a long retention time. A trap-controlled space charge limited current mechanism is proposed for the observed resistive switching behavior of the device, wherein the role played by the [ZnIIL2] complex that comprises the extended redox-active conjugated ligand backbone is revealed by corroborating electrochemical studies, spectrochemical experiments, and DFT calculations. In addition to providing significant insights into the molecular design of transition metal complexes for memory applications, this study also presents the utilization of ZnIIL2 towards the realization of non-volatile resistive random access memory (RRAM) devices with inorganic/organic hybrid active layers that are highly cost-effective and sustainable. These devices exhibited multilevel switching and low current operation, both of which are desirable for advanced memory applications.

Amorphous BN-Based Synaptic Device with High Performance in Neuromorphic Computing

The von Neumann architecture has faced challenges requiring high-fulfillment levels due to the performance gap between its processor and memory. Among the numerous resistive-switching random-access memories, the properties of hexagonal boron nitride (BN) have been extensively reported, but those of amorphous BN have been insufficiently explored for memory applications. Herein, we fabricated a Pt/BN/TiN device utilizing the resistive switching mechanism to achieve synaptic characteristics in a neuromorphic system. The switching mechanism is investigated based on the I-V curves. Utilizing these characteristics, we optimize the potentiation and depression to mimic the biological synapse. In artificial neural networks, high-recognition rates are achieved using linear conductance updates in a memristor device. The short-term memory characteristics are investigated in depression by controlling the conductance level and time interval.

Graphene-based RRAM devices for neural computing

Resistive random access memory is very well known for its potential application in in-memory and neural computing. However, they often have different types of device-to-device and cycle-to-cycle variability. This makes it harder to build highly accurate crossbar arrays. Traditional RRAM designs make use of various filament-based oxide materials for creating a channel that is sandwiched between two electrodes to form a two-terminal structure. They are often subjected to mechanical and electrical stress over repeated read-and-write cycles. The behavior of these devices often varies in practice across wafer arrays over these stresses when fabricated. The use of emerging 2D materials is explored to improve electrical endurance, long retention time, high switching speed, and fewer power losses. This study provides an in-depth exploration of neuro-memristive computing and its potential applications, focusing specifically on the utilization of graphene and 2D materials in RRAM for neural computing. The study presents a comprehensive analysis of the structural and design aspects of graphene-based RRAM, along with a thorough examination of commercially available RRAM models and their fabrication techniques. Furthermore, the study investigates the diverse range of applications that can benefit from graphene-based RRAM devices.

A Design Methodology for Fault-Tolerant Neuromorphic Computing Using Bayesian Neural Network

Memristor crossbar arrays are a promising platform for neuromorphic computing. In practical scenarios, the synapse weights represented by the memristors for the underlying system are subject to process variations, in which the programmed weight when read out for inference is no longer deterministic but a stochastic distribution. It is therefore highly desired to learn the weight distribution accounting for process variations, to ensure the same inference performance in memristor crossbar arrays as the design value. In this paper, we introduce a design methodology for fault-tolerant neuromorphic computing using a Bayesian neural network, which combines the variational Bayesian inference technique with a fault-aware variational posterior distribution. The proposed framework based on Bayesian inference incorporates the impacts of memristor deviations into algorithmic training, where the weight distributions of neural networks are optimized to accommodate uncertainties and minimize inference degradation. The experimental results confirm the capability of the proposed methodology to tolerate both process variations and noise, while achieving more robust computing in memristor crossbar arrays.

