Hybrid 2D-CMOS microchips for memristive applications.

Exploiting the excellent electronic properties of two-dimensional (2D) materials to fabricate advanced electronic circuits is a major goal for the semiconductor industry1,2. However, most studies in this field have been limited to the fabrication and characterization of isolated large (more than 1 µm2) devices on unfunctional SiO2-Si substrates. Some studies have integrated monolayer graphene on silicon microchips as a large-area (more than 500 µm2) interconnection3 and as a channel of large transistors (roughly 16.5 µm2) (refs. 4,5), but in all cases the integration density was low, no computation was demonstrated and manipulating monolayer 2D materials was challenging because native pinholes and cracks during transfer increase variability and reduce yield. Here, we present the fabrication of high-integration-density 2D-CMOS hybrid microchips for memristive applications-CMOS stands for complementary metal-oxide-semiconductor. We transfer a sheet of multilayer hexagonal boron nitride onto the back-end-of-line interconnections of silicon microchips containing CMOS transistors of the 180 nm node, and finalize the circuits by patterning the top electrodes and interconnections. The CMOS transistors provide outstanding control over the currents across the hexagonal boron nitride memristors, which allows us to achieve endurances of roughly 5 million cycles in memristors as small as 0.053 µm2. We demonstrate in-memory computation by constructing logic gates, and measure spike-timing dependent plasticity signals that are suitable for the implementation of spiking neural networks. The high performance and the relatively-high technology readiness level achieved represent a notable advance towards the integration of 2D materials in microelectronic products and memristive applications.

Programmable Optoelectronic Synaptic Transistors Based on MoS2/Ta2NiS5 Heterojunction for Energy-Efficient Neuromorphic Optical Operation.

The optoelectronic synaptic transistors with various functions, broad spectral perception, and low power consumption are an urgent need for the development of advanced optical neural network systems. However, it remains a great challenge to realize the functional diversification of the systems on a single device. 2D van der Waals (vdW) materials can combine unique properties by stacking with each other to form heterojunctions, which may provide a strategy for solving this problem. Herein, an all-2D vdW heterojunction-based programmable optoelectronic synaptic transistor based on MoS2/Ta2NiS5 heterojunctions is demonstrated. The device implements reconfigurable, multilevel non-volatile memory (NVM) states through sequential modulation of multiple optical and electrical stimuli to achieve broadband (532-808 nm), energy-efficient (17.2 fJ), hetero-synaptic functionality in a bionic manner. The intrinsic working mechanisms of the photogating effect caused by band alignment and the interfacial trapping defect modulation induced by gate voltage are revealed by Kelvin-probe force microscopy (KPFM) measurements and carrier transport analysis. Overall, the (opto)electronic synaptic weight controllability for combined in-sensor and in-memory logic processors is realized by the heterojunction properties. The proposed findings facilitate the technical realization of generic all 2D hetero-synapses for future artificial vision systems, opto-logical systems, and Internet of Things (IoT) entities.

In Situ Observation of Low-Power Nano-Synaptic Response in Graphene Oxide Using Conductive Atomic Force Microscopy.

Multiple studies have reported the observation of electro-synaptic response in different metal/insulator/metal devices. However, most of them analyzed large (>1 µm2 ) devices that do not meet the integration density required by industry (1010  devices/mm2 ). Some studies emploied a scanning tunneling microscope (STM) to explore nano-synaptic response in different materials, but in this setup there is a nanogap between the insulator and one of the metallic electrodes (i.e., the STM tip), not present in real devices. Here, it is demonstrated how to use conductive atomic force microscopy to explore the presence and quality of nano-synaptic response in confined areas <50 nm2 . Graphene oxide (GO) is selected due to its easy fabrication. Metal/GO/metal nano-synapses exhibit potentiation and paired pulse facilitation with low write current levels <1 µA (i.e., power consumption ≈3 µW), controllable excitatory post-synaptic currents, and long-term potentiation and depression. The results provide a new method to explore nano-synaptic plasticity at the nanoscale, and point to GO as an important candidate for the fabrication of ultrasmall (<50 nm2 ) electronic synapses fulfilling the integration density requirements of neuromorphic systems.

[Recommendations for performing interventions during the COVID-19 pandemic]. / Recomendaciones para la realización de intervenciones pulmonares durante la pandemia COVID-19.

