All Outputs (4)

In-Materio Extreme Learning Machines (2022)
Book Chapter
Jones, B. A., Al Moubayed, N., Zeze, D. A., & Groves, C. (2022). In-Materio Extreme Learning Machines. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tušar (Eds.), Parallel Problem Solving from Nature – PPSN XVII (505-519). Springer Verlag. https://doi.org/10.1007/978-3-031-14714-2_35

Nanomaterial networks have been presented as a building block for unconventional in-Materio processors. Evolution in-Materio (EiM) has previously presented a way to congure and exploit physical materials for computation, but their ability to scale as... Read More about In-Materio Extreme Learning Machines.

Organic Floating-Gate Memory Structures (2017)
Book Chapter
Fakher, S., Sleiman, A., Ayesh, A., Al-Ghaferi, A., Petty, M., Zeze, D., & Mabrook, M. (2017). Organic Floating-Gate Memory Structures. In P. Dimitrakis (Ed.), Emerging Materials and Structures (123-156). Springer Verlag

CNT-based two terminal organic nonvolatile memory devices. (2015)
Book Chapter
Sleiman, A., Mabrook, M., Sayers, P., & Zeze, D. (2015). CNT-based two terminal organic nonvolatile memory devices. In S. Logothetidis (Ed.), Handbook of Flexible Organic Electronics: Materials, Manufacturing and Applications (413-428). Woodhead Publishing Series

Fabrication and Characterisation of MIS Organic Memory Devices (2009)
Book Chapter
Mabrook, M., Kolb, D., Pearson, C., Zeze, D., & Petty, M. (2009). Fabrication and Characterisation of MIS Organic Memory Devices. In P. Pietro Vincenzini, & G. D'Arrigo (Eds.), Smart Materials & Micro/Nanosystems (474-479)