Spatially-Resolved Thermometry of Filamentary Nanoscale Hot Spots in TiO2 Resistive Random Access Memories to Address Device Variability

Resistive random access memories (RRAM), based on the formation and rupture of conductive nanoscale filaments, have attracted increased attention for application in neuromorphic and in-memory computing. However, this technology is, in part, limited by its variability, which originates from the stochastic formation and extreme heating of its nanoscale filaments. In this study, we used scanning thermal microscopy (SThM) to assess the effect of filament-induced heat spreading on the surface of metal oxide RRAMs with different device designs. We evaluate the variability of TiO2 RRAM devices with area sizes of 2 × 2 and 5 × 5 μm2. Electrical characterization shows that the variability indicated by the standard deviation of the forming voltage is ∼2 times larger for 5 × 5 μm2 devices than for the 2 × 2 μm2 ones. Further knowledge on the reason for this variability is gained through the SThM thermal maps. These maps show that for 2 × 2 μm2 devices the formation of one filament, i.e., hot spot at the device surface, happens reliably at the same location, while the filament location varies for the 5 × 5 μm2 devices. The thermal information, combined with the electrical, interfacial, and geometric characteristics of the device, provides additional insights into the operation and variability of RRAMs. This work suggests thermal engineering and characterization routes to optimize the efficiency and reliability of these devices.

Unravelling the Data Retention Mechanisms under Thermal Stress on 2D Memristors

Memristors based on two-dimensional (2D) materials are a rapidly growing research area due to their potential in energy-efficient in-memory processing and neuromorphic computing. However, the data retention of these emerging memristors remains sparsely investigated, despite its crucial importance to device performance and reliability. In this study, we employ kinetic Monte-Carlo simulations to investigate the data retention of a 2D planar memristor. The operation of the memristor depends on field-driven on defect migration, while thermal diffusion gradually evens the defect distribution, leading to the degradation of the high resistance state (HRS) and diminishing the ON/OFF ratio. Notably, we examine the resilience of devices based on single crystals of transition metal dichalcogenides (TMDs) in harsh environments. Specifically, our simulations show that MoS2-based devices have negligible degradation after 10 years of thermal annealing at 400 K. Furthermore, the variability in data retention lifetime across different temperatures is less than 22%, indicating a relatively consistent performance over a range of thermal conditions. We also demonstrate that device miniaturization does not compromise data retention lifetime. Moreover, employing materials with higher activation energy for defect migration can significantly enhance data retention at the cost of increased switching voltage. These findings shed light on the behavior of 2D memristors and pave the way for their optimization in practical applications.

Resistive random access memory: introduction to device mechanism, materials and application to neuromorphic computing

The modern-day computing technologies are continuously undergoing a rapid changing landscape; thus, the demands of new memory types are growing that will be fast, energy efficient and durable. The limited scaling capabilities of the conventional memory technologies are pushing the limits of data-intense applications beyond the scope of silicon-based complementary metal oxide semiconductors (CMOS). Resistive random access memory (RRAM) is one of the most suitable emerging memory technologies candidates that have demonstrated potential to replace state-of-the-art integrated electronic devices for advanced computing and digital and analog circuit applications including neuromorphic networks. RRAM has grown in prominence in the recent years due to its simple structure, long retention, high operating speed, ultra-low-power operation capabilities, ability to scale to lower dimensions without affecting the device performance and the possibility of three-dimensional integration for high-density applications. Over the past few years, research has shown RRAM as one of the most suitable candidates for designing efficient, intelligent and secure computing system in the post-CMOS era. In this manuscript, the journey and the device engineering of RRAM with a special focus on the resistive switching mechanism are detailed. This review also focuses on the RRAM based on two-dimensional (2D) materials, as 2D materials offer unique electrical, chemical, mechanical and physical properties owing to their ultrathin, flexible and multilayer structure. Finally, the applications of RRAM in the field of neuromorphic computing are presented.

