Oxygenated amorphous carbon for resistive memory applications

Experiment-Driven Atomistic Materials Modeling: A Case Study Combining X-Ray Photoelectron Spectroscopy and Machine Learning Potentials to Infer the Structure of Oxygen-Rich Amorphous Carbon

An important yet challenging aspect of atomistic materials modeling is reconciling experimental and computational results. Conventional approaches involve generating numerous configurations through molecular dynamics or Monte Carlo structure optimization and selecting the one with the closest match to experiment. However, this inefficient process is not guaranteed to succeed. We introduce a general method to combine atomistic machine learning (ML) with experimental observables that produces atomistic structures compatible with experiment by design. We use this approach in combination with grand-canonical Monte Carlo within a modified Hamiltonian formalism, to generate configurations that agree with experimental data and are chemically sound (low in energy). We apply our approach to understand the atomistic structure of oxygenated amorphous carbon (a-COx), an intriguing carbon-based material, to answer the question of how much oxygen can be added to carbon before it fully decomposes into CO and CO2. Utilizing an ML-based X-ray photoelectron spectroscopy (XPS) model trained from GW and density functional theory (DFT) data, in conjunction with an ML interatomic potential, we identify a-COx structures compliant with experimental XPS predictions that are also energetically favorable with respect to DFT. Employing a network analysis, we accurately deconvolve the XPS spectrum into motif contributions, both revealing the inaccuracies inherent to experimental XPS interpretation and granting us atomistic insight into the structure of a-COx. This method generalizes to multiple experimental observables and allows for the elucidation of the atomistic structure of materials directly from experimental data, thereby enabling experiment-driven materials modeling with a degree of realism previously out of reach.

A carbon conductive filament-induced robust resistance switching behavior for brain-inspired computing

Memristors have revolutionized the path forward for brain-inspired computing. However, the instability of the nucleation process of conductive filaments based on active metal electrodes leads to the discrete distribution of switching parameters, which hinders the realization of high-performance and low-power devices for neuromorphic computing. In response, a carbon conductive filament-induced robust memristor is demonstrated with variation coefficients as low as 3.9%/-1.18%, a threshold power as low as 10-9 W, and 3 × 106 s retention and 107 cycle endurance behaviors can be maintained. The recognition accuracy for Modified National Institute of Standards and Technology (MNIST) handwriting is as high as 96.87%, attributed to the high linearity of the iterative updating of synaptic weights. The demodulation and storage functions of the American Standard Code for Information Interchange (ASCII) are demonstrated by programmable pulse modulation. Notably, the transmission electron microscopy (TEM) images allow the observation of carbon conductive filament paths formed in the low resistance state. First-principles calculations analyze the energetics of defects involved in the diffusion of carbon atoms into MoTe2 films. This work presents a novel guideline for studying memristor-based neuromorphic computing.

Regulation of high value-added carbon nanomaterials by DC arc plasma using graphite anodes from spent lithium-ion batteries

With the extensive use of lithium-ion batteries (LIBs), neglecting to recycle graphite anodes from LIBs leads to environmental pollution and the waste of graphite resources. Thus, developing an efficient and environment-protecting approach to reusing spent graphite anodes is necessary. Here, high value-added graphene sheets (GS), carbon nanohorns (CNHs), fluorine-doped CNHs (F-CNHs), and amorphous carbon nanoballs (ACNs) were prepared from spent graphite anodes of LIBs via DC arc plasma. In order to control the conversion of spent graphite anodes into various carbon nanomaterials, the growth mechanism of carbon nanomaterials is investigated by quenching rate. Benefiting from the extremely high quenching rates (>1.8 × 106 K/s) produced by DC arc plasma, the particle size of the prepared ACNs and CNHs is small and evenly distributed. The CNHs show a "dahlia-like" structure, and the number of graphene layers is only 3-8. Furthermore, the structural transformation mechanism of carbon nanomaterials is researched by deposition temperature. The ACNs, few-layer GS, and CNHs produced by the high quenching rates are unstable and prone to structural transformation. When these carbon nanomaterials are deposited on the cathode surface and cathode holder, the ACNs, "dahlia-like" CNHs, and GS undergo processes of fusing and overlaying at high temperatures, respectively, resulting in the agglomeration and increased particle size of ACNs and "seed-like" CNHs. Meanwhile, the GS is bent and converted into carbon nanocages (CBCs). Overall, the carbon nanomaterials prepared using spent anodes from LIBs by arc plasma are a facile, environment-friendly, and economical strategy to achieve high value-added utilization of the graphite.

