APL Machine Learning
Last updated ISSN 2770-9019
APL Machine Learning is published by American Institute of Physics in materials science. It is open access. Its article processing charge is not published.
Is your paper a fit?
The surest way to know is to compare your own abstract against what this journal has actually been publishing, rather than against its aims-and-scope page. Paste your abstract and Journal Hunt will tell you how close APL Machine Learning is — and show you journals like it.
What it publishes
Recent work in APL Machine Learning concentrates on these topics, taken from its published record rather than from its own description:
- Machine Learning in Materials Science
- Advanced Memory and Neural Computing
- Neural Networks and Reservoir Computing
- Ferroelectric and Negative Capacitance Devices
- Model Reduction and Neural Networks
- Computational Drug Discovery Methods
- Neural dynamics and brain function
- Neural Networks and Applications
- Photonic and Optical Devices
- X-ray Diffraction in Crystallography
Key facts
| Publisher | American Institute of Physics |
|---|---|
| ISSN | 2770-9019 |
| Subject area | Materials Science |
| Access | Open access |
| Article processing charge | Not published |
| Indexed in | DOAJ |
| Articles published | 278 |
| Publishing since | 2023 |
Facts come from OpenAlex, DOAJ and Wikidata and may lag the journal’s own pages. Check the publisher’s site before submitting. Indexing shown here is what is recorded, not a complete picture — about a third of journals have no indexing recorded anywhere we can read, so “not recorded” does not mean a journal is absent from Scopus or Web of Science.
Journals like APL Machine Learning
Other established journals in materials science, if this one is not the right home for your paper: