{"id":"W3184304664","doi":"10.1016/j.cej.2021.131362","title":"Mercury adsorption kinetics on sulfurized biochar and solid-phase digestion using aqua regia: A synchrotron-based study","year":2021,"lang":"en","type":"article","venue":"Chemical Engineering Journal","topic":"Mercury impact and mitigation studies","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Light Source (Canada); University of Waterloo","funders":"Fundamental Research Funds for the Central Universities; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National University's Basic Research Foundation of China; Foundation for Innovative Research Groups of the National Natural Science Foundation of China; China University of Geosciences, Wuhan; Canada Research Chairs","keywords":"Aqua regia; Biochar; Chemistry; Adsorption; Mercury (programming language); Aqueous solution; Aqueous two-phase system; Solid phase extraction; Nuclear chemistry; Extraction (chemistry); Chromatography; Metal; 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":[0.0003751649,0.0002772596,0.0005350197,0.0002116824,0.0002856064,0.000315393,0.0005001692,0.0003550507,0.0006051349],"category_scores_gemma":[0.000271243,0.0002022546,0.0005431937,0.0003316462,0.0003395259,0.0002313165,0.0002102979,0.0003121929,0.000232026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003179053,"about_ca_system_score_gemma":0.0003571089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005853426,"about_ca_topic_score_gemma":0.004625275,"domain_scores_codex":[0.9997929,0.00003477253,0.0000144232,0.00004424064,0.00006429588,0.00004950825],"domain_scores_gemma":[0.9998757,0.00003714674,0.00002041677,0.0000166774,0.00004120791,0.000008905624],"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":[0.0003302285,0.0000458575,0.001146104,0.00005208257,0.00002242673,0.000038851,0.00007229295,0.0003578414,0.9966529,0.00004783237,0.00003680458,0.001196832],"study_design_scores_gemma":[0.00002667816,0.0006022579,0.01306755,0.000005871598,0.00004869873,0.0001421327,0.0001779322,0.003899631,0.9810995,0.00004980953,0.0008608733,0.00001917754],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989654,0.0001894414,0.0004192053,0.00001454469,0.00000363054,0.000003693101,0.00008629236,0.00001514987,0.0003026737],"genre_scores_gemma":[0.9982071,0.0002115501,0.0007572739,0.00001242634,0.000002713586,0.000004951612,0.0001315068,0.000008736053,0.000663741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005853426,"threshold_uncertainty_score":0.0116387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01910569049843459,"score_gpt":0.2918222555020732,"score_spread":0.2727165650036386,"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."}}