T. Venky Venkatesan1,2
University of Oklahoma1,National Institute of Standards and Technology2
T. Venky Venkatesan1,2
University of Oklahoma1,National Institute of Standards and Technology2
<br/>Artificial intelligence (AI) has been heralded as the flagbearer of the fourth industrial revolution but comes with a cost and that is computing power. It is projected that by 2040, we will need more computing energy than the total energy we can produce now. So, we need devices that can offer higher computing/ storage density with low energy consumption like neurons. We are addressing these challenges using oxide and molecular-electronic based memristors, which enable us to overcome the von Neuman bottleneck by co-locating the memory and computing functions on the same device, as in neuromorphic computing.<br/>I will discuss a variety of strategies for forming oxide based memristors using different phenomena- band filling and creating a quasi-conduction band, using oxygen vacancies to create conductive percolation, using metal-insulator transitions, or using asymmetric tunneling at a ferroelectric barrier. The relative merits of the various approaches will be detailed.<br/>In addition, I will touch upon memristive devices and circuits made from an azo-aromatic complex with extra-ordinary reproducibility, robustness, and scalability. These devices have been shown to switch with energies approaching atto-joules with measured switching times shorter than 5 ns. By using a simple cross bar array, we have shown that these devices perform with an energy-speed product 5000 times that of a state-of-the-art CMOS circuit.<br/><br/><b>References</b><br/><b>1. </b>Sreetosh Goswami*, Rajib Pramanick, Abhijeet Patra, Santi Prasad Rath, Ariando, Damien Thomson, T. Venkatesan*, Sreebrata Goswami* and R Stanley Williams*, <u>Decision Trees within a Molecular Memristor</u>, Nature, Sep. 3, 2021<br/><b>2. </b>Sreetosh Goswami, Adam J. Matula, Santi P. Rath, Svante Hedstrom, Surajit Saha Meenakshi Annamalai, Debabrata Sengupta, Abhijeet Patra, Siddhartha Ghosh, Hariom Jani, Soumya Sarkar, Mallikarjuna Rao Motapothula, Christian A. Nijhuis<sup>,</sup> Jens Martin, Sreebrata Goswami*, Victor S. Batista*, T. Venkatesan*, <u>Robust resistive memory devices using solution-processable metal-coordinated azo-aromatics</u>, Nature Materials, 16, 1216 (2017). News and views on this article: I. Valev and M. Kozicki, Non-volatile Memories: Organic Memristors come of age, Nature Materials, 16, 1170 (2017)<br/><b>3. </b> Rui Guo, Weinan Lin, Xiaobing Yan, T Venkatesan, Jingsheng Chen,<br/>Ferroic tunnel junctions and their application in neuromorphic networks, Applied Physics Reviews, 2020/3/6<br/><b>4. </b> C. J. Li, L. Huang, T. Li, W. M. Lü, X. P. Qiu, Z. Huang, Z. Q. Liu, S. W. Zeng, R. Guo, Y. L. Zhao, K. Zeng, J.MD. Coey, J.S. Chen, Ariando, T. Venkatesan* <i><u>Ultrathin BaTiO<sub>3</sub>-based Ferroelectric Tunnel Junctions through Interface Engineering</u></i>. <b>Nano Letters </b><b>15</b> <b>(4) 2568–2573 (2015<b>)</b></b>