Wafer-scale synthesis of two-dimensional ultrathin films

Two-dimensional (2D) materials, consisting of atomically thin layered crystals, have attracted tremendous interest due to their outstanding intrinsic properties and diverse applications in electronics, optoelectronics, and catalysis. The large-scale growth of high-quality ultrathin 2D films and their utilization in the facile fabrication of devices, easily adoptable in industrial applications, have been extensively sought after during the last decade; however, it remains a challenge to achieve these goals. Herein, we introduce three key concepts: (i) the microwave assisted quick (∼1 min) synthesis of wafer-scale (6-inch) anisotropic conducting ultrathin (∼1 nm) amorphous carbon and 2D semiconducting metal chalcogenide atomically thin films, (ii) a polymer-assisted deposition process for the synthesis of wafer-scale (6-inch) 2D metal chalcogenide and pyrolyzed carbon thin films, and (iii) the surface diffusion and epitaxial self-planarization induced synthesis of wafer-scale (2-inch) single crystal 2D binary and large-grain 2D ferromagnetic ternary metal chalcogenide thin films. The proposed synthesis concepts can pave a new way for the manufacture of wafer-scale high quality 2D ultrathin films and their utilization in the facile fabrication of devices.

Amorphous Carbon Films for Electronic Applications

While various crystalline carbon allotropes, including graphene, have been actively investigated, amorphous carbon (a-C) thin films have received relatively little attention. The a-C is a disordered form of carbon bonding with a broad range of the CC bond length and bond angle. Although accurate structural analysis and theoretical approaches are still insufficient, reproducible structure-property relationships have been accumulated. As the a-C thin film is now adapted as a hardmask in the semiconductor industry and new properties are reported continuously, expectations are growing that it can be practically used as active materials beyond as a simple sacrificial layer. In this perspective review article, after a brief introduction to the synthesis and properties of the a-C thin films, their potential practical applications are proposed, including hardmasks, extreme ultraviolet (EUV) pellicles, diffusion barriers, deformable electrodes and interconnects, sensors, active layers, electrodes for energy, micro-supercapacitors, batteries, nanogenerators, electromagnetic interference (EMI) shielding, and nanomembranes. The article ends with a discussion on the technological challenges in a-C thin films.

Accurate Computational Prediction of Core-Electron Binding Energies in Carbon-Based Materials: A Machine-Learning Model Combining Density-Functional Theory and GW

We present a quantitatively accurate machine-learning (ML) model for the computational prediction of core-electron binding energies, from which X-ray photoelectron spectroscopy (XPS) spectra can be readily obtained. Our model combines density functional theory (DFT) with GW and uses kernel ridge regression for the ML predictions. We apply the new approach to disordered materials and small molecules containing carbon, hydrogen, and oxygen and obtain qualitative and quantitative agreement with experiment, resolving spectral features within 0.1 eV of reference experimental spectra. The method only requires the user to provide a structural model for the material under study to obtain an XPS prediction within seconds. Our new tool is freely available online through the XPS Prediction Server.