Resistive Switching Crossbar Arrays Based on Layered Materials

Resistive switching (RS) devices are metal/insulator/metal cells that can change their electrical resistance when electrical stimuli are applied between the electrodes, and they can be used to store and compute data. Planar crossbar arrays of RS devices can offer a high integration density (>10⁸  devices mm^{- 2} ) and this can be further enhanced by stacking them three-dimensionally. The advantage of using layered materials (LMs) in RS devices compared to traditional phase-change materials and metal oxides is that their electrical properties can be adjusted with a higher precision. Here, the key figures-of-merit and procedures to implement LM-based RS devices are defined. LM-based RS devices fabricated using methods compatible with industry are identified and discussed. The focus is on small devices (size < 9 µm² ) arranged in crossbar structures, since larger devices may be affected by artifacts, such as grain boundaries and flake junctions. How to enhance device performance, so to accelerate the development of this technology, is also discussed.

Charge trapped CdS quantum dot embedded polymer matrix for a high speed and low power memristor

The data storage requirement in the digital world is increasing day by day with the advancement of the internet of things. In this respect, nonvolatile resistive random-access memory is an option that provides high density and low power data storage capabilities. In this work, zero-dimensional colloidal CdS quantum dots and a polymer composite at an appropriate ratio were used to fabricate a memristive device. Comparison with a pristine CdS quantum dot-based device reveals that a surrounding matrix around the quantum dots is needed for observing memristive behavior. The quantum dots embedded in the polymer matrix device showed extremely stable electrical switching behavior that can be operated for more than 300 cycles and 60 000 seconds. Moreover, the device needs extremely low power to operate at a very high speed. The smooth surface morphology dictates a charge trapping mechanism for the switching phenomenon; however, an interplay between different charge transport mechanisms leads to the fast switching and high on-off ratio of the device.

Charge Transport inside TiO2 Memristors Prepared via FEBID

We fabricated memristive devices using focused electron beam-induced deposition (FEBID) as a direct-writing technique employing a Pt/TiO₂/Pt sandwich layer device configuration. Pinching in the measured current-voltage characteristics (i-v), the characteristic fingerprint of memristive behavior was clearly observed. The temperature dependence was measured for both high and low resistive states in the range from 290 K down to about 2 K, showing a stretched exponential behavior characteristic of Mott-type variable-range hopping. From this observation, a valence change mechanism of the charge transport inside the TiO₂ layer can be deduced.

Study on the Electrical Conduction Mechanism of Unipolar Resistive Switching Prussian White Thin Films

The electrical conduction mechanism of resistive switching Prussian white (PW) thin films obtained by the electrodeposition method was examined by AC impedance spectroscopy and DC current-voltage measurements. Using an electrode tip to contact PW grown over Au, robust unipolar resistive switching was observed with a current change of up to three orders of magnitude, high repeatability, and reproducibility. Moreover, electrical impedance spectroscopy showed that the resistive switching comes from small conductive filaments formed by potassium ions before the establishment of larger conductive channels. Both voltammetry and EIS measurements suggest that the electrical properties and conductive filament formation are influenced by defects and ions present in the grain boundaries. Thus, PW is a potential material for the next generation of ReRAM devices.

All-Printed Flexible Memristor with Metal–Non-Metal-Doped TiO2 Nanoparticle Thin Films

A memristor is a fundamental electronic device that operates like a biological synapse and is considered as the solution of classical von Neumann computers. Here, a fully printed and flexible memristor is fabricated by depositing a thin film of metal–non-metal (chromium-nitrogen)-doped titanium dioxide (TiO₂). The resulting device exhibited enhanced performance with self-rectifying and forming free bipolar switching behavior. Doping was performed to bring stability in the performance of the memristor by controlling the defects and impurity levels. The forming free memristor exhibited characteristic behavior of bipolar resistive switching with a high on/off ratio (2.5 × 10³), high endurance (500 cycles), long retention time (5 × 10³ s) and low operating voltage (±1 V). Doping the thin film of TiO₂ with metal–non-metal had a significant effect on the switching properties and conduction mechanism as it directly affected the energy bandgap by lowering it from 3.2 eV to 2.76 eV. Doping enhanced the mobility of charge carriers and eased the process of filament formation by suppressing its randomness between electrodes under the applied electric field. Furthermore, metal–non-metal-doped TiO₂ thin film exhibited less switching current and improved non-linearity by controlling the surface defects.

