Evolving electronic transport in molecules/nanoparticles networks – EVOLMONET

Networks of molecularly functionalized nanoparticles (NPs) (hereafter called NMN : nanoparticle molecule network) have emerged as an interesting approach in molecular electronics to understand fundamental electron transport mechanisms, as well as to develop potential applications in electronics, sensing and computing circuits. NMNs with simple molecules (alkyl chains, short p-conjugated oligomers) were used to study metal-insulator transitions, plasmonic and co-tunneling for instance. NMNs were also demonstrated as useful and versatile platforms to study optically driven molecular switches and redox molecules leading to NMNs with memory and negative differential resistance behaviors.
The long-term objective of EVOLMONET in the field of electronics and unconventional computing circuits is to use a network of self-assembled metallic nanoparticles connected by electrically switchable molecules to implement reconfigurable logic gates though genetic algorithms. In the field of unconventional computing (artificial neural networks), the usefulness of these kinds of networks was theoretically proposed, and very preliminary experimental results were published for networks of atomic switches (Ag2S-based), metallic wires and by us for molecules/nanoparticles network.
In EVOLMONET, we will explore electron transport at high frequency and dynamics in NMNs made of Au NPs functionalized by various types of novel molecular building blocks, tailored to exhibit event-driven evolving functionalities. We will address three classes of molecules: i) optically driven switches; ii) THz activated switches and iii) ion molecular switches.
Nanoscale systems exhibiting strongly non-linear electron transport behaviors and complex nonlinear internal dynamics (NLID) are prone to be used in a neuro-inspired "reservoir computing (RC)" approach. Our objective is to explore how the HHG (high harmonic generation) and NLID can be modified by light or redox or ionic mechanism, which paves the way for the reconfigurable processing of multi-input signals through a device that acts as a reservoir computer.
In EVOLMONET, we define the two following objectives:
OBJECTIVE 1: Evolve the performances of the NMNs in a reservoir computing perspective by improving the NMNs performances (operation and switching speed).
This raises the question of the maximum speed operation of molecular devices: theoretical studies have predicted transit times through molecular junctions in the femtoseconds to picoseconds regime, allowing, in principle, operations in the THz regime. However, so far, molecular devices have only been demonstrated, operated, in the low-frequency regime (20 kHz), a serious limitation from a device perspective. Specifically, our aim will be to investigate possible giant enhancements (many orders of magnitudes) of the dynamic conductance as a function of the ac frequency (> 60 GHz).
The second mandatory improvement is the need for a faster conductance switching.
For the non photochromic molecules, the theoretically predicted switching between different conduction states in a molecular junction triggered by a passing electromagnetic pulse in the THz range will be explored using a THz-STM available at IEMN in the "Microwave Characterization Center".
OBJECTIVE 2: Nanoparticle/molecule networks:
Electron transport and dynamics vs. network topology: a special attention will be paid to elucidate the correlation between the evolving distribution of the conduction pathways in the NMNs and the variability of the observed functions and dynamic charge transport properties at the several output electrodes, which are likely to depend on the topology (and its modification) of the molecular conducting pathways into the NMNs upon molecule conductance switching.