{"id":"W4406091987","doi":"10.1016/j.ijbiomac.2025.139572","title":"Design of boron nitride/nanocellulose aerogel-stabilized phase change materials for efficient thermal energy capture and storage","year":2025,"lang":"en","type":"article","venue":"International Journal of Biological Macromolecules","topic":"Phase Change Materials Research","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"State Key Laboratory of Pulp and Paper Engineering; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Aerogel; Materials science; Boron nitride; PEG ratio; Thermal stability; Polyethylene glycol; Nanocellulose; Thermal conductivity; Thermal energy storage; Composite material; Chemical engineering; Cellulose","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":[0.0001013509,0.0002529293,0.0002228356,0.0001512495,0.0001870579,0.0003253257,0.0002942353,0.0002763646,0.0006168613],"category_scores_gemma":[0.0001029598,0.0001370762,0.0002549892,0.0001474499,0.0001146245,0.0002261677,0.0001511686,0.0002741338,0.0003273355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005090381,"about_ca_system_score_gemma":0.0002902245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005820245,"about_ca_topic_score_gemma":0.001338112,"domain_scores_codex":[0.9999421,0.000005484528,0.000003853621,0.0000145358,0.00001606584,0.00001805783],"domain_scores_gemma":[0.9999505,0.000006317259,0.000014708,0.000004109394,0.00001193724,0.00001250417],"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":[0.00007818222,0.0000322951,0.00009361462,0.00005904633,0.000008382286,0.00004153192,0.000009494607,0.002062024,0.9946778,0.0004200757,0.00005998596,0.002457607],"study_design_scores_gemma":[0.00001816991,0.0001567196,0.0003011717,0.000004035707,0.00001013768,0.00004473449,0.00001341568,0.0112461,0.9860008,0.00007248042,0.002120976,0.00001127191],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9749808,0.001041638,0.01961419,0.00009864912,0.00005138904,0.00009080004,0.0002393303,0.0001715055,0.003711741],"genre_scores_gemma":[0.978178,0.0004552462,0.01904907,0.00003901527,0.000007041577,0.00008575281,0.0002339283,0.00004296422,0.00190895],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006168613,"threshold_uncertainty_score":0.003693342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05088422550654809,"score_gpt":0.3161434230178083,"score_spread":0.2652591975112603,"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."}}