Coronavirus infection (SARS-CoV-2), is a pandemic disease declared by the World Health Organization (WHO). This disease reports a high risk of contagion, especially by the transmission of aerosols in health care workers. In this scenario, aerosol exposure is increased in various procedures related to the airway, lungs, and pleural space. For this reason, it is important to have recommendations that reduce the risk of exposure and infection with COVID-19. In this document, a team of international specialists in interventional pulmonology elaborated a series of recommendations, based on the available evidence to define the risk stratification, diagnostic methods and technical considerations on procedures such as bronchoscopy, tracheostomy, and pleural procedures among others. As well as the precautions to reduce the risk of contagion when carrying out pulmonary interventions.

Distinguishing Oxygen Vacancy Electromigration and Conductive Filament Formation in TiO2 Resistance Switching Using Liquid Electrolyte Contacts.

Resistance switching in TiO2 and many other transition metal oxide resistive random access memory materials is believed to involve the assembly and breaking of interacting oxygen vacancy filaments via the combined effects of field-driven ion migration and local electronic conduction leading to Joule heating. These complex processes are very difficult to study directly in part because the filaments form between metallic electrode layers that block their observation by most characterization techniques. By replacing the top electrode layer in a metal-insulator-metal memory structure with easily removable liquid electrolytes, either an ionic liquid (IL) with high resistance contact or a conductive aqueous electrolyte, we probe field-driven oxygen vacancy redistribution in TiO2 thin films under conditions that either suppress or promote Joule heating. Oxygen isotope exchange experiments indicate that exchange of oxygen ions between TiO2 and the IL is facile at room temperature. Oxygen loss significantly increases the conductivity of the TiO2 films; however, filament formation is not observed after IL gating alone. Replacing the IL with a more conductive aqueous electrolyte contact and biasing does produce electroformed conductive filaments, consistent with a requirement for Joule heating to enhance the vacancy concentration and mobility at specific locations in the film.

[A review on thoracic ultrasound]. / Aplicaciones torácicas del ultrasonido.

The use of thoracic ultrasound as a diagnostic tool in the emergency department, intensive care unit or in patients with pulmonary diseases is increasing steadily. It is used to guide percutaneous tracheostomies, to assess pleural effusions, to rule out pneumothorax, and to guide the placement of endovascular and pleural catheters. It is also useful in the assessment of patients with dyspnea. The aim of this review is to provide the practical and technical basics for the use of this diagnostic tool among internists and specialists in pulmonary diseases.

Nonepitaxial Wafer-Scale Single-Crystal 2D Materials on Insulators.

Next-generation nanodevices require 2D material synthesis on insulating substrates. However, growing high-quality 2D-layered materials, such as hexagonal boron nitride (hBN) and graphene, on insulators is challenging owing to the lack of suitable metal catalysts, imperfect lattice matching with substrates, and other factors. Therefore, developing a generally applicable approach for realizing high-quality 2D layers on insulators remains crucial, despite numerous strategies being explored. Herein, a universal strategy is introduced for the nonepitaxial synthesis of wafer-scale single-crystal 2D materials on arbitrary insulating substrates. The metal foil in a nonadhered metal-insulator substrate system is almost melted by a brief high-temperature treatment, thereby pressing the as-grown 2D layers to well attach onto the insulators. High-quality, large-area, single-crystal, monolayer hBN and graphene films are synthesized on various insulating substrates. This strategy provides new pathways for synthesizing various 2D materials on arbitrary insulators and offers a universal epitaxial platform for future single-crystal film production.

On the quality of commercial chemical vapour deposited hexagonal boron nitride.

The semiconductors industry has put its eyes on two-dimensional (2D) materials produced by chemical vapour deposition (CVD) because they can be grown at the wafer level with small thickness fluctuations, which is necessary to build electronic devices and circuits. However, CVD-grown 2D materials can contain significant amounts of lattice distortions, which degrades the performance at the device level and increases device-to-device variability. Here we statistically analyse the quality of commercially available CVD-grown hexagonal boron nitride (h-BN) from the most popular suppliers. h-BN is of strategic importance because it is one of the few insulating 2D materials, and can be used as anti-scattering substrate and gate dielectric. We find that the leakage current and electrical homogeneity of all commercially available CVD h-BN samples are significantly worse than those of mechanically exfoliated h-BN of similar thickness. Moreover, in most cases the properties of the CVD h-BN samples analysed don't match the technical specifications given by the suppliers, and the sample-to-sample variability is unsuitable for the reproducible fabrication of capacitors, transistors or memristors in different batches. In the short term, suppliers should try to provide accurate sample specifications matching the properties of the commercialized materials, and researchers should keep such inaccuracies in mind; and in the middle term suppliers should try to reduce the density of defects to enable the fabrication of high-performance devices with high reliability and reproducibility.

