{"id":"https://openalex.org/W7212258332","doi":"https://doi.org/10.26434/chemrxiv.15000518/v3","title":"Resolution-Robust Mid-IR ATR-FTIR Classification of Mixed Plastic Waste with PVC Screening and Polyethylene Subclassification","display_name":"Resolution-Robust Mid-IR ATR-FTIR Classification of Mixed Plastic Waste with PVC Screening and Polyethylene Subclassification","publication_year":2026,"publication_date":"2026-09-11","ids":{"openalex":"https://openalex.org/W7212258332","doi":"https://doi.org/10.26434/chemrxiv.15000518/v3"},"language":"en","primary_location":{"id":"doi:10.26434/chemrxiv.15000518/v3","doi":"https://doi.org/10.26434/chemrxiv.15000518/v3","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15000518/v3","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15000518/v3","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15000518/v3","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109222245","display_name":"Young Ho Jeong","orcid":"https://orcid.org/0009-0005-5083-9036","observed_orcids":["https://orcid.org/0009-0005-5083-9036"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Youngho Jeong","raw_affiliation_strings":["Korea Institute of Energy Technology"],"raw_orcid":"https://orcid.org/0009-0005-5083-9036","affiliations":[{"raw_affiliation_string":"Korea Institute of Energy Technology","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5109222245"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10753","display_name":"Microplastics and Plastic Pollution","score":0.00570000009611249,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.0026000000070780516,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mixed-plastic-waste","display_name":"mixed plastic waste","score":0.8360000252723694},{"id":"https://openalex.org/keywords/low-density-polyethylene","display_name":"low-density polyethylene","score":0.9449999928474426},{"id":"https://openalex.org/keywords/linear-low-density-polyethylene","display_name":"linear low-density polyethylene","score":0.9919999837875366},{"id":"https://openalex.org/keywords/high-density-polyethylene","display_name":"high-density polyethylene","score":1.0},{"id":"https://openalex.org/keywords/mid-infrared-spectroscopy","display_name":"mid-infrared spectroscopy","score":0.8709999918937683},{"id":"https://openalex.org/keywords/atr-ftir-spectroscopy","display_name":"ATR-FTIR spectroscopy","score":0.8130000233650208},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"principal component analysis","score":0.7860000133514404},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.8450000286102295},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.9480000138282776},{"id":"https://openalex.org/keywords/post-consumer-pet","display_name":"post-consumer PET","score":0.7139999866485596},{"id":"https://openalex.org/keywords/plastic-recycling","display_name":"plastic recycling","score":0.32100000977516174}],"concepts":[{"id":"https://openalex.org/C2779751980","wikidata":"https://www.wikidata.org/wiki/Q143429","display_name":"Polyethylene","level":2,"score":0.6887999773025513},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6610999703407288},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4959999918937683},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4713999927043915},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.4408999979496002},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.4275999963283539},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39399999380111694},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3894999921321869},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.34299999475479126},{"id":"https://openalex.org/C151304367","wikidata":"https://www.wikidata.org/wiki/Q910067","display_name":"Chemometrics","level":2,"score":0.3224000036716461},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C75841233","wikidata":"https://www.wikidata.org/wiki/Q1863987","display_name":"Linear low-density