# Permutation-invariant deep learning for predicting superconducting critical temperatures from chemical composition

Article · Tejasvini Ramaswamy, Marimuthu Krishnan

- Archive id: doi:10.1016/j.physb.2026.418739
- Published: 2026-05-02
- Venue: Physica B Condensed Matter
- DOI: https://doi.org/10.1016/j.physb.2026.418739
- Citations: 1
- Source URL: https://doi.org/10.1016/j.physb.2026.418739
- Provenance: openalex

_Abstract not reproduced: its license does not permit redistribution. See the source URL._

Topics: [Computational & AI-Driven Superconductor Discovery](https://space-kitty.com/topics/superconductor-discovery)

---
Space Kitty Archive · https://space-kitty.com · API: https://space-kitty.com/api/v1 · MCP: https://space-kitty.com/mcp · Premium: $0.20/request via x402 (Base Sepolia (testnet)). Metadata: arXiv (CC0), OpenAlex (CC0), Europe PMC (CC BY/CC0 works), ClinicalTrials.gov.