Till Zellweger

Last Name

Zellweger

First Name

Till

ORCID

0000-0001-9402-8917

Organisational unit

03925 - Luisier, Mathieu / Luisier, Mathieu

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Publications 1 - 10 of 18

Self-induced light emission in solid-state memristors replicates neuronal biophotons
Malchow, Konstantin; Zellweger, Till; Cheng, Bojun; et al. (2024)
arXiv
Key pre-synaptic and post-synaptic biological functions have been successfully implemented in various hardware systems. A noticeable example are neuronal networks constructed from memristors, which are emulating complex electro-chemical biological dynamics such a neuron's efficacy and plasticity. Neurons are highly active cells, communicating with chemical and electrical stimuli, but also emit light. These photons are suspected to be a complementary vehicle to transport information across the brain. Here, we show that a memristor also releases photons akin to the production of neuronal light. Critical attributes of so-called biophotons such as self-generation, origin, stochasticity, spectral coverage, sparsity and correlation with the neuron's activity are replicated by our solid-state approach. Our findings further extend the emulating capability of a memristor to encompass neuronal biophoton emission and open the possibility to construct a bimodal electro-optical platform with the assistance of atomic-scale devices capable of handling electrons and photons as information carriers.
Atomic scale memristive photon source
Cheng, Bojun; Zellweger, Till; Malchow, Konstantin; et al. (2022)
Light: Science & Applications
Memristive devices are an emerging new type of devices operating at the scale of a few or even single atoms. They are currently used as storage elements and are investigated for performing in-memory and neuromorphic computing. Amongst these devices, Ag/amorphous-SiOx/Pt memristors are among the most studied systems, with the electrically induced filament growth and dynamics being thoroughly investigated both theoretically and experimentally. In this paper, we report the observation of a novel feature in these devices: The appearance of new photoluminescent centers in SiOx upon memristive switching, and photon emission correlated with the conductance changes. This observation might pave the way towards an intrinsically memristive atomic scale light source with applications in neural networks, optical interconnects, and quantum communication.
An Atomistic Investigation of the Electronic and Thermal Transport Properties of Crystalline and Amorphous Germanium
Aguinsky, Luiz Felipe; Milardovich, Diego; Zellweger, Till; et al. (2024)
IEEE NANO 2024: Book of Abstracts
Atomic-Scale Memristive Plasmonics
Leuthold, Juerg; Cheng, Bojun; Koch, Ueli; et al. (2022)
OSA Technical Digest ~ Optica Advanced Photonics Congress 2022
Plasmonics is a powerful tool to miniaturize photonics. In this review, we introduce memristive plasmonics as a technique to shrink photonic devices to the atomic scale. We show atomic-scale plasmonic switches, detectors and emitters.
Phase-Change Memory from Molecular Tellurides
Schenk, Florian M.; Zellweger, Till; Kumaar, Dhananjeya; et al. (2024)
ACS Nano
Phase-change memory (PCM) is an emerging memory technology based on the resistance contrast between the crystalline and amorphous states of a material. Further development and realization of PCM as a mainstream memory technology rely on innovative materials and inexpensive fabrication methods. Here, we propose a generalizable and scalable solution-processing approach to synthesize phase-change telluride inks in order to meet demands for high-throughput material screening, increased energy efficiency, and advanced device architectures. Bulk tellurides, such as Sb₂Te₃, GeTe, Sc₂Te₃, and TiTe₂, are dissolved and purified to obtain inks of molecular metal telluride complexes. This allowed us to unlock a wide range of solution-processed ternary tellurides by the simple mixing of binary inks. We demonstrate accurate and quantitative composition control, including prototype materials (Ge–Sb–Te) and emerging rare-earth-metal telluride-doped materials (Sc–Sb–Te). Spin-coating and annealing convert ink formulations into high-quality, phase-pure telluride films with preferred orientation along the (00l) direction. Deposition engineering of liquid tellurides enables thickness-tunable films, infilling of nanoscale vias, and film preparation on flexible substrates. Finally, we demonstrate cyclable and non-volatile prototype memory devices, achieving performance indicators such as resistance contrast and low reset energy on par with state-of-the-art sputtered PCM layers.
Photon Emission by Silicon-Based Memristors
Zellweger, Till; Cheng, Bojun; Malchow, Konstantin; et al. (2022)
OSA Technical Digest ~ European Conference on Optical Communication (ECOC) 2022
We introduce a new category of nanoscale photon sources based on memristors with silicon-based switching matrices. These novel photon sources exhibit light emission during the switching of their resistive state. The photon emission is attributed to the creation and excitation of silicon nanoclusters.
Inkjet-Printed Phase Change Memory Devices
He, Hanglin; Kumaar, Dhananjeya; Portner, Kevin; et al. (2024)
Advanced Electronic Materials
Phase change memory (PCM) is among the most promising candidates for the next generation of storage-class and main memory systems in the computing era beyond Moore's law. However, the widespread installment of PCM devices is limited by the high price-per-bit and complex fabrication process. In this paper, it is shown that functional PCM memory devices can be printed, proving low-cost avenues for non-silicon memory technologies. Taking Ge-Sb-Te (GST) as a case study, PCM inks are prepared and optimize their structural, rheological, and printing parameters. GST layers are then printed onto PCM devices in the planar configuration, showing excellent performance, such as non-volatility, resistivity contrast, low cycle-to-cycle variability, and endurance of at least 100 cycles. This paper provides a novel approach to liquid-based engineered PCM devices through inkjet printing, enabling patterned memory layers, lower price-per-bit, and customizable multi-material PCM arrays.
Co-Integration of an Analog, CMOS-Compatible Electro-Optical Conductive Metal-Oxide/HfO2 Memristor with Si Photonics
Portner, Kevin; Begon-Lours, Laura; Bragaglia, Valeria; et al. (2023)
Emulating biological learning rules through neuromorphic hardware is key to create energy-efficient computing systems for artificial intelligence. In this regard, neo-Hebbian three-factor learning rules are of particular interest as they describe the influence of global neuromodulators on synaptic plasticity and thus allow for biologically plausible realizations of reinforcement learning algorithms. Three-terminal memristors are ideal candidates to directly implement three-factor learning rules on-device, provided that the third terminal can modulate their conductance independently from the two conventional electrodes. Moreover, the emulation of synaptic plasticity also requires a continuous linear and symmetric conductance modulation.
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.
Self-Induced Light Emission in Solid-State Memristors Replicates Neuronal Biophotons
Malchow, Konstantin; Zellweger, Till; Cheng, Bojun; et al. (2024)
ACS Nano
Key neuronal functions have been successfully replicated in various hardware systems. Noticeable examples are neuronal networks constructed from memristors, which emulate complex electrochemical biological dynamics such as the efficacy and plasticity of a neuron. Neurons are highly active cells, communicating with chemical and electrical stimuli, but also emit light. These so-called biophotons are suspected to be a complementary vehicle to transport information across the brain. Here, we show that a memristor also releases photons during its operation akin to the production of neuronal light. Critical attributes of biophotons, such as self-generation, stochasticity, spectral coverage, sparsity, and correlation with the neuron's electrical activity, are replicated by our solid-state approach. Importantly, our time-resolved analysis of the correlated current transport and photon activity shows that emission takes place within a nanometer-sized active area and relies on electrically induced single-to-few active electroluminescent centers excited with moderate voltage (<3 V). Our findings further extend the emulating capability of a memristor to encompass neuronal optical activity and allow to construct memristive atomic-scale devices capable of handling simultaneously electrons and photons as information carriers.

Publications 1 - 10 of 18

Till Zellweger

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