{"id":"W4387299227","doi":"10.1021/jacs.3c07443","title":"Tailored Energy Funneling in Photocatalytic π-Conjugated Polymer Nanofibers for High-Performance Hydrogen Production","year":2023,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced Photocatalysis Techniques","field":"Energy","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"H2020 European Research Council; National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Photocatalysis; Polyfluorene; Chemistry; Photochemistry; Nanofiber; Hydrogen production; Artificial photosynthesis; Nanotechnology; Quantum yield; Absorption (acoustics); Porphyrin; Polymer; Conjugated system; Chemical engineering; Materials science; Hydrogen; Optics; Organic chemistry; Catalysis; Physics; Composite material; Fluorescence","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":[0.0001566093,0.0002532742,0.0001235422,0.0001605088,0.0001338406,0.0002366777,0.0001832697,0.0002986068,0.0004590006],"category_scores_gemma":[0.0001885303,0.0001228152,0.0001467909,0.0001030647,0.00016803,0.0004106093,0.00013077,0.000230284,0.0001444103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002950854,"about_ca_system_score_gemma":0.0001131998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002522514,"about_ca_topic_score_gemma":0.0006685784,"domain_scores_codex":[0.9999394,0.000009022896,0.000005383287,0.00001956534,0.00001644472,0.00001017079],"domain_scores_gemma":[0.9998903,0.00003805121,0.00003664039,0.000008753957,0.00001334111,0.00001296725],"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":[0.00002070897,0.000022879,0.00007827517,0.00004984967,0.000005010846,0.00007090082,0.00002132222,0.001148041,0.9954283,0.0003397099,0.00007446466,0.002740439],"study_design_scores_gemma":[0.000008959459,0.00007963979,0.0004425916,0.000003997887,0.000004314402,0.00007036732,0.000008042951,0.00462531,0.993578,0.00009107631,0.001079794,0.000007942699],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9834382,0.001220462,0.01295355,0.00009836706,0.00004285527,0.00002944774,0.0001013427,0.0001998714,0.001915714],"genre_scores_gemma":[0.9891559,0.0004560921,0.009108052,0.00002451722,0.00001202853,0.00002582735,0.00005252915,0.00002027904,0.001144682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004590006,"threshold_uncertainty_score":0.002140999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0105687743528506,"score_gpt":0.2495473079174867,"score_spread":0.2389785335646361,"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."}}