Flexible Memory Device Composed of Metal-Oxide and Two-Dimensional Material (SnO2/WTe2) Exhibiting Stable Resistive Switching

Two-terminal, non-volatile memory devices are the fundamental building blocks of memory-storage devices to store the required information, but their lack of flexibility limits their potential for biological applications. After the discovery of two-dimensional (2D) materials, flexible memory devices are easy to build, because of their flexible nature. Here, we report on our flexible resistive-switching devices, composed of a bilayer tin-oxide/tungsten-ditelluride (SnO2/WTe2) heterostructure sandwiched between Ag (top) and Au (bottom) metal electrodes over a flexible PET substrate. The Ag/SnO2/WTe2/Au flexible devices exhibited highly stable resistive switching along with an excellent retention time. Triggering the device from a high-resistance state (HRS) to a low-resistance state (LRS) is attributed to Ag filament formation because of its diffusion. The conductive filament begins its development from the anode to the cathode, contrary to the formal electrochemical metallization theory. The bilayer structure of SnO2/WTe2 improved the endurance of the devices and reduced the switching voltage by up to 0.2 V compared to the single SnO2 stacked devices. These flexible and low-power-consumption features may lead to the construction of a wearable memory device for data-storage purposes.

Standards for the Characterization of Endurance in Resistive Switching Devices

Resistive switching (RS) devices are emerging electronic components that could have applications in multiple types of integrated circuits, including electronic memories, true random number generators, radiofrequency switches, neuromorphic vision sensors, and artificial neural networks. The main factor hindering the massive employment of RS devices in commercial circuits is related to variability and reliability issues, which are usually evaluated through switching endurance tests. However, we note that most studies that claimed high endurances >10⁶ cycles were based on resistance versus cycle plots that contain very few data points (in many cases even <20), and which are collected in only one device. We recommend not to use such a characterization method because it is highly inaccurate and unreliable (i.e., it cannot reliably demonstrate that the device effectively switches in every cycle and it ignores cycle-to-cycle and device-to-device variability). This has created a blurry vision of the real performance of RS devices and in many cases has exaggerated their potential. This article proposes and describes a method for the correct characterization of switching endurance in RS devices; this method aims to construct endurance plots showing one data point per cycle and resistive state and combine data from multiple devices. Adopting this recommended method should result in more reliable literature in the field of RS technologies, which should accelerate their integration in commercial products.

Enhanced Vapor Transmission Barrier Properties via Silicon-Incorporated Diamond-Like Carbon Coating

In this study, we describe reducing the moisture vapor transmission through a commercial polymer bag material using a silicon-incorporated diamond-like carbon (Si-DLC) coating that was deposited using plasma-enhanced chemical vapor deposition. The structure of the Si-DLC coating was analyzed using scanning electron microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy, energy-dispersive X-ray spectroscopy, selective area electron diffraction, and electron energy loss spectroscopy. Moisture vapor transmission rate (MVTR) testing was used to understand the moisture transmission barrier properties of Si-DLC-coated polymer bag material; the MVTR values decreased from 10.10 g/m² 24 h for the as-received polymer bag material to 6.31 g/m² 24 h for the Si-DLC-coated polymer bag material. Water stability tests were conducted to understand the resistance of the Si-DLC coatings toward moisture; the results confirmed the stability of Si-DLC coatings in contact with water up to 100 °C for 4 h. A peel-off adhesion test using scotch tape indicated that the good adhesion of the Si-DLC film to the substrate was preserved in contact with water up to 100 °C for 4 h.

From Memristive Materials to Neural Networks

The information technologies have been increasing exponentially following Moore's law over the past decades. This has fundamentally changed the ways of work and life. However, further improving data process efficiency is facing great challenges because of physical and architectural limitations. More powerful computational methodologies are crucial to fulfill the technology gap in the post-Moore's law period. The memristor exhibits promising prospects in information storage, high-performance computing, and artificial intelligence. Since the memristor was theoretically predicted by L. O. Chua in 1971 and experimentally confirmed by HP Laboratories in 2008, it has attracted great attention from worldwide researchers. The intrinsic properties of memristors, such as simple structure, low power consumption, compatibility with the complementary metal oxide-semiconductor (CMOS) process, and dual functionalities of the data storage and computation, demonstrate great prospects in many applications. In this review, we cover the memristor-relevant computing technologies, from basic materials to in-memory computing and future prospects. First, the materials and mechanisms in the memristor are discussed. Then, we present the development of the memristor in the domains of the synapse simulating, in-memory logic computing, deep neural networks (DNNs) and spiking neural networks (SNNs). Finally, the existent technology challenges and outlook of the state-of-art applications are proposed.

Carbon resistive probe memory designed for ultra-high storage density

Probe-based storage memories are considered one of the most promising solutions to address the mass storage issues in the near future. However, data size arising from conventional probe memories is usually larger than probe size due to the thermal diffusion effect. To eliminate such thermal interference and make data dimension fully dominated by probe dimension, we proposed a concept of carbon-based resistive probe memory and developed a comprehensive computational model to predict its write, rewrite and readout performances governed by electro-thermal and mass concentration processes. The physical reality of such a theoretical model was demonstrated through the good agreement between the calculated and experimental measured threshold voltages for different layered thickness. The data bit of carbon-based resistive probe memory, considered as the sp² filament inside sp³ background, is formed completely underneath the tip edge due to the localized electric field induced here. This makes the bit size fully determined by the probe tip dimension and allows for the achievement of ultra-high density using an ultra-small probe tip with low energy consumption. Such a conductive filament can be also rewritten back to its pristine sp³ state at relatively high temperature (~250 °C) and detected by sensing the device reading contrast (~1). The designed carbon-based resistive probe memory can retain its bit completeness even if we reduce the bit pitch to 28 nm for a probe size of 25 nm, exhibiting a superior immunity to thermal cross-talk effect. It, however, induces strong readout cross-talk, which is revealed from the resistance image of the multiple bit pattern. This adversely reduces the achievable recording density due to the required large bit pitch, which can be alleviated using either a very sharp tip apex or the optical readout scheme.

Controlling Cu Migration on Resistive Switching, Artificial Synapse, and Glucose/Saliva Detection by Using an Optimized AlO x Interfacial Layer in a-CO x -Based Conductive Bridge Random Access Memory

The Cu migration is controlled by using an optimized AlO _x interfacial layer, and effects on resistive switching performance, artificial synapse, and human saliva detection in an amorphous-oxygenated-carbon (a-CO _x )-based CBRAM platform have been investigated for the first time. The 4 nm-thick AlO _x layer in the Cu/AlO _x /a-CO _x /TiN _x O _y /TiN structure shows consecutive >2000 DC switching, tight distribution of SET/RESET voltages, a long program/erase (P/E) endurance of >10⁹ cycles at a low operation current of 300 μA, and artificial synaptic characteristics under a small pulse width of 100 ns. After a P/E endurance of >10⁸ cycles, the Cu migration is observed by both ex situ high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy mapping images. Furthermore, the optimized Cu/AlO _x /a-CO _x /TiN _x O _y /TiN CBRAM detects glucose with a low concentration of 1 pM, and real-time measurement of human saliva with a small sample volume of 1 μL is also detected repeatedly in vitro. This is owing to oxidation-reduction of Cu electrode, and the switching mechanism is explored. Therefore, this CBRAM device is beneficial for future artificial intelligence application.

Fabrication of Foldable Metal Interconnections by Hybridizing with Amorphous Carbon Ultrathin Anisotropic Conductive Film

With the advent of foldable electronics, it is necessary to develop a technology ensuring foldability when the circuit lines are placed on the topmost substrate rather than in the neutral plane used in the present industry. Considering the potential technological impacts, conversion of the conventional printed circuit boards to foldable ones is most desirable to achieve the topmost circuitry. This study realizes this unconventional conversion concept by coating an ultrathin anisotropic conductive film (UACF) on a printed metal circuit board. This study presents rapid large-area synthesis of hydrogenated amorphous carbon (a-C:H) thin films and their use as the UACF. Since the synthesized a-C:H thin film has electrical transparency, the metal/a-C:H hybrid board reflects the complexity of the underlying metal circuit board. The a-C:H thin film electrically connects the cracked area of the metal line; thus, the hybrid circuit board is foldable without resistance change during repeated folding cycles. The metal/UACF hybrid circuit board can be applied to the fabrication of various foldable electronic devices.

