Miklos Csontos

Last Name

Csontos

First Name

Miklos

ORCID

0000-0002-2766-6860

Organisational unit

03974 - Leuthold, Juerg / Leuthold, Juerg

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Publications 1 - 10 of 47

A fast operation of nanometer-scale metallic memristors: highly transparent conductance channels in Ag2S devices
Geresdi, Attila; Csontos, Miklos; Gubicza, Agnes; et al. (2014)
Nanoscale
The nonlinear transport properties of nanometer-scale junctions formed between an inert metallic tip and an Ag film covered by a thin Ag2S layer are investigated. Suitably prepared samples exhibit memristive behavior with technologically optimal ON and OFF state resistances yielding to resistive switching on the nanosecond time scale. Utilizing point contact Andreev reflection spectroscopy, we studied the nature of electron transport in the active volume of memristive junctions showing that both the ON and OFF states correspond to truly nanometer-scale, highly transparent metallic channels. Our results demonstrate the merits of Ag2S nanojunctions as nanometer-scale memory cells which can be switched by nanosecond voltage pulses.
Emergence of bound states in ballistic magnetotransport of graphene antidots
Rakyta, Péter; Tóvári, Endre; Csontos, Miklos; et al. (2014)
Physical Review B
An experimental method for detection of bound states around an antidot formed by a hole in a graphene sheet is proposed via measuring the ballistic two-terminal conductance. In particular, we consider the effect of bound states formed by a magnetic field on the two-terminal conductance and show that one can observe Breit-Wigner-like resonances in the conductance as a function of the Fermi level close to the energies of the bound states. In addition, we develop a numerical method utilizing a reduced computational effort compared to the existing numerical recursive Green's function methods.
VO2 Oscillator Circuits Optimized for Ultrafast, 100 MHz‐Range Operation
Pollner, Zsigmond; Török, Tímea Nóra; Pósa, László; et al. (2025)
Advanced Electronic Materials
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. VO2 Mott memristors are particularly promising building blocks for such oscillating neural networks. Until now, however, not only the maximum frequency of VO2 oscillating neural networks, but also the maximum frequency of individual VO2 oscillators is severely limited, which has restricted their efficient and energy-saving use. In this study, it is showed how to increase the oscillating frequency by more than an order of magnitude into the 100 MHz range utilizing ultrasmall, ≈30 nm wide active volume VO2 devices and optimizing the circuit layout for high frequency operation. In addition, the physical limiting factors of the oscillation frequencies are studied by investigating the complex switching dynamics of our nanoscale VO2 devices. These dynamical studies, together with simulations, provide a clear conclusion on the maximum achievable operating frequencies and the optimal operating parameters under which these can be reached.
Three‐Terminal Memristor with Tunable Volatility and Set Voltage
Srikrishnaprabhu, Kshipra; Lewerenz, Mila; Fischer-Butesheva, Markus; et al. (2025)
Advanced Electronic Materials
Brain-inspired computing solutions require a suitable hardware platform, where complex operations can be realized at low power consumption. Ideally, the hardware can be reconfigured between multiple functionalities by tuning the corresponding device parameters. In this work, a three-terminal silver–tin alloyed memristor is demonstrated, where the resistive switching characteristics can be modulated by the gate voltage. The polarity of the gate voltage determines the volatility of the device. Positive gate voltages result in primarily nonvolatile switching, while negative gate voltages facilitate primarily volatile switching. In addition, the set voltage and low resistance state can be adjusted by the magnitude of gate voltage both in the volatile and nonvolatile regimes. The dimensions of the active switching volume are 40 nm × 6 nm × 10 nm, making the design one of the most compact three-terminal memristor. Such an ultrasmall, versatile memristive device represents a viable candidate for reconfigurable, neuromorphic hardware, where the basic building blocks can be conveniently customized to perform either synaptic or neural operations.
Atomic-Scale Electronics and Photonics for Sustainable AI Technologies and Beyond
Csontos, Miklos; Emboras, Alexandros; Leuthold, Juerg; et al. (2025)
SPG Mitteilungen
Anisotropic Zeeman shift in p-type GaAs quantum point contacts
Komijani, Yashar; Csontos, Miklos; Shorubalko, Ivan; et al. (2013)
Europhysics Letters
Low-temperature electrical conductance spectroscopy measurements of quantum point contacts implemented in p-type GaAs/AlGaAs heterostructures are used to study the Zeeman splitting of 1D subbands for both in-plane and out-of-plane magnetic field orientations. The resulting in-plane g-factors agree qualitatively with those of previous experiments on quantum wires while the quantitative differences can be understood in terms of the enhanced quasi-1D confinement anisotropy. The influence of confinement potential on the anisotropy is discussed and an estimate for the out-of-plane g-factor is obtained which, in contrast to previous experiments, is close to the theoretical prediction. © Copyright EPLA, 2013.
