{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T13:53:12Z","timestamp":1785851592959,"version":"3.56.0"},"reference-count":54,"publisher":"American Chemical Society (ACS)","issue":"30","license":[{"start":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T00:00:00Z","timestamp":1784592000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010672","name":"H2020 LEIT Advanced Manufacturing and Processing","doi-asserted-by":"publisher","award":["760921"],"award-info":[{"award-number":["760921"]}],"id":[{"id":"10.13039\/100010672","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001602","name":"Science Foundation Ireland","doi-asserted-by":"publisher","award":["18\/CRT\/6223"],"award-info":[{"award-number":["18\/CRT\/6223"]}],"id":[{"id":"10.13039\/501100001602","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["18\/CRT\/6223"],"award-info":[{"award-number":["18\/CRT\/6223"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Electrospun membranes are widely used in tissue modeling because their tunable fibrous architecture can capture key structural features of the extracellular matrix of native tissues. For functional in vitro lung barrier models, membrane substrates should ideally combine stability and reproducibility with basement-membrane-relevant features, including fine fibers, reduced stiffness, and sufficient strength and extensibility to tolerate breathing-mimetic deformation. Here, poly(\u03b5-caprolactone) (PCL)\u2013poly(lactic-co-glycolic acid) (PLGA) blends were optimized to develop fully synthetic electrospun membranes that balance these competing structural and mechanical requirements. Response surface methodology (RSM) was first applied to a Box\u2013Behnken electrospinning design, in which fiber diameter, Young\u2019s modulus, ultimate tensile strength (UTS), and strain at break were treated as coequal responses. The model predicted membranes with a fiber diameter of 0.386 \u00b1 0.004 \u03bcm, Young\u2019s modulus of 152.156 \u00b1 1.751 MPa, UTS of 41.850 \u00b1 0.149 MPa, and strain at break of 2.948 \u00b1 0.020, with confirmatory experiments deviating by less than 10% from predicted values. Machine learning (ML) extended this experimentally anchored framework by adding validated augmentation, inverse property-to-parameter prediction, and multiresponse desirability optimization. A six-generator fidelity screen selected Gaussian-Copula augmentation over WGAN-GP for downstream modeling, while leakage-free leave-one-real-observation-out evaluation showed that CatBoost most robustly recovered the polymer-composition targets, with (leave-one-out) LOO R2 values of 0.675 for PCL concentration and 0.747 for PLGA concentration. XGBoost forward-surrogate optimization achieved the highest model-derived desirability at 0.895 \u00b1 0.065, compared with 0.782 for the experimentally confirmed design of experiments reference. Overall, the workflow demonstrates that ML can complement RSM by prioritizing candidate electrospinning windows, quantifying uncertainty, and clarifying property-to-parameter coupling in multiresponse fibrous membrane design.<\/jats:p>","DOI":"10.1021\/acsomega.6c03020","type":"journal-article","created":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T09:35:59Z","timestamp":1784626559000},"page":"45008-45026","source":"Crossref","is-referenced-by-count":0,"title":["Optimization of\nElectrospun PCL\u2013PLGA Substrates\nfor Lung Basement Membrane Applications Using Response Surface Methodology\nand Machine Learning Approaches"],"prefix":"10.1021","volume":"11","author":[{"given":"Golestan","family":"Salimbeigi","sequence":"first","affiliation":[{"name":"Dublin City University , , Collins Avenue Extension, Glasnevin, D09 V209 , ,","place":["Dublin, Ireland, 9"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Halima","family":"Boutouil","sequence":"additional","affiliation":[{"name":"Dublin City University , , Collins Avenue Extension, Glasnevin, D09 V209 , ,","place":["Dublin, Ireland, 9"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tanya","family":"Levingstone","sequence":"additional","affiliation":[{"name":"Dublin City University , , Collins Avenue Extension, Glasnevin, D09 V209 , ,","place":["Dublin, Ireland, 9"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1023-8667","authenticated-orcid":true,"given":"Garrett B.","family":"McGuinness","sequence":"additional","affiliation":[{"name":"Dublin City University , , Collins Avenue Extension, Glasnevin, D09 V209 , ,","place":["Dublin, Ireland, 9"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,7,21]]},"reference":[{"issue":"S4","key":"2026080409255893200_cit1","doi-asserted-by":"publisher","first-page":"467","DOI":"10.1007\/s00586-008-0745-3","article-title":"Scaffolding in tissue engineering: general approaches\nand tissue-specific considerations","volume":"17","author":"Chan","year":"2008","journal-title":"Eur. Spine\nJ."