Multimodel approach for accurate determination of industry-driven properties for Polymer Nanocomposite Materials

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ContentslistsavailableatScienceDirect

Journal

of

Computational

Science

jo u r n al ho me p a g e :w w w . e l s e v i e r . c o m / l o c a t e / j o c s

Multimodel

approach

for

accurate

determination

of

industry-driven

properties

for

Polymer

Nanocomposite

Materials

Erik

Laurini

a,∗

_,

_Domenico

_Marson

a

_,

_Maurizio

_Fermeglia

a

_,

_Sabrina

_Pricl

a,b

a_Molecular_Simulation_Engineering_(MOSE)_Laboratory,_DI3,_Piazzale_Europa_1,_University_of_Trieste,₃₄₁₂₇_Trieste,_Italy

b_National_{Interuniversity}_Consortium_for_Material_Science_and_Technology_(INSTM),_Research_Unit_MOSE-DEA,_University_of_Trieste,_Trieste,_Italy

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received7November2017

Receivedinrevisedform20February2018

Accepted4March2018

Availableonline12March2018

Keywords:

Molecularsimulations

Computationalrecipes

Polymernanocomposites

Materialpropertiesprediction

Experimentalvalidation

a

b

s

t

r

a

c

t

Theneedforeffectiveandefficientdesignandproductionofsophisticatedmaterialswithadvanced performancesonacompetitivetimescaleis stronglydrivingtheintegration ofmaterialmodeling andsimulationtechniquesintomaterialselectiondecisionprocesses.Specifically,forcomplex struc-turalmaterialssuchaspolymer-basednanocomposites(PNCs),thereisastrongindustrialdemandfor chemistry/physics-basedmodelsandmodelingworkflowsabletopredictrelevantmaterialpropertiesin anaccurateandreliableway.Underthisperspective,inthisworkwedescribetheapplicationofmultiscale molecularmodelingtechniquesforthechoiceofPNCmaterialsforaerospaceapplications.Theresults areobtainedintheframeworkoftheEuropeanprojectMulti-scaleCompositeMaterialSelectionPlatform withaSeamlessIntegrationofMaterialsModelsandMultidisciplinaryDesignFramework (COMPOSELEC-TOR),fundedbytheEuropeanCommissionwithintheH2020callAdvancingtheintegrationofmaterials modelinginbusinessprocessestoenhanceeffectiveindustrialdecisionmakingandincreasecompetitiveness. ©2018TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBYlicense (http://creativecommons.org/licenses/by/4.0/).

1. Introduction

Theintegrationofmodelingandsimulationstechniquesto sup-portmaterialselectionprocesses isoneofthemostcompelling needsinadvancingmaterialindustryandmanufactory,duetothe necessityofeffective/efﬁcientdesignandproductionof sophisti-catedmaterials,componentsandsystemswithadvanced/extreme performanceonacompetitivetimescale.Inthisarenaand, specif-ically, for complex structural materialssuch as polymer-based nanocomposites(PNCs) there isa strongindustrial demand for chemistry/physics-basedmodelsandmodelingworkﬂowsableto predictrelevantmaterialproperties(akaKeyPerformance Indica-torsorKPIs)inanaccurateandreliableway[1,2].

Developmentsand improvementshave beentaking place in disparatecommunitiesconsideringdifferenttypesofmodelsand phenomenaonseveraldifferentlengthscales,withadvancements intheso-calledmultiscaleapproaches,multi-disciplinarydesign optimization,andvisualization[3–6].Importantlinkswithina hier-archyofprocessing,nano/microstructureproperties,andexpected performancearecurrentlyavailable[7–12].Nevertheless,theyare farfrombeingsufﬁcientformaterialsdesignandselection, and

∗ Correspondingauthor.

E-mailaddress:erik.laurini@dia.units.it(E.Laurini).

sufferfromalackofintegrationacrossdifferenttypesofmodels andrelatedcommunities(especiallydiscrete/continuumand mod-eling/experimental couplingandvalidation). Materialsselection process(MSP)isfundamentallygoal-oriented,aimedat identify-ingmaterialstructuresandprocessingpathsthatdeliverrequired KPIs.Tobereliable,MSPmustbebuiltuponphysicaland engineer-ingframeworksandbasedonmethodsthataresystematic,effective andefﬁcientinmodelingcomplex,hierarchicalmaterialssuchas PNCs.Formaterialdesignandselection,understandingand quan-tifyingthelinksbetweenmaterialstructureatthenanoscaleand theirmacroscopiceffectsis,therefore,essential.As manufactur-ingandtestingisverytime-consuming,expensiveandsometimes unfeasible, the adoption of materials modeling and simulation approachesisthereforeimperative.Thisimpliestheneedfor devel-opmentandintegrationofmodelsfor thereliablepredictionof materialbehavioratdifferentscalesaswellasthederivationof efﬁcientmaterial-processing-propertyrelationships.

