{"id":"W3183017807","doi":"10.1016/j.apcatb.2021.120533","title":"Accelerating photoelectric CO2 conversion with a photothermal wavelength-dependent plasmonic local field","year":2021,"lang":"en","type":"article","venue":"Applied Catalysis B: Environmental","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Light Source (Canada); University of Alberta","funders":"Natural Science Foundation of Zhejiang Province; Canada First Research Excellence Fund; State Key Laboratory of Clean Energy Utilization; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; University of Alberta","keywords":"Photothermal therapy; Plasmon; Photoelectric effect; Wavelength; Optoelectronics; Optics; Materials science; Field (mathematics); 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":[0.0001233465,0.0002535269,0.0001651379,0.000148181,0.0002041447,0.0003019143,0.0004012698,0.0002981272,0.002385384],"category_scores_gemma":[0.0001837861,0.0001710131,0.000139216,0.0001752015,0.0003765805,0.0003436995,0.0003607967,0.0004655387,0.0004082863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000413846,"about_ca_system_score_gemma":0.0001957594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004577693,"about_ca_topic_score_gemma":0.001033296,"domain_scores_codex":[0.9999268,0.000006567101,0.000002095439,0.00002114973,0.00002350395,0.00001986752],"domain_scores_gemma":[0.9999099,0.00003385489,0.0000155848,0.00001530085,0.00001353016,0.00001173861],"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":[0.00008232013,0.00003194378,0.00008842567,0.00005014954,0.000003026545,0.00003296672,0.00003713525,0.0003645163,0.9937019,0.000836853,0.0003663274,0.004404404],"study_design_scores_gemma":[0.00002174047,0.00006911249,0.0003246002,0.000003263866,0.000005219006,0.00004575472,0.00001739292,0.004976823,0.9925613,0.00009517169,0.001873167,0.000006457914],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.960591,0.0006306263,0.02557264,0.0005924379,0.0001196766,0.00004845333,0.00007331657,0.0005991955,0.01177273],"genre_scores_gemma":[0.9890018,0.0001728562,0.006592392,0.00009540987,0.0000340481,0.00002178461,0.00002610391,0.00004825542,0.00400744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002385384,"threshold_uncertainty_score":0.00797987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005527720443561572,"score_gpt":0.1834078473602483,"score_spread":0.1778801269166868,"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."}}