{"id":"W4385632055","doi":"10.1039/d3lc00380a","title":"Probing membrane hydration in microfluidic polymer electrolyte membrane electrolyzers <i>via</i> operando synchrotron Fourier-transform infrared spectroscopy","year":2023,"lang":"en","type":"article","venue":"Lab on a Chip","topic":"Fuel Cells and Related Materials","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Light Source (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Agence Nationale de la Recherche; University of Saskatchewan; Canadian Light Source","keywords":"Synchrotron; Membrane; Electrolyte; Fourier transform infrared spectroscopy; Microfluidics; Infrared spectroscopy; Infrared; Chemical engineering; Materials science; Analytical Chemistry (journal); Polymer; Chemistry; Spectroscopy; Nanotechnology; Chromatography; Electrode; Optics; Physical chemistry; Organic chemistry; 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":[0.0002156928,0.0002553288,0.0001749235,0.0001091916,0.0001867115,0.0003363432,0.0002742106,0.0002701078,0.0009301038],"category_scores_gemma":[0.0003290366,0.0001510814,0.0001251837,0.0001497944,0.0003542421,0.0004104497,0.0002817957,0.0004938102,0.0001632149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002576483,"about_ca_system_score_gemma":0.0002263625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004211594,"about_ca_topic_score_gemma":0.0006986521,"domain_scores_codex":[0.9998741,0.000009972793,0.000007228461,0.00004158954,0.00003758485,0.00002948741],"domain_scores_gemma":[0.9998386,0.00005487363,0.00005820154,0.00001092079,0.00002086551,0.00001661651],"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":[0.00002218755,0.000008783656,0.0001509077,0.00001307813,0.000001805678,0.00001370686,0.00002177545,0.00005200377,0.9989292,0.00005794732,0.00001891662,0.000709697],"study_design_scores_gemma":[0.000002434278,0.00004894729,0.001448337,0.000001570376,0.000002332136,0.00002243836,0.00002232295,0.0009648093,0.9971423,0.00003295242,0.0003078992,0.000003751511],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906556,0.0002276493,0.007988243,0.00005902287,0.00001553444,0.00001609885,0.0001889595,0.0001496394,0.0006991955],"genre_scores_gemma":[0.9912255,0.0003259141,0.007501739,0.00004084934,0.000009659997,0.00003704465,0.000117644,0.00003019278,0.000711376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009301038,"threshold_uncertainty_score":0.003111482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004785656095410023,"score_gpt":0.1969673401086606,"score_spread":0.1921816840132506,"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."}}