},{"issue":"5","key":"2026080409255893200_cit2","doi-asserted-by":"publisher","first-page":"1197","DOI":"10.1089\/ten.2006.12.1197","article-title":"Electrospinning\nof Polymeric Nanofibers\nfor Tissue Engineering Applications: A Review","volume":"12","author":"Pham","year":"2006","journal-title":"Tissue Engineering"},{"issue":"4","key":"2026080409255893200_cit3","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1002\/jbm.10167","article-title":"Electrospun\nnanofibrous structure: A novel scaffold for tissue engineering","volume":"60","author":"Li","year":"2002","journal-title":"J. Biomed. Mater. Res."},{"issue":"1","key":"2026080409255893200_cit4","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1002\/marc.200900431","article-title":"Single-Step\nElectrospinning of Bimodal Fiber Meshes for Ease of Cellular Infiltration","volume":"31","author":"Gentsch","year":"2010","journal-title":"Macromol. Rapid Commun."},{"issue":"4","key":"2026080409255893200_cit5","doi-asserted-by":"publisher","first-page":"677","DOI":"10.1016\/j.cell.2006.06.044","article-title":"Matrix Elasticity Directs Stem Cell\nLineage Specification","volume":"126","author":"Engler","year":"2006","journal-title":"Cell"},{"key":"2026080409255893200_cit6","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.53095","article-title":"Critical Challenges\nand Frontiers in Cartilage Tissue Engineering","volume":"16","author":"Jeyaraman","year":"2024","journal-title":"Cureus"},{"key":"2026080409255893200_cit7","doi-asserted-by":"publisher","first-page":"100301","DOI":"10.1016\/j.mtbio.2022.100301","article-title":"Basement\nmembrane properties and their recapitulation in organ-on-chip applications","volume":"15","author":"Salimbeigi","year":"2022","journal-title":"Mater. 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Mater."},{"issue":"4","key":"2026080409255893200_cit10","doi-asserted-by":"publisher","first-page":"1133","DOI":"10.1152\/ajplegacy.1970.218.4.1133","article-title":"Estimation of equivalent\npore radii of pulmonary capillary and alveolar\nmembranes","volume":"218","author":"Taylor","year":"1970","journal-title":"Am. J. Physiol."},{"key":"2026080409255893200_cit11","doi-asserted-by":"publisher","first-page":"810705","DOI":"10.3389\/fbioe.2022.810705","article-title":"Pneumatospinning\nBiomimetic Scaffolds for Meniscus Tissue Engineering","volume":"10","author":"Dorthe\u0301","year":"2022","journal-title":"Front Bioeng Biotechnol"},{"issue":"2","key":"2026080409255893200_cit12","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1152\/jappl.1985.59.2.580","article-title":"Passage\nof uncharged dextrans from blood to lung lymph\nin awake sheep","volume":"59","author":"Lanken","year":"1985","journal-title":"J. Appl. Physiol."},{"issue":"39","key":"2026080409255893200_cit13","doi-asserted-by":"publisher","first-page":"1903114","DOI":"10.1002\/adfm.201903114","article-title":"Evolution\nof Bioengineered Lung Models: Recent Advances\nand Challenges in Tissue Mimicry for Studying the Role of Mechanical\nForces in Cell Biology","volume":"29","author":"Doryab","year":"2019","journal-title":"Adv. Funct Materials"},{"issue":"1","key":"2026080409255893200_cit14","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1152\/physiologyonline.1995.10.1.30","article-title":"Mechanical Properties\nof Basement\nMembrane","volume":"10","author":"Welling","year":"1995","journal-title":"Physiology"},{"key":"2026080409255893200_cit15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/cphy.c100090","article-title":"Mechanobiology\nin Lung Epithelial Cells: Measurements, Perturbations, and Responses","volume-title":"Comprehensive\nPhysiology","author":"Waters","year":"2012","edition":"1"},{"key":"2026080409255893200_cit16","doi-asserted-by":"publisher","first-page":"105493","DOI":"10.1016\/j.jmbbm.2022.105493","article-title":"Solvent\nsystem effects on the physical\nand mechanical properties of electrospun Poly(\u03b5-caprolactone)\nscaffolds for in vitro lung models","volume":"136","author":"Salimbeigi","year":"2022","journal-title":"J. Mech.