Marco A. Villena

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• PhD
• Ramón y Cajal fellow at University of Granada

This work presents a comprehensive analysis of the variability and reliability of the resistive switching (RS) behavior in Prussian Blue (a mixed-valence iron(III/II) hexacyanoferrate compound) thin films, used as the active layer. These films are fabricated through a simple and scalable electrochemical process, and exhibit robust bipolar resistive...

Hardware implementations of artificial neural networks (ANNs)—the most advanced of which are made of millions of electronic neurons interconnected by hundreds of millions of electronic synapses—have achieved higher energy efficiency than classical computers in some small-scale data-intensive computing tasks¹. State-of-the-art neuromorphic computers...

Resistive memories are outstanding electron devices that have displayed a large potential in a plethora of applications such as nonvolatile data storage, neuromorphic computing, hardware cryptography, etc. Their fabrication control and performance have been notably improved in the last few years to cope with the requirements of massive industrial p...

Interconnect materials with ultralow dielectric constant, and good thermal and mechanical properties are crucial for the further miniaturization of electronic devices. Recently, it has been demonstrated that ultrathin amorphous boron nitride (aBN) films have a very low dielectric constant, high density (above 2.1 g/cm3), high thermal stability, and...

Artificial Intelligence (AI) is currently experiencing a bloom driven by deep learning (DL) techniques, which rely on networks of connected simple computing units operating in parallel. The low communication bandwidth between memory and processing units in conventional von Neumann machines does not support the requirements of emerging applications...

Exploiting the excellent electronic properties of two-dimensional (2D) materials to fabricate advanced electronic circuits is a major goal for the semiconductors industry1-2. However, most studies in this field have been limited to the fabrication and characterization of isolated large (>1µm2) devices on unfunctional SiO2/Si substrates. Some studie...

Resistive memories are outstanding electron devices that have displayed a large potential in a plethora of applications such as nonvolatile data storage, neuromorphic computing, hardware cryptography, etc. Their fabrication control and performance have been notably improved in the last few years to cope with the requirements of massive industrial p...

Memristor‐based electronic memory have recently started commercialization, although its market size is small (~0.5%). Multiple studies claim their potential for hardware implementation of artificial neural networks, advanced data encryption, and high‐frequency switches for 5G/6G communication. Application aside, the performance and reliability of m...

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...

Discovery of ferroelectricity (FE) in binary oxides enables the advent of FE memories and a plethora of novel CMOS compatible building blocks spanning from the logic domain to high-density storage and neuromorphic computing. In this paper we develop the first comprehensive model of vertical Ferroelectric Field Effect Transistor, V-FeFET, to identif...

The introduction of 2D materials in the structure of memristors has been shown to provide the devices with enhanced flexibility and transparency. However, their use is still not well justified, as the electrical performance of 2D materials‐based memristors is still behind that of transition metal oxide (TMO)‐based memristors. This work presents the...

The existing oil-water separation materials are often limited by their cost, efficiency and environmental implications, so they are difficult to achieve effective utilization in industry. Although silica nanoparticles have excellent environmental-friendly and rich raw materials, their use has been restricted due to poor porous structure or complex...

Rutile structure IrO2 and the related alloy Ti1-xIrxO2 are studied by ab initio simulations. Iridium oxide attracts interest due its exotic metal-insulator transition which may have important applications. In addition, its alloy with TiO2 exhibits reasonable optical transparency, a large work function, high electronic conductivity, corrosion resist...

Memristors have recently gained growing interests due to their potential application as electronic synapses to build artificial neural networks for artificial intelligence systems. However, modulating the conductivity of memristors in a dynamic way to emulate biological synaptic behaviors is very challenging. Here we show the first fabrication of m...

Two-dimensional (2D) materials based memristors have shown several properties that are not shown by traditional ones, such as high transparency, robust mechanical strength and flexibility, superb chemical stability, enhanced thermal heat dissipation, ultra-low power consumption, coexistence of bipolar and threshold resistive switching (RS), and ult...

Chemical vapor deposition (CVD) is one of the most common techniques to grow large-area hexagonal boron nitride (h-BN). However, the substrate on which the h-BN is grown plays an important role in the electrical properties of this insulating material. The high temperature used during the CVD process produces the polycrystallization of the metallic...

Hexagonal boron nitride (h-BN) is a two dimensional (2D) layered insulator with superior dielectric performance that offers excellent interaction with other 2D materials (e.g. graphene, MoS2). Large-area h-BN can be readily grown on metallic substrates via chemical vapor deposition (CVD), but the impact of local inhomogeneities on the electrical pr...

Resistive switching (RS) is an interesting property shown by some materials systems that, especially during the last decade, has gained a lot of interest for the fabrication of electronic devices, with electronic nonvolatile memories being those that have received the most attention. The presence and quality of the RS phenomenon in a materials syst...

