{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ICD4IO64Q5N6W3UQDLQK4IMUQ5","short_pith_number":"pith:ICD4IO64","canonical_record":{"source":{"id":"2508.20527","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.chem-ph","submitted_at":"2025-08-28T08:14:33Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c35cf42fc3628b1b03e0da3a71282f5e4aa414f892584ab12467f697f5c0713a","abstract_canon_sha256":"4f7bf4dccf014913224534fbb69ce1c7dff845c334ab50fa971912b8d69629f9"},"schema_version":"1.0"},"canonical_sha256":"4087c43bdc875beb6e901ae0ae21948748a1aa31bd60fa36e51c124a97529660","source":{"kind":"arxiv","id":"2508.20527","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.20527","created_at":"2026-07-05T12:01:26Z"},{"alias_kind":"arxiv_version","alias_value":"2508.20527v2","created_at":"2026-07-05T12:01:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.20527","created_at":"2026-07-05T12:01:26Z"},{"alias_kind":"pith_short_12","alias_value":"ICD4IO64Q5N6","created_at":"2026-07-05T12:01:26Z"},{"alias_kind":"pith_short_16","alias_value":"ICD4IO64Q5N6W3UQ","created_at":"2026-07-05T12:01:26Z"},{"alias_kind":"pith_short_8","alias_value":"ICD4IO64","created_at":"2026-07-05T12:01:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ICD4IO64Q5N6W3UQDLQK4IMUQ5","target":"record","payload":{"canonical_record":{"source":{"id":"2508.20527","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.chem-ph","submitted_at":"2025-08-28T08:14:33Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c35cf42fc3628b1b03e0da3a71282f5e4aa414f892584ab12467f697f5c0713a","abstract_canon_sha256":"4f7bf4dccf014913224534fbb69ce1c7dff845c334ab50fa971912b8d69629f9"},"schema_version":"1.0"},"canonical_sha256":"4087c43bdc875beb6e901ae0ae21948748a1aa31bd60fa36e51c124a97529660","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:01:26.915584Z","signature_b64":"Qm7ahQiQ6QjIPcV2HcdRGaYO2+ep+f1xKn5dyzlkKmMYLeR9LV29cuW8VWhjK6L5UdjfGn/27OBS+zYxyGRNBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4087c43bdc875beb6e901ae0ae21948748a1aa31bd60fa36e51c124a97529660","last_reissued_at":"2026-07-05T12:01:26.915067Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:01:26.915067Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.20527","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T12:01:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d3hQ+SyVQXtarnsoeAV82rTS2ivT1dIPQmlYuhq8o2oLC7kea/u+noj+9LEnX5/MtHMJx8pHos/gx+NIAWUlBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T20:55:00.386984Z"},"content_sha256":"91ccdc154b24e65c3e35e1d458e66036652439a794ead50c55a19c14f06dee85","schema_version":"1.0","event_id":"sha256:91ccdc154b24e65c3e35e1d458e66036652439a794ead50c55a19c14f06dee85"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ICD4IO64Q5N6W3UQDLQK4IMUQ5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Molecular Machine Learning in Chemical Process Design","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"physics.chem-ph","authors_text":"Alexander Mitsos, Jan G. Rittig, Manuel Dahmen, Martin Grohe, Philippe Schwaller","submitted_at":"2025-08-28T08:14:33Z","abstract_excerpt":"We present a perspective on molecular machine learning (ML) in the field of chemical process engineering. Recently, molecular ML has demonstrated great potential in (i) providing highly accurate predictions for properties of pure components and their mixtures, and (ii) exploring the chemical space for new molecular structures. We review current state-of-the-art molecular ML models and discuss research directions that promise further advancements. This includes ML methods, such as graph neural networks and transformers, which can be further advanced through the incorporation of physicochemical "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.20527","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2508.20527/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T12:01:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rxl05g89jEuKI85fw1E1nUYhtNdsiGJZANNB3pbGHk/ebnyC7rNqGt0Am1yKzsk+bLFrMH0GyH575hDL2pthAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T20:55:00.387919Z"},"content_sha256":"0b42d2163dae069a661efc4722473be39cee78d9b3ea47f2940fcf6e7c58ff6a","schema_version":"1.0","event_id":"sha256:0b42d2163dae069a661efc4722473be39cee78d9b3ea47f2940fcf6e7c58ff6a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ICD4IO64Q5N6W3UQDLQK4IMUQ5/bundle.json","state_url":"https://pith.science/pith/ICD4IO64Q5N6W3UQDLQK4IMUQ5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ICD4IO64Q5N6W3UQDLQK4IMUQ5/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-17T20:55:00Z","links":{"resolver":"https://pith.science/pith/ICD4IO64Q5N6W3UQDLQK4IMUQ5","bundle":"https://pith.science/pith/ICD4IO64Q5N6W3UQDLQK4IMUQ5/bundle.json","state":"https://pith.science/pith/ICD4IO64Q5N6W3UQDLQK4IMUQ5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ICD4IO64Q5N6W3UQDLQK4IMUQ5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ICD4IO64Q5N6W3UQDLQK4IMUQ5","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":"4f7bf4dccf014913224534fbb69ce1c7dff845c334ab50fa971912b8d69629f9","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.chem-ph","submitted_at":"2025-08-28T08:14:33Z","title_canon_sha256":"c35cf42fc3628b1b03e0da3a71282f5e4aa414f892584ab12467f697f5c0713a"},"schema_version":"1.0","source":{"id":"2508.20527","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.20527","created_at":"2026-07-05T12:01:26Z"},{"alias_kind":"arxiv_version","alias_value":"2508.20527v2","created_at":"2026-07-05T12:01:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.20527","created_at":"2026-07-05T12:01:26Z"},{"alias_kind":"pith_short_12","alias_value":"ICD4IO64Q5N6","created_at":"2026-07-05T12:01:26Z"},{"alias_kind":"pith_short_16","alias_value":"ICD4IO64Q5N6W3UQ","created_at":"2026-07-05T12:01:26Z"},{"alias_kind":"pith_short_8","alias_value":"ICD4IO64","created_at":"2026-07-05T12:01:26Z"}],"graph_snapshots":[{"event_id":"sha256:0b42d2163dae069a661efc4722473be39cee78d9b3ea47f2940fcf6e7c58ff6a","target":"graph","created_at":"2026-07-05T12:01:26Z","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/2508.20527/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a perspective on molecular machine learning (ML) in the field of chemical process engineering. Recently, molecular ML has demonstrated great potential in (i) providing highly accurate predictions for properties of pure components and their mixtures, and (ii) exploring the chemical space for new molecular structures. We review current state-of-the-art molecular ML models and discuss research directions that promise further advancements. This includes ML methods, such as graph neural networks and transformers, which can be further advanced through the incorporation of physicochemical ","authors_text":"Alexander Mitsos, Jan G. Rittig, Manuel Dahmen, Martin Grohe, Philippe Schwaller","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.chem-ph","submitted_at":"2025-08-28T08:14:33Z","title":"Molecular Machine Learning in Chemical Process Design"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.20527","kind":"arxiv","version":2},"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":"sha256:91ccdc154b24e65c3e35e1d458e66036652439a794ead50c55a19c14f06dee85","target":"record","created_at":"2026-07-05T12:01:26Z","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":"4f7bf4dccf014913224534fbb69ce1c7dff845c334ab50fa971912b8d69629f9","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.chem-ph","submitted_at":"2025-08-28T08:14:33Z","title_canon_sha256":"c35cf42fc3628b1b03e0da3a71282f5e4aa414f892584ab12467f697f5c0713a"},"schema_version":"1.0","source":{"id":"2508.20527","kind":"arxiv","version":2}},"canonical_sha256":"4087c43bdc875beb6e901ae0ae21948748a1aa31bd60fa36e51c124a97529660","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4087c43bdc875beb6e901ae0ae21948748a1aa31bd60fa36e51c124a97529660","first_computed_at":"2026-07-05T12:01:26.915067Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:01:26.915067Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Qm7ahQiQ6QjIPcV2HcdRGaYO2+ep+f1xKn5dyzlkKmMYLeR9LV29cuW8VWhjK6L5UdjfGn/27OBS+zYxyGRNBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:01:26.915584Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.20527","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:91ccdc154b24e65c3e35e1d458e66036652439a794ead50c55a19c14f06dee85","sha256:0b42d2163dae069a661efc4722473be39cee78d9b3ea47f2940fcf6e7c58ff6a"],"state_sha256":"cd3dc2a9801a1590b7c058bdb61dff30a9f84438efafb7f10e71292030bd6a59"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uGW9F0fylg6hBjC+33WN+tnxa+NOtQ+glmaCYrK60M7ZXe+Ek0VZfuUQLbbFW59c++9KK02LRlsWGhWcuY5MCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T20:55:00.396148Z","bundle_sha256":"20e12a04f85bd841ee0bf1b3eac95986817a8efe51477a16be454ae2a65c4279"}}