Mathieu Luisier

Last Name

Luisier

First Name

Mathieu

ORCID

0000-0002-2212-7972

Organisational unit

03925 - Luisier, Mathieu / Luisier, Mathieu

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Publications1 - 10 of 74

Analysis of temperature-dependent optical gain in GaN-InGaN quantum-well structures
Witzigmann, Bernd; Laino, Valerio; Luisier, Mathieu; et al. (2006)
IEEE Photonics Technology Letters
The temperature dependent spectral gain in InGaN-GaN multiple quantum-well structures with 10% In content is investigated. Mode gain is measured in a temperature range between 239 K and 312 K using the Hakki-Paoli technique and compared to simulations. The simulation accounts for temperature-dependent polarization dephasing, and hence homogeneous broadening, in a rigorous fashion, without any fit parameter. It is found that the evolution of the gain spectrum with temperature at different drive currents can be modeled using a temperature-independent single value for inhomogeneous broadening. The resulting compositional fluctuations are compared to structural measurements.
Ab initio quantum transport simulations of defective devices based on 2-D materials via a projected-GW approach
Gandus, Guido; Cao, Jiang; Agarwal, Tarun Kumar; et al. (2022)
2022 International Electron Devices Meeting (IEDM)
We propose a novel ab inito defect modeling framework for devices based on two-dimensional (2-D) transition-metal dichalcogenide (TMDC) monolayers. The so-called projected (p)- GW method is combined with density functional theory and incorporated into the non-equilibrium Green’s function equations to efficiently and accurately investigate the influence of various defect types on the characteristics of 2-D field-effect transistors. Through quasi-particle correlated defect-level modeling, we show that one single defect located inside the channel under the gate is a main source to block the current flow, thus leading to a large performance degradation. Our variability study also confirms that defects inside transistors based on 2-D TMDC monolayers induce a significant threshold voltage shift and ON-state current variation.
Termination-Dependent Resistive Switching in SrTiO3 Valence Change Memory Cells
Mladenović, Marko; Kaniselvan, Manasa; Weilenmann, Christoph; et al. (2025)
ACS Applied Electronic Materials
Valence change memory (VCM) cells based on SrTiO3 (STO), a perovskite oxide, are a promising type of emerging memory device. While the operational principle of most VCM cells relies on the growth and dissolution of one or multiple conductive filaments, those based on STO are known to exhibit a distinctive “interface-type” switching, which is associated with the modulation of the Schottky barrier at their active electrode. Still, a detailed picture of the processes that lead to interface-type switching is not available. In this work, we use a fully atomistic ab initio model to study the resistive switching of a Pt-STO-Ti stack. We identify that the termination of the crystalline STO plays a decisive role in the switching mechanism, depending on the relative band alignment between the material and the Pt electrode. In particular, we show that the accumulation of oxygen vacancies at the Pt side can be the origin of resistive switching in TiO2-terminated devices by lowering the conduction band minimum of the STO layer, thus facilitating transmission through the Schottky barrier. Moreover, we investigated the possibility of filamentary switching in STO and revealed that it is most likely to occur at the Pt electrode of the SrO-terminated cells.
Multiscale Modeling of Metal-Oxide-Metal Conductive Bridging Random-Access Memory Cells: From Ab Initio to Finite-Element Calculations
Aeschlimann, Jan; Ducry, Fabian; Weilenmann, Christoph; et al. (2023)
Physical Review Applied
We present a multiscale simulation framework to compute the current versus voltage (I-V) characteristics of metal-oxide-metal structures building the core of conductive bridging random-access memory (CBRAM) cells and to shed light on their resistance switching properties. The approach relies on a finite-element model whose input material parameters are extracted either from ab initio or from machine-learned empirical calculations. The applied techniques range from molecular dynamics and nudged elastic band to electronic and thermal quantum transport. Such an approach drastically reduces the number of fitting parameters needed and makes the resulting modeling environment more accurate than traditional ones. The developed computational framework is then applied to the investigation of an Ag/a-SiO2/Pt CBRAM, reproducing experimental data very well. Moreover, the relevance of Joule heating is assessed by considering various cell geometries. It is found that self-heating manifests itself in devices with thin conductive filaments with few-nanometer diameters and at current concentrations in the tens-microampere range. With the proposed methodology it is now possible to explore the potential of not-yet fabricated memory cells and to reliably optimize their design.
InP/GaAsSb DHBTs: THz Analog Performance and Record 180-Gb/s 5.5Vppd-Swing PAM-4 DAC-Driver
Bolognesi, Colombo R.; Arabhavi, Akshay M.; Hersent, Romain; et al. (2022)
2022 IEEE BiCMOS and Compound Semiconductor Integrated Circuits and Technology Symposium (BCICTS)
