arXiv subjects

László Pósa

Publications and source records attributed to László Pósa.

7 recordsLinked to original sources

arXiv2026

Voltage-driven transition from steady-state fluctuations to phase-transition noise in nanoscale VO$_2$ devices

We investigate the electrically driven metal-to-insulator transition (MIT) in nanoscale vanadium dioxide (VO$_2$) Mott memristor through noise spectroscopy and two-dimensional resistor network simulations. Our experiments focus on both the insulating phase as the applied voltage approaches the threshold voltage (set transition) and the metallic phase as the voltage is reduced toward the reset voltage (reset transition). In both regimes, we observe an order of magnitude increase in relative current noise near the transition points. To analyze the origin of this noise enhancement, we use simulations that capture the stochastic dynamics of the phase transition. The simulations indicate that the increased noise stems from amplified phase fluctuations near the percolation threshold, where competing metallic and insulating domains lead to dynamic reconfiguration of the conduction paths. In addition, we show that the precursor current fluctuations observed near the switching threshold are consistent with the threshold voltage variability measured in repeated switching cycles, indicating that the noise sets a lower bound on the achievable variance. These findings offer key insights into the non-equilibrium processes governing phase transitions in nanoscale VO$_2$ devices under electrical stimuli.

cond-mat.mes-hall↗

arXiv2025

Memristor-Driven Spike Encoding for Fully Implantable Cochlear Implants

Objective: This work aims to demonstrate a low-power, biomimetic auditory sensing concept for fully implantable cochlear implants. The approach draws inspiration from the frequency selectivity and temporal encoding of the cochlea, and uses neuromorphic spike generation to replace conventional signal processing blocks. The goal is to establish a compact, energy-efficient front-end architecture suitable for future implantable systems. Methods: An auditory sensing unit was implemented, consisting of a piezoelectric MEMS cantilever mechanically coupled to a single VO$_2$ nanogap Mott memristor-based oscillator. This configuration enables FFT-free, frequency-selective sensing and direct spike generation, forming a biomimetic auditory front end. The concept was experimentally examined using controlled mechanical excitation. Results: The sensing unit exhibited frequency-selective detection of mechanical vibrations in the nanometer to tens-of-nanometers displacement range and generated biomimetic spiking waveforms. Spike rate-encoding of the input amplitude was demonstrated, with output spiking frequencies tunable between approximately 100 Hz and 1 kHz depending on the excitation level. The waveform was finally converted to a biphasic shape suitable for cochlear implant stimulation. Significance: Temporal encoding is fundamental to natural auditory signal processing in the nervous system. By implementing this principle through neuromorphic spike encoding, the proposed approach can provide significant benefits for cochlear implants. In addition, the circuit has the potential to reduce footprint, energy consumption, and latencies compared with current commercial solutions.

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arXiv2025

VO$_2$ oscillator circuits optimized for ultrafast, 100 MHz-range operation

Oscillating neural networks are promising candidates for a new computational paradigm, where complex optimization problems are solved by physics itself through the synchronization of coupled oscillating circuits. Nanoscale VO$_2$ Mott memristors are particularly promising building blocks for such oscillating neural networks. Until now, however, not only the maximum frequency of VO$_2$ oscillating neural networks, but also the maximum frequency of individual VO$_2$ oscillators has been severely limited, which has restricted their efficient and energy-saving use. In this paper, we show how the oscillating frequency can be increased by more than an order of magnitude into the 100 MHz range by optimizing the sample layout and circuit layout. In addition, the physical limiting factors of the oscillation frequencies are studied by investigating the switching dynamics. To this end, we investigate how much the set and reset times slow down under oscillator conditions compared to the fastest switching achieved with single dedicated pulses. These results pave the way towards the realization of ultra-fast and energy-efficient VO$_2$-based oscillating neural networks.