7D High-Dynamic Spin-Multiplexing.

Multiplexing technology creates several orthogonal data channels and dimensions for high-density information encoding and is irreplaceable in large-capacity information storage, and communication, etc. The multiplexing dimensions are constructed by light attributes and spatial dimensions. However, limited by the degree of freedom of interaction between light and material structure parameters, the multiplexing dimension exploitation method is still confused. Herein, a 7D Spin-multiplexing technique is proposed. Spin structures with four independent attributes (color center type, spin axis, spatial distribution, and dipole direction) are constructed as coding basic units. Based on the four independent spin physical effects, the corresponding photoluminescence wavelength, magnetic field, microwave, and polarization are created into four orthogonal multiplexing dimensions. Combined with the 3D of space, a 7D multiplexing method is established, which possesses the highest dimension number compared with 6 dimensions in the previous study. The basic spin unit is prepared by a self-developed laser-induced manufacturing process. The free state information of spin is read out by four physical quantities. Based on the multiple dimensions, the information is highly dynamically multiplexed to enhance information storage efficiency. Moreover, the high-dynamic in situ image encryption/marking is demonstrated. It implies a new paradigm for ultra-high-capacity storage and real-time encryption.

Tuning Hole-Injection in Organic-Light Emitting Diodes with Self-Assembled Monolayers.

Improving hole injection through the surface modification of indium tin oxide (ITO) with self-assembled monolayers (SAMs) is a promising method for modulating the carrier injection in organic light-emitting diodes (OLEDs). However, developing SAMs with the required characteristics remains a daunting challenge. Herein, we functionalize ITO with various phosphonic acid SAMs and evaluate the SAM-modified anodes in terms of their work function (WF), molecular distribution, coverage, and electrical conductivity. We fabricate and characterize green phosphorescent SAM-based OLEDs and compared their performance against devices based on the conventional poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS) hole-injection layer. We find that the usage of [2-(3,6-diiodo-9H-carbazol-9-yl)ethyl]phosphonic acid (I-2PACz) SAM yields devices with superior performance characteristics, including a maximum luminance of ∼57,300 cd m-2 and external quantum efficiency of up to ∼17%. This improvement is attributed to synergistic factors, including the deep WF of ITO/I-2PACz (5.47 eV), the formation of larger I-2PACz molecular clusters, and the intrinsic I-2PACz dipole, that collectively enhance hole-injection.

Thermal Compact Modeling and Resistive Switching Analysis in Titanium Oxide-Based Memristors.

Resistive switching devices based on the Au/Ti/TiO2/Au stack were developed. In addition to standard electrical characterization by means of I-V curves, scanning thermal microscopy was employed to localize the hot spots on the top device surface (linked to conductive nanofilaments, CNFs) and perform in-operando tracking of temperature in such spots. In this way, electrical and thermal responses can be simultaneously recorded and related to each other. In a complementary way, a model for device simulation (based on COMSOL Multiphysics) was implemented in order to link the measured temperature to simulated device temperature maps. The data obtained were employed to calculate the thermal resistance to be used in compact models, such as the Stanford model, for circuit simulation. The thermal resistance extraction technique presented in this work is based on electrical and thermal measurements instead of being indirectly supported by a single fitting of the electrical response (using just I-V curves), as usual. Besides, the set and reset voltages were calculated from the complete I-V curve resistive switching series through different automatic numerical methods to assess the device variability. The series resistance was also obtained from experimental measurements, whose value is also incorporated into a compact model enhanced version.

Anisotropic Superconducting Nb2 CTx MXene Processed by Atomic Exchange at the Wafer Scale.

