Evidence map›Paper›PMID 36545392›Full record

ArticleNanoscale advances2022

Room-temperature magnetoresistance in Ni

Mizuki Matsuzaka, Yuma Sasaki, Kyohei Hayashi, Takahiro Misawa, Takashi Komine, Tomoyuki Akutagawa, Masaya Fujioka, Junji Nishii, Hideo Kaiju

Abstract read
In one paragraph

Article in Nanoscale advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mizuki MatsuzakaFaculty of Science and Technology, Keio University Yokohama Kanagawa 223-8522 Japan.
Yuma SasakiResearch Institute for Electronic Science, Hokkaido University Sapporo Hokkaido 001-0020 Japan.
Kyohei HayashiFaculty of Science and Technology, Keio University Yokohama Kanagawa 223-8522 Japan.
Takahiro MisawaResearch Institute for Electronic Science, Hokkaido University Sapporo Hokkaido 001-0020 Japan.
Takashi KomineGraduate School of Science and Engineering, Ibaraki University Hitachi Ibaraki 316-8511 Japan.ORCID https://orcid.org/0000-0001-9149-5288
Tomoyuki AkutagawaInstitute of Multidisciplinary Research for Advanced Materials, Tohoku University Sendai Miyagi 980-8577 Japan.ORCID https://orcid.org/0000-0003-3040-1078
Masaya FujiokaResearch Institute for Electronic Science, Hokkaido University Sapporo Hokkaido 001-0020 Japan.
Junji NishiiResearch Institute for Electronic Science, Hokkaido University Sapporo Hokkaido 001-0020 Japan.
Hideo KaijuFaculty of Science and Technology, Keio University Yokohama Kanagawa 223-8522 Japan.ORCID https://orcid.org/0000-0002-5485-3661

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular spintronic devices are gaining popularity because the organic semiconductors with long spin relaxation times are expected to have long spin diffusion lengths. A typical molecular spintronic device consists of organic molecules sandwiched between two magnetic layers, which exhibits magnetoresistance (MR) effect. Nanosized devices are also expected to have a high spin polarization, leading to a large MR effect owing to effective orbital hybridization. However, most studies on nanosized molecular spintronic devices have investigated the MR effect at low temperatures because of the difficulty in observing the MR effect at room temperature. Here we focus on high-mobility molecules expected to show long spin diffusion lengths, which lead to the observation of the MR effect in nanoscale junctions at room temperature. In this study, we fabricate magnetic nanojunctions consisting of high-mobility molecules, 2,7-dioctyl[1]benzothieno[3,2-

Identifiers

PMID36545392
PMCPMC9642604

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.