Hysteresis in memristors produces conduction inductance and conduction capacitance effects.

Memristors are devices in which the conductance state can be alternately switched between a high and a low value by means of a voltage scan. In general, systems involving a chemical inductor mechanism as solar cells, asymmetric nanopores in electrochemical cells, transistors, and solid state memristive devices, exhibit a current increase and decrease over time that generates hysteresis. By performing small signal ac impedance spectroscopy, we show that memristors, or any other system with hysteresis relying on the conductance modulation effect, display intrinsic dynamic inductor-like and capacitance-like behaviours in specific input voltage ranges.

Fast Fitting of the Dynamic Memdiode Model to the Conduction Characteristics of RRAM Devices Using Convolutional Neural Networks.

In this paper, the use of Artificial Neural Networks (ANNs) in the form of Convolutional Neural Networks (AlexNET) for the fast and energy-efficient fitting of the Dynamic Memdiode Model (DMM) to the conduction characteristics of bipolar-type resistive switching (RS) devices is investigated. Despite an initial computationally intensive training phase the ANNs allow obtaining a mapping between the experimental Current-Voltage () curve and the corresponding DMM parameters without incurring a costly iterative process as typically considered in error minimization-based optimization algorithms. In order to demonstrate the fitting capabilities of the proposed approach, a complete set of s obtained from YO-based RRAM devices, fabricated with different oxidation conditions and measured with different current compliances, is considered.

Experimental and Modeling Study of Metal-Insulator Interfaces to Control the Electronic Transport in Single Nanowire Memristive Devices.

Memristive devices relying on redox-based resistive switching mechanisms represent promising candidates for the development of novel computing paradigms beyond von Neumann architecture. Recent advancements in understanding physicochemical phenomena underlying resistive switching have shed new light on the importance of an appropriate selection of material properties required to optimize the performance of devices. However, despite great attention has been devoted to unveiling the role of doping concentration, impurity type, adsorbed moisture, and catalytic activity at the interfaces, specific studies concerning the effect of the counter electrode in regulating the electronic flow in memristive cells are scarce.

Enhancing the Thermal Conductivity of Amorphous Carbon with Nanowires and Nanotubes.

The thermal conductivity of nanostructures can be obtained using atomistic classical Molecular Dynamics (MD) simulations, particularly for semiconductors where there is no significant contribution from electrons to thermal conduction. In this work, we obtain and analyze the thermal conductivity of amorphous carbon (aC) nanowires (NW) with a 2 nm radius and aC nanotubes (NT) with 0.5, 1 and 1.

Quantum Conductance in Memristive Devices: Fundamentals, Developments, and Applications.

Quantum effects in novel functional materials and new device concepts represent a potential breakthrough for the development of new information processing technologies based on quantum phenomena. Among the emerging technologies, memristive elements that exhibit resistive switching, which relies on the electrochemical formation/rupture of conductive nanofilaments, exhibit quantum conductance effects at room temperature. Despite the underlying resistive switching mechanism having been exploited for the realization of next-generation memories and neuromorphic computing architectures, the potentialities of quantum effects in memristive devices are still rather unexplored.

Nano-Memristors with 4 mV Switching Voltage Based on Surface-Modified Copper Nanoparticles.

The development of memristors operating at low switching voltages <50 mV can be very useful to avoid signal amplification in many types of circuits, such as those used in bioelectronic applications to interact with neurons and nerves. Here, it is reported that 400 nm-thick films made of dalkyl-dithiophosphoric (DDP) modified copper nanoparticles (CuNPs) exhibit volatile threshold-type resistive switching (RS) at ultralow switching voltage of ≈4 mV. The RS is observed in small nanocells with a lateral size of <50 nm , during hundreds of cycles, and with an ultralow variability.

Connectome of memristive nanowire networks through graph theory.

