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Synaptic Switching with Halide Perovskites

Objective

Metal halide perovskites are attracting much attention because they are excellent semiconductors for use in optoelectronic devices such as solar cells, LEDs, and detectors. Next to electrons, these materials also conduct ions efficiently, and both types of conduction are modulated by light. Ion migration is mostly known to have undesirable effects in optoelectronic devices, such as hysteresis, degradation, and phase segregation. However, the interaction of light, electronic conduction and ionic motion also offers a rich parameter space to envision entirely new devices, which is almost completely unexplored until now.

I want to pioneer this new field, uncovering insights to help mitigate the undesirable effects of ion migration, and at the same time creating artificial synapses and neurons as new applications based on halide perovskites. I will first develop a novel set of techniques to study ion migration, including a technique similar to impedance spectroscopy to map the energy, density, and timescale of ions and defect states. This will allow me to distinguish ions from charge traps which usually complicate measurements. Next, I will use the new tools to pursue a complete understanding and control of the material parameters that determine ion migration. This control over the ionic motion allows me to rationally design properties of the perovskite-based artificial synapses and neurons with the potential to develop massively parallel neural networks for ultra-low power neuromorphic computation.

I am in a unique position to successfully complete the proposed program because of my pioneering role in the understanding of ion migration in perovskite materials and track record of inventing new optoelectronic devices. The proposed program will both benefit the commercialization of perovskite-based electronic devices and open new avenues for ion-based innovations.

Field of science

  • /natural sciences/physical sciences/electromagnetism and electronics/optoelectronics
  • /natural sciences/computer and information sciences/artificial intelligence/computational intelligence

Call for proposal

ERC-2020-STG
See other projects for this call

Funding Scheme

ERC-STG - Starting Grant

Host institution

STICHTING NEDERLANDSE WETENSCHAPPELIJK ONDERZOEK INSTITUTEN
Address
Winthontlaan 2
3526 KV Utrecht
Netherlands
Activity type
Research Organisations
EU contribution
€ 1 500 000

Beneficiaries (1)

STICHTING NEDERLANDSE WETENSCHAPPELIJK ONDERZOEK INSTITUTEN
Netherlands
EU contribution
€ 1 500 000
Address
Winthontlaan 2
3526 KV Utrecht
Activity type
Research Organisations