Abstract
The fabrication of integrated circuits (ICs) employing two-dimensional (2D) materials is a major goal of semiconductor industry for the next decade, as it may allow the extension of the ...Moore’s law, aids in in-memory computing and enables the fabrication of advanced devices beyond conventional complementary metal-oxide-semiconductor (CMOS) technology. However, most circuital demonstrations so far utilizing 2D materials employ methods such as mechanical exfoliation that are not up-scalable for wafer-level fabrication, and their application could achieve only simple functionalities such as logic gates. Here, we present the fabrication of a crossbar array of memristors using multilayer hexagonal boron nitride (h-BN) as dielectric, that exhibit analog bipolar resistive switching in >96% of devices, which is ideal for the implementation of multi-state memory element in most of the neural networks, edge computing and machine learning applications. Instead of only using this memristive crossbar array to solve a simple logical problem, here we go a step beyond and present the combination of this h-BN crossbar array with CMOS circuitry to implement extreme learning machine (ELM) algorithm. The CMOS circuit is used to design the encoder unit, and a h-BN crossbar array of 2D hexagonal boron nitride (h-BN) based memristors is used to implement the decoder functionality. The proposed hybrid architecture is demonstrated for complex audio, image, and other non-linear classification tasks on real-time datasets.
The electroplating of copper layers on acrylonitrile–butadiene–styrene (ABS) polymer surfaces is a common need in industrial applications. The development of new eco-friendly techniques to promote ...ABS–copper adhesion is crucial due to the harsh and expensive chemicals used in the existing processes. The initial path involves establishing a better understanding on chemistry-dependent ABS–copper adhesion mechanisms. By formulating the material with more functional groups, the adhesion between ABS and the coated copper layer was characterized through a multiscale approach. At the atomic scale, we performed ab initio density functional theory simulations to obtain the variations in the adsorption energy. At the nano and micro scales, we adopted atomic force microscopy to measure the adhesion forces on the bulk polymer surfaces. At the macro scale, we compared these adhesion results with both 90-degree peeling tests and finite element model analyses. This study presents the first comprehensive approach for bridging information gaps across the scales (from nano to macro) with computational and experimental data, facilitating the design of formulated ABS additives.
Heat transfer processes in micro- and nanoscale devices have become more and more important during the last decades. Scanning thermal microscopy (SThM) is an atomic force microscopy (AFM) based ...method for analyzing local thermal conductivities of layers with thicknesses in the range of several nm to µm. In this work, we investigate ultrathin films of hexagonal boron nitride (h-BN), copper iodide in zincblende structure (γ-CuI) and some test sample structures fabricated of silicon (Si) and silicon dioxide (SiO
) using SThM. Specifically, we analyze and discuss the influence of the sample topography, the touching angle between probe tip and sample, and the probe tip temperature on the acquired results. In essence, our findings indicate that SThM measurements include artefacts that are not associated with the thermal properties of the film under investigation. We discuss possible ways of influence, as well as the magnitudes involved. Furthermore, we suggest necessary measuring conditions that make qualitative SThM measurements of ultrathin films of h-BN with thicknesses at or below 23 nm possible.
Memristive electronic synapses are attractive to construct artificial neural networks (ANNs) for neuromorphic computing systems, owing to their excellent electronic performance, high integration ...density, and low cost. However, the necessity of initializing their conductance through a forming process requires additional peripheral hardware and complex programming algorithms. Herein, the first fabrication of memristors that are initially in low‐resistive state (LRS) is reported, which exhibit homogenous initial resistance and switching voltages. When used as electronic synapses in a neuromorphic system to classify images from the CIFAR‐10 dataset (Canadian Institute For Advanced Research), the memristors offer ×1.83 better throughput per area and consume ×0.85 less energy than standard memristors (i.e., with the necessity of forming), which stems from ≈63% better density and ≈17% faster operation. It is demonstrated in the results that tuning the local properties of materials embedded in memristive electronic synapses is an attractive strategy that can lead to an improved neuromorphic performance at the system level.
Herein, discontinuous TiO2 films are used to develop memristors that are initially in low‐resistive state, and which initial resistance is highly homogeneous. Artificial neural networks using such devices offer ×1.83 better throughput per area and consume ×0.85 less energy than those using standard memristors (i.e., with the necessity of forming), which stems from ≈63% better density and ≈17% faster operation.
Some memristors with metal/insulator/metal (MIM) structure have exhibited random telegraph noise (RTN) current signals, which makes them ideal to build true random number generators (TRNG) for ...advanced data encryption. However, there is still no clear guide on how essential manufacturing parameters like materials selection, thicknesses, deposition methods, and device lateral size can influence the quality of the RTN signal. In this paper, an exhaustive statistical analysis on the quality of the RTN signals produced by different MIM‐like memristors is reported, and straightforward guidelines for the fabrication of memristors with enhanced RTN performance are presented, which are: i) Ni and Ti electrodes show better RTN than Au electrodes, ii) the 50 μm × 50 μm devices show better RTN than the 5 μm × 5 μm ones, iii) TiO2 shows better RTN than HfO2 and Al2O3, iv) sputtered‐oxides show better RTN than ALD‐oxides, and v) 10 nm thick oxides show better RTN than 5 nm thick oxides. The RTN signals recorded have been used as entropy sources in high‐throughput TRNG circuits, which have passed the randomness tests of the National Institute of Standards and Technology. The work can serve as a useful guide for materials scientists and electronic engineers when fabricating MIM‐like memristors for RTN applications.
