Wettability of soft PLGA surfaces predicted by experimentally augmented atomistic models

A challenging topic in surface engineering is predicting the wetting properties of soft interfaces with different liquids. However, a robust computational protocol suitable for predicting wettability with molecular precision is still lacking. In this article, we propose a workflow based on molecular...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	MRS bulletin Jg. 48; H. 2; S. 108 - 117
Hauptverfasser:	Bellussi, Francesco Maria, Roscioni, Otello Maria, Rossi, Edoardo, Cardellini, Annalisa, Provenzano, Marina, Persichetti, Luca, Kudryavtseva, Valeriya, Sukhorukov, Gleb, Asinari, Pietro, Sebastiani, Marco, Fasano, Matteo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Cham Springer International Publishing 01.02.2023
Schlagworte:	Applied and Technical Physics Characterization and Evaluation of Materials Chemistry and Materials Science Energy Materials Impact Article Materials Engineering Materials Science Nanotechnology Nanoscale Polymer Interface Computation/computing Fluid
ISSN:	0883-7694, 1938-1425
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	A challenging topic in surface engineering is predicting the wetting properties of soft interfaces with different liquids. However, a robust computational protocol suitable for predicting wettability with molecular precision is still lacking. In this article, we propose a workflow based on molecular dynamics simulations to predict the wettability of polymer surfaces and test it against the experimental contact angle of several polar and nonpolar liquids, namely water, formamide, toluene, and hexane. The specific case study addressed here focuses on a poly(lactic- co -glycolic acid) (PLGA) flat surface, but the proposed experimental-modeling protocol may have broader fields of application. The structural properties of PLGA slabs have been modeled on the surface roughness determined with microscopy measurements, while the computed surface tensions and contact angles were validated against standardized characterization tests, reaching a discrepancy of less than 3% in the case of water. Overall, this work represents the initial step toward an integrated multiscale framework for predicting the wettability of more complex soft interfaces, which will eventually take into account the effect of surface topology at higher scales and synergically be employed with experimental characterization techniques. Impact statement Controlling the wettability of surfaces has important implications for energy (e.g., self-cleaning solar panels), mechanical (e.g., enhanced heat transfer), chemical (e.g., fluids separation), and biomedical (e.g., implants biocompatibility) industries. Wetting properties arise from a combination of chemical and physical features of surfaces, which are inherently intertwined and multiscale. Therefore, tailoring wettability to target functionalities is a time-intensive process, especially if relying on a trial-and-error approach only. This becomes even more challenging with soft materials, since their surface configuration depends on the solid-liquid interactions at the molecular level and could not be defined a priori . The improved accuracy of atomistic models allows detailing how the effective properties of materials arise from their nanoscale features. In this article, we propose and validate a new molecular dynamics protocol for assessing the wettability of soft interfaces with polar and nonpolar liquids. The prediction capabilities of simulations are augmented by a close comparison with microscopy and contact angle experiments. Since smooth copolymer surfaces are considered, here the effort mainly focuses on the effect of chemical features on wettability. In perspective, the proposed atomistic in silico approach could be coupled with computational models at higher scales to include the effect of surface microstructures, eventually easing the development of multi-scale surfaces with tunable wettability. Graphical abstract
AbstractList	A challenging topic in surface engineering is predicting the wetting properties of soft interfaces with different liquids. However, a robust computational protocol suitable for predicting wettability with molecular precision is still lacking. In this article, we propose a workflow based on molecular dynamics simulations to predict the wettability of polymer surfaces and test it against the experimental contact angle of several polar and nonpolar liquids, namely water, formamide, toluene, and hexane. The specific case study addressed here focuses on a poly(lactic- co -glycolic acid) (PLGA) flat surface, but the proposed experimental-modeling protocol may have broader fields of application. The structural properties of PLGA slabs have been modeled on the surface roughness determined with microscopy measurements, while the computed surface tensions and contact angles were validated against standardized characterization tests, reaching a discrepancy of less than 3% in the case of water. Overall, this work represents the initial step toward an integrated multiscale framework for predicting the wettability of more complex soft interfaces, which will eventually take into account the effect of surface topology at higher scales and synergically be employed with experimental characterization techniques. Impact statement Controlling the wettability of surfaces has important implications for energy (e.g., self-cleaning solar panels), mechanical (e.g., enhanced heat transfer), chemical (e.g., fluids separation), and biomedical (e.g., implants biocompatibility) industries. Wetting properties arise from a combination of chemical and physical features of surfaces, which are inherently intertwined and multiscale. Therefore, tailoring wettability to target functionalities is a time-intensive process, especially if relying on a trial-and-error approach only. This becomes even more challenging with soft materials, since their surface configuration depends on the solid-liquid interactions at the molecular level and could not be defined a priori . The improved accuracy of atomistic models allows detailing how the effective properties of materials arise from their nanoscale features. In this article, we propose and validate a new molecular dynamics protocol for assessing the wettability of soft interfaces with polar and nonpolar liquids. The prediction capabilities of simulations are augmented by a close comparison with microscopy and contact angle experiments. Since smooth copolymer surfaces are considered, here the effort mainly focuses on the effect of chemical features on wettability. In perspective, the proposed atomistic in silico approach could be coupled with computational models at higher scales to include the effect of surface microstructures, eventually easing the development of multi-scale surfaces with tunable wettability. Graphical abstract
