MEMMEA

Hybrid MEMristor-CMOS Micro Electrode Array bio-sensing platform

Partner

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Prof. Dr. Catherine Dubourdieu

Prof. Dr. Catherine Dubourdieu

Helmholtz-Zentrum Berlin für Materialien und Energie GmbH

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Dr.-Ing. Stephan Menzel

Dr.-Ing. Stephan Menzel

Forschungszentrum Jülich

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Prof. Roland Thewes

Prof. Roland Thewes

FG Sensorik u. Aktuatorik, TU Berlin

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Dr. Peter Jones

Dr. Peter Jones

NMI an der Universität Tübingen

Outcome

MEMMEA emulator at embedded world 2024
All-in-OComparative study of usefulness of FeFET, FTJ and ReRAM technology for ternary arithmeticne Solution

Dietmar Fey; John Reuben; Stefan Slesazeck

2021 28th IEEE International Conference on Electronics, Circuits, and Systems (ICECS), 28 November 2021 - 01 December 2021, Dubai, United Arab Emirates

DOI: 10.1109/ICECS53924.2021.9665635

INVOLVED SCIENTISTS

Onur Toprak

Onur Toprak

PhD Student

Helmholtz-Zentrum Berlin für Materialien und Energie GmbH

Rana Walied Ahmad

Rana Walied Ahmad

PhD Student

Forschungszentrum Jülich

Alex Wiemhoefer

Alex Wiemhoefer

PhD Student

FG Sensorik u. Aktuatorik, TU Berlin

Tom Stumpp

Tom Stumpp

PhD Student

NMI an der Universität Tübingen

Project Description

Recording of neuronal activities provides a path to understanding brain’s functionality. Chip-based neuronal probes such as CMOS -based micro-electrode arrays (MEA) have made significant progress in recent years providing a platform to record neuronal electrical signals in vitro from multiple sites. This has tremendously progressed neuronal activity recording in real-time. However, it is essential to have low power circuit architecture capable of on-chip neuronal signal processing and electrical stimulation to enable implantable brain stimulation chips. Current CMOS-only neuronal probes have restrictions in power budget to achieve such fully implantable autonomous neuroprosthetics. Therefore, one needs research efforts bringing together energy efficient devices and novel low power circuit design techniques to develop a power efficient system.

Memristive devices with their unique characteristics of gradual resistance change, pulse summation, and thresholding behavior can enable compact circuits for neuronal data processing. Therefore, we propose to explore and develop an integrated platform of memristive devices and CMOS MEAs to enable real time power-efficient neuronal sensing probes. This proposal targets on-chip co-integration of memristive devices with CMOS MEA circuits to detect, process neural tissue activity and eventually provide ability for electrical stimulation feedback. In the proposed research, novel memristor-CMOS hybrid circuits will be developed to achieve on-chip signal processing. The development of these new circuit techniques will open doors for broader bio sensing applications.

To conduct such an ambitious project, the proposal brings together the best expertise from a broad range of areas: device fabrication and electrical characterization, physical and compact modeling, CMOS circuit design, and in vitro biological characterization. The consortium consists of researchers from HZB, TUB, FZJ, and NMI, leveraging the expertise of four partners who are internationally recognized players in their respective area. In order to demonstrate the neuronal probe platform following objectives are targeted:

Objective 1: Development of smart neuron sensors through fabrication of memristive devices on top of CMOS micro-electrode array (MEA) neuron activity sensing chips.

Objective 2: Development of a memristive device compact model based on fabricated device characteristics and utilization for circuit design.

Objective 3: Optimization of memristive device architecture to achieve power efficient and reliable processing of biological neuronal signals (spike detection in single cells and populations).

Objective 4: Characterization of memristive device response to wide range of pulse widths generated on-chip (down to ~1 ns) to advance device physics understanding as well as compact model optimization.

The ultimate vision of the proposal is to develop an energy efficient bio-sensing platform based on memristive device-CMOS hybrid circuits.

 

Further involved scientists

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Onur Toprak

Onur Toprak

Helmholtz-Zentrum Berlin für Materialien und Energie GmbH

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Tom Stumpp

Tom Stumpp

NMI an der Universität Tübingen

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Walied Ahmad

Walied Ahmad

Forschungszentrum Jülich