4.8 Article

Flexible and Insoluble Artificial Synapses Based on Chemical Cross-Linked Wool Keratin

Journal

ADVANCED FUNCTIONAL MATERIALS
Volume 30, Issue 45, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/adfm.202002882

Keywords

artificial synapses; chemical cross-link; flexible electronics; keratin; memristors

Funding

  1. China Scholarship Council
  2. NUS AcRF Tier 1 [R-144-000-416-114]
  3. 111 project [B16029]
  4. Doctoral Fund of the Ministry of Education [20130121110018]
  5. Science and Technology Project of Xiamen City [3502Z20183012]
  6. Science and Technology Planning Project of Guangdong Province [2018B030331001]
  7. Shenzhen Science and technology plan project [JCYJ20180504170208402]
  8. Natural Science Foundation of China [61306098, 61674050, 61422407, 61874158]
  9. Natural Science Foundation of Hebei Province [E2012201088, E2013201176]
  10. Science Research Program of University in Hebei Province [ZH2012019]
  11. project of enhancement comprehensive strength of the Midwest universities of Hebei University
  12. Outstanding Youth Project of Hebei Province [F2016201220]

Ask authors/readers for more resources

Designing suitable material systems to construct artificial synapses and exploring novel synaptic functions is a crucial step toward the realization of efficient large-scale bioinspired neuromorphic systems. In this work, flexible and insoluble bio-memristor devices are fabricated by precisely engineering the molecular structures of wool keratin. This flexible Ag/keratin/indium tin oxide-polyethylene naphthalate synaptic device possesses enhanced mechanical resistance, which is achieved by photo-cross-linking keratin molecules, and can withstand a bending radius of up to 1.2 mm. This device is promising for implantable applications because it is water-resistant. When modulated by triangle-wave DC voltages and pulsed voltages, this flexible electronic device emulates typical memristor characteristics and synaptic functions, including potentiation/depression, spike timing dependent plasticity, and long-term/short-term plasticity. Simulation results indicate that a memristor network made by this wool-keratin based device has approximate to 95.8% memory learning accuracy and capability for pattern learning. Combined, these features prove that the cross-linked wool-keratin based device has potential in wearable and flexible neuron computing systems.

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