Author	Kudryavtseva, Valeriya Sukhorukov, Gleb Cardellini, Annalisa Rossi, Edoardo Asinari, Pietro Fasano, Matteo Persichetti, Luca Bellussi, Francesco Maria Roscioni, Otello Maria Provenzano, Marina Sebastiani, Marco
Author_xml	– sequence: 1 givenname: Francesco Maria surname: Bellussi fullname: Bellussi, Francesco Maria organization: Department of Energy, Politecnico di Torino – sequence: 2 givenname: Otello Maria surname: Roscioni fullname: Roscioni, Otello Maria organization: MaterialX Ltd., Easton Business Centre – sequence: 3 givenname: Edoardo surname: Rossi fullname: Rossi, Edoardo organization: Department of Engineering, Università degli studi Roma Tre – sequence: 4 givenname: Annalisa surname: Cardellini fullname: Cardellini, Annalisa organization: Department of Energy, Politecnico di Torino – sequence: 5 givenname: Marina surname: Provenzano fullname: Provenzano, Marina organization: Department of Energy, Politecnico di Torino – sequence: 6 givenname: Luca surname: Persichetti fullname: Persichetti, Luca organization: Department of Science, Università degli studi Roma Tre, Department of Physics, Tor Vergata University – sequence: 7 givenname: Valeriya surname: Kudryavtseva fullname: Kudryavtseva, Valeriya organization: School of Engineering and Materials Science, Queen Mary University of London – sequence: 8 givenname: Gleb surname: Sukhorukov fullname: Sukhorukov, Gleb organization: School of Engineering and Materials Science, Queen Mary University of London – sequence: 9 givenname: Pietro surname: Asinari fullname: Asinari, Pietro organization: Department of Energy, Politecnico di Torino, Istituto Nazionale di Ricerca Metrologica – sequence: 10 givenname: Marco surname: Sebastiani fullname: Sebastiani, Marco email: marco.sebastiani@uniroma3.it organization: Department of Engineering, Università degli studi Roma Tre – sequence: 11 givenname: Matteo orcidid: 0000-0002-3997-3681 surname: Fasano fullname: Fasano, Matteo email: matteo.fasano@polito.it organization: Department of Energy, Politecnico di Torino
BookMark	eNp9kMtKAzEUhoNUsFZfwFVeIJrJpUmWpWgVCrpQdBcyuZSU6aQkKThv79S6ctHVOXD-78D_XYNJn3oPwF2D7xvOxUNhlAuBMCEIYyoxUhdg2igqUcMIn4AplpIiMVfsClyXssW44VjwKfj69LWaNnaxDjAFWFKo8G29WsByyMFYX-A-exdt9Q62A_Tfe5_jzvfVdN0AzWFz3MebqWkXS40W7pLzXbkBl8F0xd_-zRn4eHp8Xz6j9evqZblYI0spr8jKOW2VU4GxBnNprMKWExPmVAZOW0vmxjEaiHBKchNYi60iLRPejQ2EcHQG5OmvzamU7IO2sZoaU1-ziZ1usD4a0idDejSkfw1pNaLkH7ofq5k8nIfoCSpjuN_4rLfpkPux4jnqB_G6fLQ
CitedBy_id	crossref_primary_10_1007_s00894_024_06023_x crossref_primary_10_1557_s43577_022_00423_1 crossref_primary_10_1021_acs_jpcb_4c07518 crossref_primary_10_3390_s24237665
Cites_doi	10.1021/ct200908r 10.1021/acs.jctc.5b00080 10.1134/S1560090416060191 10.1021/acsnano.8b04632 10.1557/mrs.2016.139 10.1021/acs.jpcb.9b02797 10.1098/rstl.1805.0005 10.1039/C5GC02725J 10.1016/j.physleta.2016.03.015 10.1016/j.csite.2018.06.005 10.1103/PhysRevE.92.052403 10.1002/anie.201702945 10.1016/S0169-4332(01)00432-9 10.1021/acs.jpcc.5b10267 10.1088/0256-307X/22/4/002 10.1557/mrs.2013.26 10.1007/s10404-021-02455-6 10.1557/mrs.2020.271 10.1002/app.51242 10.1021/acs.macromol.0c01593 10.1021/acs.jpcc.7b00484 10.1557/s43578-021-00127-3 10.1039/C4TA06347C 10.1063/5.0057145 10.1038/s41598-019-54751-5 10.1021/ct300976t 10.1021/acs.macromol.0c00110 10.1021/nn2005393 10.1039/C8CP03762K 10.1016/j.apsusc.2019.144002 10.1016/j.mtchem.2017.02.006 10.1021/jp209024r 10.1021/ct200731v 10.1039/D0NR05392A 10.1006/jcph.1995.1039 10.1002/adfm.201200988 10.1063/1.1747248 10.1103/PhysRevFluids.3.074201 10.1039/TF9444000546 10.1088/0957-4484/17/19/033 10.1073/pnas.1616138113 10.1016/j.polymer.2020.122903 10.1063/1.2715577 10.1103/RevModPhys.81.739 10.1021/acs.nanolett.8b04335 10.1021/j100834a012 10.1016/j.cej.2021.133052 10.1557/mrs.2013.99 10.1016/j.saa.2021.120140 10.3390/ijms15033640 10.1016/j.jmb.2021.166841 10.1021/ie50320a024 10.1186/1758-2946-4-17 10.1021/j100308a038 10.1163/156856201744425 10.1063/1.2121687 10.1016/j.cej.2021.133036 10.2478/s11534-011-0096-2 10.1021/acs.langmuir.5b01394 10.1016/j.jconrel.2013.08.024 10.1063/1.479595 10.3390/polym3031377 10.1016/j.matdes.2021.109902 10.1016/J.CIS.2009.07.003 10.1038/s41467-019-12093-w 10.5281/zenodo.6629427 10.1016/j.polymer.2015.12.052 10.1021/acs.jpcb.1c07642 10.1021/acs.jpclett.0c01793 10.1016/j.jcis.2011.04.051 10.1021/acs.jpcb.9b06681 10.1017/jfm.2015.517 10.1021/acs.macromol.0c02234 10.1063/1.4821604 10.1039/C9CP04120F 10.1002/app.1969.070130815
ContentType	Journal Article
Copyright	The Author(s) 2022
Copyright_xml	– notice: The Author(s) 2022
DBID	C6C AAYXX CITATION
DOI	10.1557/s43577-022-00380-9
DatabaseName	Springer Nature OA Free Journals CrossRef
DatabaseTitle	CrossRef
DatabaseTitleList
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Physics
EISSN	1938-1425
EndPage	117
ExternalDocumentID	10_1557_s43577_022_00380_9
GrantInformation_xml	– fundername: Politecnico di Torino – fundername: H2020 Industrial Leadership grantid: 760827 funderid: http://dx.doi.org/10.13039/100010667
