- King Abdullah University of Science and Technology
- China
About Mario Lanza
Mario Lanza is an Associate Professor of Materials Science and Engineering at the King Abdullah University of Science and Technology (KAUST), in Saudi Arabia since October 2020. Dr. Lanza got his PhD in Electronic Engineering with honors in 2010 at Universitat Autonoma de Barcelona. During the PhD he was a visiting scholar at The University of Manchester (UK) and Infineon Technologies (Germany). In 2010-2011 he was NSFC postdoc at Peking University, and in 2012-2013 he was Marie Curie postdoc at Stanford University. On October 2013 he joined Soochow University as Associate Professor, and in March 2017 he was promoted to Full Professor. Prof. Lanza has published over 120 research papers, including Science, Nature Electronics, Nature Chemistry, and IEDM, edited a book for Wiley-VCH, and registered four patents (one of them granted with 5.6 Million CNY). Prof. Lanza has received the 2017 Young Investigator Award from Microelectronic Engineering (Elsevier), and the 2015 Young 1000 Talent award (among others), and in 2019 he was appointed as Distinguished Lecturer of the Electron Devices Society (IEEE-EDS). Prof. Lanza is Associate Editor of Scientific Reports (Nature) and Microelectronic Engineering (Elsevier), and serves in the board of many others, like Advanced Electronic Materials (Wiley-VCH), Nanotechnology and Nano Futures (IOP). He is also an active member of the technical committee of several world-class international conferences, including IEEE-IEDM, IEEE-IRPS, IEEE-IPFA and APS. Prof. Lanza leads a research group formed by 10-15 PhD students and postdocs, and they investigate how to improve electronic devices using 2D materials, with special emphasis on two-dimensional (layered) dielectrics and memristors for non-volatile digital information storage and artificial intelligence computing systems.
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Nature Electronics
Wafer-scale integration of 2D materials in high-density memristive crossbar arrays for artificial neural networks
Memristors made of multilayer hexagonal boron nitride exhibit multiple properties (such as ultra-low power consumption and multiple stable states) that make them ideal for the construction of crossbar arrays for artificial neural networks.
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Very nice paper and prototype, congratulations for the excellent work ! As a constructive observation, the endurance plot could be improved by presenting one data point per cycle instead of one data point per decade (see also M. Lanza et al. ACS Nano 2021, 15, 11, 17214–17231, also available here: https://pubs.acs.org/doi/10.1021/acsnano.1c06980).
Congratulations, outstanding work in the field of 2D materials !
Wonderful work, congratulations !
That is a very attractive work because it goes towards wafer scale integration and shows variability information. Congratulations to the authors !
Excellent work, congratulations to the entire team !
This is a fantastic work because it really addresses the problem of 2D solid-state microelectronic devices and circuits, which is integration and device-to-device variability. Congratulations to all the authors.
Congratulations Chetan ! Very beautiful stuff, I feel very happy for you. Well deserved !
Wonderful contribution and flatchat :-)