{"id":"W2889685640","doi":"10.1063/1.5044456","title":"Surface reaction kinetics in atomic layer deposition: An analytical model and experiments","year":2018,"lang":"en","type":"article","venue":"Journal of Applied Physics","topic":"Semiconductor materials and devices","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Atomic layer deposition; Chemistry; Chemisorption; Substrate (aquarium); Physisorption; Desorption; Kinetics; Deposition (geology); Chemical kinetics; Reaction rate constant; Chemical engineering; Adsorption; Thermodynamics; Physical chemistry; Analytical Chemistry (journal); Layer (electronics); Chromatography; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005501702,0.00007405734,0.0001369167,0.00002176278,0.00001317594,0.00003068504,0.00004566842,0.00004161058,0.000004476332],"category_scores_gemma":[5.697722e-7,0.00006864928,0.0000149981,0.0000526251,0.00002063229,0.0001571452,0.000008823533,0.00007580744,0.00000276137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003638594,"about_ca_system_score_gemma":0.000007053353,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002241389,"about_ca_topic_score_gemma":0.000001623548,"domain_scores_codex":[0.9995675,0.000004602394,0.0001903138,0.00005758303,0.00009468904,0.00008530828],"domain_scores_gemma":[0.9997916,0.000007321122,0.00005257749,0.00006638858,0.00003160926,0.00005055572],"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":[0.00003744331,0.00003323235,0.00003742185,0.000009204162,0.00001242482,0.000001109969,0.0003341018,0.03537152,0.9635795,0.0003779366,0.00004503041,0.0001611323],"study_design_scores_gemma":[0.0003958124,0.00006136972,0.0007164982,0.00001821185,0.00001867156,0.00001029675,0.0001149618,0.4295606,0.5666372,0.002334897,0.0000285191,0.0001029335],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980648,0.00003663036,0.0008148197,0.000002462627,0.0001288853,0.00002944321,0.000001207582,0.00001217651,0.0009096401],"genre_scores_gemma":[0.9975403,0.00002042794,0.002064487,0.00002659212,0.0003311898,4.344436e-7,0.000001191272,0.00001410688,0.000001272308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3969422,"threshold_uncertainty_score":0.2799436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0334839413210176,"score_gpt":0.2797005853822567,"score_spread":0.2462166440612391,"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."}}