GroupedDBID	-2P -2V -E. .FH 0E1 0R~ 123 2JN 4.4 406 5VS 74X 74Y 7~V 8FE 8FG 8UJ AAAZR AABES AABWE AACDK AACJH AAEWM AAGFV AAHNG AAJBT AAKTX AARAB AASML AATID AATMM AATNV AAUKB ABAKF ABBXD ABECU ABEFU ABGDZ ABJCF ABJNI ABKKG ABMQK ABMWE ABQTM ABROB ABTEG ABTKH ABTMW ABZCX ABZUI ACAOD ACBEA ACBEK ACBMC ACDTI ACETC ACGFS ACHSB ACIMK ACIWK ACPIV ACQPF ACRPL ACUIJ ACXSD ACZBM ACZOJ ACZUX ADCGK ADFEC ADNMO ADOVH ADOVT AEBAK AEFQL AEHGV AEMFK AEMSY AEMTW AENEX AENGE AESKC AEYYC AFBBN AFFUJ AFKQG AFKRA AFLOS AFLVW AFQWF AFUTZ AGLWM AGMZJ AGQEE AHQXX AIGIU AIGNW AIHIV AIOIP AISIE AJCYY AJPFC AJQAS AKYQF AKZCZ ALMA_UNASSIGNED_HOLDINGS ALVPG ALWZO AMTXH AMXSW AMYLF ARABE ARZZG ATUCA AUXHV AYIQA BBLKV BCGOX BENPR BESQT BGHMG BGLVJ BJBOZ BMAJL BQFHP C0O C6C CBIIA CCPQU CCUQV CFAFE CFBFF CGQII CZ9 D1I DC4 DOHLZ DPUIP EBLON EBS EJD FIGPU HCIFZ HG- HST HZ~ I.6 I.7 I.9 IH6 IKXTQ IOEEP IOO IS6 IWAJR I~P J36 J38 J3A JHPGK JKPOH JQKCU JZLTJ KAFGG KB. KC. KCGVB KFECR L98 LHUNA LLZTM M-V M7~ M8. NIKVX NPVJJ NQJWS O9- PDBOC PYCCK RAMDC RCA RNS ROL RR0 RSV S0W S6- S6U SAAAG SJYHP SNE SNPRN SOHCF SOJ SRMVM SSLCW T9M TN5 UT1 WQ3 WXU WXY ZDLDU ZE2 ZJOSE ZMEZD ZYDXJ ~V1 AAUYE AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC AEZWR AFDZB AFFHD AFHIU AFOHR AGQPQ AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION KOV M7S PHGZM PHGZT PQGLB PTHSS
ID	FETCH-LOGICAL-c335t-c863b9d9f441058ac90c52af638f53bc26ad43f27d985af4b0c92b47ed01577d3
IEDL.DBID	RSV
ISICitedReferencesCount	9
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000852931100004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0883-7694
IngestDate	Tue Nov 18 21:21:05 EST 2025 Sat Nov 29 03:39:10 EST 2025 Fri Feb 21 02:43:45 EST 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	2
Keywords	Nanoscale Polymer Interface Computation/computing Fluid
Language	English
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c335t-c863b9d9f441058ac90c52af638f53bc26ad43f27d985af4b0c92b47ed01577d3
ORCID	0000-0002-3997-3681
OpenAccessLink	https://link.springer.com/10.1557/s43577-022-00380-9
PageCount	10
ParticipantIDs	crossref_citationtrail_10_1557_s43577_022_00380_9 crossref_primary_10_1557_s43577_022_00380_9 springer_journals_10_1557_s43577_022_00380_9
PublicationCentury	2000
PublicationDate	20230200 2023-02-00
PublicationDateYYYYMMDD	2023-02-01
PublicationDate_xml	– month: 2 year: 2023 text: 20230200
PublicationDecade	2020
PublicationPlace	Cham
PublicationPlace_xml	– name: Cham
PublicationTitle	MRS bulletin
PublicationTitleAbbrev	MRS Bulletin
PublicationYear	2023
Publisher	Springer International Publishing
Publisher_xml	– name: Springer International Publishing
References	Z. Zhang, X. Wang, R. Zhu, Y. Wang, B. Li, Y. Ma, Y. Yin, Polym. Sci. Ser. B58, 720 (2016). https://doi.org/10.1134/S1560090416060191 BellussiFMRoscioniOMRicciMFasanoMJ. Phys. Chem. B20211254312020120271:CAS:528:DC%2BB3MXitlWmurzO10.1021/acs.jpcb.1c07642 WenzelRNInd. Eng. Chem.19362889889941:CAS:528:DyaA28Xkslentg%3D%3D10.1021/ie50320a024 ProdhanSQiuJRicciMRoscioniOMWangLBeljonneDJ. Phys. Chem. Lett.20201116651965251:CAS:528:DC%2BB3cXhsVaqsbrM10.1021/acs.jpclett.0c01793 CassieABDBaxterSTrans. Faraday Soc.1944405465511:CAS:528:DyaH2MXhsFKqsA%3D%3D10.1039/TF9444000546 JohanssonPCarlsonAHessBJ. Fluid Mech.20157816957111:CAS:528:DC%2BC2MXhvValtbnK10.1017/jfm.2015.517 CardelliniAFasanoMChiavazzoEAsinariPPhys. Lett. A201638020173517401:CAS:528:DC%2BC28XktlKhtLo%3D10.1016/j.physleta.2016.03.015 X.S. Wu, N. Wang, J. Biomater. Sci. Polym. Ed.12(1), 21 (2001). https://doi.org/10.1163/156856201744425 T. Young III, Philos. Trans. R. Soc. Lond.95, 65 (1805). https://doi.org/10.1098/rstl.1805.0005 LiuHLiYKrauseWERojasOJPasquinelliMAJ. Phys. Chem. B20121165157015781:CAS:528:DC%2BC38XhsVyrs7c%3D10.1021/jp209024r RossiEMPhaniPSGuillemetRCholetJJusseyDOliverWCSebastianiMJournal of Materials Research20213611235723701:CAS:528:DC%2BB3MXitFSgtb7F10.1557/s43578-021-00127-3 YaghoubiHForoutanMAppl. Surf. Sci.20205001:CAS:528:DC%2BC1MXhvFGmurbJ10.1016/j.apsusc.2019.144002 JungYCBhushanBNanotechnology20061719497049801:CAS:528:DC%2BD28Xht1Klt7fF10.1088/0957-4484/17/19/033 HanwellMDCurtisDELonieDCVandermeerschTZurekEHutchisonGRJ. Cheminf.2012411171:CAS:528:DC%2BC3sXhsVGksLg%3D10.1186/1758-2946-4-17 PeiKYingYChuCMater. Today Chem.20174909610.1016/j.mtchem.2017.02.006 MatesJEIbrahimRVeraAGuggenheimSQinJCalewartsDWaldroupDEMegaridisCMGreen Chem.2016187218521921:CAS:528:DC%2BC2MXhvFClu7vN10.1039/C5GC02725J AndrewsJBlaisten-BarojasEJ. Phys. Chem. B20191234810233102441:CAS:528:DC%2BC1MXitFagtbbP10.1021/acs.jpcb.9b06681 LeroyFMüller-PlatheFLangmuir20153130833583451:CAS:528:DC%2BC2MXhtFGisL7L10.1021/acs.langmuir.5b01394 Hong-KaiGHai-PingFChin. Phys. Lett.200522478710.1088/0256-307X/22/4/002 ChenQZhangXChenKWuXZongTFengCZhangDChem. Eng. J.20224301:CAS:528:DC%2BB3MXitlamsbzJ10.1016/j.cej.2021.133036 ParentMNouvelCKoerberMSapinAMaincentPBoudierAJ. Controlled Release201317212923041:CAS:528:DC%2BC3sXhslOku77K10.1016/j.jconrel.2013.08.024 FasanoMBevilacquaAChiavazzoEHumplikTAsinariPSci. Rep.2019911121:CAS:528:DC%2BC1MXitlGhsrnI10.1038/s41598-019-54751-5 LiowSSKarimAALohXJMRS Bull.20164175575661:CAS:528:DC%2BC28XhtFOjt7fF10.1557/mrs.2016.139 ZhangJBorgMKSefianeKReeseJMPhys. Rev. E201592510.1103/PhysRevE.92.052403 European Committee for Standardization: CEN Workshop Agreement CWA 17284: Materials modelling - Terminology, classification and metadata (2018). https://emmc.info/wp-content/uploads/2018/05/CWA_17284.pdf VegaCde MiguelEJ. Chem. Phys.2007126151:CAS:528:DC%2BD2sXkvF2rsbo%3D10.1063/1.2715577 R.J. Good, L.A. Girifalco, J. Phys. Chem.64(5), 561 (1960). https://doi.org/10.1021/j100834a012 Govind RajanAStranoMSBlankschteinDNano Lett.2019193153915511:CAS:528:DC%2BC1MXitVChtbo%3D10.1021/acs.nanolett.8b04335 A. Pérez de la Luz, G.A. Méndez-Maldonado, E. Núñez-Rojas, F. Bresme, J. Alejandre, J. Chem. Theory Comput.11(6), 2792 (2015). https://doi.org/10.1021/acs.jctc.5b00080 European Committee for Standardization: CEN Workshop Agreement CWA 17815: Materials characterisation - Terminology, metadata and classification (2021). https://www.cencenelec.eu/media/CEN-CENELEC/CWAs/ICT/cwa17815.pdf XuYKooDGersteinEAKimC-SPolymer2016841211311:CAS:528:DC%2BC28Xlt1akuw%3D%3D10.1016/j.polymer.2015.12.052 BuehlerMJMRS Bull.20133821691761:CAS:528:DC%2BC3sXksVGksr0%3D10.1557/mrs.2013.26 KoishiTYasuokaKFujikawaSZengXCACS Nano201159683468421:CAS:528:DC%2BC3MXhtVKhtLbO10.1021/nn2005393 R. Mažeikienė, G. Niaura, A. Malinauskas, Spectrochim. Acta AMol. Biomol. Spectrosc. 