Technische Universität Dresden

Contact

Dr. Adnan Mehonic
University College London
Department of Electronic & Electrical Engineering
Torrington Place – London WC1E 7JE

+44(0)20 7679 3162

At University Colleg London

Research Field and Activities

  • Neuromorphic systems based on nano electronic resistance switching devices
  • Fabrication and characterization of resistive switching devices
  • Numerical methods

Short Biography

Dr. Adnan Mehonic is an Associate Professor of Nanoelectronics and Royal Academy of Engineering Senior Research Fellow at University College London and the Co-founder and Chief Technology Officer of Intrinsic Semiconductor Technologies. His research spans energy-efficient nanoelectronic devices and systems, encompassing fundamental materials science, novel device design, and memory and efficient computing hardware design.
He pioneered the development of oxide-based memristors, providing key insights into switching mechanisms, device-, algorithm- and system-level designs. Adnan has published more than 100 journal articles and conference papers and is named on 15 international patents. He has been recognised by inclusion in MIT Technology Review’s “35 Innovators Under 35, EMRS EU-40 Prize, ” Wiley’s “Rising Star,” and UCL’s “One to Watch.”
Alongside his academic career, he has successfully translated academic research into industrial impact, securing over £15 million in venture funding for Intrinsic Semiconductor Technologies, building a successful start-up consisting of a team of 15 highly skilled engineers and scientists, and developing mature industry prototypes through multiple collaborations with international industrial centres. He is the founding Editor-in-Chief of APL Machine Learning, where he fosters collaboration between applied physics and artificial intelligence communities, and a co-director of NeuMat, the Neuromorphic Network in the UK, dedicated to supporting and uniting researchers, industry professionals, and innovators working on neuromorphic technologies for advanced, novel, and energy-efficient AI hardware.

References / Teachings

  • A. Mehonic, D. Jokšas, W.H. Ng, A. Buckwell, and A.J. Kenyon, “Simulation of Inference Accuracy Using Realistic RRAM Devices,” Frontiers in Neuroscience, vol. 13, p. 593, 2019. DOI: https://doi.org/10.3389/fnins.2019.00593
  • A. Mehonic, A.L. Shluger, D. Gao, I. Valov, E. Miranda, D. Ielmini, A. Bricalli, E. Ambrosi, C. Li, J.J. Yang, and Q. Xia, “Silicon Oxide (SiOx): A Promising Material for Resistance Switching?” Advanced Materials, vol. 30, no. 3, 1801187, 2018. DOI: https://doi.org/10.1002/adma.201801187
  • W.H. Ng, A. Mehonic, M.S. Munde, M. Buckwell, D. Jokšas, and A.J. Kenyon, “The interplay between structure and function in redox-based resistance switching,” Faraday Discussions, 2018. DOI: https://doi.org/10.1039/c8fd00125f
  • S. Munde, A. Mehonic, W.H. Ng, M. Buckwell, L. Montesi, M. Bosman, A.L. Shluger, and A.J. Kenyon, “Intrinsic Resistance Switching in Amorphous Silicon Suboxides: The Role of Columnar Microstructure,” Scientific Reports, vol. 7, no. 1, p. 9274, 2017. DOI: https://doi.org/10.1038/s41598-017-09981-1
  • A. Mehonic, M.S. Munde, W.H. Ng, M. Buckwell, L. Montesi, M. Bosman, A.L. Shluger, and A.J. Kenyon, “Intrinsic resistance switching in amorphous silicon oxide for high performance SiOx ReRAM devices,” Microelectronic Engineering, vol. 178, pp. 98–103, 2017. DOI: https://doi.org/10.1016/j.mee.2017.03.008
  • A. Mehonic, M. Buckwell, L. Montesi, M. Munde, D. Gao, S. Hudziak, R.J. Chater, S. Fearn, D. McPhail, M. Bosman, and A.L. Shluger, “Nanoscale Transformations in Metastable, Amorphous, Silicon-Rich Silica,” Advanced Materials, vol. 28, no. 34, pp. 7486–7493, 2016. DOI: https://doi.org/10.1002/adma.201603469
  • A. Mehonic and A.J. Kenyon, “Emulating the electrical activity of the neuron using a silicon oxide RRAM cell,” Frontiers in Neuroscience, vol. 10, p. 57, 2016. DOI: https://doi.org/10.3389/fnins.2016.00057
  • A. Mehonic, A. Vrajitoarea, S. Cueff, S. Hudziak, H. Howe, C. Labbe, R. Rizk, M. Pepper, and A.J. Kenyon, “Quantum conductance in silicon oxide resistive memory devices,” Scientific Reports, 2013. DOI: https://doi.org/10.1038/srep03299
  • A. Mehonic, S. Cueff, M. Wojdak, S. Hudziak, C. Labbé, R. Rizk, and A.J. Kenyon, “Electrically tailored resistance switching in silicon oxide,” Nanotechnology, vol. 23, no. 45, p. 455201, 2012. DOI: https://doi.org/10.1088/0957-4484/23/45/455201
  • A. Mehonic, S. Cueff, M. Wojdak, S. Hudziak, O. Jambois, C. Labbé, B. Garrido, R. Rizk, and A.J. Kenyon, “Resistive switching in silicon suboxide films,” Journal of Applied Physics, vol. 111, no. 7, p. 074507, 2012. DOI: https://doi.org/10.1063/1.4710579
  • A. Mehonic, et al., “Resistive switching in silicon suboxide films,” Journal of Applied Physics, vol. 111, p. 074507, 2012. DOI: https://doi.org/10.1063/1.3701581
  • A. Mehonic and A.J. Kenyon, “Brain-inspired computing needs a master plan,” Nature, vol. 604, pp. 255–260, 2022. DOI: https://doi.org/10.1038/s41586-021-04362-w