Evidence map›Paper›PMID 42290015›Full record

ArticleSmall methods2026

Unlocking Nanoscale Microstructural Detail in Aluminum Alloys Through Differential Phase Contrast Segmentation in STEM.

Matheus A Tunes, Martin Hasenburger, Rostislav Daniel, Oscar M Prada-Ramirez, Philip Aster, Sebastian Samberger, Thomas M Kremmer, Johannes A Österreicher

Abstract read
In one paragraph

Article in Small methods, 2026. 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

8 authors.

Matheus A TunesDepartment Metallurgy, Chair of Nonferrous Metallurgy, Leoben, Austria.ORCID https://orcid.org/0000-0002-5988-5363
Martin HasenburgerDepartment Metallurgy, Chair of Nonferrous Metallurgy, Leoben, Austria.ORCID https://orcid.org/0009-0000-9027-5558
Rostislav DanielDepartment Materials Science, Chair Functional Materials and Materials Systems, Leoben, Austria.ORCID https://orcid.org/0000-0001-8835-8047
Oscar M Prada-RamirezDepartamento de Engenharia Metalúrgica e de Materiais, Universidade de São Paulo, São Paulo, Brazil.ORCID https://orcid.org/0000-0001-6904-8959
Philip AsterDepartment Metallurgy, Chair of Nonferrous Metallurgy, Leoben, Austria.ORCID https://orcid.org/0009-0005-3679-082X
Sebastian SambergerDepartment Metallurgy, Chair of Nonferrous Metallurgy, Leoben, Austria.ORCID https://orcid.org/0009-0000-2559-0172
Thomas M KremmerDepartment Metallurgy, Chair of Nonferrous Metallurgy, Leoben, Austria.ORCID https://orcid.org/0000-0002-0489-8167
Johannes A ÖsterreicherLKR Light Metals Technologies, AIT Austrian Institute of Technology, Ranshofen, Austria.ORCID https://orcid.org/0000-0003-1518-6963

Funding

APT 884644European Union 101124514FFG 858040
6 · The paper itself

Abstract

Differential phase contrast (DPC) imaging in scanning transmission electron microscopy (STEM) maps projected electric/magnetic fields through the phase sensitivity of segmented low-angle detectors. Although typically applied to atomic-resolution imaging at low beam currents, STEM-DPC is here demonstrated as a rapid micro and nanoscale image-segmentation tool for materials characterization with particular focus on advanced aluminum alloys. Decomposition of false-color DPC micrographs in hue-saturation-value space enables simultaneous identification and quantification of nanoclusters, GP zones, intermediate precipitate phases, dislocation cores, and associated strain fields within a single field of view. The method is demonstrated across multiple alloy systems, including clustering and strain-field mapping in a deformed AlMgZn(Cu) crossover alloy, precipitate identification in a paint-baked automotive sheet alloy, phase-variant segmentation in overaged AA7075-T7, and nanopore and nanoparticle detection in an anodic coating on AA2024-T3. Coupling DPC with neural-network segmentation further enables automated grain-boundary delineation and quantification in nanocrystalline aluminum thin films. Combined with STEM-EDX, DPC-based segmentation enables correlative microstructural analysis, establishing DPC as a rapid complement to techniques such as SPED and 4D-STEM.

Indexed as

differential phase contrastscanning transmission electron microscopysegmentation

Identifiers

PMID42290015
PMCPMC13353894

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.