Electrochemical Oxidation Induced Multi-Level Memory in Carbon-Based Resistive Switching Devices

In this work, we report for the first time the electrochemical oxidation as a technique to improve the electrical performances of carbon-based resistive switching devices. The devices obtained through the anodic oxidation of carbon-structures possess superior electrical performances i.e. a 3-level memory behavior and an ON/OFF ratio two order of magnitude higher than the non-oxidized carbon-based devices. It is demonstrated that the chemical composition of the carbon structures (i.e. percentage of oxygen groups, sp² and sp³ carbon atoms) plays a key role in the improvement of the carbon-based devices. The electrochemical oxidation allows the possibility to control the oxidation degree, and therefore, to tailor the devices electrical performances. We demonstrated that the resistive switching behavior in the electrochemically oxidized devices is originated from the formation of conductive filament paths, which are built from the oxygen vacancies and structural defects of the anodic oxidized carbon materials. The novelty of this work relies on the anodic oxidation as a time- and cost-effective technique that can be employed for the engineering and improvement of the electrical performances of next generation carbon-based resistive switching devices.

Role of GO and r-GO in resistance switching behavior of bilayer TiO2 based RRAM

Graphene-based resistance random access memory devices (RRAMs) have shown promise as a suitable replacement for flash memories, owing to their fast switching speed, low programming voltage, better scalability and great reliability. Furthermore, recent research works have shown bi-layer RRAM devices exhibiting better performance along the same parameters, where titania is one of the most commonly used materials. In the present work, we have studied the resistance switching behavior in a bi-layer RRAM device structure of TiO₂ with graphene oxide (GO) and reduced graphene oxide (rGO). Switching mechanism in these devices has been investigated by detailed experimental characterization in conjunction with a finite element modeling (FEM) simulation. A dual conical conductive filament has been used in the present work, based on the modeling of the electroforming process carried out by FEM. It has been demonstrated that for the GO/TiO₂ based hybrid RRAM device structure, GO acts as an active filament formation layer, whereas in the rGO/TiO₂ bi-layer structure, rGO acts as a mere electrode.

Sensory gating in bilayer amorphous carbon memristors

Multi-state amorphous carbon-based memory devices have been developed that exhibit both bipolar and unipolar resistive switching behaviour. These modes of operation were implemented independently to access multiple resistance states, enabling higher memory density than conventional binary non-volatile memory technologies. The switching characteristics have been further utilised to study synaptic computational functions that could be implemented in artificial neural networks. Notably, paired-pulse inhibition (PPI) is observed at bio-realistic timescales (<100 ms). Devices displaying this rich synaptic behaviour could function as robust stand-alone synapse-inspired memory or be applied as filters for specialised neuromorphic circuits and sensors.

Zero-static power radio-frequency switches based on MoS2 atomristors

Recently, non-volatile resistance switching or memristor (equivalently, atomristor in atomic layers) effect was discovered in transitional metal dichalcogenides (TMD) vertical devices. Owing to the monolayer-thin transport and high crystalline quality, ON-state resistances below 10 Ω are achievable, making MoS₂ atomristors suitable as energy-efficient radio-frequency (RF) switches. MoS₂ RF switches afford zero-hold voltage, hence, zero-static power dissipation, overcoming the limitation of transistor and mechanical switches. Furthermore, MoS₂ switches are fully electronic and can be integrated on arbitrary substrates unlike phase-change RF switches. High-frequency results reveal that a key figure of merit, the cutoff frequency (f_c), is about 10 THz for sub-μm² switches with favorable scaling that can afford f_c above 100 THz for nanoscale devices, exceeding the performance of contemporary switches that suffer from an area-invariant scaling. These results indicate a new electronic application of TMDs as non-volatile switches for communication platforms, including mobile systems, low-power internet-of-things, and THz beam steering.

The wide application of wireless communications in various technologies calls for the development of robust yet compact radio-frequency switches. Here, Kim et al. utilize MoS₂ based non-volatile memristors to switch up to THz frequencies in sub µm² areas, whilst the switches consume zero-static energy.

