{"data":{"event":{"id":"cf6abc96-8165-4afd-90cd-1de8c3b567de","slug":"berkeley-a-lab-autonomous-synthesis","title":"Berkeley A-Lab autonomously synthesizes computationally proposed inorganic compounds","short_summary":"Lawrence Berkeley’s A-Lab, published 29 November 2023 alongside GNoME, used ML, literature NLP, and robotics to synthesize 41 of 58 targeted solids in 17 days, including materials suggested from DeepMind stability data.","full_description":"An active-learning loop proposed recipes; failed syntheses were analyzed. A January 2026 author correction later updated parts of the record, so some details should be read with the correction. The platform is a research autonomous lab, not a factory.","ledger_type":"benefit","primary_domain_id":"5967400b-72d1-43e0-8355-37061fd039bb","event_status":"verified","event_date":"2023-11-29T00:00:00.000Z","discovery_date":"2023-11-29T00:00:00.000Z","first_published_date":"2023-11-29T00:00:00.000Z","last_reviewed_date":"2023-11-29T00:00:00.000Z","geographic_scope":"Lawrence Berkeley National Laboratory, USA","affected_population":"Autonomous-lab and materials-synthesis researchers","base_impact_tier":3,"base_score":"10.00","attribution_multiplier":"0.4000","evidence_multiplier":"0.7000","realization_multiplier":"0.6000","durability_multiplier":"0.5500","current_event_score":"0.542900","confidence_level":"high","score_explanation":"High-throughput autonomous synthesis of predicted solids is major (tier 3). Modest AI attribution (NLP + planners assist humans/robots). Peer review with a later correction. Realization is 17-day campaign products. Medium durability.","methodology_version_id":"d7881163-fb23-4e71-8625-bac1a8662c0f","original_methodology_version_id":"d7881163-fb23-4e71-8625-bac1a8662c0f","published_at":"2023-11-29T00:00:00.000Z","created_at":"2026-09-13T20:47:20.075Z","updated_at":"2026-09-13T20:47:20.075Z","flags":[],"domain_name":"Materials Science","domain_slug":"materials-science","methodology_version":"0.1"},"contributions":[{"id":"dc8219d3-2500-423e-8ab9-da1dd1afdae9","event_id":"cf6abc96-8165-4afd-90cd-1de8c3b567de","model_id":"8fffdd7a-d88d-4946-8467-759f6baadcfe","role_description":"Provided a subset of computationally stable targets.","attribution_multiplier":"0.3000","credit_share":"0.2500","contribution_score":"0.173300","attribution_rationale":"Some targets came from DeepMind/Materials Project stability data, not the synthesis policy.","attribution_confidence":"medium","first_used_date":"2023-11-29T00:00:00.000Z","model_version_if_known":null,"review_status":"approved","created_at":"2026-09-13T20:47:20.075Z","model_slug":"gnome","model_name":"GNoME","identity_class":"named_release","is_internal":false,"family_name":"GNoME","family_slug":"google-deepmind-gnome","organization_name":"Google DeepMind","organization_slug":"google-deepmind"},{"id":"029edcfe-0890-499b-88bb-1520c6f785d5","event_id":"cf6abc96-8165-4afd-90cd-1de8c3b567de","model_id":"4a4f6d37-651c-4496-ac32-fa32f8e63372","role_description":"Proposed synthesis recipes from literature-trained models.","attribution_multiplier":"0.4000","credit_share":"0.4000","contribution_score":"0.369600","attribution_rationale":"NLP and active learning planned experiments; robotics and human infrastructure executed them.","attribution_confidence":"medium","first_used_date":"2023-11-29T00:00:00.000Z","model_version_if_known":null,"review_status":"approved","created_at":"2026-09-13T20:47:20.075Z","model_slug":"literature-nlp-recipe-model","model_name":"Literature NLP Recipe Model","identity_class":"named_release","is_internal":false,"family_name":"Materials NLP","family_slug":"lawrence-berkeley-national-laboratory-materials-nlp","organization_name":"Lawrence Berkeley National Laboratory","organization_slug":"lawrence-berkeley-national-laboratory"}],"sources":[{"id":"0744ad6f-e41e-4fbf-a57d-c177a89ade80","event_id":"cf6abc96-8165-4afd-90cd-1de8c3b567de","url":"https://www.nature.com/articles/s41586-023-06734-w","canonical_url":"https://www.nature.com/articles/s41586-023-06734-w","source_type":"peer_reviewed","publisher":"Nature","author":null,"publication_date":"2023-11-29T00:00:00.000Z","retrieved_at":"2026-09-13T20:47:20.075Z","title":"An autonomous laboratory for the accelerated synthesis of inorganic materials","excerpt":null,"content_hash":null,"source_reliability_class":"high","is_primary_source":true,"is_independent":true,"is_peer_reviewed":true,"archived_url":null,"created_at":"2026-09-13T20:47:20.075Z"},{"id":"d60f0996-1977-4c0c-8085-da60dba57ba0","event_id":"cf6abc96-8165-4afd-90cd-1de8c3b567de","url":"https://www.nature.com/articles/s41586-025-09992-y","canonical_url":"https://www.nature.com/articles/s41586-025-09992-y","source_type":"peer_reviewed","publisher":"Nature","author":null,"publication_date":"2026-01-19T00:00:00.000Z","retrieved_at":"2026-09-13T20:47:20.075Z","title":"Author Correction: An autonomous laboratory for the accelerated synthesis of inorganic materials","excerpt":null,"content_hash":null,"source_reliability_class":"high","is_primary_source":true,"is_independent":true,"is_peer_reviewed":true,"archived_url":null,"created_at":"2026-09-13T20:47:20.075Z"}],"claims":[{"id":"811ede25-776e-40fd-be9d-791c74cfeb85","event_id":"cf6abc96-8165-4afd-90cd-1de8c3b567de","claim_text":"A-Lab realized a majority of selected computational targets during a 17-day autonomous campaign.","claim_type":"outcome","claim_status":"supported","confidence_score":null,"created_at":"2026-09-13T20:47:20.075Z","updated_at":"2026-09-13T20:47:20.075Z"},{"id":"99321ae4-8ea4-4ed8-8710-895d1c8c18ad","event_id":"cf6abc96-8165-4afd-90cd-1de8c3b567de","claim_text":"A 2026 author correction revised aspects of the published record.","claim_type":"significance","claim_status":"supported","confidence_score":null,"created_at":"2026-09-13T20:47:20.075Z","updated_at":"2026-09-13T20:47:20.075Z"}],"revisions":[{"id":"624513a7-3f53-469b-92c4-490813ec9393","event_id":"cf6abc96-8165-4afd-90cd-1de8c3b567de","model_id":null,"previous_score":"0.000000","new_score":"0.542900","previous_factors":{},"new_factors":{"evidence":0.7,"base_score":10,"durability":0.55,"attribution":0.4,"realization":0.6},"change_reason":"Initial adjudicated seed score under methodology 0.1.","trigger_type":"seed","trigger_source_ids":null,"reviewer_id":null,"review_status":"published","created_at":"2026-09-13T20:47:20.075Z"}],"secondary":[{"name":"Chemistry","slug":"chemistry"},{"name":"Engineering","slug":"engineering"}]},"methodology_version":"0.1"}