{"id":"W2623467178","doi":"10.1039/c7ce00883j","title":"An impedance match method used to tune the electromagnetic wave absorption properties of hierarchical ZnO assembled by porous nanosheets","year":2017,"lang":"en","type":"article","venue":"CrystEngComm","topic":"Electromagnetic wave absorption materials","field":"Materials Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Materials science; Calcination; Reflection loss; Porosity; Microwave; Absorption (acoustics); Permittivity; Electrical impedance; Scattering; Reflection (computer programming); Nanoparticle; Porous medium; Electromagnetic radiation; Chemical engineering; Optoelectronics; Composite material; Nanotechnology; Optics; Dielectric; Composite number; Telecommunications; Catalysis","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":[0.00009325729,0.0002159381,0.0001369761,0.0001729593,0.0001022281,0.0001706081,0.0002511633,0.0002548757,0.000612596],"category_scores_gemma":[0.0002381511,0.0001422412,0.0002179181,0.0001862299,0.0001404215,0.0003678202,0.000161871,0.0002895733,0.000141546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001997425,"about_ca_system_score_gemma":0.00006665033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002664121,"about_ca_topic_score_gemma":0.0006459468,"domain_scores_codex":[0.9999033,0.000006297965,0.000008219971,0.00003137017,0.00003379918,0.0000169482],"domain_scores_gemma":[0.9999166,0.00002545516,0.00002767246,0.000007937219,0.00001543109,0.000007042631],"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":[0.00001578942,0.000005493275,0.00005890629,0.00003079505,0.000002567112,0.00002672644,0.00001064955,0.0001340576,0.998013,0.0001399983,0.00002092637,0.001540885],"study_design_scores_gemma":[0.000005299186,0.00003259848,0.0003438266,0.000001178523,0.000004507378,0.00003539983,0.000008140051,0.001652802,0.9972655,0.00004332429,0.0006044844,0.000002981799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9267683,0.001095564,0.06910099,0.0001133833,0.00008621787,0.00005614779,0.0002520226,0.0003146914,0.00221277],"genre_scores_gemma":[0.979919,0.0002928157,0.01876735,0.00003113331,0.000007231779,0.0000324381,0.00008406265,0.00002534915,0.0008406005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000612596,"threshold_uncertainty_score":0.002049327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03493018444420838,"score_gpt":0.298311897267071,"score_spread":0.2633817128228626,"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."}}