Reconfigurable impedance in memristive devices

Memristors have been a prospering topic in nanoelectronics research for the last decade. Their attributes have been diligently studied by multiple research groups and multiple applications that leverage their state-dependent programmability in a static fashion, have appeared. Practical applications of memristor-based AC circuits have been rather sparse, with only a few examples found in the literature where their use is only emulated. In this work a methodology is presented, which can be used to characterise memristive impedance. Using the developed methodology, the behaviour of metal-oxide memristors under a non-invasive AC perturbation is studied. Metal-oxide memristors are found to behave as RC low-pass filters and they present a variable cut-of frequency when their state is switched, thus providing a window of reconfigurability when used as filters. This window of reconfigurability can be engineered by changing the geometrical properties of the devices. Multiple material combinations have been tested to ascertain the best working device to use in the future. The most promising stack has been electrically and physically characterised to understand the reason behind its superiority against other combinations and to use that knowledge to actively fabricate better devices. Making use of findings from this study, concerning device AC and DC behaviour, a new 3-terminal configuration is fabricated and characterised. It is found to be able to form in both serial and antiserial connection of constituent memristive devices. This new stack is found to allow fine tuning of states, through a coarse/fine tuning arrangement of constituent devices, and an increased state density due to the combination of allowed states. In this case AC behaviour is similar to single device stacks, with both devices contributing to the cut-of frequency. This study extends current knowledge on metal-oxide memristors by characterising their frequency dependent characteristics, as well as their DC characteristics, and providing useful insights for their use in reconfigurable AC circuits

A Ka-Band SiGe BiCMOS Quasi-F⁻¹ Power Amplifier Using a Parasitic Capacitance Cancellation Technique <xref rid="fn1-jlpea-2268306" ref-type="fn">†</xref>

This paper deals with the design, analysis, and implementation of a Ka-band, single-stage, quasi-inverse class F power amplifier (PA). A detailed methodology for the evaluation of the active device’s output capacitance is described, enabling the designing of a second-harmonically tuned load and resulting in enhanced performance. A simplified model for the extraction of time-domain intrinsic voltage and current waveforms at the output of the main active core is introduced, enforcing the implementation process of the proposed quasi-inverse class F technique. The PA is fabricated in a 130 nm SiGe BiCMOS technology with fT/fmax=250/370 GHz and it is suitable for 5G applications. It achieves 33% peak power-added efficiency (PAE), 18.8 dBm saturation output power Psat, and 14.7 dB maximum large-signal power gain G at the operating frequency of 38 GHz. The PA’s response is also tested under a modulated-signal excitation and simulation results are denoted in this paper. The chip size is 0.605×0.712 mm2 including all pads

Parametric study of selective magnetic separation and applications

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Μικροσυστήματα και Νανοδιατάξεις

Technology agnostic frequency characterization methodology for memristors

Over the past decade memristors have been extensively studied for a number of applications, almost exclusively with DC characterization techniques. Studies of memristors in AC circuits are sparse, with only a few examples found in the literature, and characterization methods with an AC input are also sparingly used. However, publications concerning the usage of memristors in this working regime are currently on the rise. Here we propose a "technology agnostic" methodology for memristor testing in certain frequency bands. A measurement process is initially proposed, with specific instructions on sample preparation, followed by an equipment calibration and measurement protocol. This article is structured in way which aims to facilitate the usage of any available measurement equipment and it can be applied on any type of memristive technology. The second half of this work is centered around the representation of data received from following this process. Bode plot and Nyquist plot representations are considered and the information received from them is evaluated. Finally, examples of expected behaviors are given, characterizing simulated scenarios which represent different internal device models and different switching behaviors, such as capacitive or inductive switching. This study aims at providing a cohesive way for memristor characterization, to be used as a good starting point for frequency applications, and for understanding physical processes inside the devices, by streamlining the measuring process and providing a frame in which data representation and comparison will be facilitated

Technology Agnostic Frequency Characterization Methodology for Memristors

Dataset for peer-reviewed article titled &quot;Technology Agnostic Frequency Characterization Methodology for Memristors&quot; accepted in Scientific Reports. Includes data used to produce the figures seen in this article.</span

Dataset supporting an article &quot;Selectively biased tri-terminal vertically-integrated memristor configuration&quot;

Dataset for peer-reviewed article titled &quot;Selectively biased tri-terminal vertically-integrated memristor configuration&quot; accepted in Scientific Reports. Includes data used to produce the figures seen in this article.</span

Palimpsest memories stored in memristive synapses

Biological synapses store multiple memories on top of each other in a palimpsest fashion and at different time scales. Palimpsest consolidation is facilitated by the interaction of hidden biochemical processes governing synaptic efficacy during varying lifetimes. This arrangement allows idle memories to be temporarily overwritten without being forgotten, while previously unseen memories are used in the short term. While embedded artificial intelligence can greatly benefit from this functionality, a practical demonstration in hardware is missing. Here, we show how the intrinsic properties of metal-oxide volatile memristors emulate the processes supporting biological palimpsest consolidation. Our memristive synapses exhibit an expanded doubled capacity and protect a consolidated memory while up to hundreds of uncorrelated short-term memories temporarily overwrite it, without requiring specialized instructions. We further demonstrate this technology in the context of visual working memory. This showcases how emerging memory technologies can efficiently expand the capabilities of artificial intelligence hardware toward more generalized learning memories