Molecular nanostructures & computing

  • Nanoparticle-molecule networks (NMNs) for computing

ToCWe demonstrate optically-driven switchable logical operations in nanoparticles self-assembled networks of molecular switches (azobenzene derivatives) interconnected by Au nanoparticles.  The complex non-linearity of electron transport and dynamics in these highly connected and recurrent networks of molecular junctions exhibit rich high harmonics generation (HHG) required for reservoir computing (RC) approaches. These results, without direct analogs in semiconductor devices, open new perspectives to molecular electronics in unconventional computing  [Y. Viero et al., Adv. Func. Mater. (2018)].

Main coll. : M. Calame (EMPA & Univ. Basel, Switzerland).

  • Organic synapstor (synapse-transistor)

org synapstorIn 2010, we demonstrated the concept of synapstor (synapse transistor) that the main functionalities of a biological synapse are achievable with an organic hybrid transistor (organic semiconductor and gold nanoparticles) [F. Alibart et al. Adv. Func. Mater.  (2010), F. Alibart et al., Adv. Func. Mater. (2012)]. Recently, we extended these results with the demonstration of the operation of these synapstors at very low voltages (50 mV), in an electrolyte-gated configuration [S. Desbief et al. Org. Electron. (2015); M. di Lauro et al., Adv. Electron. Mater. (2017)], and we demonstrated that they can be interfaced with living biological neurons [S. Desbief et al. Org. Electron. (2016)], which made these devices prone for a possible brain/neurocomputer interface.

Main coll.: C. Gamrat (CEA-LIST), F. Biscarini (Dipartimento di Scienze della Vita,
Università di Modena e Reggio Emilia, Modena, Italy); Y. Geerts (Lab. Chimie des Polymères,
Université Libre de Bruxelles, Belgium).

  • Organic electrochemical transistors for reservoir computing.

OECT-RCWe investigated iono-electronic materials and devices, in which electronic conduction is controlled by ion dynamics [S. Pecqueur et al., Org. Electron. (2018), S.Pecqueur et al. Org. Electron. (2019)]. We have demonstrated pattern recognitions in a network of OECTs (organic electrochemical transistor) interacting in a common electrolyte [S. Pecqueur et al., Adv. Electron. Mater. (2018)]. based on the concept of  “reservoir computing” (i.e. a spatio-temporal data processing in a network with complex dynamics and strong non-linearities).

Main coll.: P. Blanchard, J. Roncali (CNRS, Moltech-Anjou, U. Angers); C. Gamrat (CEA-LIST, Saclay), Z. Crljen (RBI, Zagreb, Croatia).