{"id":"W2477960899","doi":"10.1039/c6ra09274h","title":"Interactions of Pt nanoparticles with molecular components in polymer electrolyte membrane fuel cells: multi-scale modeling approach","year":2016,"lang":"en","type":"article","venue":"RSC Advances","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ballard Power Systems (Canada); Burnaby Hospital","funders":"National Research Foundation of Korea; U.S. Department of Energy","keywords":"Hydronium; Nafion; Nanoparticle; Electrolyte; Polymer; Chemical engineering; Graphite; Membrane; Fuel cells; Materials science; Phase (matter); Electrochemistry; Polymer electrolytes; Nanotechnology; Chemistry; Electrode; Physical chemistry; Organic chemistry; Molecule; Composite material; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003090918,0.0007365121,0.001017124,0.0005978371,0.0008580933,0.00105492,0.001548821,0.002802191,0.002217984],"category_scores_gemma":[0.0005534898,0.0006676945,0.001326167,0.0005213028,0.0006284476,0.001388575,0.0005788516,0.0008268239,0.0003871134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482555,"about_ca_system_score_gemma":0.001101628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02427446,"about_ca_topic_score_gemma":0.01216001,"domain_scores_codex":[0.9998749,0.00003940229,0.000006045857,0.00001813424,0.00003250944,0.00002891381],"domain_scores_gemma":[0.9997794,0.0001131618,0.00002749925,0.00001806743,0.00003907985,0.00002273016],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002597647,0.00005130075,0.000260357,0.00003112135,0.00001989234,0.0001127577,0.00002417154,0.990086,0.002966325,0.005319064,0.0001304745,0.0009725335],"study_design_scores_gemma":[0.000007389866,0.000007970805,0.00006718326,0.000002581956,0.000005253284,0.000006863713,0.000008603739,0.9987412,0.0003202595,0.0006903485,0.0001383818,0.000004003206],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.820433,0.002283071,0.1196581,0.002460481,0.0002012016,0.0001733325,0.0005898897,0.0003068533,0.05389408],"genre_scores_gemma":[0.9796637,0.0009577425,0.008835588,0.0001645804,0.00004336978,0.0001798359,0.0001252165,0.00006793241,0.009961986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02427446,"threshold_uncertainty_score":0.04826635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01219989054928448,"score_gpt":0.2124279443639022,"score_spread":0.2002280538146178,"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."}}