Hardware implementation of neural networks represents a milestone for exploiting the advantages of neuromorphic-type data processing and for making use of the inherent parallelism associated with such structures. In this context, memristive devices with their analogue functionalities are called to be promising building blocks for the hardware realization of artificial neural networks. As an alternative to conventional crossbar architectures where memristive devices are organized with a top-down approach in a grid-like fashion, neuromorphic-type data processing and computing capabilities have been explored in networks realized according to the principle of self-organization similarity found in biological neural networks.

SPICE Implementation of the Dynamic Memdiode Model for Bipolar Resistive Switching Devices.

This paper reports the fundamentals and the SPICE implementation of the Dynamic Memdiode Model (DMM) for the conduction characteristics of bipolar-type resistive switching (RS) devices. Following Prof. Chua's memristive devices theory, the memdiode model comprises two equations, one for the electron transport based on a heuristic extension of the quantum point-contact model for filamentary conduction in thin dielectrics and a second equation for the internal memory state related to the reversible displacement of atomic species within the oxide film.

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 >10 cycles were based on resistance cycle plots that contain very few data points (in many cases even <20), and which are collected in only one device.

On the Thermal Models for Resistive Random Access Memory Circuit Simulation.

Resistive Random Access Memories (RRAMs) are based on resistive switching (RS) operation and exhibit a set of technological features that make them ideal candidates for applications related to non-volatile memories, neuromorphic computing and hardware cryptography. For the full industrial development of these devices different simulation tools and compact models are needed in order to allow computer-aided design, both at the device and circuit levels. Most of the different RRAM models presented so far in the literature deal with temperature effects since the physical mechanisms behind RS are thermally activated; therefore, an exhaustive description of these effects is essential.

Cross-reactivity between and in immunotherapy extracts for the treatment of allergy to .

and are the two most common subspecies of the genus. and have exhibited cross-reactivity in previous studies. pollen is the main cause of allergy in the Mediterranean area.

Memristors for Neuromorphic Circuits and Artificial Intelligence Applications.

Artificial Intelligence has found many applications in the last decade due to increased computing power. Artificial Neural Networks are inspired in the brain structure and consist in the interconnection of artificial neurons through artificial synapses in the so-called Deep Neural Networks (DNNs). Training these systems requires huge amounts of data and, after the network is trained, it can recognize unforeseen data and provide useful information.

On the Application of a Diffusive Memristor Compact Model to Neuromorphic Circuits.

Memristive devices have found application in both random access memory and neuromorphic circuits. In particular, it is known that their behavior resembles that of neuronal synapses. However, it is not simple to come by samples of memristors and adjusting their parameters to change their response requires a laborious fabrication process.

Impact of the precursor chemistry and process conditions on the cell-to-cell variability in 1T-1R based HfO RRAM devices.

The Resistive RAM (RRAM) technology is currently in a level of maturity that calls for its integration into CMOS compatible memory arrays. This CMOS integration requires a perfect understanding of the cells performance and reliability in relation to the deposition processes used for their manufacturing. In this paper, the impact of the precursor chemistries and process conditions on the performance of HfO based memristive cells is studied.

Silicon Oxide (SiO ): A Promising Material for Resistance Switching?

Interest in resistance switching is currently growing apace. The promise of novel high-density, low-power, high-speed nonvolatile memory devices is appealing enough, but beyond that there are exciting future possibilities for applications in hardware acceleration for machine learning and artificial intelligence, and for neuromorphic computing. A very wide range of material systems exhibit resistance switching, a number of which-primarily transition metal oxides-are currently being investigated as complementary metal-oxide-semiconductor (CMOS)-compatible technologies.

Tuning the Hydrolytic Stability of Next Generation Maleimide Cross-Linkers Enables Access to Albumin-Antibody Fragment Conjugates and tri-scFvs.

We describe investigations to expand the scope of next generation maleimide cross-linkers for the construction of homogeneous protein-protein conjugates. Diiodomaleimides are shown to offer the ideal properties of rapid bioconjugation with reduced hydrolysis, allowing the cross-linking of even sterically hindered systems. The optimized linkers are exploited to link human serum albumin to antibody fragments (Fab or scFv) as a prospective half-life extension platform, with retention of antigen binding and robust serum stability.