Hexagonal boron nitride (h-BN) is an attractive insulating material for nanoelectronic devices due to its high reliability as dielectric and excellent compatibility with other two dimensional (2D) materials (e.g. graphene, MoS2). Multilayer h-BN stacks have been readily grown on Cu and Pt substrates via chemical vapor deposition (CVD) approach, con...

Moisture and water penetration is one of the main phenomena altering the electrical characteristics and performance of resistive switching (RS) devices based on metal/insulator/metal nanojunctions. However, the effect of these phenomena in RS devices made of two dimensional (2D) materials has never been studied. In this paper it is shown that 2D ma...

Multilayer hexagonal boron nitride (h-BN) is an insulating 2D material that shows good interaction with graphene and MoS2, and it is considered a very promising dielectric for future 2D-materials-based electronic devices. Previous studies analyzed the dielectric properties of thick (>10 nm) mechanically exfoliated h-BN nanoflakes (diameter < 20 μm)...

Large-area hexagonal boron nitride (h-BN) can be grown on polycrystalline metallic substrates via chemical vapor deposition (CVD), but the impact of local inhomogeneities on the electrical properties of the h-BN and their effect in electronic devices is unknown. Conductive atomic force microscopy (CAFM) and probe station characterization show that...

We analyzed resistive switching-based memristors by using the charge–flux relations instead of the traditional current–voltage approach. We employed simulated and experimental data to develop a model that can be easily included in circuit simulators. Physical simulations of devices with different conductive filament sizes were employed to fit the 3...

Insulating films are essential in multiple electronic devices because they can provide essential functionalities, such as capacitance effects and electrical fields. Two dimensional (2D) layered materials have superb electronic, physical, chemical, thermal and optical properties, and they can be effectively used to provide additional performances (f...

In the last few years, resistive random access memory (RRAM) has been proposed as one of the most promising candidates to overcome the current Flash technology in the market of non-volatile memories. These devices have the ability to change their resistance state in a reversible and controlled way applying an external voltage. In this way, the resu...

In order to fulfill the information storage needs of modern societies, the performance of electronic nonvolatile memories (NVMs) should be continuously improved. In the past few years, resistive random access memories (RRAM) have raised as one of the most promising technologies for future information storage due to their excellent performance and e...

Despite the enormous interest raised by graphene and related materials, recent global concern about their real usefulness in industry has raised, as there is a preoccupying lack of 2D materials based electronic devices in the market. Moreover, analytical tools capable of describing and predicting the behavior of the devices (which are necessary bef...

A simulation study to characterize the influence of an elongation of the conductive filament in resistive switching devices is presented. A previously developed simulation tool has been used for this purpose. This simulator accounts for ohmic conduction through conductive filaments and for quantum conduction through a barrier (the last resulting in...

A new SPICE model that includes quantum conduction through a constriction by means of the Quantum Point Contact (QPC) model has been developed. A detailed comparison with a numerical physical simulator is given.

In this work, a new parameter is defined to describe the charge transport regime and to understand the physics behind the operation of Ni/HfO2/Si-n+-based RRAMs. An extraction process of the parameter from experimental reset I–V curves is proposed. The new parameter allows to know the relative importance of the two main transport mechanisms involve...

We analyzed ReRAM-based memristors by using the charge-flux relations instead of the traditional current-voltage approach. We used simulated and experimental data to develop a circuit model. Simulations of devices with different conductive filament sizes were employed to fit a 3-parameter model, later on the relations between the model parameters w...

Reset transitions in HfO2 based RRAMs operated at different temperatures have been studied. Ni/HfO2/Si-n+ devices were fabricated and measured at temperatures ranging from 233 K to 473 K to characterize their reset features. In addition, a simulator including several coupled conductive filaments, series resistance and quantum effects was employed t...

A physically based circuit model is proposed for SPICE simulation of thermally assisted reset transitions in resistive switching devices. The model allows the simulation of conductive filaments with complex structures, such as a main filament with several subfilaments attached forming a tree structure, or several filaments interlaced between them....

An in-depth study of reset processes in RRAMs (Resistive Random Access Memories) based on Ni/HfO2/Si-n+ structures has been performed. To do so, we have developed a physically based simulator where both ohmic and tunneling based conduction regimes are considered along with the thermal description of the devices. The devices under study have been su...

Reset processes in resistive random-access memory devices have been studied in depth. In particular, progressive transitions, where no clear current reduction steps are seen, are analysed by using a previously developed simulator and by comparing with experimental data of devices based on HfO2 oxides. It has been reported that the characterization...

An in-depth characterization of the thermal reset transition in RRAM has been performed based on coupling self-consistent simulations to experimental results. A complete self-consistent simulator accounting for the electrical and thermal descriptions of the conductive filaments (CFs) has been developed for the numerical study of the temporal evolut...