MRS Meetings and Events


EQ11.04.05 2022 MRS Spring Meeting

Fully-Printed Ag/TiO2/Ag Electronic Synapses for Brain-Inspired Computing

When and Where

May 10, 2022
3:15pm - 3:30pm

Hawai'i Convention Center, Level 3, 318A



Varvara Salonikidou1,2,Adnan Mehonic3,Yasunori Takeda4,Jonathan England1,Judith MacManus-Driscoll2,Shizuo Tokito4,Radu Sporea1

University of Surrey1,University of Cambridge2,University College London3,Yamagata University4


Varvara Salonikidou1,2,Adnan Mehonic3,Yasunori Takeda4,Jonathan England1,Judith MacManus-Driscoll2,Shizuo Tokito4,Radu Sporea1

University of Surrey1,University of Cambridge2,University College London3,Yamagata University4
Synapses play a key role in learning and perception and avail as a model for efficient brain-inspired computing. Devices that emulate bio-synaptic plasticity present an auspicious route to energy-efficient and agile neuromorphic computing. <i>Synaptic plasticity</i> refers to the ability of synapses to alter interneural strength in an event-based manner, according to the history and timing characteristics of preceding trigger impulses[1]. Synaptic plasticity entails activity-dependent transitions from short-term potentiation (STP) to long-term potentiation (LTP) (<i>memorization effect</i>) and vice versa (<i>forgetting effect</i>). The trigger firing conditions (sequence, timing, intensity) under which these effects occur govern memorization and adaptive learning[2], thus constitute the foundation of information processing and in-memory computing in neuromorphic electronics. The most promising candidates for computational nodes are the two-terminal resistive switching (RS) memristive devices due to their intrinsic property to alter their resistance states in a step wise manner when voltage trigger applied across their terminal, enabling analog RS with both volatile and non-volatile properties[3]. The dynamic nature of their transitional properties is shown to have commonalities with bio-synaptic plasticity, and this is a rich field far from fully explored[4].<br/>The present work demonstrates an alternative approach to the realization of electronic synapses for in-memory computing. The fabrication was realized through low-cost and self-sufficient processes. A solely additive approach, the emerging inkjet printing technique [5–8] was used as a universal fabrication method. The developed fully printed devices were based on Ag/a-TiO<sub>2</sub>/Ag structures and developed by implementing an a-TiO<sub>2</sub> custom-made ink, functionalised for inkjet printing compatibility, while also retaining its printing and electrical properties for an optimal period (&gt;five months). The ink produced crack-free nanolayers with adjustable functional thickness in the range of 80 to 350 nm.<br/>The printed nano-electronic synapses were characterised electrically through voltage pulses in order to investigate their dynamic properties in time. Due to the amorphous phase of the active layer, the RS was able to be induced under low voltage pulses, thus reducing the overall power requirement. The devices demonstrated transitions from STP to LTP that occurred in a step wise and event-based manner, emulating bio-synaptic plasticity. This memorisation effect along with the switching rate and reset process were all effectively controlled by changing solely the trigger’s duty cycle (α = pulse duration / period (%)). Notably, there is an indication of <i>homeostatic regulation</i> in RS. Similar to biology, the synaptic strength (here conductance) did not increase perpetually but was bounded within a range thus maintaining an equilibrium.<br/>Consequently, these minimally structured, low-cost and eco-friendly neuromorphic nodes constitute a fruitful avenue toward the development of flexible neural networks. The optimized ink formulation and the thorough investigation of the electrical framework under which these devices respond synaptically represent a path to unconventional computing with applications in biomimetic sensing and prosthetics.<br/><i>[1] W.A.Catterall, A.P. Few, Neuron <b>2008</b>, 59, 882<br/>[2] J.Fiser, P.Berkes, G.Orbán, M.Lengyel,Trends Cogn. Sci. <b>2010</b>, 4,119<br/>[3] C.Wang, W.He, Y.Tong, R.Zhao, Sci. Rep. <b>2016</b>, 6, 1<br/>[4] S.Choi, J.Yang, G.Wang, Adv. Mater. <b>2020</b>,32,1<br/>[5] W.Lee, T.Someya, Chem. Mater. <b>2019</b>, acs. chemmater<br/>[6] W.Banerjee, S.H.Kim, S.Lee, D.Lee, H.Hwang, <b>2021</b><br/>[7] T.Someya, Z. Bao, G. G. Malliaras, Nature <b>2016</b>, 540, 379</i><br/><i>[8] B.Salonikidou, Y.Takeda, B.Le Borgne, J.England, T.Shizuo, R.A.Sporea, ACS Appl. Electron. Mater. <b>2019</b>, 1</i>


ink-jet printing | thermal diffusivity

Symposium Organizers

Yoeri van de Burgt, Technische Universiteit Eindhoven
Yiyang Li, University of Michigan
Francesca Santoro, Forschungszentrum Jülich/RWTH Aachen University
Ilia Valov, Research Center Juelich

Symposium Support

Nextron Corporation

Publishing Alliance

MRS publishes with Springer Nature