Interface-Modulated Resistive Switching in Mo-Irradiated ReS2 for Neuromorphic Computing

Coupling charge impurity scattering effects and charge-carrier modulation by doping can offer intriguing opportunities for atomic-level control of resistive switching (RS). Nonetheless, such effects have remained unexplored for memristive applications based on 2D materials. Here a facile approach is reported to transform an RS-inactive rhenium disulfide (ReS₂ ) into an effective switching material through interfacial modulation induced by molybdenum-irradiation (Mo-i) doping. Using ReS₂ as a model system, this study unveils a unique RS mechanism based on the formation/dissolution of metallic β-ReO₂ filament across the defective ReS₂ interface during the set/reset process. Through simple interfacial modulation, ReS₂ of various thicknesses are switchable by modulating the Mo-irradiation period. Besides, the Mo-irradiated ReS₂ (Mo-ReS₂ ) memristor further exhibits a bipolar non-volatile switching ratio of nearly two orders of magnitude, programmable multilevel resistance states, and long-term synaptic plasticity. Additionally, the fabricated device can achieve a high MNIST learning accuracy of 91% under a non-identical pulse train. The study's findings demonstrate the potential for modulating RS in RS-inactive 2D materials via the unique doping-induced charged impurity scattering property.

Novel charm of 2D materials engineering in memristor: when electronics encounter layered morphology

The family of two-dimensional (2D) materials composed of atomically thin layers connected via van der Waals interactions has attracted much curiosity due to a variety of intriguing physical, optical, and electrical characteristics. The significance of analyzing statistics on electrical devices and circuits based on 2D materials is seldom underestimated. Certain requirements must be met to deliver scientific knowledge that is beneficial in the field of 2D electronics: synthesis and fabrication must occur at the wafer level, variations in morphology and lattice alterations must be visible and statistically verified, and device dimensions must be appropriate. The authors discussed the most recent significant concerns of 2D materials in the provided prose and attempted to highlight the prerequisites for synthesis, yield, and mechanism behind device-to-device variability, reliability, and durability benchmarking under memristors characteristics; they also indexed some useful approaches that have already been reported to be advantageous in large-scale production. Commercial applications, on the other hand, will necessitate further effort.

Switching-behavior improvement in HfO2/ZnO bilayer memory devices by tailoring of interfacial and microstructural characteristics

We investigated the effect of top contact interface and microstructural characteristics of the insulating layers on resistive switching behaviors by fabricating and characterizing the HfO₂/ZnO bilayer heterostructures. Different thickness of ZnO underlying layer and different deposition temperatures of the upper HfO₂layer were designed to analyze the intrinsic contribution of the crystalline microstructure of the insulating bilayer. Pt and Ti top electrodes were used to demonstrate the extrinsic contribution of the interface configuration. It was observed that all devices show bipolar RS characteristics. Unlike the device composed of Pt/HfO₂/ZnO/Pt that exhibit an abrupt switching, a gradually continuous switching in the reset process was identified in the device composed of Ti/HfO₂/ZnO/Pt. Interfacial charge migration process/characteristic plays a key role in the RS process as well as its conduction mechanism. The RS performance of the former is significantly better than that of the latter, including much lower reset voltage, two orders of magnitude larger OFF/ON ratio and HRS resistance. In addition, as compared to the intrinsic contribution arising from the microstructure of the HfO₂/ZnO bilayer to the RS performances and current transport mechanism, the extrinsic effect contributed from the electrode characteristics (and its interface) is dominant.

