{"id":"W2956114943","doi":"10.1109/tuffc.2019.2926211","title":"Thin Film PZT-Based PMUT Arrays for Deterministic Particle Manipulation","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control","topic":"Microfluidic and Bio-sensing Technologies","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"FujiFilm VisualSonics (Canada)","funders":"National Institute of Biomedical Imaging and Bioengineering; National Defense Science and Engineering Graduate; Sunnybrook Research Institute; National Science Foundation","keywords":"Materials science; PMUT; Lead zirconate titanate; Piezoelectricity; Ultrasonic sensor; Acoustics; Diaphragm (acoustics); Waveform; Microfluidics; Transducer; Sound pressure; Particle (ecology); Levitation; Electromechanical coupling coefficient; Voltage; Optoelectronics; Dielectric; Electrical engineering; Composite material; Nanotechnology; Ferroelectricity; Vibration; Engineering","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":[0.000202703,0.0003350162,0.0002663202,0.0001954081,0.0001635243,0.0003266185,0.0005157969,0.0005098221,0.0007930151],"category_scores_gemma":[0.0005040793,0.0003734434,0.0001412491,0.0002460986,0.0002300029,0.000434909,0.0003424361,0.0002936311,0.0004032206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002797473,"about_ca_system_score_gemma":0.0002037966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002566186,"about_ca_topic_score_gemma":0.0006975569,"domain_scores_codex":[0.9997843,0.00002236207,0.00001370285,0.00005906692,0.0001030018,0.00001758697],"domain_scores_gemma":[0.9997944,0.00006956669,0.00005580056,0.00002355606,0.00004039784,0.00001633754],"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":[0.00002265618,0.00000599882,0.000118485,0.00004932215,0.000003283498,0.00003702661,0.00002121313,0.0007145944,0.9931921,0.0002175428,0.00009072745,0.005527089],"study_design_scores_gemma":[0.00000708654,0.00009412242,0.000537442,0.000003631701,0.000008222584,0.0001024104,0.00001325368,0.01007987,0.9868934,0.0000629067,0.002189153,0.000008479554],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7327831,0.003282163,0.2563265,0.0003588716,0.0002979061,0.0001670716,0.0003970909,0.001210551,0.005176722],"genre_scores_gemma":[0.7470558,0.001293137,0.2452989,0.0001654838,0.0000543663,0.0001855787,0.0002423435,0.00006085475,0.00564356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007930151,"threshold_uncertainty_score":0.002652884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01155493331430625,"score_gpt":0.2040343192162407,"score_spread":0.1924793859019344,"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."}}