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Updated: Aug 13, 2026
08:07
Ultrahigh Density Array of Vertically Aligned Small-molecular Organic Nanowires on Arbitrary Substrates
Published on: June 18, 2013
C─H Arylation-Derived Organic Conjugated Molecules for Optoelectronic Synaptic Transistors
Yiyu Chen1, Bin Hu1, Jingpeng Wu1
1Frontier Institute of Science and Technology, State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an, China.
Small (Weinheim an Der Bergstrasse, Germany)
|August 12, 2026
Summary
Researchers developed eco-friendly organic molecules for neuromorphic computing. These materials enable high-performance photonic transistors that mimic brain functions, advancing artificial intelligence hardware.
Area of Science:
- Organic electronics
- Neuromorphic computing
- Materials science
Background:
- Photonic organic field-effect transistors (OFETs) are crucial for neuromorphic computing.
- Current organic optoelectronic materials have limited functionality.
- Conventional synthesis methods lack atom economy.
Purpose of the Study:
- Develop novel organic conjugated molecules for enhanced OFET performance.
- Utilize eco-friendly synthesis strategies.
- Create high-performance synaptic transistors for artificial neural networks.
Main Methods:
- Synthesized two isomeric organic conjugated molecules (p-Ph2FTT and o-Ph2FTT) using direct C─H activation.
- Investigated molecular planarity and its effect on charge transport.
- Fabricated and tested p-Ph2FTT/PDVT-10 synaptic transistors under blue light stimulation.
Main Results:
- p-Ph2FTT exhibited superior planarity and charge transport compared to o-Ph2FTT.
- The p-Ph2FTT/PDVT-10 transistor showed distinct synaptic responses and high photosensitivity (6.7 × 10^4).
- An artificial neural network using this transistor achieved 92.84% accuracy in handwritten digit recognition.
Conclusions:
- Established a paradigm for green synthesis of multifunctional molecular materials.
- Demonstrated the integration of eco-friendly chemistry and high-performance electronics.
- Advanced the development of organic transistors for efficient neuromorphic computing.
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