{"id":"W2341423989","doi":"10.1016/j.apenergy.2016.04.074","title":"Template-free synthesis of three-dimensional nanoporous N-doped graphene for high performance fuel cell oxygen reduction reaction in alkaline media","year":2016,"lang":"en","type":"article","venue":"Applied Energy","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":53,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"Donghua University; National Natural Science Foundation of China","keywords":"Graphene; Catalysis; X-ray photoelectron spectroscopy; Materials science; Nanoporous; Electrocatalyst; Scanning electron microscope; Electrochemistry; Chemical engineering; Electrochemical energy conversion; BET theory; Cathode; Specific surface area; Nanotechnology; Inorganic chemistry; Electrode; Chemistry; Composite material; Organic chemistry","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":[0.00007553399,0.0002386946,0.0001629105,0.0002234875,0.0001437322,0.0002085873,0.0003838573,0.0003466966,0.0006382044],"category_scores_gemma":[0.0001274557,0.0001454838,0.0002547231,0.0001502715,0.0001287041,0.0002482502,0.000186914,0.0002670962,0.0002665612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002652482,"about_ca_system_score_gemma":0.0001712447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007363454,"about_ca_topic_score_gemma":0.002625589,"domain_scores_codex":[0.9999343,0.000004306201,0.000005385874,0.00001283884,0.00002992111,0.00001323559],"domain_scores_gemma":[0.9999608,0.00000687934,0.000009696253,0.000007845978,0.00000610588,0.00000872169],"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":[0.00002610131,0.00001634087,0.00006559322,0.00005428231,0.000007884179,0.00005562467,0.0000144448,0.0005160731,0.9959759,0.0002753186,0.00009867841,0.002893834],"study_design_scores_gemma":[0.000006279833,0.00004375311,0.0004439785,0.000002566221,0.000007219859,0.0000447491,0.000008346287,0.004041794,0.9939809,0.00008343132,0.001328484,0.000008522729],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764913,0.001097318,0.01433918,0.0001437183,0.0001137369,0.00004483507,0.0005877255,0.0003912371,0.006791029],"genre_scores_gemma":[0.9928919,0.0002871814,0.005488294,0.00001900868,0.000008450749,0.00001400687,0.0001806826,0.00002019191,0.001090391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007363454,"threshold_uncertainty_score":0.002135038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008015397591920128,"score_gpt":0.1848786040777865,"score_spread":0.1768632064858663,"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."}}