Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Aluminum is the second most widely used metal worldwide, with essential roles in transportation, construction, packaging, and energy infrastructure. Recycling aluminum can save up to 95% of the energy required for primary production, making it a cornerstone of low-carbon manufacturing. However, recycled aluminum alloys inevitably contain higher levels of iron, which promotes the formation of brittle microscopic phases that degrade performance and limit industrial use. These phases can appear in different forms and dispersion depending on alloy composition and processing. Yet, practical guidelines for controlling them remain largely empirical and qualitative, especially when data are limited. To improve this situation, this work separates two key questions that are often conflated in alloy design: which phase type forms, and how strongly that phase affects material behavior once it appears. Using data representative of industrial conditions, we show how alloy chemistry and processing history determine which phases form and govern whether these phases develop as a few large, platelet-like features or as many small, compact particles. By clarifying these distinct roles of composition and processing, the results provide a simple and actionable framework for mitigating deleterious iron-rich phases in recycled aluminum alloys and enabling more quantitative, predictable, and impurity-tolerant sustainable alloy design.

Authors

Institutions

Publication Details

Journal
Advanced Science
Published
2026-04-30
DOI
https://doi.org/10.1002/advs.75446
Primary Topic
Aluminum Alloy Microstructure Properties
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

J WANG, Waleed Mohammed, Dierk Raabe
Advanced Science
Aluminum Alloy Microstructure Properties
article

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

J WANG, Waleed Mohammed, Dierk Raabe
article en

Abstract

Aluminum is the second most widely used metal worldwide, with essential roles in transportation, construction, packaging, and energy infrastructure. Recycling aluminum can save up to 95% of the energy required for primary production, making it a cornerstone of low-carbon manufacturing. However, recycled aluminum alloys inevitably contain higher levels of iron, which promotes the formation of brittle microscopic phases that degrade performance and limit industrial use. These phases can appear in different forms and dispersion depending on alloy composition and processing. Yet, practical guidelines for controlling them remain largely empirical and qualitative, especially when data are limited. To improve this situation, this work separates two key questions that are often conflated in alloy design: which phase type forms, and how strongly that phase affects material behavior once it appears. Using data representative of industrial conditions, we show how alloy chemistry and processing history determine which phases form and govern whether these phases develop as a few large, platelet-like features or as many small, compact particles. By clarifying these distinct roles of composition and processing, the results provide a simple and actionable framework for mitigating deleterious iron-rich phases in recycled aluminum alloys and enabling more quantitative, predictable, and impurity-tolerant sustainable alloy design.

Advanced Science
Kyungpook National University (KR), Max-Planck-Institut für Nachhaltige Materialien (DE)
Deutsche Forschungsgemeinschaft, Max-Planck-Gesellschaft
Industry, innovation and infrastructure
Openalex Percentile: Top 3%
Aluminum Alloy Microstructure Properties
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.