{"id":"W2977435499","doi":"10.1149/09208.0801ecst","title":"Balancing Reactant Transport and PTL-CL Contact in PEM Electrolyzers by Optimizing PTL Design Parameters via Stochastic Pore Network Modeling","year":2019,"lang":"en","type":"article","venue":"ECS Transactions","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Porosity; Materials science; Electrolyte; Electrolysis; Chemical engineering; Wetting; Surface roughness; Composite material; Chemistry; Electrode","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":[0.0005116165,0.0003020344,0.0003330793,0.0002259196,0.0001548122,0.0004730142,0.0004725537,0.0004523835,0.0002728587],"category_scores_gemma":[0.001064216,0.0002648293,0.0002541576,0.0002023178,0.0002935066,0.0006833434,0.0003184088,0.0002628328,0.00007830621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008933329,"about_ca_system_score_gemma":0.0005316008,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001981035,"about_ca_topic_score_gemma":0.002899276,"domain_scores_codex":[0.9998441,0.00004032721,0.000007413656,0.00003021884,0.00005579519,0.0000222326],"domain_scores_gemma":[0.9996365,0.0002241819,0.00007804094,0.00001524507,0.00003445087,0.00001148462],"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":[0.00007894382,0.00005313844,0.0007239848,0.00007662283,0.00001200213,0.00004597608,0.00002915019,0.9333171,0.05869913,0.001548177,0.00006402217,0.005351797],"study_design_scores_gemma":[0.000005504328,0.00002459188,0.00009560583,0.000001327521,0.000004645207,0.000006176872,0.000004979922,0.9876317,0.01187099,0.00021665,0.0001346741,0.000003129603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6404995,0.0005570115,0.3548878,0.0002493284,0.00001634942,0.00006741771,0.0001384935,0.0002736548,0.003310449],"genre_scores_gemma":[0.986514,0.0001430939,0.01295398,0.00001178531,0.000002061712,0.00003352304,0.00002069943,0.00001537319,0.0003053687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001981035,"threshold_uncertainty_score":0.006481647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006101830033124456,"score_gpt":0.1711691317878163,"score_spread":0.1650673017546918,"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."}}