262, 120140 (2021). https://doi.org/10.1016/j.saa.2021.120140 GerberJLendenmannTEghlidiHSchutziusTMPoulikakosDNat. Commun.20191011101:CAS:528:DC%2BC1MXitValtLfL10.1038/s41467-019-12093-w YangH-CXieYChanHNarayananBChenLWaldmanRZSankaranarayananSKElamJWDarlingSBACS Nano2018128867886851:CAS:528:DC%2BC1cXhsFWhtbrK10.1021/acsnano.8b04632 A.I. Jewett, D. Stelter, J. Lambert, S.M. Saladi, O.M. Roscioni, M. Ricci, L. Autin, M. Maritan, S.M. Bashusqeh, T. Keyes, R.T. Dame, J.-E. Shea, G.J. Jensen, D.S. Goodsell, J. Mol. Biol.433(11), 166841 (2021). https://doi.org/10.1016/j.jmb.2021.166841 SedinDLRowlenKLApplied Surface Science2001182140481:CAS:528:DC%2BD3MXnt1aqurw%3D10.1016/S0169-4332(01)00432-9 ZhangLLuanBZhouRJ. Phys. Chem. B201912334724372521:CAS:528:DC%2BC1MXhsFShtLrF10.1021/acs.jpcb.9b02797 WongT-SSunTFengLAizenbergJMRS Bull.20133853663711:CAS:528:DC%2BC3sXnvV2msLY%3D10.1557/mrs.2013.99 ZubillagaRALabastidaACruzBMartínezJCSánchezEAlejandreJJ. Chem. Theory Comput.201393161116151:CAS:528:DC%2BC3sXht1Kksrw%3D10.1021/ct300976t KhodayariAFasanoMBigdeliMBMohammadnejadSChiavazzoEAsinariPCase Stud. Therm. Eng.20181245446110.1016/j.csite.2018.06.005 NečasDKlapetekPCent. Eur. J. Phys.20121018118810.2478/s11534-011-0096-2 Chemical & Physical Properties of Select Polymers (n.d.). https://www.absorbables.com/technical/properties AndrewsJHandlerRABlaisten-BarojasEPolymer20202061:CAS:528:DC%2BB3cXhs1Sru7jO10.1016/j.polymer.2020.122903 MasuduzzamanMKimBMicrofluid. Nanofluid.202125611410.1007/s10404-021-02455-6 CalemanCvan MaarenPJHongMHubJSCostaLTvan der SpoelDJ. Chem. Theory Comput.20128161741:CAS:528:DC%2BC3MXhsF2itrbE10.1021/ct200731v AbascalJLFVegaCJ. Chem. Phys.2005123231:CAS:528:DC%2BD28XltVOg10.1063/1.2121687 W.F. van Gunsteren, X. Daura, N. Hansen, A.E. Mark, C. Oostenbrink, S. Riniker, L.J. Smith, Angew. Chem. Int. Ed.57(4), 884 (2018). https://doi.org/10.1002/anie.201702945 WangPZhengGDaiKLiuCShenCChem. Eng. J.20224301:CAS:528:DC%2BB3MXitlamsb3K10.1016/j.cej.2021.133052 BormashenkoEJ. Colloid Interface Sci.201136013173191:CAS:528:DC%2BC3MXmvFymsro%3D10.1016/j.jcis.2011.04.051 PlimptonSJ. Comput. Phys.199511711191:CAS:528:DyaK2MXlt1ejs7Y%3D10.1006/jcph.1995.1039 S.W.I. Siu, K. Pluhackova, R.A. Böckmann, J. Chem. Theory Comput.8(4), 1459 (2012) https://doi.org/10.1021/ct200908r. https://doi.org/10.1021/ct200908r LAMMPS Molecular Dynamics Simulator (n.d.). https://www.lammps.org WangWLiHLiQLuoZJ. Appl. Polym. Sci.202113842512421:CAS:528:DC%2BB3MXhsFSks7%2FK10.1002/app.51242 GuitonBSStefikMAugustynVBanerjeeSBardeenCJBartlettBMLiJLópez-MejíasVMacGillivrayLRMorrisAMRS Bull.2020451195196410.1557/mrs.2020.271 M. Ricci, O.M. Roscioni, L. Querciagrossa, C. Zannoni, Phys. Chem. Chem. Phys.21, 26195 (2019). https://doi.org/10.1039/C9CP04120F GentilePChionoVCarmagnolaIHattonPVInt. J. Mol. Sci.2014153364036591:CAS:528:DC%2BC2cXhtlWhtbjI10.3390/ijms15033640 PannuzzoMHortaBACLa RosaCDecuzziPMacromolecules20205310364336541:CAS:528:DC%2BB3cXovF2isrw%3D10.1021/acs.macromol.0c00110 CardelliniAMaria BellussiFRossiEChiavariniLBeckerCCantDAsinariPSebastianiMMater. Des.20212081:CAS:528:DC%2BB3MXhsVWitLfE10.1016/j.matdes.2021.109902 Jmol: An open-source Java viewer for chemical structures in 3D (n.d.). http://www.jmol.org CottenyeNAnselmeKPlouxLVebert-NardinCAdv. Funct. Mater.2012222348911:CAS:528:DC%2BC38XhtVKntbvK10.1002/adfm.201200988 ZhuCGaoYLiHMengSLiLFranciscoJSZengXCProc. Natl. Acad. Sci. U.S.A.20161134612946129511:CAS:528:DC%2BC28XhslKmtrnP10.1073/pnas.1616138113 YehI-CBerkowitzMLJ. Chem. Phys.19991117315531621:CAS:528:DyaK1MXkslyht7o%3D10.1063/1.479595 BonnDEggersJIndekeuJMeunierJRolleyERev. Mod. Phys.2009817398051:CAS:528:DC%2BD1MXnsFCgur8%3D10.1103/RevModPhys.81.739 MakadiaHKSiegelSJPolymers201133137713971:CAS:528:DC%2BC3MXhtFOis7jJ10.3390/polym3031377 P. Cignoni, M. Callieri, M. Corsini, M. Dellepiane, F. Ganovelli, G. Ranzuglia, “MeshLab: An Open-Source Mesh Processing Tool,” in Proceedings of the Eurographics Italian Chapter Conference (Eurographics Association, 2008), pp. 129. https://doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2008/129-136 F.M. Bellussi, O.M. Roscioni, A. Cardellini, M. Provenzano, M. Fasano, Zenodo (2022). https://doi.org/10.5281/zenodo.6629427 GaoYYaoWSunJZhangHWangZWangLYangDZhangLYangHJ. Mater. Chem. A20153107381:CAS:528:DC%2BC2MXks1ejs78%3D10.1039/C4TA06347C Dortmund Data Bank, Surface Tension of Hexane (n.d.). http://www.ddbst.com/en/EED/PCP/SFT_C89.php KirkwoodJGBuffFPJ. Chem. Phys.19491733383431:CAS:528:DyaH1MXivVOlug%3D%3D10.1063/1.1747248 DelabieJDe WinterJDeschaumeOBarticCGerbauxPVerbiestTKoeckelberghsGMacromolecules2020532411098111051:CAS:528:DC%2BB3cXisVejt7%2FL10.1021/acs.macromol.0c01593 NguyenTTKhuatHTTAsakuraSMizutaniGMurakamiYOkadaTJ. Chem. Phys.202115581:CAS:528:DC%2BB3MXhvV2rs7rE10.1063/5.0057145 LeroyFLiuSZhangJJ. Phys. Chem. C20151195128470284811:CAS:528:DC%2BC2MXhvFWrsLnK10.1021/acs.jpcc.5b10267 Avogadro: An open-source molecular builder and visualization tool, version 1.XX (n.d.). http://avogadro.cc V. Sresht, A. Govind Rajan, E. Bordes, M.S. Strano, A.A.H. Pádua, D. Blankschtein, J. Phys. Chem. C121(16), 9022 (2017). https://doi.org/10.1021/acs.jpcc.7b00484 YaghoubiHForoutanMPhys. Chem. Chem. Phys.20182022308223191:CAS:528:DC%2BC1cXhsVCnsbrJ10.1039/C8CP03762K OzcelikHGSatirogluEBarisikMNanoscale2020124121376213911:CAS:528:DC%2BB3cXhvFajsbnF10.1039/D0NR05392A OwensDKWendtRCJ. Appl. Polym. Sci.1969138174117471:CAS:528:DyaF1MXltFegtLc%3D10.1002/app.1969.070130815 JohanssonPHessBPhys. Rev. Fluids2018310.1103/PhysRevFluids.3.074201 ChauTTBruckardWJKohPTLNguyenAVAdv. Colloid Interface Sci.200915021061151:CAS:528:DC%2BD1MXpvFaqtL8%3D10.1016/J.CIS.2009.07.003 BallalDChapmanWGJ. Chem. Phys.2013139111:CAS:528:DC%2BC3sXhsV2jsLfL10.1063/1.4821604 EthaSADesaiPRSacharHSDasSMacromolecules20215425845961:CAS:528:DC%2BB3MXptVyjtA%3D%3D10.1021/acs.macromol.0c02234 BerendsenHJCGrigeraJRStraatsmaTPJ. Phys. Chem.19879124626962711:CAS:528:DyaL2sXmt1els7w%3D10.1021/j100308a038 SA Etha (380_CR40) 2021; 54 JLF Abascal (380_CR75) 2005; 123 P Gentile (380_CR83) 2014; 15 D Bonn (380_CR22) 2009; 81 H Yaghoubi (380_CR34) 2018; 20 380_CR82 W Wang (380_CR13) 2021; 138 N Cottenye (380_CR2) 2012; 22 M Masuduzzaman (380_CR58) 2021; 25 P Wang (380_CR10) 2022; 430 YC Jung (380_CR52) 2006; 17 G Hong-Kai (380_CR56) 2005; 22 HG Ozcelik (380_CR62) 2020; 12 MJ Buehler (380_CR21) 2013; 38 J Zhang (380_CR57) 2015; 92 H