Manufacturing parameters such as type of metallic electrodes, type of insulator, thickness of the insulator, deposition methods, lateral size have an important influence on the electrical properties of memristors. In this paper, the effect of each parameter on the quality and stability random telegraph noise signals driven by memristors is discussed, and the devices showing best the performance to emulate true random generators for encrypted code generation are used.
Two-dimensional (2D) materials may be used to fabricate electronic devices and circuits with enhanced electronic properties. Memristors made of hexagonal boron nitride (h-BN) have shown potential for ...many applications; however, in most cases they are tested using the current limitation tool of the semiconductor parameter analyzer, which does not match real circuit implementations and produces current overshoots. In this article, we present the first all-2D materials-based one-transistor- one-memristor (1T1M) cells exhibiting threshold-type RS. We connect 4 μm2 molybdenum disulfide (MoS2) transistors in series with 0.3 μm2 h-BN memristors, leading 1T1M cells able to self-limiting the current. The switching is observed at low voltages below 1 V for >1000 cycles. Our results are a step forward towards the use of 2D materials in electronic devices and circuits.
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•All-2D based one-transistor-one-memristor cells are presented, in which transistor works as current limitation element.•Reproducible threshold resistive switching for >1000 cycles is obtained.•The memristors switch at low voltages compatible with the CMOS technology, and without the need of forming.
2D materials have many outstanding properties that make them attractive for the fabrication of electronic devices, such as high conductivity, flexibility, and transparency. However, integrating 2D ...materials in commercial devices and circuits is challenging because their structure and properties can be damaged during the fabrication process. Recent studies have demonstrated that standard metal deposition techniques (like electron beam evaporation and sputtering) significantly damage the atomic structure of 2D materials. Here it is shown that the deposition of metal via inkjet printing technology does not produce any observable damage in the atomic structure of ultrathin 2D materials, and it can keep a sharp interface. These conclusions are supported by abundant data obtained via atomistic simulations, transmission electron microscopy, nanochemical metrology, and device characterization in a probe station. The results are important for the understanding of inkjet printing technology applied to 2D materials, and they could contribute to the better design and optimization of electronic devices and circuits.
The evaporation of Au or the sputtering of Cr on 2D layered hexagonal boron nitride (h‐BN) produces local atomic defects in its structure, specially at its interfaces, which increases the leakage current across it. It is found that the deposition of metal on hexagonal boron nitride (h‐BN) using inkjet printing does not introduce any defect, and maintains its layered structure free of defects.
Advanced data encryption requires the use of true random number generators (TRNGs) to produce unpredictable sequences of bits. TRNG circuits with high degree of randomness and low power consumption ...may be fabricated by using the random telegraph noise (RTN) current signals produced by polarized metal/insulator/metal (MIM) devices as entropy source. However, the RTN signals produced by MIM devices made of traditional insulators, i.e., transition metal oxides like HfO2 and Al2O3, are not stable enough due to the formation and lateral expansion of defect clusters, resulting in undesired current fluctuations and the disappearance of the RTN effect. Here, the fabrication of highly stable TRNG circuits with low power consumption, high degree of randomness (even for a long string of 224 − 1 bits), and high throughput of 1 Mbit s−1 by using MIM devices made of multilayer hexagonal boron nitride (h‐BN) is shown. Their application is also demonstrated to produce one‐time passwords, which is ideal for the internet‐of‐everything. The superior stability of the h‐BN‐based TRNG is related to the presence of few‐atoms‐wide defects embedded within the layered and crystalline structure of the h‐BN stack, which produces a confinement effect that avoids their lateral expansion and results in stable operation.
The few‐atoms‐wide and amorphous native defects in multilayer hexagonal boron nitride (h‐BN) synthesized by chemical vapor deposition can drive out‐of‐plane random telegraph noise current signals that are more stable than those traditionally observed in transition metal oxides. The reason is that these defects are confined and completely surrounded by 2D layered and crystalline h‐BN. This allows fabrication of high‐performance true random number generators for advanced data encryption.
Resistive switching (RS) devices are being studied exhaustively for multiple applications such as information storage and bio-inspired computing, but some reliability problems are still hindering ...their massive use. Among them, random telegraph noise (RTN) is one of the phenomena that still needs to be understood. In this work, we develop a general model to describe RTN in RS devices by demonstrating the existence of coupling effects between multiple traps, and their effect in the current amplitude deviation. We accurately describe anomalous RTN signals observed in high resistive state (HRS) and low-resistance state (LRS) of RS devices based on TiO 2 and hexagonal boron nitride (h-BN).
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