Amorphization Optimization of Ge₂Sb₂Te₅ Media for Electrical Probe Memory Applications

Electrical probe memory using Ge₂Sb₂Te₅ media has been considered a promising candidate in the future archival storage market due to its potential for ultra-high density and long data retention time. However, most current research efforts have been devoted to the writing of crystalline bits using electrical probe memory while ignoring the viability of writing amorphous bits. Therefore, this paper proposes a physical, realistic, full three-dimensional model to optimize the practicable media stack by spatially and temporally calculating temperature distributions inside the active media during the writing of amorphous bits. It demonstrates the feasibility of using an optimized device that follows a Silicon/Titanium Nitride/Ge₂Sb₂Te₅/Diamond-Like Carbon design with appropriate electro-thermal properties and thickness to achieve ultra-high density, low energy consumption, and a high data rate without inducing excessive temperature. The ability to realize multi-bit recording and rewritability using the designed device is also proven, making it attractive and suitable for practicable applications.

Probing the Mechanism for Bipolar Resistive Switching in Annealed Graphene Oxide Thin Films

The bipolar resistive switching (BRS) between a metallic low resistance state (LRS) and an insulating high resistance state (HRS) is demonstrated for annealed graphene oxide (GO) thin film-based device structures with aluminum (Al) as one of the contact electrodes. An optimal switching of ∼10⁴ order is recorded for Al/GO (200 °C)/indium tin oxide (ITO) among the device structures in metal (M₂)/GO (T)/metal (M₁) configurations (M₁ = Al, Au, or ITO and M₂ = Au or Al), fabricated using GO (T)/metal (M₁), annealed at different temperatures, T = 100, 200, 300, and 400 °C. The initial Ohmic conduction for electronic transport and the presence of metal contents through GO thin films in the X-ray photoelectron spectroscopy support the physical evidence of Al filament formation between the two electrodes as imaged by the high-resolution transmission electron microscopy. The speculated mechanism for BRS in repeated voltage sweep cycles is attributed to the current triggered breaking of metal filaments because of the combined effect of Joule's heating and Peltier heat generation at LRS → HRS transition, and electric field induced migration of metal atoms, leading to the formation of metal filaments through the GO film at the HRS → LRS transition. The higher switching ratio exhibited in the current study could be translated to engineer simple and low-cost resistive memory devices.

Memristive effects in oxygenated amorphous carbon nanodevices

Computing with resistive-switching (memristive) memory devices has shown much recent progress and offers an attractive route to circumvent the von-Neumann bottleneck, i.e. the separation of processing and memory, which limits the performance of conventional computer architectures. Due to their good scalability and nanosecond switching speeds, carbon-based resistive-switching memory devices could play an important role in this respect. However, devices based on elemental carbon, such as tetrahedral amorphous carbon or ta-C, typically suffer from a low cycling endurance. A material that has proven to be capable of combining the advantages of elemental carbon-based memories with simple fabrication methods and good endurance performance for binary memory applications is oxygenated amorphous carbon, or a-CO _x . Here, we examine the memristive capabilities of nanoscale a-CO _x devices, in particular their ability to provide the multilevel and accumulation properties that underpin computing type applications. We show the successful operation of nanoscale a-CO _x memory cells for both the storage of multilevel states (here 3-level) and for the provision of an arithmetic accumulator. We implement a base-16, or hexadecimal, accumulator and show how such a device can carry out hexadecimal arithmetic and simultaneously store the computed result in the self-same a-CO _x cell, all using fast (sub-10 ns) and low-energy (sub-pJ) input pulses.

Atomristor: Nonvolatile Resistance Switching in Atomic Sheets of Transition Metal Dichalcogenides