Metal-containing organic compounds for memory and data storage applications

With the upcoming trend of Big Data era, some new types of memory technologies have emerged as substitutes for the traditional Si-based semiconductor memory devices, which are encountering severe scaling down technical obstacles. In particular, the resistance random access memory (RRAM) and magnetic random access memory (MRAM) hold great promise for the in-memory computing, which are regarded as the optimal strategy and pathway to solve the von Neumann bottleneck by high-throughput in situ data processing. As far as the active materials in RRAM and MRAM are concerned, organic semiconducting materials have shown increasing application perspectives in memory devices due to their rich structural diversity and solution processability. With the introduction of metal elements into the backbone of molecules, some new properties and phenomena will emerge accordingly. Consequently, the RRAM and MRAM devices based on metal-containing organic compounds (including the small molecular metal complexes, metallopolymers, metal-organic frameworks (MOFs) and organic-inorganic-hybrid perovskites (OIHPs)) have been widely explored and attracted intense attention. In this review, we highlight the fundamentals of RRAM and MRAM, as well as the research progress of the applications of metal-containing organic compounds in both RRAM and MRAM. Finally, we discuss the challenges and future directions for the research of organic RRAM and MRAM.

Tunable dual-channel slow light in a graphene grating plasmonic waveguide

We propose a plasmonic waveguide comprising a single-layer graphene, a silica dielectric layer, and a silicon grating substrate to realize dual-channel slow surface plasmon polaritons. The dual-channel results from the introduction of two kinds of periodic structures with defects in the waveguide. According to the Bragg equation, we match the appropriate structure parameters to ensure the slow light dual-channel working around λ₁=9369.1nm (32 THz) and λ₂=7138.2nm (42 THz). The influence of the structure parameters on the slow light effect is discussed, and the largest value of the normalized delay bandwidth product (NDBP) is up to 7.38. Then, by shifting the gate voltage, obvious linear blueshift of the dual-channel is achieved. In this process, the slow light performance of the dual-channel exhibits good stability, and the average values of the NDBP are 4.5 and 4.4. Due to the flexible tunability, the waveguide may pave the way for the design of slow light devices.

Contact Engineering Approach to Improve the Linearity of Multilevel Memristive Devices

Physical mechanisms underlying the multilevel resistive tuning over seven orders of magnitude in structures based on TiO₂/Al₂O₃ bilayers, sandwiched between platinum electrodes, are responsible for the nonlinear dependence of the conductivity of intermediate resistance states on the writing voltage. To improve the linearity of the electric-field resistance tuning, we apply a contact engineering approach. For this purpose, platinum top electrodes were replaced with aluminum and copper ones to induce the oxygen-related electrochemical reactions at the interface with the Al₂O₃ switching layer of the structures. Based on experimental results, it was found that electrode material substitution provokes modification of the physical mechanism behind the resistive switching in TiO₂/Al₂O₃ bilayers. In the case of aluminum electrodes, a memory window has been narrowed down to three orders of magnitude, while the linearity of resistance tuning was improved. For copper electrodes, a combination of effects related to metal ion diffusion with oxygen vacancies driven resistive switching was responsible for a rapid relaxation of intermediate resistance states in TiO₂/Al₂O₃ bilayers.

First-principles study of bipolar resistive memories based on monolayerα-GeTe

In this work, the electrical properties of monolayerα-GeTe (MLα-GeTe) based on first-principles were studied, in which armchairα-GeTe shows an ohmic current-voltage relationship and zigzagα-GeTe shows an obvious nonlinear current. The potential distribution and band structure explain the mechanism for the anisotropy and nonlinearity. Then, based on calculation of the binding energy and Mulliken population, eight interface structures between graphene (GR) and MLα-GeTe were constructed, in which GC3 and TC3 were found to be relatively stable. Next, GR/MLα-GeTe/GR was established based on the two interfaces (GC3 and TC3). The current-voltage (IV) characteristics were calculated to show that the device has bipolar resistance characteristics, suitable set and reset voltages and a high window value (10⁴). Further analysis of electron density inferred that the resistance mechanism was based on the drift of Te vacancies forming conductive filaments. And the performance of GR/MLα-GeTe/GR was found to be improved by the creation of Te vacancies. This work indicates that GR/MLα-GeTe/GR has the potential to be used to build resistive random access memory (RRAM) with good performance and may be instructive and valuable for the manufacture and application of RRAM.