polyethylene","level":3,"score":0.26840001344680786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.26434/chemrxiv.15000518/v3","doi":"https://doi.org/10.26434/chemrxiv.15000518/v3","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15000518/v3","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15000518/v3","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.26434/chemrxiv.15000518/v3","doi":"https://doi.org/10.26434/chemrxiv.15000518/v3","is_oa":true,"landing_page_url":"https://doi.org/10.26434/chemrxiv.15000518/v3","pdf_url":"https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15000518/v3","source":{"id":"https://openalex.org/S4393918830","display_name":"ChemRxiv","issn_l":"2573-2293","issn":["2573-2293"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/12","score":0.807699978351593,"display_name":"Responsible consumption and production"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7212258332.pdf","grobid_xml":"https://content.openalex.org/works/W7212258332.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7133196621","https://openalex.org/W4220854003","https://openalex.org/W3161702062","https://openalex.org/W6941508505","https://openalex.org/W3015056210","https://openalex.org/W7128815433","https://openalex.org/W3163706078","https://openalex.org/W7071213731","https://openalex.org/W7214996055","https://openalex.org/W2373649389"],"abstract_inverted_index":{"Reliable":[0],"and":[1,12,42,56,83,92,116,136,154,168,196,200,206,215,225],"chemistry-specific":[2],"presorting":[3],"of":[4,44,62,142,194],"mixed":[5],"plastic":[6,134,232],"waste":[7],"is":[8,35],"essential":[9],"for":[10,37,230],"safe":[11],"efficient":[13],"valorization.":[14],"In":[15],"this":[16],"study,":[17],"a":[18,110,222],"resolution-robust":[19],"mid-infrared":[20],"attenuated":[21],"total":[22,61],"reflectance":[23],"Fourier":[24],"transform":[25],"infrared":[26],"spectroscopy":[27],"(ATR-FTIR)":[28],"workflow":[29,229],"coupled":[30],"with":[31,89,166],"simple":[32,143],"machine-learning":[33],"classifiers":[34,144,159,182],"presented":[36],"poly(vinyl":[38],"chloride)":[39],"(PVC)":[40],"screening":[41],"subclassification":[43],"three":[45],"polyethylene":[46,50,54,58],"(PE)":[47],"grades:":[48],"low-density":[49,53],"(LDPE),":[51],"linear":[52],"(LLDPE),":[55],"high-density":[57],"(HDPE).":[59],"A":[60],"770":[63],"ATR-FTIR":[64],"spectra":[65],"in":[66],"the":[67,104,133,140,163,176],"fingerprint":[68,122],"region":[69],"(2500\u2013500":[70],"cm\u207b\u00b9)":[71],"were":[72,160],"collected":[73],"from":[74],"seven":[75],"plastics:":[76],"LDPE,":[77],"LLDPE,":[78],"HDPE,":[79],"PP,":[80],"PS,":[81],"PET,":[82],"PVC,":[84],"using":[85],"commercial":[86],"pellets":[87],"together":[88],"post-consumer":[90],"PET":[91],"discarded":[93],"PVC":[94,211],"gloves.":[95],"Principal":[96],"component":[97],"analysis":[98],"(PCA)":[99],"was":[100],"used":[101],"to":[102,190],"compress":[103],"high-dimensional,":[105],"correlated":[106],"spectral":[107,192],"inputs":[108],"into":[109],"low-dimensional":[111,130],"score":[112],"space,":[113],"reducing":[114],"multicollinearity":[115],"overfitting":[117],"risk":[118],"while":[119],"preserving":[120],"class-identifiable":[121],"information.":[123],"The":[124],"resulting":[125],"PCA":[126,164],"structure":[127],"showed":[128],"clear":[129],"separability":[131],"among":[132],"classes":[135],"PE":[137],"subclasses,":[138],"supporting":[139],"use":[141],"rather":[145],"than":[146],"heavily":[147],"parameterized":[148],"black-box":[149],"architectures.":[150],"Support-vector":[151],"machine":[152],"(SVM)":[153],"artificial":[155],"neural":[156],"network":[157],"(ANN)":[158],"trained":[161],"on":[162],"scores,":[165],"internal-test":[167],"strictly":[169],"independent":[170],"external-validation":[171,185,208],"performances":[172],"evaluated":[173],"separately.":[174],"For":[175],"baseline":[177],"dataset":[178],"(2":[179],"cm\u207b\u00b9),":[180],"both":[181],"achieved":[183],"100%":[184,207],"accuracy.":[186],"Even":[187],"after":[188],"degradation":[189],"effective":[191],"resolutions":[193],"8":[195],"16":[197],"cm\u207b\u00b9,":[198],"SVM":[199],"ANN":[201],"maintained":[202],"99.68%":[203],"internal":[204],"accuracy":[205,209],"across":[210],"screening,":[212],"PE-grade":[213],"subclassification,":[214],"full":[216],"seven-class":[217],"discrimination.":[218],"These":[219],"results":[220],"demonstrate":[221],"resolution-robust,":[223],"PCA-interpretable,":[224],"externally":[226],"validated":[227],"ATR-FTIR/ML":[228],"practical":[231],"presorting.":[233]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-09-12T00:00:00"}