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arXiv2024

Neural information processing and time-series prediction with only two dynamical memristors

Memristive devices are commonly benchmarked by the multi-level programmability of their resistance states. Neural networks utilizing memristor crossbar arrays as synaptic layers largely rely on this feature. However, the dynamical properties of memristors, such as the adaptive response times arising from the exponential voltage dependence of the resistive switching speed remain largely unexploited. Here, we propose an information processing scheme which fundamentally relies on the latter. We realize simple dynamical memristor circuits capable of complex temporal information processing tasks. We demonstrate an artificial neural circuit with one nonvolatile and one volatile memristor which can detect a neural spike pattern in a very noisy environment, fire a single voltage pulse upon successful detection and reset itself in an entirely autonomous manner. Furthermore, we implement a circuit with only two nonvolatile memristors which can learn the operation of an external dynamical system and perform the corresponding time-series prediction with high accuracy.

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arXiv2023

Voltage-time dilemma and stochastic threshold voltage variation in pure silver atomic switches

The formation and dissolution of silver nanowires plays a fundamental role in a broad range of resistive switching devices, fundamentally relying on the electrochemical metallization phenomenon. It was shown, however, that resistive switching may also appear in pure metallic nanowires lacking any silver-ion-hosting embedding environment, but this pure atomic switching mechanism fundamentally differs from the conventional electrochemical-metallization-based resistive switching. To facilitate the quantitative description of the former phenomenon, we investigate broad range of Ag atomic junctions with a special focus on the frequency-dependence and the fundamentally stochastic cycle-to-cycle variation of the switching threshold voltage. These devices are established in an ultra-high purity environment where electrochemical metallization can be excluded. The measured characteristics are successfully described by a vibrational pumping model, yielding consistent predictions for the weak frequency dependence and the large variance of the switching threshold voltage. We also demonstrate that electrochemical-metallization-based resistive switching and pure atomic switching may appear in the same device structure, and therefore the proper understanding of the pure atomic switching mechanism has a distinguished importance in silver-based electrochemical metallization cells.

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arXiv2021

1/f noise spectroscopy and noise tailoring of nanoelectronic devices

In this paper, we review the 1/f-type noise properties of nanoelectronic devices focusing on three demonstrative platforms: resistive switching memories, graphene nanogaps and single-molecule nanowires. The functionality of such ultrasmall devices is confined to an extremely small volume, where bulk considerations on the noise loose their validity: the relative contribution of a fluctuator heavily depends on its distance from the device bottleneck, and the noise characteristics are sensitive to the nanometer-scale device geometry and the details of the mostly non-classical transport mechanism. All these are reflected by a highly system-specific dependence of the noise properties on the active device volume (and the related device resitance), the frequency, or the applied voltage. Accordingly, 1/f-type noise measurements serve as a rich fingerprint of the relevant transport and noise-generating mechanisms in the studied nanoelectronic systems. Finally, we demonstrate that not only the fundamental understanding and the targeted noise suppression is fueled by the 1/f-type noise analysis, but novel probabilistic computing hardware platforms heavily seek well tailorable nanoelectric noise sources.

cond-mat.mes-hall↗

arXiv2016

Precursor configurations and post-rupture evolution of Ag-CO-Ag single-molecule junctions

Experimental correlation analysis and first-principles theory are used to probe the structure and evolution of Ag-CO-Ag single-molecule junctions, both before the formation, and after the rupture of the junctions. Two dimensional correlation histograms and conditional histograms demonstrate that prior to the single-molecule bridge configuration the CO molecule is already bound parallel to the Ag single-atom contact. This molecular precursor configuration is accompanied by the opening of additional conductance channels compared to the single-channel transport in pure Ag monoatomic junctions. To investigate the post-rupture evolution of the junction we introduce a cross-correlation analysis between the opening and the subsequent closing conductance traces. This analysis implies that the molecule is bound rigidly to the apex of one electrode, and so the same single-molecule configuration is re-established as the junction is closed. The experimental results are confirmed by ab initio simulations of the evolution of contact geometries, transmission eigenvalues and scattering wavefunctions.

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