{
  "id": 15838723,
  "title": "GBClaw: An agentic AI framework for atomistic grain boundary research and mechanistic discovery",
  "url": "https://urgent.news/2026/10/20/gbclaw-an-agentic-ai-framework-for-atomistic-grain-boundary-research",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-20T17:59:40.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.28629v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Agentic artificial intelligence (AI) systems hold immense potential for automating complex workflows in materials discovery and design, but extending them to domain-intensive mechanistic investigations remains challenging. Here, we present GBClaw, an agentic AI framework for investigating the structure and deformation of general grain boundaries (GBs). Although general GBs constitute the vast…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}