\nBehav. Biomed. Mater."},{"issue":"19","key":"2026080409255893200_cit17","doi-asserted-by":"publisher","first-page":"52131","DOI":"10.1002\/app.52131","article-title":"Electrospun\npoly(e-caprolactone)\/propolis\nfiber morphology: A process optimization study","volume":"139","author":"Salimbeigi","year":"2022","journal-title":"J. Appl. Polym. Sci."},{"issue":"4","key":"2026080409255893200_cit18","doi-asserted-by":"publisher","first-page":"045404","DOI":"10.1088\/2053-1591\/aaba1d","article-title":"Modeling and\nprocess optimization of electrospinning of chitosan-collagen nanofiber\nby response surface methodology","volume":"5","author":"Amiri","year":"2018","journal-title":"Mater. Res.\nExpress"},{"issue":"4","key":"2026080409255893200_cit19","doi-asserted-by":"publisher","first-page":"2000678","DOI":"10.1002\/mame.202000678","article-title":"Box-Behnken\nDesign a Key Tool to Achieve Optimized PCL\/Gelatin Electrospun Mesh","volume":"306","author":"Guerreiro","year":"2021","journal-title":"Macro Materials & Eng."},{"issue":"6","key":"2026080409255893200_cit20","doi-asserted-by":"publisher","first-page":"2411","DOI":"10.1002\/pc.25545","article-title":"Optimization of the electrospinning\nprocess variables for gelatin\/silver nanoparticles\/bioactive glass\nnanocomposites for bone tissue engineering","volume":"41","author":"Akturk","year":"2020","journal-title":"Polym. Compos."},{"issue":"6","key":"2026080409255893200_cit21","doi-asserted-by":"publisher","first-page":"1191","DOI":"10.1002\/btpr.67","article-title":"Bioprocess optimization using design-of-experiments\nmethodology","volume":"24","author":"Mandenius","year":"2008","journal-title":"Biotechnol. Prog."},{"issue":"4","key":"2026080409255893200_cit22","doi-asserted-by":"publisher","first-page":"190","DOI":"10.30657\/pea.2020.26.33","article-title":"Challenges\nfor the DOE methodology\nrelated to the introduction of Industry 4.0","volume":"26","author":"Pietraszek","year":"2020","journal-title":"Prod. Eng. Arch."},{"issue":"1","key":"2026080409255893200_cit23","doi-asserted-by":"publisher","first-page":"11370","DOI":"10.1038\/s41598-019-47846-6","article-title":"A Design of Experiments (DoE) Approach\nAccelerates the Optimization of Copper-Mediated 18F-Fluorination Reactions\nof Arylstannanes","volume":"9","author":"Bowden","year":"2019","journal-title":"Sci. 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Appl. Stat."},{"key":"2026080409255893200_cit27","doi-asserted-by":"publisher","first-page":"100640","DOI":"10.1016\/j.tbs.2023.100640","article-title":"Machine learning techniques for evaluating\nthe nonlinear\nlink between built-environment characteristics and travel behaviors:\nA systematic review","volume":"33","author":"Aghaabbasi","year":"2023","journal-title":"Travel Behav. Soc."},{"issue":"10","key":"2026080409255893200_cit28","doi-asserted-by":"publisher","first-page":"561","DOI":"10.3390\/bioengineering9100561","article-title":"The Role\nof Machine Learning and Design of Experiments in the Advancement of\nBiomaterial and Tissue Engineering Research","volume":"9","author":"Al-Kharusi","year":"2022","journal-title":"Bioengineering"},{"issue":"31","key":"2026080409255893200_cit29","doi-asserted-by":"publisher","first-page":"14095","DOI":"10.1007\/s10853-024-09994-7","article-title":"Machine learning\napplications for\nelectrospun nanofibers: a review","volume":"59","author":"Subeshan","year":"2024","journal-title":"J. Mater.\nSci."},{"issue":"5\u20136","key":"2026080409255893200_cit30","doi-asserted-by":"publisher","first-page":"2823","DOI":"10.1007\/s00170-026-17480-4","article-title":"Data-driven prediction and optimization of electrospun\nnanofibrous scaffold diameters for tissue engineering applications\nusing machine learning and genetic algorithms","volume":"143","author":"Subeshan","year":"2026","journal-title":"Int. J. Adv. Des. Manuf. Technol."},{"issue":"8","key":"2026080409255893200_cit31","doi-asserted-by":"publisher","first-page":"7434","DOI":"10.1021\/acsnano.8b04726","article-title":"How To\nOptimize Materials and Devices via Design of Experiments\nand Machine Learning: Demonstration Using\nOrganic Photovoltaics","volume":"12","author":"Cao","year":"2018","journal-title":"ACS Nano"},{"issue":"5","key":"2026080409255893200_cit32","doi-asserted-by":"publisher","first-page":"1930","DOI":"10.1021\/acssuschemeng.3c06025","article-title":"Machine Learning and\nTaguchi DOE Combined Approach for Modeling Dynamic Ultrasound-Assisted\nFresh-Cut Leafy Green Sanitation","volume":"12","author":"Dong","year":"2024","journal-title":"ACS Sustainable\nChem. Eng."