Forseveralreasons,currentevaluationandselection method-ologiesforcomposites(and,thus,compositesstructuraldesign)do notyetmakeextensiveuseofmaterialsmodelingtools,largely rely-ingonempiricalmethods.Ontheonehand,sinceproductshave becomemoreandmorecomplexandsustainabilityissuescoupled withaworldwideﬁerceeconomiccompetitionaresoaring, mod-elingandsimulation–fromdesignthroughmaterialselectionand productionprocess–aremorethaneverneeded.Theirultimate

https://doi.org/10.1016/j.jocs.2018.03.002

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goalsareshorterlead-time,betterproductquality,more compet-itivecost, andhigher customersatisfaction. Ontheotherhand, thecomplexityofactualtechnologiescombinedwiththelackofa continuativeandsolidconnectionbetweenindustryandacademia presentsaconditioninwhichanear-deadlocksituationseemsto emerge.

Inthisarea,thisworkaimsatdemonstratingtheusein COM-POSELECTORofamulti-disciplinary,multi-modelapproachforthe accurate,reliable,efficientandcost-effectiveindustry-drivenKPIs determinationforPNCmaterials,therebyfillingthegapbetween businessprocessesandmaterialsscience/engineeringworkflows. Specifically,the resultsobtainedfor a case studypertaining to aerospaceapplicationsandtherelevantKPIsdetermination (i.e., mechanical, viscoelasticand interfacialproperties) willbe pre-sented and discussed. The high degree of modeling and data predictionintegrationintoMSPswillthenprovidevaluable infor-mationabout current“holes inproperty space”,enable what-if scenariosandprovidemechanisticinsightsintothehigh perfor-manceofthesefascinatingmaterials.

2. Theoryandcomputationalmethodologies

2.1. Theindustrialcase

Whiletheuseoftheso-called“reinforced”plastics(RPs) has become a mainstay in aircraft production, the choice of poly-mericmatrixand,especially,(nano)fillers/fibersremainsalargely unexploredscenario.Currently,manyindustrialaircraft manufac-turesareconsideringsubstitutingthermosetRPs–mostcommonly employedin theair transport sector –with thermoplasticRPs. Thislastfamilyofmaterialsoffersseveralkeyadvantagesoverthe former,includingexcellentfatigueanddamagetolerance proper-ties,shortermanufacturingcycles,lowermoistureabsorption,and almostcomplete recyclability.Thislastpropertymakes thermo-plasticcompositesinaerospaceapplicationsveryattractivesince anymajoraircraftindustryandtheirsuppliersproducehundreds oftonsofwastematerialeachyear[13].Inthequestofnew nano-RPsforaircraftspecificapplications,inCOMPOSELECTORtwomain materialgoalsarepursued:a)theuseofpoly(etherethylketone) (PEEK)asthermoplasticpolymericmatrixinplaceofthewidely employedthermosetting(e.g.,epoxy)resins;b)thereplacement ofactualcarbonfiberswithmultiwallcarbonnanotubes (MWC-NTs).Accordingly,thefollowingindustrialKPIsdeterminationwere identifiedastestscasesforMSPimplementation:i)glass transi-tiontemperature(Tg),ii)mechanicalmoduli,andiii)viscoelastic

propertiesofthePEEK/MWCNTnanocompositesystemsas func-tionoftheﬁllercontent.Furthermore,sincetheinterfacialstress transferbetweentheCNTandthepolymermatrixinthe nanocom-positemainlydependsonthejoiningstrengthamongthenanoﬁller andthepolymer,andthepulloutofCNTsfromthematrixisoneof themaininterfacialmechanismsexperimentallyobserved,an addi-tionalKPIwasselected,namelytheestimationofthepullingforces ofaCNTfromthePEEKmatrix.Accordingly,computationalmodels ondifferentscalesweredevised,run,andthepredictvaluesforthe aboveKPIswherevalidatedagainstexperimentaldata,asdescribed below.