"Type-II" InP/GaAsSb DHBTs are the first non-GaInAs -based transistors to show oscillation frequencies > 1 THz with the associated benefits of higher breakdown voltages, low power dissipation, and superior linearity and scaling characteristics. Whereas no large-signal characterization of THz transistors is found in the literature, THz InP/GaAsSb DHBTs display attractive 94 GHz load-pull characteristics, and less aggressively scaled devices achieve record saturated output power and output power density per unit emitter area. The physical advantages of Type-II InP/GaAsSb are reviewed here. Beyond impressive analog small/large-signal performance metrics, we report a record mixed-signal performance for a PAM-4 DAC-driver designed and fabricated at III-V Lab in a 0.7-μm InP/GaAsSb DHBT technology implemented on epitaxial layers grown at ETHZ. The DAC-driver offers an unprecedented 5.5-Vppd 90-GBd (180 Gb/s) differential output swing with high eye diagram quality and over 12-dB gain control capability at a 1.1-W power consumption, leading to a record 3.1-GBd E/O modulator driver figure-of-merit (FoM). PAM-4 operation at 112-Gb (224 Gb/s) is also demonstrated with 3.35-Vppd and 0.6-W dissipation, also with a record 2.6-GBb E/O FoM. A 110 GHz bandwidth linear driver with a 16.7 dB gain and 0.85-W consumption was also implemented in the same technology, enabling a 4.1-Vppd output swing at 100 Gb/s both in PAM-4 and NRZ signaling. The all-around outstanding performance of InP/GaAsSb DHBTs makes them attractive for a wide variety of analog and mixed-signal circuit blocks used in modern telecommunication applications.
Atomic-Scale Electronics and Photonics for Sustainable AI Technologies and Beyond
Csontos, Miklos; Emboras, Alexandros; Leuthold, Juerg; et al. (2025)
SPG Mitteilungen
Light-Controlled Switching in Electro-Optical Memristors
Portner, Kevin; Weilenmann, Christoph; Maeder, Alexander; et al. (2022)
Technical Digest Series ~ Conference on Lasers and Electro-Optics
We demonstrate a new concept in an electro-optical memristor where a global light stimulus induces non-volatile conductance changes. The optical signal acts as a third, independent stimulation channel, similar to neuromodulators in three-factor learning rules.
Distinct Contact Scaling Effects in MoS2 Transistors Revealed with Asymmetrical Contact Measurements
Cheng, Zhihui; Backman, Jonathan; Zhang, Huairuo; et al. (2023)
Advanced Materials
2D semiconducting materials have immense potential for future electronics due to their atomically thin nature, which enables better scalability. While the channel scalability of 2D materials has been extensively studied, the current understanding of contact scaling in 2D devices is inconsistent and oversimplified. Here physically scaled contacts and asymmetrical contact measurements (ACMs) are combined to investigate the contact scaling behavior in 2D field-effect transistors. The ACMs directly compare electron injection at different contact lengths while using the exact same MoS2 channel, eliminating channel-to-channel variations. The results show that scaled source contacts can limit the drain current, whereas scaled drain contacts do not. Compared to devices with long contact lengths, devices with short contact lengths (scaled contacts) exhibit larger variations, 15% lower drain currents at high drain-source voltages, and a higher chance of early saturation and negative differential resistance. Quantum transport simulations reveal that the transfer length of Ni-MoS2 contacts can be as short as 5 nm. Furthermore, it is clearly identified that the actual transfer length depends on the quality of the metal-2D interface. The ACMs demonstrated here will enable further understanding of contact scaling behavior at various interfaces.
Single neuromorphic memristor closely emulates multiple synaptic mechanisms for energy efficient neural networks
Weilenmann, Christoph; Ziogas, Alexandros Nikolaos; Zellweger, Till; et al. (2024)
Nature Communications
Biological neural networks do not only include long-term memory and weight multiplication capabilities, as commonly assumed in artificial neural networks, but also more complex functions such as short-term memory, short-term plasticity, and meta-plasticity - all collocated within each synapse. Here, we demonstrate memristive nano-devices based on SrTiO3 that inherently emulate all these synaptic functions. These memristors operate in a non-filamentary, low conductance regime, which enables stable and energy efficient operation. They can act as multi-functional hardware synapses in a class of bio-inspired deep neural networks (DNN) that make use of both long- and short-term synaptic dynamics and are capable of meta-learning or learning-to-learn. The resulting bio-inspired DNN is then trained to play the video game Atari Pong, a complex reinforcement learning task in a dynamic environment. Our analysis shows that the energy consumption of the DNN with multi-functional memristive synapses decreases by about two orders of magnitude as compared to a pure GPU implementation. Based on this finding, we infer that memristive devices with a better emulation of the synaptic functionalities do not only broaden the applicability of neuromorphic computing, but could also improve the performance and energy costs of certain artificial intelligence applications.
Atomistic Modeling of Valence Change Memory Devices: What Can We Learn from Simulations?
Mladenović, Marko; Luisier, Mathieu (2025)
Advanced Electronic Materials
Resistive switching devices based on the valence change effect have shown promise for applications in emerging in-memory and neuromorphic computing architectures. To support the development of such valence change memory (VCM) cells and enhance their figures of merit, a deep understanding of their operational principle is essential. Atomistic simulations can provide important insight to reach these objectives. Indeed, advanced models have been used to link the atomic structure and functionality of VCMs, as well as to simulate the key processes occurring in them. In particular, their electro-forming and cycling behavior can be revealed through accurate simulations, while optimized device stacks with improved performance have been suggested and demonstrated experimentally. In this review, we therefore discuss how different atomistic modeling techniques can be combined and leveraged to shed light on the operation of VCM cells. Specifically, we outline which properties can be extracted with each method and give examples to illustrate the strengths and weaknesses of the approaches considered.

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Mathieu Luisier

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