},{"issue":"2","key":"2026080409255893200_cit33","doi-asserted-by":"publisher","first-page":"1131","DOI":"10.1002\/qre.3025","article-title":"Design of Experiments\nand machine learning for product innovation: A systematic literature\nreview","volume":"38","author":"Arboretti","year":"2022","journal-title":"Quality & Reliability Eng."},{"key":"2026080409255893200_cit34","doi-asserted-by":"publisher","first-page":"111098","DOI":"10.1016\/j.matdes.2022.111098","article-title":"Design of experiments\ninformed deep learning for modeling of directed energy deposition\nprocess with a small-size experimental dataset","volume":"222","author":"Chen","year":"2022","journal-title":"Mater. Des."},{"key":"2026080409255893200_cit35","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.polymer.2014.12.046","article-title":"Electrospinning predictions\nusing artificial neural\nnetworks","volume":"58","author":"Brooks","year":"2015","journal-title":"Polymer"},{"issue":"1","key":"2026080409255893200_cit36","doi-asserted-by":"publisher","first-page":"9679","DOI":"10.1038\/s41598-023-36431-7","article-title":"Electrospun nanofiber membrane diameter prediction\nusing a combined response surface methodology and machine learning\napproach","volume":"13","author":"Pervez","year":"2023","journal-title":"Sci. Rep"},{"issue":"43","key":"2026080409255893200_cit37","doi-asserted-by":"publisher","first-page":"24858","DOI":"10.1039\/C9RA04927D","article-title":"Application\nof ANN modeling techniques in the prediction of the diameter of PCL\/gelatin\nnanofibers in environmental and medical studies","volume":"9","author":"Kalantary","year":"2019","journal-title":"RSC Adv."},{"key":"2026080409255893200_cit38","doi-asserted-by":"publisher","first-page":"110923","DOI":"10.1016\/j.compbiomed.2025.110923","article-title":"Predicting\ndiameter and tensile strength of electrospun fibers for biomedicine:\nA comparison of Box-Behnken design, traditional machine learning and\ndeep learning","volume":"196","author":"Badaraev","year":"2025","journal-title":"Comput. Biol. Med."},{"key":"2026080409255893200_cit39","doi-asserted-by":"publisher","first-page":"102826","DOI":"10.1016\/j.rineng.2024.102826","article-title":"Data-driven prediction of electrospun nanofiber diameter\nusing machine learning: A comprehensive study and web-based tool development","volume":"24","author":"Sukpancharoen","year":"2024","journal-title":"Results Eng."},{"issue":"1","key":"2026080409255893200_cit40","doi-asserted-by":"publisher","first-page":"21017","DOI":"10.1038\/s41598-024-71824-2","article-title":"Machine learning to\npredict morphology, topography and mechanical properties of sustainable\ngelatin-based electrospun scaffolds","volume":"14","author":"Rolda\u0301n","year":"2024","journal-title":"Sci. Rep"},{"key":"2026080409255893200_cit41","doi-asserted-by":"publisher","first-page":"106630","DOI":"10.1016\/j.jmbbm.2024.106630","article-title":"Machine learning to\nmechanically assess 2D and 3D biomimetic electrospun scaffolds for\ntissue engineering applications: Between the predictability and the\ninterpretability","volume":"157","author":"Rolda\u0301n","year":"2024","journal-title":"J. Mech. Behav. Biomed. Mater."},{"issue":"12","key":"2026080409255893200_cit42","doi-asserted-by":"publisher","first-page":"3033","DOI":"10.1080\/00405000.2025.2472089","article-title":"Optimising\nthe manufacturing\nof electrospun nanofibrous structures for textile applications: a\nmachine learning approach","volume":"116","author":"Rolda\u0301n","year":"2025","journal-title":"J. Text. Inst."},{"key":"2026080409255893200_cit43","doi-asserted-by":"publisher","first-page":"arXiv:2601.04873","DOI":"10.48550\/ARXIV.2601.04873","article-title":"FibreCastML:\nAn Open Web Platform for Predicting Electrospun\nNanofibre Diameter Distributions [Internet]","author":"Roldan","year":"2026","journal-title":"arXiv"},{"issue":"33","key":"2026080409255893200_cit44","doi-asserted-by":"publisher","first-page":"2402440","DOI":"10.1002\/advs.202402440","article-title":"Multi-Objective Bayesian\nOptimization for Laminate-Inspired\nMechanically Reinforced Piezoelectric Self-Powered Sensing Yarns","volume":"11","author":"Yang","year":"2024","journal-title":"Adv. Sci."