{"id":"W4409924672","doi":"10.26434/chemrxiv-2025-k697f","title":"Enhanced Flow Battery Electrolyte Solubility andStability via Synergistic Anthraquinone Interactions","year":2025,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Advanced battery technologies research","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Fonds de recherche du Québec – Nature et technologies; Concordia University","keywords":"Electrolyte; Anthraquinone; Solubility; Battery (electricity); Chemistry; Flow battery; Chemical engineering; Flow (mathematics); Inorganic chemistry; Electrode; Organic chemistry; Thermodynamics; Physical chemistry; Engineering; Mechanics; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001662858,0.0003840564,0.000210216,0.0002002852,0.000160467,0.0003904559,0.0001730903,0.0003115643,0.001856615],"category_scores_gemma":[0.0002490693,0.0001351667,0.000186145,0.0001452538,0.0002150663,0.0005647971,0.0005187703,0.0004489624,0.0004476479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001722536,"about_ca_system_score_gemma":0.0001101541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001736645,"about_ca_topic_score_gemma":0.000372298,"domain_scores_codex":[0.9998814,0.00001783534,0.000008176165,0.00003161521,0.00003818909,0.00002278108],"domain_scores_gemma":[0.9999149,0.00002505594,0.00002310677,0.000007536944,0.00001473397,0.00001464067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003508118,0.00001625395,0.00007813837,0.00003865925,0.000006287928,0.00002751057,0.00001561298,0.0001751553,0.9968066,0.0002763986,0.00007214787,0.002452228],"study_design_scores_gemma":[0.00000537907,0.00005985825,0.0002599437,0.000002310925,0.000007998969,0.00003806386,0.000007161092,0.001284883,0.9967348,0.00006717361,0.001529203,0.000003287827],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831283,0.001091787,0.01028426,0.0001753219,0.0000428685,0.000034955,0.0001215715,0.0002424059,0.004878582],"genre_scores_gemma":[0.9924035,0.0006185862,0.004666436,0.00005684693,0.00001435572,0.00002688541,0.00008648931,0.00002877391,0.002098158],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001856615,"threshold_uncertainty_score":0.006211042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686169411024659,"score_gpt":0.2883768572166701,"score_spread":0.2715151631064235,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}