{"id":"W2299390272","doi":"10.1117/12.2218486","title":"Advances with vertical epitaxial heterostructure architecture (VEHSA) phototransducers for optical to electrical power conversion efficiencies exceeding 50 percent","year":2016,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"solar cell performance optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Ottawa; Institut interdisciplinaire d'innovation technologique; Optech (Canada); Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Optoelectronics; Heterojunction; Materials science; Stacking; Diode; Absorption (acoustics); Metalorganic vapour phase epitaxy; Fabrication; Semiconductor; Gallium arsenide; Optics; Epitaxy; Nanotechnology; Chemistry; Physics; Layer (electronics)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003273076,0.0004624723,0.0004850047,0.000170268,0.0001200129,0.0001089461,0.0007184359,0.0002645153,0.00002180799],"category_scores_gemma":[0.0003850348,0.000313322,0.0004569419,0.0003807696,0.0002668454,0.0006286268,0.00008424218,0.0003249344,0.00000198906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003614089,"about_ca_system_score_gemma":0.00003289414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001073413,"about_ca_topic_score_gemma":1.491778e-7,"domain_scores_codex":[0.9973853,2.509306e-8,0.0005924985,0.0004966727,0.0008124102,0.0007130786],"domain_scores_gemma":[0.9984105,0.0002224499,0.000103663,0.00007483136,0.0009350092,0.0002536007],"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":[0.0005745159,0.00006355889,0.0002869674,0.0004156207,0.000223345,1.201927e-7,0.0003744006,0.007540355,0.956982,0.03187525,0.0007591309,0.0009047102],"study_design_scores_gemma":[0.003588974,0.002032045,0.001303973,0.0007925956,0.0002651982,0.00005374612,0.0009365487,0.1373751,0.8453296,0.0003368559,0.006897367,0.001088013],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899547,0.00008394627,0.00646481,0.00119886,0.0003708423,0.00103022,0.00004690882,0.000197897,0.0006518789],"genre_scores_gemma":[0.8255281,0.0001283169,0.1735676,0.00007781771,0.0003353853,0.000210991,0.0000071721,0.0001148744,0.000029626],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1671028,"threshold_uncertainty_score":0.9999319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005295845396684872,"score_gpt":0.1985219448939435,"score_spread":0.1932260994972586,"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."}}