Admissibility-First Materials Discovery: Collapse-Surface Gating, Corridor Non-Emptiness, and a Reproducible 3D Percolation–Spectral Validation for a Paradox Ceramic Class
Abstract
Description This paper presents an admissibility-first contraction framework for multi-objective materials discovery. Microstructures are represented as graphs/voxel fields. Collapse surfaces are defined via deterministic predicates: film spanning (percolation) and free-backbone spectral continuity. A constructive 3D lattice instantiation proves corridor non-emptiness and enables reproducible contraction analysis. A numerical sweep on a 3D cubic lattice (N=20, 40 trials per p) reports spanning probabilities and spectral radius behavior, replacing speculative threshold scalings with empirical gates. The contribution is a falsifiable admissibility certificate framework, not a materials recipe.
Fields of Study & Subjects
Machine Learning in Materials Science
Theoretical and Computational Physics
Material Selection and Properties
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 16 February 2026
- Language
- EN
- Document type
- Preprint