title: Perovskite-LLM: Knowledge-Enhanced Large Language Models for Perovskite
    Solar Cell Research
summary: The rapid advancement of perovskite solar cells (PSCs) has led to an
  exponential growth in research publications, creating an urgent need for
  efficient knowledge management and reasoning systems in this domain. We present
  a comprehensive knowledge-enhanced system for PSCs that integrates three key
  components. First, we develop Perovskite-KG, a domain-specific knowledge graph
  constructed from 1,517 research papers, containing 23,789 entities and 22,272
  relationships. Second, we create two complementary datasets: Perovskite-Chat,
  comprising 55,101 high-quality question-answer pairs generated through a novel
  multi-agent framework, and Perovskite-Reasoning, containing 2,217 carefully
  curated materials science problems. Third, we introduce two specialized large
  language models: Perovskite-Chat-LLM for domain-specific knowledge assistance
  and Perovskite-Reasoning-LLM for scientific reasoning tasks. Experimental
  results demonstrate that our system significantly outperforms existing models
  in both domain-specific knowledge retrieval and scientific reasoning tasks,
  providing researchers with effective tools for literature review, experimental
  design, and complex problem-solving in PSC research.
paper_authors._id: 67b58c806e53744c2a373351
paper_authors.name: Xiang Liu
paper_authors.status: admin_assigned
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paper_authors.fullname: Xiang Liu
paper_authors.type: user
paper_authors.user: Dominic789654
paper_authors._id: 67b58c806e53744c2a373352
paper_authors.name: Penglei Sun
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paper_authors.user: sunpenglei
paper_authors._id: 67b58c806e53744c2a373353
paper_authors.name: Shuyan Chen
paper_authors._id: 67b58c806e53744c2a373354
paper_authors.name: Longhan Zhang
paper_authors._id: 67b58c806e53744c2a373355
paper_authors.name: Peijie Dong
paper_authors._id: 67b58c806e53744c2a373356
paper_authors.name: Huajie You
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paper_authors.fullname: Huajie You
paper_authors.type: user
paper_authors.user: FrankYOU
paper_authors._id: 67b58c806e53744c2a373357
paper_authors.name: Yongqi Zhang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-02-19T09:35:12.059Z
paper_authors._id: 64473221dcbe1333b64b2db2
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paper_authors.fullname: yongqi zhang
paper_authors.type: user
paper_authors.user: yongqi2023
paper_authors._id: 67b58c806e53744c2a373358
paper_authors.name: Chang Yan
paper_authors._id: 67b58c806e53744c2a373359
paper_authors.name: Xiaowen Chu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-02-19T09:35:20.611Z
paper_authors._id: 6676935fcd0b89a0115174b0
paper_authors.avatarUrl: /avatars/4caca1b672d29e787814f9a30bf20bcc.svg
paper_authors.fullname: Xiaowen Chu
paper_authors.type: user
paper_authors.user: wenxinsiju
paper_authors._id: 67b58c806e53744c2a37335a
paper_authors.name: Tong-yi Zhang
paper_title: Perovskite-LLM: Knowledge-Enhanced Large Language Models for Perovskite
    Solar Cell Research
paper_summary: The rapid advancement of perovskite solar cells (PSCs) has led to an
  exponential growth in research publications, creating an urgent need for
  efficient knowledge management and reasoning systems in this domain. We present
  a comprehensive knowledge-enhanced system for PSCs that integrates three key
  components. First, we develop Perovskite-KG, a domain-specific knowledge graph
  constructed from 1,517 research papers, containing 23,789 entities and 22,272
  relationships. Second, we create two complementary datasets: Perovskite-Chat,
  comprising 55,101 high-quality question-answer pairs generated through a novel
  multi-agent framework, and Perovskite-Reasoning, containing 2,217 carefully
  curated materials science problems. Third, we introduce two specialized large
  language models: Perovskite-Chat-LLM for domain-specific knowledge assistance
  and Perovskite-Reasoning-LLM for scientific reasoning tasks. Experimental
  results demonstrate that our system significantly outperforms existing models
  in both domain-specific knowledge retrieval and scientific reasoning tasks,
  providing researchers with effective tools for literature review, experimental
  design, and complex problem-solving in PSC research.