Evidence map›Paper›PMID 33671034›Full record

ArticleMicromachines2021

Mechanical/Electrical Characterization of ZnO Nanomaterial Based on AFM/Nanomanipulator Embedded in SEM.

Mei Liu, Weilin Su, Xiangzheng Qin, Kai Cheng, Wei Ding, Li Ma, Ze Cui, Jinbo Chen, Jinjun Rao, Hangkong Ouyang and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 48% of its field
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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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

11 authors at 1 institution in 1 country.

Mei LiuShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Weilin SuShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Xiangzheng QinShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Kai ChengShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Wei DingShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Li MaShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Ze CuiShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Jinbo ChenShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Jinjun RaoShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Hangkong OuyangShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
Tao SunShanghai Key Laboratory of Intelligent Manufacturing and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.ORCID 0000-0002-0381-4910
Shanghai University · CN

Funding

National Natural Science Foundation of China 51205245, 61573236
6 · The paper itself

Abstract

ZnO nanomaterials have been widely used in micro/nano devices and structure due to special mechanical/electrical properties, and its characterization is still deficient and challenging. In this paper, ZnO nanomaterials, including nanorod and nanowire are characterized by atomic force microscope (AFM) and nanomanipulator embedded in scanning electron microscope (SEM) respectively, which can manipulate and observe simultaneously, and is efficient and cost effective. Surface morphology and mechanical properties were observed by AFM. Results showed that the average Young's modulus of ZnO nanorods is 1.40 MPa and the average spring rate is 0.08 N/m. Electrical properties were characterized with nanomanipulator, which showed that the ZnO nanomaterial have cut-off characteristics and good schottky contact with the tungsten probes. A two-probe strategy was proposed for piezoelectric property measurement, which is easy to operate and adaptable to multiple nanomaterials. Experiments showed maximum voltage of a single ZnO nanowire is around 0.74 mV. Experiment criteria for ZnO manipulation and characterization were also studied, such as acceleration voltage, operation duration, sample preparation. Our work provides useful references for nanomaterial characterization and also theoretical basis for nanomaterials application.

Indexed as

atomic force microscopemechanical/electrical characterizationnanomanipulatorpiezoelectric propertyZnO

Identifiers

PMID33671034
PMCPMC7997223
OpenAlexW3135007877

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.