Highly Efficient and Wide Range Humidity Response of Biocompatible Egg White Thin Film

Biopolymers are a solution to solve the increasing problems caused by the advances and revolution in the electronic industry owing to the use of hazardous chemicals. In this work, we have used egg white (EW) as the low-cost functional layer of a biocompatible humidity sensor and deposited it on gold (Au) interdigitated electrodes (IDEs) patterned through the state-of-the-art fabrication technology of thermal vacuum evaporation. The presence of hydrophilic proteins inside the thin film of EW makes it an attractive candidate for sensing humidity. Usually, the dependence of the percentage of relative humidity (%RH) on the reliability of measurement setup is overlooked for impedimetric humidity sensors but we have used a modified experimental setup to enhance the uniformity of the obtained results. The characteristics of our device include almost linear response with a quick response time (1.2 s) and fast recovery time (1.7 s). High sensitivity of 50 kΩ/%RH was achieved in the desirable detection range of 10–85%RH. The device size was intentionally kept small for its potential integration in a marketable chip. Results for the response of our fabricated sensor for dry and wet fingertips, along with determining the rate of breathing through the mouth, are part of this study, making it a potential device for health monitoring.

Mobility Extraction in 2D Transition Metal Dichalcogenide Devices-Avoiding Contact Resistance Implicated Overestimation

Schottky barrier (SB) transistors operate distinctly different from conventional metal-oxide semiconductor field-effect transistors, in a unique way that the gate impacts the carrier injection from the metal source/drain contacts into the channel region. While it has been long recognized that this can have severe implications for device characteristics in the subthreshold region, impacts of contact gating of SB in the on-state of the devices, which affects evaluation of intrinsic channel properties, have been yet comprehensively studied. Due to the fact that contact resistance (R_C ) is always gate-dependent in a typical back-gated device structure, the traditional approach of deriving field-effect mobility from the maximum transconductance (g_m ) is in principle not correct and can even overestimate the mobility. In addition, an exhibition of two different threshold voltages for the channel and the contact region leads to another layer of complexity in determining the true carrier concentration calculated from Q = C_OX * (V_G -V_TH ). Through a detailed experimental analysis, the effect of different effective oxide thicknesses, distinct SB heights, and doping-induced reductions in the SB width are carefully evaluated to gain a better understanding of their impact on important device metrics.

Interface-Driven Multifunctionality in Two-Dimensional TiO2 Nanosheet/Poly(Dimercaptothiadiazole-Triazine) Hybrid Resistive Random Access Memory Device

Interface-driven multifunctional facets are gearing up in the field of science and technology. Here, we present the interface-activated resistive switching (RS), negative differential resistance, diode behavior, and ultraviolet (UV) light sensing in nanosheet-based hybrid devices. A hybrid device i.e., titanium dioxide nanosheet (TiO₂-NS)/poly(dimercaptothiadiazole-triazine)[Poly(DMcT-CC)] is fabricated by spin coating Poly(DMcT-CC) polymer on hydrothermally as-grown TiO₂-NS. The pristine devices of both materials show either small or no magnitude of RS, but the hybrid device shows highly enhanced RS of nearly four orders due to the formation of a p-n junction at the NS/polymer interface. The resistive random access memory feature appears to be more prominent in the hybrid device i.e., high and low current states are found to be stable in repetitive cycles since the interface acts as a trapping center for the carriers. The UV sensing ability of the hybrid device has been demonstrated by a threefold increment in a current at 60 mV. The impedance spectroscopy has been employed to show that the multifunctional features are directly associated to the NS/polymer interface, which deduce that the manipulation of such interfaces can pave the way for developing the hybrid structures.