Application of machine learning for advanced material prediction and design
importance 6/10
ai assisted
Machine Learning in Materials Science materials science stage: research
Problem
Traditional experimental and computational approaches in materials science consume enormous time and resources and may not yield satisfactory results.
Why it matters
Slow, costly materials development limits progress across material-dependent industries.
What the AI did
The review surveys machine learning methods for predicting material properties, discovering new materials, and predicting structural information.
Results
not stated in source
Impact
The abstract claims machine learning provides reliable and accurate performance in materials science, without specific figures.
Record
| Venue | EcoMat |
|---|---|
| Published | 2022 |
| Work type | article |
| Authors | Cheuk Hei Chan, Mingzi Sun, Bolong Huang |
| Citations | 123 (OpenAlex, at import time) |
| References | 140 |
| Model or method | not stated in source |
| Organization | not stated in source |
| Primary source | https://doi.org/10.1002/eom2.12194 |
| Open access | gold |
| Keywords | machine learning, materials science, property prediction, materials discovery, review |
Importance rating
6
significant — thousands to millions affected
Slow, costly traditional materials development limits material-dependent industries; abstract claims enormous time/resources but no numbers.
More in Engineering & Materials
| # | Paper | Year | Citations | Importance |
|---|---|---|---|---|
| 1 | Scaling deep learning for materials discovery | 2023 | 1,471 |
8
|
| 2 | Application of Machine Learning in Material Synthesis and Property Prediction | 2023 | 165 |
7
|
| 3 | Machine learning-guided discovery of ionic polymer electrolytes for lithium metal batteries | 2023 | 115 |
7
|
| 4 | Machine Learning for Structural Health Monitoring of Aerospace Structures: A Review | 2025 | 44 |
7
|
| 5 | Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology | 2023 | 42 |
7
|