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Understanding how junction resistances impact the conduction mechanism in nano-networks

Author

Listed:
  • Cian Gabbett

    (CRANN & AMBER Research Centres, Trinity College Dublin)

  • Adam G. Kelly

    (CRANN & AMBER Research Centres, Trinity College Dublin
    Universidade NOVA de Lisboa, Campus de Caparica)

  • Emmet Coleman

    (CRANN & AMBER Research Centres, Trinity College Dublin)

  • Luke Doolan

    (CRANN & AMBER Research Centres, Trinity College Dublin)

  • Tian Carey

    (CRANN & AMBER Research Centres, Trinity College Dublin)

  • Kevin Synnatschke

    (CRANN & AMBER Research Centres, Trinity College Dublin)

  • Shixin Liu

    (CRANN & AMBER Research Centres, Trinity College Dublin)

  • Anthony Dawson

    (CRANN & AMBER Research Centres, Trinity College Dublin)

  • Domhnall O’Suilleabhain

    (CRANN & AMBER Research Centres, Trinity College Dublin)

  • Jose Munuera

    (CRANN & AMBER Research Centres, Trinity College Dublin
    University of Oviedo)

  • Eoin Caffrey

    (CRANN & AMBER Research Centres, Trinity College Dublin)

  • John B. Boland

    (CRANN & AMBER Research Centres, Trinity College Dublin)

  • Zdeněk Sofer

    (University of Chemistry and Technology Prague)

  • Goutam Ghosh

    (Delft University of Technology)

  • Sachin Kinge

    (Toyota Motor Europe)

  • Laurens D. A. Siebbeles

    (Delft University of Technology)

  • Neelam Yadav

    (Trinity College Dublin 2)

  • Jagdish K. Vij

    (Trinity College Dublin 2)

  • Muhammad Awais Aslam

    (Montanuniversität Leoben)

  • Aleksandar Matkovic

    (Montanuniversität Leoben)

  • Jonathan N. Coleman

    (CRANN & AMBER Research Centres, Trinity College Dublin)

Abstract

Networks of nanowires, nanotubes, and nanosheets are important for many applications in printed electronics. However, the network conductivity and mobility are usually limited by the resistance between the particles, often referred to as the junction resistance. Minimising the junction resistance has proven to be challenging, partly because it is difficult to measure. Here, we develop a simple model for electrical conduction in networks of 1D or 2D nanomaterials that allows us to extract junction and nanoparticle resistances from particle-size-dependent DC network resistivity data. We find junction resistances in porous networks to scale with nanoparticle resistivity and vary from 5 Ω for silver nanosheets to 24 GΩ for WS2 nanosheets. Moreover, our model allows junction and nanoparticle resistances to be obtained simultaneously from AC impedance spectra of semiconducting nanosheet networks. Through our model, we use the impedance data to directly link the high mobility of aligned networks of electrochemically exfoliated MoS2 nanosheets (≈ 7 cm2 V−1 s−1) to low junction resistances of ∼2.3 MΩ. Temperature-dependent impedance measurements also allow us to comprehensively investigate transport mechanisms within the network and quantitatively differentiate intra-nanosheet phonon-limited bandlike transport from inter-nanosheet hopping.

Suggested Citation

  • Cian Gabbett & Adam G. Kelly & Emmet Coleman & Luke Doolan & Tian Carey & Kevin Synnatschke & Shixin Liu & Anthony Dawson & Domhnall O’Suilleabhain & Jose Munuera & Eoin Caffrey & John B. Boland & Zde, 2024. "Understanding how junction resistances impact the conduction mechanism in nano-networks," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48614-5
    DOI: 10.1038/s41467-024-48614-5
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    References listed on IDEAS

    as
    1. Zhaoyang Lin & Yuan Liu & Udayabagya Halim & Mengning Ding & Yuanyue Liu & Yiliu Wang & Chuancheng Jia & Peng Chen & Xidong Duan & Chen Wang & Frank Song & Mufan Li & Chengzhang Wan & Yu Huang & Xiang, 2018. "Solution-processable 2D semiconductors for high-performance large-area electronics," Nature, Nature, vol. 562(7726), pages 254-258, October.
    2. Cian Gabbett & Luke Doolan & Kevin Synnatschke & Laura Gambini & Emmet Coleman & Adam G. Kelly & Shixin Liu & Eoin Caffrey & Jose Munuera & Catriona Murphy & Stefano Sanvito & Lewys Jones & Jonathan N, 2024. "Quantitative analysis of printed nanostructured networks using high-resolution 3D FIB-SEM nanotomography," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    3. Hao Qiu & Tao Xu & Zilu Wang & Wei Ren & Haiyan Nan & Zhenhua Ni & Qian Chen & Shijun Yuan & Feng Miao & Fengqi Song & Gen Long & Yi Shi & Litao Sun & Jinlan Wang & Xinran Wang, 2013. "Hopping transport through defect-induced localized states in molybdenum disulphide," Nature Communications, Nature, vol. 4(1), pages 1-6, December.
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