},{"key":"2026080409255893200_cit45","doi-asserted-by":"publisher","first-page":"arXiv:2602.09120","DOI":"10.48550\/ARXIV.2602.09120","article-title":"SpinCastML an Open\nDecision-Making Application for Inverse Design\nof Electrospinning Manufacturing: A Machine Learning, Optimal Sampling\nand Inverse Monte Carlo Approach","author":"Roldan","year":"2026","journal-title":"arXiv"},{"key":"2026080409255893200_cit46","doi-asserted-by":"publisher","first-page":"106564","DOI":"10.1016\/j.jmbbm.2024.106564","article-title":"Mechanical properties of hydrated\nelectrospun polycaprolactone\n(PCL) nanofibers","volume":"155","author":"Alharbi","year":"2024","journal-title":"J. Mech. Behav. Biomed. Mater."},{"issue":"4","key":"2026080409255893200_cit47","doi-asserted-by":"publisher","first-page":"662","DOI":"10.3390\/polym13040662","article-title":"Morphological and Mechanical Properties of Electrospun\nPolycaprolactone Scaffolds: Effect of Applied Voltage","volume":"13","author":"Can-Herrera","year":"2021","journal-title":"Polymers"},{"issue":"4","key":"2026080409255893200_cit48","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1002\/jbm.a.30318","article-title":"Mechanism(s) of increased vascular\ncell adhesion on nanostructured poly(lactic- co -glycolic\nacid) films","volume":"73A","author":"Miller","year":"2005","journal-title":"J. Biomedical Materials Res."},{"issue":"20","key":"2026080409255893200_cit49","doi-asserted-by":"publisher","first-page":"2025","DOI":"10.1016\/S0142-9612(00)00079-X","article-title":"Smooth muscle cell\nadhesion to tissue engineering scaffolds","volume":"21","author":"Nikolovski","year":"2000","journal-title":"Biomaterials"},{"issue":"5","key":"2026080409255893200_cit50","doi-asserted-by":"publisher","first-page":"3259","DOI":"10.1039\/D4RA07881K","article-title":"Optimizing\nsolvent systems for electrospun PLGA scaffolds:\neffects on microstructure and mechanical properties for biomedical\napplications","volume":"15","author":"Salimbeigi","year":"2025","journal-title":"RSC Adv."},{"key":"2026080409255893200_cit51","first-page":"123","article-title":"Biodegradable Poly-Epsilon-Caprolactone\n(PCL) For Tissue Engineering Applications: A Review","volume":"34","author":"Abedalwafa","year":"2013","journal-title":"Rev. Adv. Mater. Sci"},{"issue":"1","key":"2026080409255893200_cit52","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1038\/s41597-025-06520-5","article-title":"Cogni-e-SpinDB 1.0: Open Dataset of Electrospinning Parameter Configurations\nand Resultant Nanofiber Morphologies","volume":"13","author":"Mahdian","year":"2026","journal-title":"Sci. Data"},{"issue":"23","key":"2026080409255893200_cit53","doi-asserted-by":"publisher","first-page":"16424","DOI":"10.1007\/s10853-026-12821-w","article-title":"Computational precision\ncontrol of electrospun polymer\nnanofiber morphology using machine learning and genetic algorithm\noptimization","volume":"61","author":"Subeshan","year":"2026","journal-title":"J. Mater. Sci."},{"issue":"1","key":"2026080409255893200_cit54","doi-asserted-by":"publisher","first-page":"11034","DOI":"10.1038\/s41598-026-40692-3","article-title":"A surrogate-based\ninverse design\nframework for targeted diameter control of electrospun nanofibers","volume":"16","author":"Mahdian","year":"2026","journal-title":"Sci. Rep"}],"container-title":["ACS Omega"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acsomega.6c03020","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/acsodf\/article-pdf\/11\/30\/45008\/66080493\/acsomega.6c03020.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/acsodf\/article-pdf\/11\/30\/45008\/66080493\/acsomega.6c03020.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T13:27:00Z","timestamp":1785850020000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/acsodf\/article\/11\/30\/45008\/5224176\/Optimization-of-Electrospun-PCL-PLGA-Substrates"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,21]]},"references-count":54,"journal-issue":{"issue":"30","published-online":{"date-parts":[[2026,7,21]]},"published-print":{"date-parts":[[2026,8,4]]}},"URL":"https:\/\/doi.org\/10.1021\/acsomega.6c03020","relation":{},"ISSN":["2470-1343"],"issn-type":[{"value":"2470-1343","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,21]]}}}