RESUMO
Given the current maturity of printed technologies, Organic Thin-Film Transistors (OTFT) still show high initial variability, which can be beneficial for its exploitation in security applications. In this work, the process-related variability and aging of commercial OTFTs have been characterized to evaluate the feasibility of OTFTs-based Physical Unclonable Functions (PUFs) implementation. For our devices, ID-based PUFs show good uniformity and uniqueness. However, PUFs' reliability could be compromised because of the observed transient and aging effects in the OTFTs, which could hinder the reproducibility of the generated fingerprints. A systematic study of the aging of OTFTs has been performed to evaluate the PUFs' reliability. Our results suggest that the observed transient and aging effects could be mitigated so that the OTFTs-based PUFs' reliability could be improved.
RESUMO
A fully-unsupervised learning algorithm for reaching self-organization in neuromorphic architectures is provided in this work. We experimentally demonstrate spike-timing dependent plasticity (STDP) in Oxide-based Resistive Random Access Memory (OxRAM) devices, and propose a set of waveforms in order to induce symmetric conductivity changes. An empirical model is used to describe the observed plasticity. A neuromorphic system based on the tested devices is simulated, where the developed learning algorithm is tested, involving STDP as the local learning rule. The design of the system and learning scheme permits to concatenate multiple neuromorphic layers, where autonomous hierarchical computing can be performed.
RESUMO
Low-power, high-performance metal-insulator-metal (MIM) non-volatile resistive memories based on HfO2 high- k dielectric are fabricated using a drop-on-demand inkjet printing technique as a low-cost and eco-friendly method. The characteristics of resistive switching of Pt (bottom)/HfO2/Ag (top) stacks on Si/SiO2 substrates are investigated in order to study the bottom electrode's interaction with the HfO2 dielectric layer and the resulting effects on resistive switching. The devices show low Set and Reset voltages, high ON/OFF current ratio, and relatively low switching current (â¼1 µA), which are comparable to the characteristics of current commercial CMOS memories. In order to understand the resistive switching mechanism, direct structural observation is carried out by field-emission scanning electron microscopy (FE-SEM) and high-resolution transmission electron microscopy (HRTEM) on cross-sectioned samples prepared by focused ion beam (FIB). In addition, electron energy loss spectroscopy (EELS) inspections discard a silver electro-migration effect.
RESUMO
For advanced atomic force microscopy (AFM) investigation of chemical surface modifications or very soft organic sample surfaces, the AFM probe tip needs to be operated in a liquid environment because any attractive or repulsive forces influenced by the measurement environment could obscure molecular forces. Due to fluid properties, the mechanical behavior of the AFM cantilever is influenced by the hydrodynamic drag force due to viscous friction with the liquid. This study provides a numerical model based on computational fluid dynamics (CFD) and investigates the hydrodynamic drag forces for different cantilever geometries and varying fluid conditions for Peakforce Tapping (PFT) in liquids. The developed model was verified by comparing the predicted values with published results of other researchers and the findings confirmed that drag force dependence on tip speed is essentially linear in nature. We observed that triangular cantilever geometry provides significant lower drag forces than rectangular geometry and that short cantilever offers reduced flow resistance. The influence of different liquids such as ultrapure water or an ethanol-water mixture as well as a temperature induced variation of the drag force could be demonstrated. The acting forces are lowest in ultrapure water, whereas with increasing ethanol concentrations the drag forces increase.