D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Materials Science D-index 63 Citations 12,331 244 World Ranking 3745 National Ranking 946

Overview

What is he best known for?

The fields of study he is best known for:

  • Composite material
  • Polymer
  • Carbon nanotube

Kun Dai mainly investigates Composite material, Carbon nanotube, Electrical conductor, Thermoplastic polyurethane and Nanocomposite. His Composite material study frequently draws connections to adjacent fields such as Percolation threshold. His Carbon nanotube study combines topics from a wide range of disciplines, such as Ultimate tensile strength, Thermal stability, Polyamide and Deformation.

As a part of the same scientific study, Kun Dai usually deals with the Thermoplastic polyurethane, concentrating on Graphene and frequently concerns with Polymer chemistry. His study looks at the relationship between Nanocomposite and fields such as Polyurethane, as well as how they intersect with chemical problems. His Carbon black study also includes fields such as

  • Flexibility most often made with reference to Polydimethylsiloxane,
  • Electrical resistivity and conductivity which connect with Microstructure, Viscoelasticity and Polypropylene.

His most cited work include:

  • Lightweight conductive graphene/thermoplastic polyurethane foams with ultrahigh compressibility for piezoresistive sensing (371 citations)
  • Electrically conductive thermoplastic elastomer nanocomposites at ultralow graphene loading levels for strain sensor applications (337 citations)
  • Electrically conductive strain sensing polyurethane nanocomposites with synergistic carbon nanotubes and graphene bifillers (279 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Composite material, Carbon nanotube, Electrical conductor, Composite number and Carbon black. His study focuses on the intersection of Composite material and fields such as Percolation threshold with connections in the field of Dispersion. The Carbon nanotube study combines topics in areas such as Bending, Nanocomposite, Epoxy and Deformation.

His research in Electrical conductor intersects with topics in Durability, EMI, Polydimethylsiloxane, Electrical resistivity and conductivity and Conductive polymer composite. He has included themes like Temperature coefficient, Polyethylene, Polypropylene and Capillary action in his Carbon black study. His research integrates issues of Porosity, Piezoresistive effect and Graphene in his study of Thermoplastic polyurethane.

He most often published in these fields:

  • Composite material (101.10%)
  • Carbon nanotube (43.41%)
  • Electrical conductor (45.60%)

What were the highlights of his more recent work (between 2019-2021)?

  • Composite material (101.10%)
  • Electrical conductor (45.60%)
  • Carbon nanotube (43.41%)

In recent papers he was focusing on the following fields of study:

Kun Dai spends much of his time researching Composite material, Electrical conductor, Carbon nanotube, Composite number and Thermoplastic polyurethane. His Composite material study combines topics in areas such as Electrical resistivity and conductivity and Graphene. His Electrical conductor study integrates concerns from other disciplines, such as EMI and Optoelectronics.

He combines subjects such as Dielectric loss, Polyimide and Reflection loss with his study of Carbon nanotube. His work deals with themes such as Ultimate tensile strength, Thermal conductivity, Electromagnetic interference, Polymer and Electromagnetic shielding, which intersect with Composite number. He works mostly in the field of Thermoplastic polyurethane, limiting it down to topics relating to Piezoresistive effect and, in certain cases, Percolation threshold.

Between 2019 and 2021, his most popular works were:

  • Asymmetric conductive polymer composite foam for absorption dominated ultra-efficient electromagnetic interference shielding with extremely low reflection characteristics (35 citations)
  • Lightweight and Robust Carbon Nanotube/Polyimide Foam for Efficient and Heat-Resistant Electromagnetic Interference Shielding and Microwave Absorption. (35 citations)
  • Ultra-stretchable triboelectric nanogenerator as high-sensitive and self-powered electronic skins for energy harvesting and tactile sensing (28 citations)

In his most recent research, the most cited papers focused on:

  • Composite material
  • Polymer
  • Ceramic

Kun Dai mainly investigates Composite material, Graphene, Electromagnetic interference, EMI and Electromagnetic shielding. His work in the fields of Composite material, such as Thermoplastic polyurethane, intersects with other areas such as Gauge factor. His Thermoplastic polyurethane research is multidisciplinary, relying on both Porosity and Carbon black.

The various areas that Kun Dai examines in his Graphene study include Biocompatibility, Durability and Electrospinning. His Electromagnetic interference research incorporates elements of Electrical conductor, Optoelectronics, Composite number and Carbon nanotube. His Carbon nanotube research integrates issues from Ultimate tensile strength, Electromagnetic interference shielding and Polyimide.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Lightweight conductive graphene/thermoplastic polyurethane foams with ultrahigh compressibility for piezoresistive sensing

Hu Liu;Hu Liu;Mengyao Dong;Wenju Huang;Jiachen Gao.
Journal of Materials Chemistry C (2017)

537 Citations

Electrically conductive thermoplastic elastomer nanocomposites at ultralow graphene loading levels for strain sensor applications

Hu Liu;Yilong Li;Kun Dai;Guoqiang Zheng.
Journal of Materials Chemistry C (2016)

492 Citations

Electrically conductive strain sensing polyurethane nanocomposites with synergistic carbon nanotubes and graphene bifillers

Hu Liu;Hu Liu;Jiachen Gao;Wenju Huang;Kun Dai.
Nanoscale (2016)

447 Citations

Electrically conductive polymer composites for smart flexible strain sensors: a critical review

Hu Liu;Hu Liu;Qianming Li;Shuaidi Zhang;Rui Yin.
Journal of Materials Chemistry C (2018)

414 Citations

Continuously prepared highly conductive and stretchable SWNT/MWNT synergistically composited electrospun thermoplastic polyurethane yarns for wearable sensing

Yahong Li;Bing Zhou;Guoqiang Zheng;Xianhu Liu.
Journal of Materials Chemistry C (2018)

357 Citations

Flexible electrically resistive-type strain sensors based on reduced graphene oxide-decorated electrospun polymer fibrous mats for human motion monitoring

Yalong Wang;Ji Hao;Zhenqi Huang;Guoqiang Zheng.
Carbon (2018)

283 Citations

The effect of filler dimensionality on the electromechanical performance of polydimethylsiloxane based conductive nanocomposites for flexible strain sensors

Yanjun Zheng;Yilong Li;Zeyu Li;Yalong Wang.
Composites Science and Technology (2017)

248 Citations

Carbon Nanotubes-Adsorbed Electrospun PA66 Nanofiber Bundles with Improved Conductivity and Robust Flexibility.

Xiaoyang Guan;Guoqiang Zheng;Kun Dai;Chuntai Liu.
ACS Applied Materials & Interfaces (2016)

246 Citations

Electrically conductive carbon black (CB) filled in situ microfibrillar poly(ethylene terephthalate) (PET)/polyethylene (PE) composite with a selective CB distribution

Kun Dai;Xiang-Bin Xu;Zhong-Ming Li.
Polymer (2007)

246 Citations

A highly stretchable and stable strain sensor based on hybrid carbon nanofillers/polydimethylsiloxane conductive composites for large human motions monitoring

Yanjun Zheng;Yilong Li;Kun Dai;Kun Dai;Yan Wang.
Composites Science and Technology (2018)

235 Citations

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