{"id":"W2942710958","doi":"10.1088/1361-665x/ab1f14","title":"Improving the performance of lead-free piezoelectric composites by using polycrystalline inclusions and tuning the dielectric matrix environment","year":2019,"lang":"en","type":"article","venue":"Smart Materials and Structures","topic":"Dielectric materials and actuators","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"European Regional Development Fund; Ministerio de Economía y Competitividad; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Piezoelectricity; Materials science; Crystallite; Composite material; Dielectric; Composite number; Microstructure; Context (archaeology); Fabrication; Optoelectronics","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":[0.000136146,0.0002957397,0.0001895972,0.000177826,0.0001820794,0.0003947161,0.0002251912,0.000280862,0.0009023568],"category_scores_gemma":[0.0002250062,0.0001406648,0.00009144314,0.0002161682,0.0001692516,0.0003400871,0.0002015761,0.0003646071,0.000284992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001851272,"about_ca_system_score_gemma":0.0001392542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004099925,"about_ca_topic_score_gemma":0.001572625,"domain_scores_codex":[0.9998808,0.000008075173,0.000007735306,0.00002526768,0.00005247658,0.00002565516],"domain_scores_gemma":[0.999816,0.00005379937,0.00004434702,0.00001659952,0.00004799704,0.0000212974],"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":[0.00002693162,0.00002031119,0.0001175674,0.00003647245,0.000003240586,0.00002517402,0.00001702127,0.0007154422,0.99747,0.00008937391,0.00005052926,0.001427949],"study_design_scores_gemma":[0.000004058843,0.00008589962,0.0004225477,0.00000315653,0.000005408801,0.00001502514,0.00001194849,0.005302044,0.9935922,0.0000237382,0.0005297614,0.000004202015],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943805,0.0004549363,0.003226772,0.00005130331,0.00002708263,0.000007617772,0.00005444495,0.00008729284,0.001710201],"genre_scores_gemma":[0.9960747,0.0002241882,0.002967593,0.00001357756,0.000004067296,0.00001118688,0.00003865901,0.00002860016,0.0006375448],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009023568,"threshold_uncertainty_score":0.003018677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003240561101482072,"score_gpt":0.175168197164522,"score_spread":0.17192763606304,"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."}}