Evidence map›Paper›PMID 42179023›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness.

Dezhi Chen, Chao Xu, Jingyue Yu, Qi Wang, Hongze Fang, Shuo Yin, Turab Lookman, Ruirun Chen

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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.

Dezhi ChenNational Key Laboratory For Precision Hot Processing of Metals, Harbin Institute of Technology, Harbin, P. R. China.ORCID https://orcid.org/0009-0000-9246-4141
Chao XuNational Key Laboratory For Precision Hot Processing of Metals, Harbin Institute of Technology, Harbin, P. R. China.ORCID https://orcid.org/0009-0006-9067-8932
Jingyue YuNational Key Laboratory For Precision Hot Processing of Metals, Harbin Institute of Technology, Harbin, P. R. China.
Qi WangNational Key Laboratory For Precision Hot Processing of Metals, Harbin Institute of Technology, Harbin, P. R. China.
Hongze FangNational Key Laboratory For Precision Hot Processing of Metals, Harbin Institute of Technology, Harbin, P. R. China.
Shuo YinDepartment of Mechanical, Manufacturing, and Biomedical Engineering, Trinity College, University of Dublin, Dublin, Ireland.
Turab LookmanState Key Laboratory For Mechanical Behavior of Materials, State Key Laboratory of Porous Metal Materials, School of Materials Science and Engineering, Xi'an Jiatong University, Xi'an, P. R. China.ORCID https://orcid.org/0000-0001-8122-5671
Ruirun ChenNational Key Laboratory For Precision Hot Processing of Metals, Harbin Institute of Technology, Harbin, P. R. China.

Funding

National Key Laboratory of Special Rare Metal Materials SKL2024K006National Natural Science Foundation of China 52404357National Natural Science Foundation of China 52425401Northwest Rare Metal Materials Research Institute, Natural Science Foundation of Heilongjiang Province LH2024E027Young Elite Scientists Sponsorship Program by CAST 2024QNRC001
6 · The paper itself

Abstract

A continuing challenge in aerospace materials is the search for alloys that have desired functional properties to operate at higher temperatures with lower densities. This improves aero-engine efficiency and reduces CO

Indexed as

machine learningmodel interpretabilityNb─Si alloysstrengthening mechanisms

Identifiers

PMID42179023
PMCPMC13336009

What OpenQuestion holds

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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.