Investigation on the Conductive Filament Growth Dynamics in Resistive Switching Memory via a Universal Monte Carlo Simulator.

In resistive random access memories, modeling conductive filament growing dynamics is important to understand the switching mechanism and variability. In this paper, a universal Monte Carlo simulator is developed based on a cell switching model and a tunneling-based transport model. Driven by external electric field, the growing process of the nanoscale filament occurring in the gap region is actually dominated by cells' conductive/insulating switching, modeled through a phenomenological physics-based probability function.

Analysis on the Filament Structure Evolution in Reset Transition of Cu/HfO2/Pt RRAM Device.

The resistive switching (RS) process of resistive random access memory (RRAM) is dynamically correlated with the evolution process of conductive path or conductive filament (CF) during its breakdown (rupture) and recovery (reformation). In this study, a statistical evaluation method is developed to analyze the filament structure evolution process in the reset operation of Cu/HfO2/Pt RRAM device. This method is based on a specific functional relationship between the Weibull slopes of reset parameters' distributions and the CF resistance (R on).

Statistical characteristics of reset switching in Cu/HfO2/Pt resistive switching memory.

A major challenge of resistive switching memory (resistive random access memory (RRAM)) for future application is how to reduce the fluctuation of the resistive switching parameters. In this letter, with a statistical methodology, we have systematically analyzed the reset statistics of the conductive bridge random access memory (CBRAM) with a Cu/HfO2/Pt structure which displays bipolar switching property. The experimental observations show that the distributions of the reset voltage (V reset) and reset current (I reset) are greatly influenced by the initial on-state resistance (R on) which is closely related to the size of the conductive filament (CF) before the reset process.

A plug-and-play approach to antibody-based therapeutics via a chemoselective dual click strategy.

Although recent methods for the engineering of antibody-drug conjugates (ADCs) have gone some way to addressing the challenging issues of ADC construction, significant hurdles still remain. There is clear demand for the construction of novel ADC platforms that offer greater stability, homogeneity and flexibility. Here we describe a significant step towards a platform for next-generation antibody-based therapeutics by providing constructs that combine site-specific modification, exceptional versatility and high stability, with retention of antibody binding and structure post-modification.

Development of the designed ankyrin repeat protein (DARPin) G3 for HER2 molecular imaging.

Purpose: Human epidermal growth factor receptor-2 (HER2) overexpression is a predictor of response to anti-HER2 therapy in breast and gastric cancer. Currently, HER2 status is assessed by tumour biopsy, but this may not be representative of the larger tumour mass or other metastatic sites, risking misclassification and selection of suboptimal therapy. The designed ankyrin repeat protein (DARPin) G3 binds HER2 with high affinity at an epitope that does not overlap with trastuzumab and is biologically inert.

Homogeneous bispecifics by disulfide bridging.

We report on a chemical platform to generate site-specific, homogeneous, antibody-antibody conjugates by targeting and bridging disulfide bonds. A bispecific antibody construct was produced in good yield through simple reduction and bridging of antibody fragment disulfide bonds, using a readily synthesized bis-dibromomaleimide cross-linker. Binding activity of antibodies was maintained, and in vitro binding of target antigens was observed.

Voltage and power-controlled regimes in the progressive unipolar RESET transition of HfO₂-based RRAM.

Resistive switching (RS) based on the formation and rupture of conductive filament (CF) is promising in novel memory and logic device applications. Understanding the physics of RS and the nature of CF is of utmost importance to control the performance, variability and reliability of resistive switching memory (RRAM). Here, the RESET switching of HfO2-based RRAM was statistically investigated in terms of the CF conductance evolution.

Generation and characterization of a diabody targeting the αvβ6 integrin.

The αvβ6 integrin is up-regulated in cancer and wound healing but it is not generally expressed in healthy adult tissue. There is increasing evidence that it has a role in cancer progression and will be a useful target for antibody-directed cancer therapies. We report a novel recombinant diabody antibody fragment that targets specifically αvβ6 and blocks its function.