Multiple Physical Time Scales and Dead Time Rule in Few-Nanometers Sized Graphene–SiOx-Graphene Memristors
Pósa, László; El Abbassi, Maria; Makk, Péter; et al. (2017)
Nano Letters
The resistive switching behavior in SiOx-based phase change memory devices confined by few nanometer wide graphene nanogaps is investigated. Our experiments and analysis reveal that the switching dynamics is not only determined by the commonly observed bias voltage dependent set and reset times. We demonstrate that an internal time scale, the dead time, plays a fundamental role in the system’s response to various driving signals. We associate the switching behavior with the formation of microscopically distinct SiOx amorphous and crystalline phases between the graphene electrodes. The reset transition is attributed to an amorphization process due to a voltage driven self-heating; it can be triggered at any time by appropriate voltage levels. In contrast, the formation of the crystalline ON state is conditional and only occurs after the completion of a thermally assisted structural rearrangement of the as-quenched OFF state which takes place within the dead time after a reset operation. Our results demonstrate the technological relevance of the dead time rule which enables a zero bias access of both the low and high resistance states of a phase change memory device by unipolar voltage pulses.
Anomalous Hall Effect in the (In,Mn)Sb Dilute Magnetic Semiconductor
Mihály, György; Csontos, Miklos; Bordacs, Sándor; et al. (2008)
Physical Review Letters
High magnetic field study of Hall resistivity in the ferromagnetic phase of (In,Mn)Sb allows one to separate its normal and anomalous components. We show that the anomalous Hall term is not proportional to the magnetization, and that it even changes sign as a function of magnetic field. We also show that the application of pressure modifies the scattering process, but does not influence the Hall effect. These observations suggest that the anomalous Hall effect in (In,Mn)Sb is an intrinsic property and supports the application of the Berry phase theory for (III,Mn)V semiconductors. We propose a phenomenological description of the anomalous Hall conductivity, based on a field-dependent relative shift of the heavy- and light-hole valence bands and the split-off band.
Noise diagnostics of graphene interconnects for atomic-scale electronics
Pósa, László; Balogh, Zoltán; Krisztián, Dávid; et al. (2021)
npj 2D Materials and Applications
Graphene nanogaps are considered as essential building blocks of two-dimensional electronic circuits, as they offer the possibility to interconnect a broad range of atomic-scale objects. Here we provide an insight into the microscopic processes taking place during the formation of graphene nanogaps through the detailed analysis of their low-frequency noise properties. Following the evolution of the noise level, we identify the fundamentally different regimes throughout the nanogap formation. By modeling the resistance and bias dependence of the noise, we resolve the major noise-generating processes: atomic-scale junction-width fluctuations in the nanojunction regime and sub-atomic gap-size fluctuations in the nanogap regime. As a milestone toward graphene-based atomic electronics, our results facilitate the automation of an optimized electrical breakdown protocol for high yield graphene nanogap fabrication.
Picosecond Femtojoule Resistive Switching in Nanoscale VO2 Memristors
Schmid, Sebastian Werner; Pósa, László; Török, Tímea Nóra; et al. (2024)
Beyond-Moore computing technologies are expected to provide a sustainable alternative to the von Neumann approach not only by their down-scaling potential but also via exploiting device-level functional complexity at the lowest possible energy consumption. The dynamics of the Mott transition in correlated electron oxides, such as vanadium dioxide, has been identified as a rich and reliable source of such functional complexity. However, its full potential in high-speed and low-power operation has been largely unexplored. We studied nanoscale VO2 devices in a broad-band setup to reveal the speed and energy limitations of their resistive switching operation. Our picosecond time-resolution, real-time resistive switching experiments and numerical simulations demonstrate that tunable low-resistance states can be set by the application of 20 ps long, <1.7 V amplitude voltage pulses at 15 ps incubation times and switching energies starting from 1 fJ. Moreover, we demonstrate that at nanometer-scale device sizes not only the electric field induced insulator-to-metal transition is ultra-fast, but also the thermal conduction limited metal-to-insulator transition can take place at timescales of 100's of picoseconds. These orders of magnitude breakthroughs open the route to the design of high-speed and low-power dynamical circuits for a plethora of neuromorphic computing applications from pattern recognition to numerical optimization.

Publications 1 - 10 of 47

Miklos Csontos

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