Superconductivty has recently been induced in MXenes through surface modification. However, the previous reports have mostly been based on powders or cold-pressed pellets, with no known reports on the intrinsic superconsucting properties of MXenes at the nanoale. Here, it is developed a high-temperature atomic exchange process in NH3 atmosphere which induces superconductivity in either singleflakes or thin films of Nb2 CTx MXene. The exchange process between nitrogen atoms and fluorine, carbon, and oxygen atoms in the MXene lattice and related structural adjustments are studied using both experiments and density functional theory. Using either single-flake or thin-film devices, an anisotropic magnetic response of the 2D superconducting transformation has been successfully revealed. The anisotropic superconductivity is further demonstrated using superconducting thin films uniformly deposited over a 4 in. wafers, which opens up the possibility of scalable MXene-based superconducting devices.

Hardware implementation of memristor-based artificial neural networks.

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 that rely extensively on large sets of data. More recent computing paradigms, such as high parallelization and near-memory computing, help alleviate the data communication bottleneck to some extent, but paradigm- shifting concepts are required. Memristors, a novel beyond-complementary metal-oxide-semiconductor (CMOS) technology, are a promising choice for memory devices due to their unique intrinsic device-level properties, enabling both storing and computing with a small, massively-parallel footprint at low power. Theoretically, this directly translates to a major boost in energy efficiency and computational throughput, but various practical challenges remain. In this work we review the latest efforts for achieving hardware-based memristive artificial neural networks (ANNs), describing with detail the working principia of each block and the different design alternatives with their own advantages and disadvantages, as well as the tools required for accurate estimation of performance metrics. Ultimately, we aim to provide a comprehensive protocol of the materials and methods involved in memristive neural networks to those aiming to start working in this field and the experts looking for a holistic approach.

The expression of platelet serotonin transporter (SERT) in human obesity.

BACKGROUND: Serotonin (5-HT) is a well-known modulator of eating behavior. However, the molecular mechanisms linking its action to body weight balance have been only partially elucidated. Since platelets are a suitable peripheral model to study 5-HT transport, metabolism and release, we herein evaluated the expression of the platelet 5-HT re-uptake system (SERT) by [3H]-paroxetine binding assay. A cohort of 114 unrelated individuals (34 males, 80 females; age, mean ± SD: 38.57 ± 12.47 years) without major psychiatric disorders, was recruited following a naturalistic design regarding age or gender and classified accordingly to their body mass index (BMI). Subjects were divided into 5 groups: normal-weight (NW), overweight (OW) and grade I-III obese (OB) individuals. For gender analyses, data were transformed into [3H]-paroxetine density (Bmax)/BMI ratios to overcome both the disparity of women vs. men number and anthropometric differences between sexes. RESULTS: [3H]-paroxetine Bmax (SERT density, fmol/mg proteins) was reduced in platelet membranes of grade II (p < 0.01) and III (p < 0.001) obese subjects vs. controls and in overweight subjects (p < 0.05) vs. grade III obese individuals. Considering all patients together, a strong negative correlation between Bmax and BMI (r = -0.449; P < 0.0001) was demonstrated. Conversely, [3H]-paroxetine KD (dissociation constant, nM) did not differ among groups. No gender-related variation concerning Bmax/BMI ratios was observed in this cohort of subjects. CONCLUSIONS: The down-regulation of SERT in platelet membranes of severe human obesity (BMI > 35 Kg/m2) confirms the involvement of 5-HT system in body weight gain. Moreover, this findings may help to elucidate those monoamine-endocrine networks acting on fat storage, adipocyte signaling and energy balance. Targeting 5-HT/5-HT-related markers will possibly uncover the existence of human obesity subtypes.

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.

Revealing the improved stability of amorphous boron-nitride upon carbon doping.

We report on a large improvement of the thermal stability and mechanical properties of amorphous boron-nitride upon carbon doping. By generating versatile force fields using first-principles and machine learning simulations, we investigate the structural properties of amorphous boron-nitride with varying contents of carbon (from a few percent to 40 at%). We found that for 20 at% of carbon, the sp3/sp2 ratio reaches a maximum with a negligible graphitisation effect, resulting in an improvement of the thermal stability by up to 20% while the bulk Young's modulus increases by about 30%. These results provide a guide to experimentalists and engineers to further tailor the growth conditions of BN-based compounds as non-conductive diffusion barriers and ultralow dielectric coefficient materials for a number of applications including interconnect technology.

