{"id":"W4319791618","doi":"10.1002/adfm.202212301","title":"Stable, Cost‐Effective TiN‐Based Plasmonic Nanocomposites with over 99% Solar Steam Generation Efficiency","year":2023,"lang":"en","type":"article","venue":"Advanced Functional Materials","topic":"Solar-Powered Water Purification Methods","field":"Energy","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Materials science; Tin; Plasmon; Energy conversion efficiency; Graphene; Photothermal therapy; Absorption (acoustics); Plasmonic nanoparticles; Chemical engineering; Tin oxide; Nanotechnology; Nanoparticle; Nanocomposite; Optoelectronics; Composite material; Metallurgy; Doping","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006972183,0.0003461082,0.0003714128,0.0002741338,0.0003548719,0.0001402121,0.000176633,0.0001508338,0.001379663],"category_scores_gemma":[0.0001620478,0.0002996454,0.00006746218,0.0007111563,0.00008603701,0.0004830651,0.00005063649,0.0001272677,0.0007306561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002147643,"about_ca_system_score_gemma":0.0001050658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006230475,"about_ca_topic_score_gemma":0.00002167078,"domain_scores_codex":[0.9973716,0.0004662746,0.0004724818,0.0006755807,0.000514355,0.0004997808],"domain_scores_gemma":[0.9984561,0.0004638952,0.0002547465,0.0004648397,0.000250095,0.0001103676],"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":[0.0005308088,0.00007705965,0.0003299227,0.00002984417,0.00005358407,0.000006372957,0.00004563259,0.157895,0.8363001,0.00159718,0.0004506553,0.002683778],"study_design_scores_gemma":[0.001799872,0.0002552742,0.01305899,0.00003942223,0.00004016088,0.000008318849,0.00003033085,0.002318984,0.9676566,0.0004557887,0.01394723,0.000389092],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9549164,0.00006015124,0.03991428,0.0001017118,0.00204376,0.001428275,0.0001600075,0.000662353,0.0007130848],"genre_scores_gemma":[0.982629,0.00001711988,0.01212136,0.000273311,0.0004095911,0.001809837,0.00143327,0.0001041393,0.001202384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.155576,"threshold_uncertainty_score":0.9999456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0231972770404672,"score_gpt":0.2742773201550775,"score_spread":0.2510800431146103,"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."}}