Recently, two-dimensional (2D) atomic sheets have inspired new ideas in nanoscience including topologically protected charge transport,1,2 spatially separated excitons,3 and strongly anisotropic heat transport.4 Here, we report the intriguing observation of stable nonvolatile resistance switching (NVRS) in single-layer atomic sheets sandwiched between metal electrodes. NVRS is observed in the prototypical semiconducting (MX₂, M = Mo, W; and X = S, Se) transitional metal dichalcogenides (TMDs),5 which alludes to the universality of this phenomenon in TMD monolayers and offers forming-free switching. This observation of NVRS phenomenon, widely attributed to ionic diffusion, filament, and interfacial redox in bulk oxides and electrolytes,6-9 inspires new studies on defects, ion transport, and energetics at the sharp interfaces between atomically thin sheets and conducting electrodes. Our findings overturn the contemporary thinking that nonvolatile switching is not scalable to subnanometre owing to leakage currents.10 Emerging device concepts in nonvolatile flexible memory fabrics, and brain-inspired (neuromorphic) computing could benefit substantially from the wide 2D materials design space. A new major application, zero-static power radio frequency (RF) switching, is demonstrated with a monolayer switch operating to 50 GHz.

Monitoring the transformation of aliphatic and fullerene molecules by high-energy electrons using surface-enhanced Raman spectroscopy

We report on using 100 keV electrons to obtain amorphous carbon from aliphatic and fullerene molecules, and study this process by monitoring their Raman signal. In this regard, we use self-assembled monolayers of gold nanoparticles to provide high electromagnetic field enhancement, which allows the detection of the Raman signal from even nanometer-thick layers of analyte. Our results show different dynamics in the amorphization process of the two molecules, although both show suppression of their original vibrational resonances even at low exposure doses. We have also used atomic-force microscopy to evaluate the sensitivity of the C₆₀ molecules to electron beams in forming networks of amorphized molecules that are less soluble in the development process. This method allows precise patterning possibilities as well as in situ functionalization of carbonaceous thin films in the perspective of using in electronic device applications.

Multilevel Ultrafast Flexible Nanoscale Nonvolatile Hybrid Graphene Oxide-Titanium Oxide Memories

Graphene oxide (GO) resistive memories offer the promise of low-cost environmentally sustainable fabrication, high mechanical flexibility and high optical transparency, making them ideally suited to future flexible and transparent electronics applications. However, the dimensional and temporal scalability of GO memories, i.e., how small they can be made and how fast they can be switched, is an area that has received scant attention. Moreover, a plethora of GO resistive switching characteristics and mechanisms has been reported in the literature, sometimes leading to a confusing and conflicting picture. Consequently, the potential for graphene oxide to deliver high-performance memories operating on nanometer length and nanosecond time scales is currently unknown. Here we address such shortcomings, presenting not only the smallest (50 nm), fastest (sub-5 ns), thinnest (8 nm) GO-based memory devices produced to date, but also demonstrate that our approach provides easily accessible multilevel (4-level, 2-bit per cell) storage capabilities along with excellent endurance and retention performance-all on both rigid and flexible substrates. Via comprehensive experimental characterizations backed-up by detailed atomistic simulations, we also show that the resistive switching mechanism in our Pt/GO/Ti/Pt devices is driven by redox reactions in the interfacial region between the top (Ti) electrode and the GO layer.

Flexible Multistate Data Storage Devices Fabricated Using Natural Lignin at Room Temperature

The growing interest in bioinspired and sustainable electronics has induced research on biocompatible and biodegradable materials. However, conventional electronic devices have been restricted due to their nonbiodegradable and sometimes harmful and toxic materials, which can even cause environmental issues. Here, we report a resistive switching random access memory (ReRAM) device based on lignin, which is a biodegradable waste product of the paper industry. The active layer of the device can be easily formed using a simple solution process on a plastic substrate. The memory devices show stable bipolar resistive switching behavior with good endurance and retention. Appropriate control of the maximum reset voltage and compliance current can yield multibit data storage capability with at least four resistance states, which can be exploited to realize a high-density memory device. The resistive switching mechanism may be a result of formation and rupture of carbon-rich filaments. These results suggest that lignin is a promising candidate material for an inexpensive and environmentally benign ReRAM device. We believe that this study can initiate a new route toward development of biocompatible and flexible electronics.

Resistive switching of alkanethiolated nanoparticle monolayers patterned by electron-beam exposure

Nanoscale structures are fabricated by the direct electron-beam exposure of 10 nm gold nanoparticle monolayers and development in an emulsion. We observe resistive switching in these structures of up to five orders of magnitude.