Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2019Anchoring a Co/2-methylimidazole complex on ion-exchange resin and its transformation to Co/N-doped carbon as an electrocatalyst for the ORR13citations
  • 2018Graphene-oxide-loaded superparamagnetic iron oxide nanoparticles for ultrasensitive electrocatalytic detection of microRNA48citations
  • 2017Self-assembly of polymeric micelles made of asymmetric polystyrene-b-polyacrylic acid-b-polyethylene oxide for the synthesis of mesoporous nickel ferrite8citations

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Chart of shared publication
Miyake, Koji
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Uchida, Yoshiaki
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Cazorla-Amorós, Diego
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Hirota, Yuichiro
1 / 1 shared
Shu, Yasuhiro
1 / 1 shared
Nishiyama, Norikazu
1 / 1 shared
Gabe, Atsushi
1 / 1 shared
Zhu, Yexin
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Morallon, Emilia
1 / 39 shared
Shiddiky, Muhammad J. A.
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Hossain, Md Shahriar A.
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Yamauchi, Yusuke
2 / 19 shared
Nguyen, Nam Trung
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Gorgannezhad, Lena
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Masud, Mostafa Kamal
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Islam, Md Nazmul
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Farooq, Wazirzada Aslam
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Fatehmulla, Amanullah
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Bando, Yoshio
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Kani, Kenya
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Kaneti, Yusuf Valentino
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Ishii, Daisuke
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Yusa, Yunqi Li Shin Ichi
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Bastakoti, Bishnu Prasad
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2019
2018
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Co-Authors (by relevance)

  • Miyake, Koji
  • Uchida, Yoshiaki
  • Cazorla-Amorós, Diego
  • Hirota, Yuichiro
  • Shu, Yasuhiro
  • Nishiyama, Norikazu
  • Gabe, Atsushi
  • Zhu, Yexin
  • Morallon, Emilia
  • Shiddiky, Muhammad J. A.
  • Hossain, Md Shahriar A.
  • Yamauchi, Yusuke
  • Nguyen, Nam Trung
  • Gorgannezhad, Lena
  • Masud, Mostafa Kamal
  • Islam, Md Nazmul
  • Farooq, Wazirzada Aslam
  • Fatehmulla, Amanullah
  • Bando, Yoshio
  • Kani, Kenya
  • Kaneti, Yusuf Valentino
  • Ishii, Daisuke
  • Yusa, Yunqi Li Shin Ichi
  • Bastakoti, Bishnu Prasad
OrganizationsLocationPeople

article

Graphene-oxide-loaded superparamagnetic iron oxide nanoparticles for ultrasensitive electrocatalytic detection of microRNA

  • Shiddiky, Muhammad J. A.
  • Hossain, Md Shahriar A.
  • Yamauchi, Yusuke
  • Tanaka, Shunsuke
  • Nguyen, Nam Trung
  • Gorgannezhad, Lena
  • Masud, Mostafa Kamal
  • Islam, Md Nazmul
Abstract

We report the electrocatalytic activity of a new class of superparamagnetic nanoparticles, graphene-oxide-loaded iron oxide (GO/IO hybrid material), towards the reduction of ruthenium hexaammine(III) chloride (Ru(NH3)6]<sup>3+</sup>, RuHex). Leveraging the electrocatalytic activity of the GO/IO hybrid material and the signal enhancement capacity of [Ru(NH<sub>3</sub>)<sub>6</sub>]<sup>3+</sup>/[Fe(CN)<sub>6</sub>]<sup>3−</sup> in an electrocatalytic cycle, an ultrasensitive and specific electrochemical sensor was developed for the detection of cancer-related microRNA (miRNA). Using the direct affinity interaction between RNA and graphene oxide, magnetically isolated and purified target miRNA were directly adsorbed onto a screen-printed electrode modified with the GO/IO hybrid material. The detection was enabled by chronocoulometric (CC) readout of charge-compensating [Ru(NH<sub>3</sub>)<sub>6</sub>]<sup>3+</sup> followed by an enhancement in CC charge display through the Ru(NH<sub>3</sub>)<sub>6</sub>]<sup>3+</sup>/[Fe(CN)<sub>6</sub>]<sup>3− </sup>system. We demonstrate an excellent limit of detection of 1.0 fM by accurately detecting miR-21 in synthetic samples and showcase its clinical utility in ovarian cancer cell lines with high sensitivity (ten cells) and good reproducibility (% RSD=&lt;5 %, for <i>n</i>=3).

Topics
  • nanoparticle
  • iron
  • Ruthenium