2.2. Computationalrecipes 2.2.1. Generaldetails

Allsimulationswerecarriedoutusingtheparallelversionof theopensourcecodeLAMMPS(http://lammps.sandia.gov/), run-ningonourownCPU/GPUcluster,usingtheCOMPASSforceﬁeld [14].StartingfromtheoptimizedPEEKmonomerunit,3 indepen-dentconﬁgurationsofaPEEKchainwerebuiltusingtheRotational

Fig.1.SimulationcellofPEEK/MWCNTnanocompositesystems.ThePEEKchains

areshownasatom-coloredspheres(C,darkgray,O,red,H,lightgray)whilethe

MWCNTisportrayedasdimgraysticks-and-balls.(Forinterpretationofthe

refer-encestocolourinthisﬁgurelegend,thereaderisreferredtothewebversionofthis

article.)

IsomericState(RIS)method[15]ateachdesiredtemperature.For eachofthesechains,athree-dimensional(3D)simulationboxwith periodicboundaryconditions(PBCs)wasbuilt,eitherusingonly PEEKchainsor1multi-wallcarbonnanotubesurroundedbya num-berofPEEKchainsrequiredtoachieveaspeciﬁcweightfraction (videinfra),andtheresultingcellwasrelaxedbyenergy minimiza-tion.Accordingly,3different3Dsimulationboxeswereobtained foreachRISgeneratedPEEKchain,andthecomputationalrecipe forthedeterminationofagivenpropertywasappliedtoeachof theseboxes(seeFig.1).

Thus,eachresultingpropertyisexpressedastheaveragevalue over 3 distinct simulations.The Berendsen thermostat/barostat [16]withcouplingtimeconstants_␶T=0.1sand␶P=0.5ps,wasused

fortemperatureandpressurecontrolduringMDruns.Short-range intermolecularinteractionsoffullatomisticpolymermodelswere accountedfor bytheLennard-Jones9-6 potentialfunctionwith geometricmeancombinationrules.Long-rangeelectrostatic inter-actionsofpolymermodelswerehandledwiththeparticlemesh Ewald(PME)[17]method(accuracy0.001kcal/mol).Thecut-off distance for truncationof all non-bonding interactions was set equaltohalfofthesimulationcelllength.InallMDsimulations, integrationofNewton’sequationsofmotionwasachievedusingthe velocityVerletalgorithmwithanintegrationtimestepof1fs,ifnot otherwisestates.ThelengthofeachMDsimulationandthe num-berofframescollectedalongeachMDtrajectoryvarieddepending onthespeciﬁcsystemandtherelevantpropertytobeestimated. Therefore,detailswillbegiveninthespeciﬁcsectionsbelow. 2.2.2. Computationalrecipeforthepredictionofglasstransition temperatureinPEEK/MWCNTnanocomposites

TheestimationoftheTgforthepurePEEKmatrixanditsMWCNT

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weightfractionswererealizedbyvaryingthenumberofpolymer chainswithrespecttothefixednanotubecontent.Theresulting cellconfigurationswereoptimizedviathefollowingrefinement protocol: i) initialsystem energy relaxation ii) briefMD simu-lationrun(0.5ns)intheconstantvolume-constanttemperature (i.e.,thecanonicalorNVT)ensembleat298K,andiii)finalenergy minimizationviacombinedconjugategradient/Newton-Raphson methodsusing10−3kcal/(molÅ)astheconvergencecriterionfor theenergygradient.Therelaxedsimulationboxeswerethen sub-jectedtoMDrunsintheisochoric-isothermal(NPT)ensemblefor 2.5nstoreachrealisticdensityvaluesatthedesiredtemperature andpressure(1atm).Thesimulationcellwasfurtherrelaxedby carryingoutanNPT-basedMDsimulationannealingprotocolas follows:eachsystemwasfirstheatedfromthedesired temper-atureT(e.g.,298K)tothetemperatureT+200K (e.g.,498K)in incrementsof20K,andthencooledbacktotheinitialtemperature withthesametemperaturevariationscheme.Thetotalduration oftheannealingprocesswas0.2ns.Attheend oftheannealing process,eachcellwasagainenergyminimized,accordingtothe fol-lowingprotocol:first,acombinationofsteepestdescent/conjugate gradientmethodswasapplieduntiltheenergyderivativeonany atomdecreasedto1000kcal/molÅ.Next,Newton-Raphson mini-mizationwasperformeduntiltheenergyderivativebecameless than0.1kcal/molÅ.Forthefinal equilibriumdensity determina-tion,starting fromthewell-relaxed simulationcellsobtainedat theendofthesimulatedannealingprocessfurther1nsNPTMD simulationrunwasperformedfordataacquisitionatthedesired temperature.Thefirst0.5nswerediscardedandonlythelast0.5ns oftheequilibratedNPTMDtrajectorywereretainedfordata analy-sis.MDframesweresavedevery5ps,foratotalnumberofframesof 100.Theentiresequencedescribedabove,fromPEEKchain gener-ationviaRIStodataproductionNPTruns,wasrepeatedtoestimate thedensityvaluesforallPEKsystemsinthetemperaturerangeof interest(i.e.,298–500K).Fromtheequilibriumdensityvalues,the specificvolume(reciprocalofdensity,Vsp)ateachtemperaturewas

