{"id":"W2744955431","doi":"10.1016/j.ijhydene.2017.07.143","title":"A first principles study of hydrogen storage in lithium decorated defective phosphorene","year":2017,"lang":"en","type":"article","venue":"International Journal of Hydrogen Energy","topic":"MXene and MAX Phase Materials","field":"Materials Science","cited_by":74,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada; University of Toronto; U.S. Department of Energy","keywords":"Phosphorene; Hydrogen storage; Gravimetric analysis; Density functional theory; Vacancy defect; Materials science; Hydrogen; Lithium (medication); Chemical physics; Molecule; Doping; Charge density; Graphene; Computational chemistry; Nanotechnology; Chemistry; Crystallography; Optoelectronics; Physics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001961903,0.0002549833,0.0007357845,0.0001539738,0.0005263679,0.0007011383,0.0007851413,0.000494722,0.003291784],"category_scores_gemma":[0.0001981627,0.0002434365,0.0003658344,0.0001985765,0.0007447511,0.0005698305,0.0003666112,0.0006574441,0.0001396117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004934937,"about_ca_system_score_gemma":0.0003621608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009909251,"about_ca_topic_score_gemma":0.001729948,"domain_scores_codex":[0.9999354,0.000008144046,0.000001213204,0.000006916615,0.00002893236,0.00001941253],"domain_scores_gemma":[0.9999353,0.00003505847,0.000005949947,0.00000987115,0.000008402036,0.000005497954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001286773,0.0006370565,0.002117146,0.002348679,0.0001846839,0.001959835,0.0009227198,0.1801083,0.4862975,0.3027379,0.003467488,0.01793198],"study_design_scores_gemma":[0.000215681,0.0007008994,0.002038526,0.00007421617,0.00006637251,0.0002729376,0.0003360168,0.8649875,0.1140532,0.01369965,0.003497387,0.00005759497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759681,0.000687085,0.009019181,0.0003457237,0.00006063194,0.00004395786,0.00009778368,0.00009113824,0.01368644],"genre_scores_gemma":[0.9934943,0.0002785494,0.003019223,0.00004365877,0.000006942526,0.00002219829,0.00004540655,0.00002673061,0.003062885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003291784,"threshold_uncertainty_score":0.01101214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0269239786065073,"score_gpt":0.2911182669839079,"score_spread":0.2641942883774006,"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."}}