Yaghoubi (380_CR35) 2020; 500 C Zhu (380_CR39) 2016; 113 380_CR74 JE Mates (380_CR6) 2016; 18 RN Wenzel (380_CR25) 1936; 28 380_CR37 DK Owens (380_CR16) 1969; 13 RA Zubillaga (380_CR49) 2013; 9 380_CR79 A Cardellini (380_CR33) 2021; 208 C Vega (380_CR50) 2007; 126 380_CR78 M Pannuzzo (380_CR67) 2020; 53 TT Chau (380_CR53) 2009; 150 FM Bellussi (380_CR61) 2021; 125 380_CR73 T Koishi (380_CR36) 2011; 5 380_CR71 S Plimpton (380_CR72) 1995; 117 380_CR70 L Zhang (380_CR31) 2019; 123 T-S Wong (380_CR20) 2013; 38 H Liu (380_CR38) 2012; 116 M Fasano (380_CR9) 2019; 9 380_CR64 C Caleman (380_CR48) 2012; 8 380_CR63 SS Liow (380_CR3) 2016; 41 380_CR23 A Khodayari (380_CR46) 2018; 12 J Andrews (380_CR45) 2020; 206 F Leroy (380_CR29) 2015; 31 A Cardellini (380_CR4) 2016; 380 P Johansson (380_CR27) 2018; 3 H-C Yang (380_CR8) 2018; 12 380_CR17 S Prodhan (380_CR60) 2020; 11 F Leroy (380_CR30) 2015; 119 380_CR11 P Johansson (380_CR28) 2015; 781 380_CR55 TT Nguyen (380_CR12) 2021; 155 EM Rossi (380_CR18) 2021; 36 380_CR54 A Govind Rajan (380_CR32) 2019; 19 D Nečas (380_CR80) 2012; 10 380_CR59 K Pei (380_CR66) 2017; 4 J Andrews (380_CR68) 2019; 123 ABD Cassie (380_CR26) 1944; 40 380_CR51 M Parent (380_CR42) 2013; 172 JG Kirkwood (380_CR81) 1949; 17 Y Gao (380_CR1) 2015; 3 E Bormashenko (380_CR24) 2011; 360 HK Makadia (380_CR43) 2011; 3 D Ballal (380_CR7) 2013; 139 BS Guiton (380_CR19) 2020; 45 DL Sedin (380_CR84) 2001; 182 MD Hanwell (380_CR69) 2012; 4 Q Chen (380_CR5) 2022; 430 J Delabie (380_CR14) 2020; 53 380_CR44 HJC Berendsen (380_CR76) 1987; 91 J Gerber (380_CR15) 2019; 10 380_CR41 I-C Yeh (380_CR77) 1999; 111 Y Xu (380_CR65) 2016; 84 380_CR47
References_xml	– reference: CardelliniAFasanoMChiavazzoEAsinariPPhys. Lett. A201638020173517401:CAS:528:DC%2BC28XktlKhtLo%3D10.1016/j.physleta.2016.03.015 – reference: ChenQZhangXChenKWuXZongTFengCZhangDChem. Eng. J.20224301:CAS:528:DC%2BB3MXitlamsbzJ10.1016/j.cej.2021.133036 – reference: ProdhanSQiuJRicciMRoscioniOMWangLBeljonneDJ. Phys. Chem. Lett.20201116651965251:CAS:528:DC%2BB3cXhsVaqsbrM10.1021/acs.jpclett.0c01793 – reference: GerberJLendenmannTEghlidiHSchutziusTMPoulikakosDNat. Commun.20191011101:CAS:528:DC%2BC1MXitValtLfL10.1038/s41467-019-12093-w – reference: MasuduzzamanMKimBMicrofluid. Nanofluid.202125611410.1007/s10404-021-02455-6 – reference: BellussiFMRoscioniOMRicciMFasanoMJ. Phys. Chem. B20211254312020120271:CAS:528:DC%2BB3MXitlWmurzO10.1021/acs.jpcb.1c07642 – reference: AndrewsJBlaisten-BarojasEJ. Phys. Chem. B20191234810233102441:CAS:528:DC%2BC1MXitFagtbbP10.1021/acs.jpcb.9b06681 – reference: LeroyFLiuSZhangJJ. Phys. Chem. C20151195128470284811:CAS:528:DC%2BC2MXhvFWrsLnK10.1021/acs.jpcc.5b10267 – reference: AndrewsJHandlerRABlaisten-BarojasEPolymer20202061:CAS:528:DC%2BB3cXhs1Sru7jO10.1016/j.polymer.2020.122903 – reference: SedinDLRowlenKLApplied Surface Science2001182140481:CAS:528:DC%2BD3MXnt1aqurw%3D10.1016/S0169-4332(01)00432-9 – reference: MakadiaHKSiegelSJPolymers201133137713971:CAS:528:DC%2BC3MXhtFOis7jJ10.3390/polym3031377 – reference: WangPZhengGDaiKLiuCShenCChem. Eng. J.20224301:CAS:528:DC%2BB3MXitlamsb3K10.1016/j.cej.2021.133052 – reference: A.I. Jewett, D. Stelter, J. Lambert, S.M. Saladi, O.M. Roscioni, M. Ricci, L. Autin, M. Maritan, S.M. Bashusqeh, T. Keyes, R.T. Dame, J.-E. Shea, G.J. Jensen, D.S. Goodsell, J. Mol. Biol.433(11), 166841 (2021). https://doi.org/10.1016/j.jmb.2021.166841 – reference: PlimptonSJ. Comput. Phys.199511711191:CAS:528:DyaK2MXlt1ejs7Y%3D10.1006/jcph.1995.1039 – reference: Chemical & Physical Properties of Select Polymers (n.d.). https://www.absorbables.com/technical/properties/ – reference: PeiKYingYChuCMater. Today Chem.20174909610.1016/j.mtchem.2017.02.006 – reference: GaoYYaoWSunJZhangHWangZWangLYangDZhangLYangHJ. Mater. Chem. A20153107381:CAS:528:DC%2BC2MXks1ejs78%3D10.1039/C4TA06347C – reference: WenzelRNInd. Eng. Chem.19362889889941:CAS:528:DyaA28Xkslentg%3D%3D10.1021/ie50320a024 – reference: S.W.I. Siu, K. Pluhackova, R.A. Böckmann, J. Chem. Theory Comput.8(4), 1459 (2012) https://doi.org/10.1021/ct200908r. https://doi.org/10.1021/ct200908r – reference: ParentMNouvelCKoerberMSapinAMaincentPBoudierAJ. Controlled Release201317212923041:CAS:528:DC%2BC3sXhslOku77K10.1016/j.jconrel.2013.08.024 – reference: OzcelikHGSatirogluEBarisikMNanoscale2020124121376213911:CAS:528:DC%2BB3cXhvFajsbnF10.1039/D0NR05392A – reference: JohanssonPHessBPhys. Rev. Fluids2018310.1103/PhysRevFluids.3.074201 – reference: CottenyeNAnselmeKPlouxLVebert-NardinCAdv. Funct. Mater.2012222348911:CAS:528:DC%2BC38XhtVKntbvK10.1002/adfm.201200988 – reference: NguyenTTKhuatHTTAsakuraSMizutaniGMurakamiYOkadaTJ. Chem. Phys.202115581:CAS:528:DC%2BB3MXhvV2rs7rE10.1063/5.0057145 – reference: YaghoubiHForoutanMAppl. Surf. Sci.20205001:CAS:528:DC%2BC1MXhvFGmurbJ10.1016/j.apsusc.2019.144002 – reference: LiuHLiYKrauseWERojasOJPasquinelliMAJ. Phys. Chem. B20121165157015781:CAS:528:DC%2BC38XhsVyrs7c%3D10.1021/jp209024r – reference: KhodayariAFasanoMBigdeliMBMohammadnejadSChiavazzoEAsinariPCase Stud. Therm. Eng.20181245446110.1016/j.csite.2018.06.005 – reference: Avogadro: An open-source molecular builder and visualization tool, version 1.XX (n.d.). http://avogadro.cc/ – reference: VegaCde MiguelEJ. Chem. Phys.2007126151:CAS:528:DC%2BD2sXkvF2rsbo%3D10.1063/1.2715577 – reference: European Committee for Standardization: CEN Workshop Agreement CWA 17284: Materials modelling - Terminology, classification and metadata (2018). https://emmc.info/wp-content/uploads/2018/05/CWA_17284.pdf – reference: NečasDKlapetekPCent. Eur. J. Phys.20121018118810.2478/s11534-011-0096-2 – reference: R.J. Good, L.A. Girifalco, J. Phys. Chem.64(5), 561 (1960). https://doi.org/10.1021/j100834a012 – reference: PannuzzoMHortaBACLa RosaCDecuzziPMacromolecules20205310364336541:CAS:528:DC%2BB3cXovF2isrw%3D10.1021/acs.macromol.0c00110 – reference: RossiEMPhaniPSGuillemetRCholetJJusseyDOliverWCSebastianiMJournal of Materials Research20213611235723701:CAS:528:DC%2BB3MXitFSgtb7F10.1557/s43578-021-00127-3 – reference: LeroyFMüller-PlatheFLangmuir20153130833583451:CAS:528:DC%2BC2MXhtFGisL7L10.1021/acs.langmuir.5b01394 – reference: KoishiTYasuokaKFujikawaSZengXCACS Nano201159683468421:CAS:528:DC%2BC3MXhtVKhtLbO10.1021/nn2005393 – reference: MatesJEIbrahimRVeraAGuggenheimSQinJCalewartsDWaldroupDEMegaridisCMGreen Chem.2016187218521921:CAS:528:DC%2BC2MXhvFClu7vN10.1039/C5GC02725J – reference: CalemanCvan MaarenPJHongMHubJSCostaLTvan der SpoelDJ. Chem. Theory Comput.20128161741:CAS:528:DC%2BC3MXhsF2itrbE10.1021/ct200731v – reference: YehI-CBerkowitzMLJ. Chem. Phys.19991117315531621:CAS:528:DyaK1MXkslyht7o%3D10.1063/1.479595 – reference: CardelliniAMaria BellussiFRossiEChiavariniLBeckerCCantDAsinariPSebastianiMMater. Des.20212081:CAS:528:DC%2BB3MXhsVWitLfE10.1016/j.matdes.2021.109902 – reference: JungYCBhushanBNanotechnology20061719497049801:CAS:528:DC%2BD28Xht1Klt7fF10.1088/0957-4484/17/19/033 – reference: BormashenkoEJ. Colloid Interface Sci.201136013173191:CAS:528:DC%2BC3MXmvFymsro%3D10.1016/j.jcis.2011.04.051 – reference: Z. Zhang, X. Wang, R. Zhu, Y. Wang, B. Li, Y. Ma, Y. Yin, Polym. Sci. Ser. B58, 720 (2016). https://doi.org/10.1134/S1560090416060191 – reference: WangWLiHLiQLuoZJ. Appl. Polym. Sci.202113842512421:CAS:528:DC%2BB3MXhsFSks7%2FK10.1002/app.51242 – reference: DelabieJDe WinterJDeschaumeOBarticCGerbauxPVerbiestTKoeckelberghsGMacromolecules2020532411098111051:CAS:528:DC%2BB3cXisVejt7%2FL10.1021/acs.macromol.0c01593 – reference: M. Ricci, O.M. Roscioni, L. Querciagrossa, C. Zannoni, Phys. Chem. Chem. Phys.21, 26195 (2019). https://doi.org/10.1039/C9CP04120F – reference: AbascalJLFVegaCJ. Chem. Phys.2005123231:CAS:528:DC%2BD28XltVOg10.1063/1.2121687 – reference: T. Young III, Philos. Trans. R. Soc. Lond.95, 65 (1805). https://doi.org/10.1098/rstl.1805.0005 – reference: W.F. van Gunsteren, X. Daura, N. Hansen, A.E. Mark, C. Oostenbrink, S. Riniker, L.J. Smith, Angew. Chem. Int. Ed.57(4), 884 (2018). https://doi.org/10.1002/anie.201702945 – reference: ZhangJBorgMKSefianeKReeseJMPhys. Rev. E201592510.1103/PhysRevE.92.052403 – reference: Dortmund Data Bank, Surface Tension of Hexane (n.d.). http://www.ddbst.com/en/EED/PCP/SFT_C89.php – reference: CassieABDBaxterSTrans. Faraday Soc.1944405465511:CAS:528:DyaH2MXhsFKqsA%3D%3D10.1039/TF9444000546 – reference: XuYKooDGersteinEAKimC-SPolymer2016841211311:CAS:528:DC%2BC28Xlt1akuw%3D%3D10.1016/j.polymer.2015.12.052 – reference: GentilePChionoVCarmagnolaIHattonPVInt. J. Mol. Sci.2014153364036591:CAS:528:DC%2BC2cXhtlWhtbjI10.3390/ijms15033640 – reference: European Committee for Standardization: CEN Workshop Agreement CWA 17815: Materials characterisation - Terminology, metadata and classification (2021). https://www.cencenelec.eu/media/CEN-CENELEC/CWAs/ICT/cwa17815.pdf – reference: Hong-KaiGHai-PingFChin. Phys. Lett.200522478710.1088/0256-307X/22/4/002 – reference: ZhuCGaoYLiHMengSLiLFranciscoJSZengXCProc. Natl. Acad. Sci. U.S.A.20161134612946129511:CAS:528:DC%2BC28XhslKmtrnP10.1073/pnas.1616138113 – reference: F.M. Bellussi, O.M. Roscioni, A. Cardellini, M. Provenzano, M. Fasano, Zenodo (2022). https://doi.org/10.5281/zenodo.6629427 – reference: LAMMPS Molecular Dynamics Simulator (n.d.). https://www.lammps.org – reference: BallalDChapmanWGJ. Chem. Phys.2013139111:CAS:528:DC%2BC3sXhsV2jsLfL10.1063/1.4821604 – reference: BonnDEggersJIndekeuJMeunierJRolleyERev. Mod. Phys.2009817398051:CAS:528:DC%2BD1MXnsFCgur8%3D10.1103/RevModPhys.81.739 – reference: KirkwoodJGBuffFPJ. Chem. Phys.19491733383431:CAS:528:DyaH1MXivVOlug%3D%3D10.1063/1.1747248 – reference: HanwellMDCurtisDELonieDCVandermeerschTZurekEHutchisonGRJ. Cheminf.2012411171:CAS:528:DC%2BC3sXhsVGksLg%3D10.1186/1758-2946-4-17 – reference: GuitonBSStefikMAugustynVBanerjeeSBardeenCJBartlettBMLiJLópez-MejíasVMacGillivrayLRMorrisAMRS Bull.2020451195196410.1557/mrs.2020.271 – reference: YangH-CXieYChanHNarayananBChenLWaldmanRZSankaranarayananSKElamJWDarlingSBACS Nano2018128867886851:CAS:528:DC%2BC1cXhsFWhtbrK10.1021/acsnano.8b04632 – reference: FasanoMBevilacquaAChiavazzoEHumplikTAsinariPSci. Rep.2019911121:CAS:528:DC%2BC1MXitlGhsrnI10.1038/s41598-019-54751-5 – reference: ZubillagaRALabastidaACruzBMartínezJCSánchezEAlejandreJJ. Chem. Theory Comput.201393161116151:CAS:528:DC%2BC3sXht1Kksrw%3D10.1021/ct300976t – reference: R. Mažeikienė, G. Niaura, A. Malinauskas, Spectrochim. Acta AMol. Biomol. Spectrosc. 262, 120140 (2021). https://doi.org/10.1016/j.saa.2021.120140 – reference: V. Sresht, A. Govind Rajan, E. Bordes, M.S. Strano, A.A.H. Pádua, D. Blankschtein, J. Phys. Chem. C121(16), 9022 (2017). https://doi.org/10.1021/acs.jpcc.7b00484 – reference: P. Cignoni, M. Callieri, M. Corsini, M. Dellepiane, F. Ganovelli, G. Ranzuglia, “MeshLab: An Open-Source Mesh Processing Tool,” in Proceedings of the Eurographics Italian Chapter Conference (Eurographics Association, 2008), pp. 129. https://doi.org/10.2312/LocalChapterEvents/ItalChap/ItalianChapConf2008/129-136 – reference: A. Pérez de la Luz, G.A. Méndez-Maldonado, E. Núñez-Rojas, F. Bresme, J. Alejandre, J. Chem. Theory Comput.11(6), 2792 (2015). https://doi.org/10.1021/acs.jctc.5b00080 – reference: OwensDKWendtRCJ. Appl. Polym. Sci.1969138174117471:CAS:528:DyaF1MXltFegtLc%3D10.1002/app.1969.070130815 – reference: EthaSADesaiPRSacharHSDasSMacromolecules20215425845961:CAS:528:DC%2BB3MXptVyjtA%3D%3D10.1021/acs.macromol.0c02234 – reference: Jmol: An open-source Java viewer for chemical structures in 3D (n.d.). http://www.jmol.org/ – reference: LiowSSKarimAALohXJMRS Bull.20164175575661:CAS:528:DC%2BC28XhtFOjt7fF10.1557/mrs.2016.139 – reference: JohanssonPCarlsonAHessBJ. Fluid Mech.20157816957111:CAS:528:DC%2BC2MXhvValtbnK10.1017/jfm.2015.517 – reference: ChauTTBruckardWJKohPTLNguyenAVAdv. Colloid Interface Sci.200915021061151:CAS:528:DC%2BD1MXpvFaqtL8%3D10.1016/J.CIS.2009.07.003 – reference: BerendsenHJCGrigeraJRStraatsmaTPJ. Phys. Chem.19879124626962711:CAS:528:DyaL2sXmt1els7w%3D10.1021/j100308a038 – reference: ZhangLLuanBZhouRJ. Phys. Chem. B201912334724372521:CAS:528:DC%2BC1MXhsFShtLrF10.1021/acs.jpcb.9b02797 – reference: BuehlerMJMRS Bull.20133821691761:CAS:528:DC%2BC3sXksVGksr0%3D10.1557/mrs.2013.26 – reference: Govind RajanAStranoMSBlankschteinDNano Lett.2019193153915511:CAS:528:DC%2BC1MXitVChtbo%3D10.1021/acs.nanolett.8b04335 – reference: WongT-SSunTFengLAizenbergJMRS Bull.20133853663711:CAS:528:DC%2BC3sXnvV2msLY%3D10.1557/mrs.2013.99 – reference: X.S. Wu, N. Wang, J. Biomater. Sci. Polym. Ed.12(1), 