Holistic Variability Analysis in Resistive Switching Memories Using a Two-Dimensional Variability Coefficient.

We present a new methodology to quantify the variability of resistive switching memories. Instead of statistically analyzing few data points extracted from current versus voltage (I-V) plots, such as switching voltages or state resistances, we take into account the whole I-V curve measured in each RS cycle. This means going from a one-dimensional data set to a two-dimensional data set, in which every point of each I-V curve measured is included in the variability calculation. We introduce a new coefficient (named two-dimensional variability coefficient, 2DVC) that reveals additional variability information to which traditional one-dimensional analytical methods (such as the coefficient of variation) are blind. This novel approach provides a holistic variability metric for a better understanding of the functioning of resistive switching memories.

Solid Platinum Nanoprobes for Highly Reliable Conductive Atomic Force Microscopy.

Conductive atomic force microscopy (CAFM) is a powerful technique to investigate electrical and mechanical properties of materials and devices at the nanoscale. However, its main challenge is the reliability of the probe tips and their interaction with the samples. The most common probe tips used in CAFM studies are made of Si coated with a thin (∼20 nm) film of Pt or Pt-rich alloys (such as Pt/Ir), but this can degrade fast due to high current densities (>102A/cm2) and mechanical frictions. Si tips coated with doped diamond and solid doped diamond tips are more durable, but they are significantly more expensive and their high stiffness often damages the surface of most samples. One growing alternative is to use solid Pt tips, which have an intermediate price and are expected to be more durable than metal-coated silicon tips. However, a thorough characterization of the performance of solid Pt probes for CAFM research has never been reported. In this article, we characterize the performance of solid Pt probes for nanoelectronics research by performing various types of experiments and compare them to Pt/Ir-coated Si probes. Our results indicate that solid Pt probes exhibit a lateral resolution that is very similar to that of Pt/Ir-coated Si probes but with the big advantage of a much longer lifetime. Moreover, the probe-to-probe deviation of the electrical data collected is small. The use of solid Pt probes can help researchers to enhance the reliability of their CAFM experiments.

Cellular automata imbedded memristor-based recirculated logic in-memory computing.

Memristor-based circuits offer low hardware costs and in-memory computing, but full-memristive circuit integration for different algorithm remains limited. Cellular automata (CA) has been noticed for its well-known parallel, bio-inspired, computational characteristics. Running CA on conventional chips suffers from low parallelism and high hardware costs. Establishing dedicated hardware for CA remains elusive. We propose a recirculated logic operation scheme (RLOS) using memristive hardware and 2D transistors for CA evolution, significantly reducing hardware complexity. RLOS's versatility supports multiple CA algorithms on a single circuit, including elementary CA rules and more complex majority classification and edge detection algorithms. Results demonstrate up to a 79-fold reduction in hardware costs compared to FPGA-based approaches. RLOS-based reservoir computing is proposed for edge computing development, boasting the lowest hardware cost (6 components/per cell) among existing implementations. This work advances efficient, low-cost CA hardware and encourages edge computing hardware exploration.

Nanoscale temperature sensing of electronic devices with calibrated scanning thermal microscopy.

Heat dissipation threatens the performance and lifetime of many electronic devices. As the size of devices shrinks to the nanoscale, we require spatially and thermally resolved thermometry to observe their fine thermal features. Scanning thermal microscopy (SThM) has proven to be a versatile measurement tool for characterizing the temperature at the surface of devices with nanoscale resolution. SThM can obtain qualitative thermal maps of a device using an operating principle based on a heat exchange process between a thermo-sensitive probe and the sample surface. However, the quantification of these thermal features is one of the most challenging parts of this technique. Developing reliable calibration approaches for SThM is therefore an essential aspect to accurately determine the temperature at the surface of a sample or device. In this work, we calibrate a thermo-resistive SThM probe using heater-thermometer metal lines with different widths (50 nm to 750 nm), which mimic variable probe-sample thermal exchange processes. The sensitivity of the SThM probe when scanning the metal lines is also evaluated under different probe and line temperatures. Our results reveal that the calibration factor depends on the probe measuring conditions and on the size of the surface heating features. This approach is validated by mapping the temperature profile of a phase change electronic device. Our analysis provides new insights on how to convert the thermo-resistive SThM probe signal to the scanned device temperature more accurately.