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ReciNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction

Advanced Manufacturing

Summary

arXiv:2502.02748v4 Announce Type: replace-cross Abstract: Predicting properties of crystals from their structures is a fundamental yet challenging task in materials science. Unlike molecules, crystal structures exhibit infinite periodic arrangements of atoms, requiring methods capable of capturing both local and global information effectively. However, current works fall short of capturing long-range interactions within periodic structures.

Why It Matters

This Advanced Manufacturing development raises the bar for precision and smart-factory capability in the region. For Asia, it is a signal worth tracking: it shapes who supplies, who scales, and who sets the standard over the next five years.

Key Facts

  • SectorAdvanced Manufacturing
  • Market
  • ImpactLow (42/100)
  • SignalResearch

Original Sources

arXiv Condensed Matter ↗ https://arxiv.org/abs/2502.02748

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