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A FeFET based super-low-power ultra-fast embedded NVM technology for 22nm FDSOI and beyond

Dunkel, S., Trentzsch, M., Richter, R., Moll, P., Fuchs, C., Gehring, O., Majer, M., Wittek, S., Muller, B., Melde, T., Mulaosmanovic, H., Slesazeck, S., Muller, S., Ocker, J., Noack, M., Lohr, D.-A., Polakowski, P., Muller, J., Mikolajick, T., Hontschel, J., Rice, B., Pellerin, J., Beyer, S.·2017·2017 IEEE International Electron Devices Meeting (IEDM)

Abstract

We show the implementation of a ferroelectric field effect transistor (FeFET) based eNVM solution into a leading edge 22nm FDSOI CMOS technology. Memory windows of 1.5 V are demonstrated in aggressively scaled FeFET cells with an area as small as 0.025 μm2At this point program/erase endurance cycles up to 105are supported. Complex pattern are written into 32 MBit arrays using ultrafast program/erase pulses in a 10 ns range at 4.2 V. High temperature retention up to 300 °C is achieved. It makes FeFET based eNVM a viable choice for overall low-cost and low-power IoT applications in 22nm and beyond technology nodes.

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Metadata

Authors
Dunkel, S., Trentzsch, M., Richter, R., Moll, P., Fuchs, C., Gehring, O., Majer, M., Wittek, S., Muller, B., Melde, T., Mulaosmanovic, H., Slesazeck, S., Muller, S., Ocker, J., Noack, M., Lohr, D.-A., Polakowski, P., Muller, J., Mikolajick, T., Hontschel, J., Rice, B., Pellerin, J., & Beyer, S.
Venue
2017 IEEE International Electron Devices Meeting (IEDM)
Publisher
IEEE
Published
2017-12
Pages
19.7.1-19.7.4
ISSN
0163-1918 (ISSN-L)
OpenAlex
W2786159202
Cited by
540
References
0
FWCI
50.20
Type
conference paper
Language
en
Open access
closed

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The paper
Dunkel, S., Trentzsch, M., Richter, R., Moll, P., Fuchs, C., Gehring, O., Majer, M., Wittek, S., Muller, B., Melde, T., Mulaosmanovic, H., Slesazeck, S., Muller, S., Ocker, J., Noack, M., Lohr, D.-A., Polakowski, P., Muller, J., Mikolajick, T., . . . Beyer, S. (2017). A FeFET based super-low-power ultra-fast embedded NVM technology for 22nm FDSOI and beyond. 2017 IEEE International Electron Devices Meeting (IEDM). https://doi.org/10.1109/iedm.2017.8268425

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.