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Atomic defects in high-k materials affect the performance, reliability, variability, and scaling potential of electronic devices. Their characterization is thus of paramount importance, and methods exploiting electrical measurements are highly demanded. In this work we present a novel method for extracting the defect properties from I-V curve hysteresis measured at low electric field in thick metal-insulator-metal (MIM) stacks. The I-V curve hysteresis allows detecting the defects located near the electrode-insulator interfaces and aligned with the stack Fermi level, and extracting their properties. The defects are profiled cross-correlating the information provided by the low-field current hysteresis and the high-field steady-state current. This technique can be applied to MIM stacks fabricated in Back-End-of-Line for capacitors, embedded memories and thin film transistors.

Originally introduced in electronic manufacturing to replace the SiO2 insulating layer, metal oxides are now extensively used in a multitude of electronic devices. Understanding charge transport mechanisms in metal oxides is of paramount importance for device optimization; however, a detailed and self-consistent discussion of electron conduction at all applied electric fields is lacking in the literature. In this work, we investigated the conduction mechanisms in three model systems, Al2O3, HfO2, and Al-doped HfO2 metal-insulator-metal capacitors, determining the path that the electrons travel within the metal oxide. Traps properties are extracted from experimental current-voltage characteristics using the Ginestra® simulation software. Furthermore, the analysis allowed to visualize the location of traps most involved in the conduction and the dominant transport mechanisms at each applied electric field. Despite the different oxide properties, a similar trend was recognized at low electric fields, the electron transport through the oxide is negligible, and the dominant contribution to the measured current is ascribed to the charge/discharge of traps located near the metal/oxide interfaces, leading to displacement currents. At high electric fields, the transport of electrons occurs through the defect rich oxides in the two following ways: if a large density of traps is energetically located near the electrodes Fermi level (as in HfO2), the electrons tunnel from trap to trap until they reach the anode; otherwise, when traps are closer to the conduction band (as in Al2O3 and AlHfO), the electrons tunnel from the cathode into one trap and then into the oxide conduction band, interacting only with traps near the cathode.

In this chapter we present results on system-level integration of memristive devices with neuromorphic circuits and systems. Specifically we present an overview of the current state-of-the-art hybrid memristive-complementary metal–oxide–semiconductor (CMOS) mixed-signal neuromorphic circuits for learning and plasticity and present perspectives toward integration of memristive devices in neuromorphic spiking neural network architectures. We focus on neuromorphic circuits and architectures that allow for a relatively natural integration of memristive devices, irrespective of the specific characteristics of the specific memristive device technology adopted. We address the cointegration of memristive devices with on-chip learning mechanisms, using both analog and digital CMOS circuits, to build a solid background of the functionality of neuromorphic circuits explaining how memristive devices can be implemented on them. Furthermore we also address the system-level integration of such architectures in multicore and multichip systems, for connecting them to input and output devices, such as sensors, actuators, and conventional CMOS processing devices.

Objectives—The aim of this study was to evaluate the application of shear waveelastography (SWE) in the routine management of thyroid nodules, as a possibleadditional tool to the standard sonographic triage.Methods—A total of 248 consecutive patients scheduled for ultrasound-guidedthyroidfine-needle aspiration were included in the study. The presence of a purecolloid lesion was an exclusion criterion. Absolute and relative SWE stiffnessmeasurements on color-coded elastograms, expressed in kilopascals and metersper second, were correlated with radiologic and pathologic features.Results—SWE values in thyroid nodules were significantly higher than normalthyroid tissue (P= .0001), proving the different elastic properties of the patho-logic tissues. Regarding the radiologic characteristics of the nodules, SWE high-est values were associated with the largest lesions (P= .0105) but independentfrom sonographic and Dopplerfindings. The SWE elasticity was not influencedby the characteristics of the biopsy smears. Thefinal correlation between theSWE results and the pathologic diagnoses showed a trend in stiffness fromtender tumors (follicular adenoma) to papillary thyroid carcinoma (P= .016).Conclusions—SWE allows the identification of nodules within normal paren-chyma; however, the present study does not confirm the potential role in differ-entiating between benign and malignant thyroid nodules.