{"id":"W2900747657","doi":"10.1039/c8qm00503f","title":"Multi-length scale morphology of nonfullerene all-small molecule blends and its relation to device function in organic solar cells","year":2018,"lang":"en","type":"article","venue":"Materials Chemistry Frontiers","topic":"Organic Electronics and Photovoltaics","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carbon Engineering (Canada)","funders":"Office of Naval Research; National Natural Science Foundation of China; Royal Society; Chinese Academy of Sciences; Chinese Chemical Society; Royal Society of Chemistry; U.S. Department of Energy","keywords":"Organic solar cell; Small molecule; Materials science; Morphology (biology); Molecule; Mesoscale meteorology; Length scale; Function (biology); Chemical physics; Scattering; Chemical engineering; Crystallography; Chemistry; Polymer; Optics; Physics; Composite material; Organic chemistry; Biology; Meteorology","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.00014943,0.0001550547,0.0002298563,0.00003958472,0.00003697118,0.00002837851,0.00009864616,0.0001846807,0.0003136972],"category_scores_gemma":[0.00001367365,0.0001800702,0.0000159631,0.0001323548,0.000020609,0.00004362576,0.0000525166,0.00008657975,0.0000172602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008230295,"about_ca_system_score_gemma":0.00002510829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002564664,"about_ca_topic_score_gemma":0.00003021789,"domain_scores_codex":[0.9991738,0.00001704311,0.0002718476,0.0002144811,0.00006340291,0.0002594527],"domain_scores_gemma":[0.9996646,0.000006610196,0.00005176934,0.0001608895,0.00004546169,0.00007068089],"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":[0.00003980422,0.00001671956,0.00005087309,0.0001319814,0.00002971545,0.000001200246,0.0001685533,0.00009391439,0.9989941,4.498002e-7,0.0004115535,0.00006117581],"study_design_scores_gemma":[0.0004170909,0.00005330888,0.0001863779,0.00002040617,0.0000271274,0.000003848137,0.00004530187,0.001961025,0.9963608,0.00001585051,0.0007386809,0.0001701854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965822,0.0002231677,0.002332017,0.0000198081,0.0004440629,0.0001313726,0.00002689246,0.00005278052,0.000187693],"genre_scores_gemma":[0.9982567,0.0001328147,0.001238833,0.00003004534,0.00008181234,0.00001015475,0.00003380399,0.00004273298,0.0001730925],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002633262,"threshold_uncertainty_score":0.7343051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007095019590875418,"score_gpt":0.1883642418520645,"score_spread":0.1812692222611891,"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."}}