{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GRXXVAR3JSQKBOPOLY44MUQZ7G","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"b6e2e3096dd0fb8ee7462a747159b2324a3441eaf6c077ead0d1075ca45acb9a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-31T06:31:15Z","title_canon_sha256":"8547862c3594b89f94ff9b7b5994e34fcd148b0977914ba35a3b3f9467952e09"},"schema_version":"1.0","source":{"id":"2503.23766","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.23766","created_at":"2026-07-05T10:41:59Z"},{"alias_kind":"arxiv_version","alias_value":"2503.23766v1","created_at":"2026-07-05T10:41:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.23766","created_at":"2026-07-05T10:41:59Z"},{"alias_kind":"pith_short_12","alias_value":"GRXXVAR3JSQK","created_at":"2026-07-05T10:41:59Z"},{"alias_kind":"pith_short_16","alias_value":"GRXXVAR3JSQKBOPO","created_at":"2026-07-05T10:41:59Z"},{"alias_kind":"pith_short_8","alias_value":"GRXXVAR3","created_at":"2026-07-05T10:41:59Z"}],"graph_snapshots":[{"event_id":"sha256:28a4ac5825211606d40d5c43ca181c49d4083f95f5e3583d413f9570a44cf1c1","target":"graph","created_at":"2026-07-05T10:41:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2503.23766/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Organic photovoltaic (OPV) materials offer a promising avenue toward cost-effective solar energy utilization. However, optimizing donor-acceptor (D-A) combinations to achieve high power conversion efficiency (PCE) remains a significant challenge. In this work, we propose a framework that integrates large-scale pretraining of graph neural networks (GNNs) with a GPT-2 (Generative Pretrained Transformer 2)-based reinforcement learning (RL) strategy to design OPV molecules with potentially high PCE. This approach produces candidate molecules with predicted efficiencies approaching 21\\%, although f","authors_text":"Fankun Zeng, Hao Zhang, Hou Hei Lam, Jiangjie Qiu, Siwei Fu, Wentao Li, Xiaonan Wang, Xiuyuan Hu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-31T06:31:15Z","title":"Accelerating High-Efficiency Organic Photovoltaic Discovery via Pretrained Graph Neural Networks and Generative Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.23766","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:79fc6864624071234ab5ad1dbb7c00e142416223d06e0e5ef5c0cfcf4b3617aa","target":"record","created_at":"2026-07-05T10:41:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"b6e2e3096dd0fb8ee7462a747159b2324a3441eaf6c077ead0d1075ca45acb9a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-03-31T06:31:15Z","title_canon_sha256":"8547862c3594b89f94ff9b7b5994e34fcd148b0977914ba35a3b3f9467952e09"},"schema_version":"1.0","source":{"id":"2503.23766","kind":"arxiv","version":1}},"canonical_sha256":"346f7a823b4ca0a0b9ee5e39c65219f98a5b806f17a1c5c246e5039d7b12f45c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"346f7a823b4ca0a0b9ee5e39c65219f98a5b806f17a1c5c246e5039d7b12f45c","first_computed_at":"2026-07-05T10:41:59.527775Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:41:59.527775Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"edsB3tIPYybUAyk4IQVeD/FyPty7hcshf3zRR/7k/1xYBE0tRxA90cpaIeEvDib8g/bZL+2lXRQY4uWoSSCNBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:41:59.528260Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.23766","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:79fc6864624071234ab5ad1dbb7c00e142416223d06e0e5ef5c0cfcf4b3617aa","sha256:28a4ac5825211606d40d5c43ca181c49d4083f95f5e3583d413f9570a44cf1c1"],"state_sha256":"ed6da3dd90775a6df08d8e5a28d9bf3860ec4f8758c9906bdeeb9f8548934933"}