Evidence map›Paper›PMID 34851676›Full record

ArticleScience advances2021

A macro-nano-atomic-scale high-throughput approach for material research.

Yiwei Ju, Shuai Li, Xiaofei Yuan, Lei Cui, Andy Godfrey, Yunjie Yan, Zhiying Cheng, Xiaoyan Zhong, Jing Zhu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Science advances, 2021. 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.

Yiwei JuNational Center for Electron Microscopy in Beijing, School of Materials Science and Engineering, The State Key Laboratory of New Ceramics and Fine Processing, Key Laboratory of Advanced Materials (MOE), Tsinghua University, Beijing 100084, People's Republic of China.ORCID 0000-0002-4545-8977
Shuai LiNational Center for Electron Microscopy in Beijing, School of Materials Science and Engineering, The State Key Laboratory of New Ceramics and Fine Processing, Key Laboratory of Advanced Materials (MOE), Tsinghua University, Beijing 100084, People's Republic of China.
Xiaofei YuanDekai Intelligent Casting Co. Ltd., Hebei 072750, People's Republic of China.
Lei CuiDepartment of Computer Science and Technology, Tsinghua University, Beijing 100084, People's Republic of China.
Andy GodfreyNational Center for Electron Microscopy in Beijing, School of Materials Science and Engineering, The State Key Laboratory of New Ceramics and Fine Processing, Key Laboratory of Advanced Materials (MOE), Tsinghua University, Beijing 100084, People's Republic of China.ORCID 0000-0002-5496-0424
Yunjie YanNational Center for Electron Microscopy in Beijing, School of Materials Science and Engineering, The State Key Laboratory of New Ceramics and Fine Processing, Key Laboratory of Advanced Materials (MOE), Tsinghua University, Beijing 100084, People's Republic of China.
Zhiying ChengNational Center for Electron Microscopy in Beijing, School of Materials Science and Engineering, The State Key Laboratory of New Ceramics and Fine Processing, Key Laboratory of Advanced Materials (MOE), Tsinghua University, Beijing 100084, People's Republic of China.
Xiaoyan ZhongNational Center for Electron Microscopy in Beijing, School of Materials Science and Engineering, The State Key Laboratory of New Ceramics and Fine Processing, Key Laboratory of Advanced Materials (MOE), Tsinghua University, Beijing 100084, People's Republic of China.ORCID 0000-0001-8990-2198
Jing ZhuNational Center for Electron Microscopy in Beijing, School of Materials Science and Engineering, The State Key Laboratory of New Ceramics and Fine Processing, Key Laboratory of Advanced Materials (MOE), Tsinghua University, Beijing 100084, People's Republic of China.ORCID 0000-0002-2175-9476

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the properties of materials requires structural characterization over large areas and different scales to link microstructure with performance. Here, we demonstrate a single-beam high-throughput scanning electron microscope allowing the collection of both secondary electron and backscattered electron signals over large areas. Combined with machine learning, a high efficiency in material research is achieved, illustrated here by a multiscale investigation of carbides in a second-generation nickel-base single-crystal superalloy. The resulting terabyte-sized panoramic atlas data, combined with conventional electron microscopy, enable a simultaneous multiscale analysis of carbide evolution during creep regarding specific type, location, composition, size, shape, and relationship with the matrix, providing sample-scale quantitative statistical data and giving a precise insight into the effect of carbides in the superalloy in a way not previously possible.

Identifiers

PMID34851676
PMCPMC8635436

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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.