21 (2001). https://doi.org/10.1163/156856201744425 – reference: YaghoubiHForoutanMPhys. Chem. Chem. Phys.20182022308223191:CAS:528:DC%2BC1cXhsVCnsbrJ10.1039/C8CP03762K – ident: 380_CR74 doi: 10.1021/ct200908r – ident: 380_CR47 doi: 10.1021/acs.jctc.5b00080 – ident: 380_CR54 doi: 10.1134/S1560090416060191 – volume: 12 start-page: 8678 issue: 8 year: 2018 ident: 380_CR8 publication-title: ACS Nano doi: 10.1021/acsnano.8b04632 – volume: 41 start-page: 557 issue: 7 year: 2016 ident: 380_CR3 publication-title: MRS Bull. doi: 10.1557/mrs.2016.139 – volume: 123 start-page: 7243 issue: 34 year: 2019 ident: 380_CR31 publication-title: J. Phys. Chem. B doi: 10.1021/acs.jpcb.9b02797 – ident: 380_CR23 doi: 10.1098/rstl.1805.0005 – volume: 18 start-page: 2185 issue: 7 year: 2016 ident: 380_CR6 publication-title: Green Chem. doi: 10.1039/C5GC02725J – volume: 380 start-page: 1735 issue: 20 year: 2016 ident: 380_CR4 publication-title: Phys. Lett. A doi: 10.1016/j.physleta.2016.03.015 – volume: 12 start-page: 454 year: 2018 ident: 380_CR46 publication-title: Case Stud. Therm. Eng. doi: 10.1016/j.csite.2018.06.005 – volume: 92 issue: 5 year: 2015 ident: 380_CR57 publication-title: Phys. Rev. E doi: 10.1103/PhysRevE.92.052403 – ident: 380_CR55 doi: 10.1002/anie.201702945 – volume: 182 start-page: 40 issue: 1 year: 2001 ident: 380_CR84 publication-title: Applied Surface Science doi: 10.1016/S0169-4332(01)00432-9 – volume: 119 start-page: 28470 issue: 51 year: 2015 ident: 380_CR30 publication-title: J. Phys. Chem. C doi: 10.1021/acs.jpcc.5b10267 – volume: 22 start-page: 787 issue: 4 year: 2005 ident: 380_CR56 publication-title: Chin. Phys. Lett. doi: 10.1088/0256-307X/22/4/002 – volume: 38 start-page: 169 issue: 2 year: 2013 ident: 380_CR21 publication-title: MRS Bull. doi: 10.1557/mrs.2013.26 – volume: 25 start-page: 1 issue: 6 year: 2021 ident: 380_CR58 publication-title: Microfluid. Nanofluid. doi: 10.1007/s10404-021-02455-6 – volume: 45 start-page: 951 issue: 11 year: 2020 ident: 380_CR19 publication-title: MRS Bull. doi: 10.1557/mrs.2020.271 – volume: 138 start-page: 51242 issue: 42 year: 2021 ident: 380_CR13 publication-title: J. Appl. Polym. Sci. doi: 10.1002/app.51242 – volume: 53 start-page: 11098 issue: 24 year: 2020 ident: 380_CR14 publication-title: Macromolecules doi: 10.1021/acs.macromol.0c01593 – ident: 380_CR37 doi: 10.1021/acs.jpcc.7b00484 – volume: 36 start-page: 2357 issue: 11 year: 2021 ident: 380_CR18 publication-title: Journal of Materials Research doi: 10.1557/s43578-021-00127-3 – volume: 3 start-page: 10738 year: 2015 ident: 380_CR1 publication-title: J. Mater. Chem. A doi: 10.1039/C4TA06347C – volume: 155 issue: 8 year: 2021 ident: 380_CR12 publication-title: J. Chem. Phys. doi: 10.1063/5.0057145 – volume: 9 start-page: 1 issue: 1 year: 2019 ident: 380_CR9 publication-title: Sci. Rep. doi: 10.1038/s41598-019-54751-5 – volume: 9 start-page: 1611 issue: 3 year: 2013 ident: 380_CR49 publication-title: J. Chem. Theory Comput. doi: 10.1021/ct300976t – volume: 53 start-page: 3643 issue: 10 year: 2020 ident: 380_CR67 publication-title: Macromolecules doi: 10.1021/acs.macromol.0c00110 – volume: 5 start-page: 6834 issue: 9 year: 2011 ident: 380_CR36 publication-title: ACS Nano doi: 10.1021/nn2005393 – volume: 20 start-page: 22308 year: 2018 ident: 380_CR34 publication-title: Phys. Chem. Chem. Phys. doi: 10.1039/C8CP03762K – volume: 500 year: 2020 ident: 380_CR35 publication-title: Appl. Surf. Sci. doi: 10.1016/j.apsusc.2019.144002 – volume: 4 start-page: 90 year: 2017 ident: 380_CR66 publication-title: Mater. Today Chem. doi: 10.1016/j.mtchem.2017.02.006 – volume: 116 start-page: 1570 issue: 5 year: 2012 ident: 380_CR38 publication-title: J. Phys. Chem. B doi: 10.1021/jp209024r – volume: 8 start-page: 61 issue: 1 year: 2012 ident: 380_CR48 publication-title: J. Chem. Theory Comput. doi: 10.1021/ct200731v – volume: 12 start-page: 21376 issue: 41 year: 2020 ident: 380_CR62 publication-title: Nanoscale doi: 10.1039/D0NR05392A – volume: 117 start-page: 1 issue: 1 year: 1995 ident: 380_CR72 publication-title: J. Comput. Phys. doi: 10.1006/jcph.1995.1039 – ident: 380_CR79 – volume: 22 start-page: 4891 issue: 23 year: 2012 ident: 380_CR2 publication-title: Adv. Funct. Mater. doi: 10.1002/adfm.201200988 – volume: 17 start-page: 338 issue: 3 year: 1949 ident: 380_CR81 publication-title: J. Chem. Phys. doi: 10.1063/1.1747248 – ident: 380_CR44 – volume: 3 year: 2018 ident: 380_CR27 publication-title: Phys. Rev. Fluids doi: 10.1103/PhysRevFluids.3.074201 – volume: 40 start-page: 546 year: 1944 ident: 380_CR26 publication-title: Trans. Faraday Soc. doi: 10.1039/TF9444000546 – volume: 17 start-page: 4970 issue: 19 year: 2006 ident: 380_CR52 publication-title: Nanotechnology doi: 10.1088/0957-4484/17/19/033 – volume: 113 start-page: 12946 issue: 46 year: 2016 ident: 380_CR39 publication-title: Proc. Natl. Acad. Sci. U.S.A. doi: 10.1073/pnas.1616138113 – volume: 206 year: 2020 ident: 380_CR45 publication-title: Polymer doi: 10.1016/j.polymer.2020.122903 – ident: 380_CR64 – volume: 126 issue: 15 year: 2007 ident: 380_CR50 publication-title: J. Chem. Phys. doi: 10.1063/1.2715577 – volume: 81 start-page: 739 year: 2009 ident: 380_CR22 publication-title: Rev. Mod. Phys. doi: 10.1103/RevModPhys.81.739 – volume: 19 start-page: 1539 issue: 3 year: 2019 ident: 380_CR32 publication-title: Nano Lett. doi: 10.1021/acs.nanolett.8b04335 – ident: 380_CR70 – ident: 380_CR17 doi: 10.1021/j100834a012 – volume: 430 year: 2022 ident: 380_CR10 publication-title: Chem. Eng. J. doi: 10.1016/j.cej.2021.133052 – volume: 38 start-page: 366 issue: 5 year: 2013 ident: 380_CR20 publication-title: MRS Bull. doi: 10.1557/mrs.2013.99 – ident: 380_CR11 doi: 10.1016/j.saa.2021.120140 – ident: 380_CR51 – volume: 15 start-page: 3640 issue: 3 year: 2014 ident: 380_CR83 publication-title: Int. J. Mol. Sci. doi: 10.3390/ijms15033640 – ident: 380_CR71 doi: 10.1016/j.jmb.2021.166841 – volume: 28 start-page: 988 issue: 8 year: 1936 ident: 380_CR25 publication-title: Ind. Eng. Chem. doi: 10.1021/ie50320a024 – volume: 4 start-page: 1 issue: 1 year: 2012 ident: 380_CR69 publication-title: J. Cheminf. doi: 10.1186/1758-2946-4-17 – volume: 91 start-page: 6269 issue: 