Showing posts with label Neuromorphic computing. Show all posts
Showing posts with label Neuromorphic computing. Show all posts

Apr 3, 2026

[paper] Memristors SPICE Compact Modeling

Thomas Günkel1,2, Aleix Barrera1, Lluís Balcells1, Narcís Mestres1, 
Enrique Miranda2, Anna Palau1, Jordi Suñé2
SPICE-Compatible Compact Modeling of Cuprate-Based Memristors Across
a Wide Temperature Range 
Advanced Electronic Materials (2026): e00861
DOI: https://doi.org/10.1002/aelm.202500861

1 Institut de Ciència de Materials de Barcelona, ICMAB-CSIC, Bellaterra (SP)
2 Departament d’Enginyeria Electrònica, Universitat Autònoma de Barcelona (SP)

ABSTRACT: Cryogenic memristors based on the high-temperature superconductor YBa2 CuO7−δ offer significant potential as nonvolatile memory elements or unit cell for analog artificial neural networks for future applications such as control units for quantum processors, cryogenic data centers or space-related electronics. In this work, the experimental switching capabilities of cuprate-based memristors are analyzed in terms of the material-specific physics. This work investigates the experimental switching behavior of cuprate-based memristors across temperatures from cryogenic to room temperature. The underlying interpretation, namely the trapping of injected charge carriers at a metal interface and field-induced detrapping, is incorporated into a physically inspired compact model. The core equations of this model consist of a differential balance equation and a current equation, which is derived from space-charge limited conduction. Comparison with experimental data shows that the model successfully reproduces the key features of the measured switching behavior across a wide temperature range, spanning from 80 to 300 K. Additionally, we implement the model in SPICE, enabling circuit-level simulations. The resulting compact model provides a useful framework for guiding experimental studies, capturing key features of the switching behavior, and bridging the gap between device-levelcharacterization and circuit-level design.

FIG: LTspice Simulations: (a) Implementation of the compact model into a LTspice schematic. The diagram is explained in more detail in the main text. Simulation results of the hysteron V(r) and the 𝐼𝑉 -characteristics abs(I(B2)) depending on the input signal V(v) are given for a simple sinusoidal input signal in (b) and a damped waveform in (c).
 
Acknowledgments: The authors acknowledge financial support from the Spanish Ministry of Science and Innovation MCIN/ AEI /10.13039/501100011033/ through CHIST-ERA PCI2021-122028-2A co-financed by the European Union Next Generation EU/PRTR, the “Severo Ochoa” Programme for Centres of Excellence CEX2023-001263-S, HTSUPERFUN PID2021-124680OB-I00,and HTS-4ICT PID2024-156025OB-I00, co-financed by ERDF A way of making Europe. The Spanish Nanolito networking project (RED2022-134096-T). The European COST Action SUPERQUMAP (CA 21144). EMand JS would like to thank the support the Spanish Ministerio deCiencia e Innovación (MCIN) / Agencia Española de investigación (AEI)10.13039/501100011 033 (Under project No. PID2022-139586NB-C41). TG acknowledge support from AGAUR Catalan Government Predoctoral Fellowship (2022 FISDU 00115). J.S. and E. M. acknowledge the support of the EU through the HORIZON Chips-JU 101194172 NeAIxt Project and the Agencia Española de Investigación (AEI)/10.13039/501100011033 under Project PCI2025-163216. The authors acknowledge the Scientific Servicesat ICMAB and the UAB PhD program in Materials Science.



Feb 21, 2023

[Book] More-than-Moore Devices and Integration for Semiconductors

More-than-Moore Devices and Integration
for Semiconductors
Editors: Francesca Iacopi and Francis Balestra
Publisher: Springer Cham
DOI: 10.1007/978-3-031-21610-7

This book provides readers with a comprehensive, state-of-the-art reference for miniaturized More-than-Moore systems with a broad range of functionalities that can be added to 3D microsystems, including flexible electronics, metasurfaces and power sources. The book also includes examples of applications for brain-computer interfaces and event-driven imaging systems.
  • Provides a comprehensive, state-of-the-art reference for miniaturized More-than-Moore systems;
  • Covers functionalities to add to 3D microsystems, including flexible electronics, metasurfaces and power sources;
  • Includes current applications, such as brain-computer interfaces, event - driven imaging and edge computing.
Table of contents (7 chapters)
  • Front Matter Pages i-xiv
  • Energy Harvesters and Power Management Pages 1-45
    Michail E. Kiziroglou, Eric M. Yeatman
  • SiC and GaN Power Devices Pages 47-104
    Konstantinos Zekentes, Victor Veliadis, Sei-Hyung Ryu, Konstantin Vasilevskiy, Spyridon Pavlidis, Arash Salemi et al.
  • Flexible and Printed Electronics Pages 105-125
    Benjamin Iñiguez
  • Terahertz Metasurfaces, Metawaveguides, and Applications Pages 127-156
    Wendy S. L. Lee, Shaghik Atakaramians, Withawat Withayachumnankul
  • Mechanical Robustness of Patterned Structures and Failure Mechanisms
    Ehrenfried Zschech, Maria Reyes Elizalde Pages 157-189
  • Neuromorphic Computing for Compact LiDAR Systems Pages 191-240
    Dennis Delic, Saeed Afshar
  • Integrated Sensing Devices for Brain-Computer Interfaces Pages 241-258
    Tien-Thong Nguyen Do, Ngoc My Hanh Duong, Chin-Teng Lin
Acknowledgements: We would like to thank the following colleagues for their help in peer-reviewing this book’s material: Dr. Yang Yang and Dr. Diep Nguyen (University of Technology Sydney, Australia); Prof. Xuan-Tu Tran (Vietnam National University Hanoi), Prof. Gustavo Ardila and Prof. Pascal Xavier (University Grenoble Alpes, France); and Prof. Edwige Bano (Grenoble INP, France). FI would also like to acknowledge support from the Australian Research Council Centre of Excellence in Transformative MetaOptical Systems (TMOS, CE200100010).

Francesca Iacopi, Ultimo, NSW, Australia 
Francis Balestra, Grenoble, France