24 year: 1987 ident: 380_CR76 publication-title: J. Phys. Chem. doi: 10.1021/j100308a038 – ident: 380_CR78 – ident: 380_CR41 doi: 10.1163/156856201744425 – volume: 123 issue: 23 year: 2005 ident: 380_CR75 publication-title: J. Chem. Phys. doi: 10.1063/1.2121687 – volume: 430 year: 2022 ident: 380_CR5 publication-title: Chem. Eng. J. doi: 10.1016/j.cej.2021.133036 – volume: 10 start-page: 181 year: 2012 ident: 380_CR80 publication-title: Cent. Eur. J. Phys. doi: 10.2478/s11534-011-0096-2 – volume: 31 start-page: 8335 issue: 30 year: 2015 ident: 380_CR29 publication-title: Langmuir doi: 10.1021/acs.langmuir.5b01394 – volume: 172 start-page: 292 issue: 1 year: 2013 ident: 380_CR42 publication-title: J. Controlled Release doi: 10.1016/j.jconrel.2013.08.024 – ident: 380_CR63 – volume: 111 start-page: 3155 issue: 7 year: 1999 ident: 380_CR77 publication-title: J. Chem. Phys. doi: 10.1063/1.479595 – volume: 3 start-page: 1377 issue: 3 year: 2011 ident: 380_CR43 publication-title: Polymers doi: 10.3390/polym3031377 – volume: 208 year: 2021 ident: 380_CR33 publication-title: Mater. Des. doi: 10.1016/j.matdes.2021.109902 – volume: 150 start-page: 106 issue: 2 year: 2009 ident: 380_CR53 publication-title: Adv. Colloid Interface Sci. doi: 10.1016/J.CIS.2009.07.003 – volume: 10 start-page: 1 issue: 1 year: 2019 ident: 380_CR15 publication-title: Nat. Commun. doi: 10.1038/s41467-019-12093-w – ident: 380_CR82 doi: 10.5281/zenodo.6629427 – volume: 84 start-page: 121 year: 2016 ident: 380_CR65 publication-title: Polymer doi: 10.1016/j.polymer.2015.12.052 – volume: 125 start-page: 12020 issue: 43 year: 2021 ident: 380_CR61 publication-title: J. Phys. Chem. B doi: 10.1021/acs.jpcb.1c07642 – volume: 11 start-page: 6519 issue: 16 year: 2020 ident: 380_CR60 publication-title: J. Phys. Chem. Lett. doi: 10.1021/acs.jpclett.0c01793 – ident: 380_CR73 – volume: 360 start-page: 317 issue: 1 year: 2011 ident: 380_CR24 publication-title: J. Colloid Interface Sci. doi: 10.1016/j.jcis.2011.04.051 – volume: 123 start-page: 10233 issue: 48 year: 2019 ident: 380_CR68 publication-title: J. Phys. Chem. B doi: 10.1021/acs.jpcb.9b06681 – volume: 781 start-page: 695 year: 2015 ident: 380_CR28 publication-title: J. Fluid Mech. doi: 10.1017/jfm.2015.517 – volume: 54 start-page: 584 issue: 2 year: 2021 ident: 380_CR40 publication-title: Macromolecules doi: 10.1021/acs.macromol.0c02234 – volume: 139 issue: 11 year: 2013 ident: 380_CR7 publication-title: J. Chem. Phys. doi: 10.1063/1.4821604 – ident: 380_CR59 doi: 10.1039/C9CP04120F – volume: 13 start-page: 1741 issue: 8 year: 1969 ident: 380_CR16 publication-title: J. Appl. Polym. Sci. doi: 10.1002/app.1969.070130815
SSID	ssj0015075
Score	2.4395707
Snippet	A challenging topic in surface engineering is predicting the wetting properties of soft interfaces with different liquids. However, a robust computational...
SourceID	crossref springer
SourceType	Enrichment Source Index Database Publisher
StartPage	108
SubjectTerms	Applied and Technical Physics Characterization and Evaluation of Materials Chemistry and Materials Science Energy Materials Impact Article Materials Engineering Materials Science Nanotechnology
Title	Wettability of soft PLGA surfaces predicted by experimentally augmented atomistic models
URI	https://link.springer.com/article/10.1557/s43577-022-00380-9
Volume	48
WOSCitedRecordID	wos000852931100004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVAVX databaseName: SpringerLINK Contemporary 1997-Present customDbUrl: eissn: 1938-1425 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0015075 issn: 0883-7694 databaseCode: RSV dateStart: 19970101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1bS8MwGA06FfTBy1ScN_Lgmwa6Jm2axyFOH2QMr3srzU2EuY2mE_bvTdJ2bCADff9awkm-fAnfyTkAXGGtAy4oQZkmEhGRCJSwtkZaZczWC0ZUKL3ZBO31ksGA9atHYaZmu9ctSb9Te48ee203trBTihz73LWzAsTWwYYtd4kzbHh6fpv3DqJSXtemD0Y0ZqR6KvP7P5bL0XIv1JeY7t7_BrcPdqsjJeyUa-AArKlRE-wsCA02wZYnegpzCAbvqihKbe4ZHGto7DYM-4_3HWimuXb8LDjJXfPGnkQhn8FFB4DhDGbTD6_iKaG9rH95kWfozXTMEXjt3r3cPqDKXQEJjKMCiSTGnEmmiWN6JplggYjCTNuE1BHmIowzSbAOqWRJZGeSB4KFnFAlLcSUSnwMGqPxSJ0AyAlTWCohCdUEc86ojlUgbDSWWGDSAu0a5FRU0uPOAWOYuiuIxS8t8UstfqnHL2UtcD3_ZlIKb6yMvqnnJa2S0KwIP_1b-BnYdi7zJVn7HDSKfKouwKb4Lj5NfulX3w_Ae9TY
linkProvider	Springer Nature
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1bS8MwFD7oVNQHL1NxXvPgmwa6Jl2aRxHnxDnE695KcxNhTmk7Yf_eJO1EQQb6flrCl5ychPPl-wCOiDGBkIzi1FCFqYwljnnTYKNTbusFpzpU3myC9Xpxv89vqkdh-YTtPmlJ-p3ae_TYa3tuCztj2LHPXTsrwHwW5qitWE4x__bu8at3EJXyujZ9CGYtTqunMr__42c5-tkL9SWmvfq_wa3BSnWkRKflGliHGT2sw_I3ocE6LHiip8w3oP-ki6LU5h6jN4Nyuw2jm-7FKcpHmXH8LPSeueaNPYkiMUbfHQAGY5SOnr2Kp0L2sv7qRZ6RN9PJN-GhfX5_1sGVuwKWhEQFlnGLCK64oY7pGaeSBzIKU2MT0kREyLCVKkpMyBSPIzuTIpA8FJRpZSFmTJEtqA3fhnobkKBcE6WlosxQIgRnpqUDaaOJIpLQBjQnICeykh53DhiDxF1BLH5JiV9i8Us8fglvwPHXN--l8MbU6JPJvCRVEuZTwnf-Fn4Ii537627Svexd7cKSc5wvidt7UCuykd6HeflRvOTZgV-Jn8Q617w
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1bS8MwFD7ovKAPXqbivObBNw12Tbo0j6JORRkDb3srzU0EnWPthP17k7QbG8hAfD8t5UtOTw7ny_cBnBBjAiEZxamhClMZSxzzusFGp9zWC051qLzZBGu14k6Htydu8Xu2-2gkWdxpcCpN3fy8p0zh12Nb-MwWecawY6K70VaA-TwsUEekd_3648t4jhAVUrs2lQhmDU7LazO_v2O6NE3PRX25aa7__0M3YK08aqKLYm9swpzuVmF1QoCwCkueACqzLei86jwvNLuH6MugzP6eUfvh5gJlg75xvC3U67uhjj2hIjFEk84AH0OUDt68uqdCton_9OLPyJvsZNvw3Lx-urzFpesCloREOZZxgwiuuKGOARqnkgcyClNjE9VERMiwkSpKTMgUjyO7wiKQPBSUaWXhZkyRHah0v7p6F5CgXBOlpaLMUCIEZ6ahA2mjiSKS0BrUR4AnspQkd84YH4lrTSx-SYFfYvFLPH4Jr8Hp-JleIcgxM_pstEZJmZzZjPC9v4Ufw3L7qpk83LXu92HFGdEXfO4DqOT9gT6ERfmdv2f9I78pfwBDFOCg
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Wettability+of+soft+PLGA+surfaces+predicted+by+experimentally+augmented+atomistic+models&rft.jtitle=MRS+bulletin&rft.au=Bellussi%2C+Francesco+Maria&rft.au=Roscioni%2C+Otello+Maria&rft.au=Rossi%2C+Edoardo&rft.au=Cardellini%2C+Annalisa&rft.date=2023-02-01&rft.pub=Springer+International+Publishing&rft.issn=0883-7694&rft.eissn=1938-1425&rft.volume=48&rft.issue=2&rft.spage=108&rft.epage=117&rft_id=info:doi/10.1557%2Fs43577-022-00380-9&rft.externalDocID=10_1557_s43577_022_00380_9
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0883-7694&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0883-7694&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0883-7694&client=summon