nextdetermined,andthecorrespondingTgwasestimatedfromthe

intersectionofthelinearregressionsoftheVspvs.Tcurvesinthe

two(glassyandrubbery)regimes.

2.2.3. Computationalrecipeforthepredictionofmechanical moduliofPEEK/MWCNTnanocomposites

Todeterminestress-strainrelationshipforthedifferent PEEK-MWCNT PNC systems, starting from the equilibrated systems obtainedasdescribedinSection2.2.2,theﬁrststeprequires achiev-ingtheminimuminitialstressstateforthecorrespondingperiodic box.Tothepurpose,eachsimulationboxwasconsecutively sub-jectedtoMDsimulationsinthecanonical(NVT)andmicrocanonical (constantvolume-constant energy,NVE)ensemblesfor5nsand 2ns,respectively.Next,eachunitcellsizewasadjustedto mini-mizetheinitialstressesusingNPTMDsimulations(simulationtime uptoseveralthousandsteps,dependingonthemolecularmodel andcellsize),followedbyfurtherequilibration(2ns)intheNVE ensemble.

Foreachequilibratedsystem,auniformstrainfield(0.5%)along therequireddirectionswasappliedbyproportionatelyscalingthe correspondingunitcellandtheatomicpositionsofthePEEKchains, whilekeepingthepositionsoftheMWCNTunchanged,inorder topreserveanun-deformedshapeofthenanotubes.Byapplying thiscomputationaltechnique,eachsimulation cellwasstrained tocalculatedunidirectionaltension/compressionandhydrostatic tension/compression, respectively. In the first case, strain was appliedalongonedirectionatime,andtheprocedurewasrepeated forthetwootherdirectionsstartingfromtheunstrainedcell.In thecaseofhydrostatictension/compressionsimulations,thesame strainfieldwasappliedsimultaneouslytoallnormaldirections.

Attheatomiclevel,stressisexpressedinavirialform:

ij=−_V1

a

Mava ivaj + 1 2

b/=aF ab i rabj

(1)

inwhichVisthevolumeofthesimulationcell,givenbythesumof eachatomvolumeVa_._va

i andv a

j arethei-thandj-thcomponents ofthevelocityofatoma,F_iab isthei-thcomponentoftheforce betweenatomsaandb,andrab

j isthedistancebetweenthesame twoatoms.Thenegativesignistointroducedtoexpresstensile stressasapositivequantity.

Intheframework of continuummechanics,theassumptions thati)boththepolymericmatrixandtherelevantnanocomposites areendowedwithmaterialsymmetryandii)therelationbetween stressandstrainislinearbothhold.Accordingly,thegeneralized constitutiverelationoftheequivalentcontinuumreads:

⎧

⎪

⎨

⎪

⎩

11 22 33

⎫

⎪

⎬

⎪

⎭

=

⎡

⎢

⎣

C11 C12 C12 C12 C11 C12 C12 C12 C11

⎤

⎥

⎦

⎧

⎪

⎨

⎪

⎩

ε11 ε12 ε13

⎫

⎪

⎬

⎪

⎭

(2)

inwhich␴ijand␧ijarethestressandstraincomponents,

respec-tively,andCijaretheelasticconstants.

Asmentioned aboveand inlinewithotherworksonsimilar systems[18–20],topredictstress-strainbehaviorunder unidirec-tionaltensionor compression,a 0.5%strainwasappliedtothe un-deformedcellalongonedirectionatime.Underthiscondition, andtakingdirection1astheﬁrstchoice,theonlynon-zerostrain componentis␧11.ExpandingtheﬁrstrowofEq.(2),weget:

11=C11ε11 (3)

Utterlysimilar expressionscan bewrittenbydeformingthe cellalong direction2or3.Hence,foreachsimulatedtensionor compressionthreedifferentvaluesoftheelasticconstantC11are

obtained.Sincethestrainisapplieduniformlyineach direction (␧11=␧22=␧33),C11canbefurtheraveraged.

Underconditionsofhydrostatictensionandcompression,the elasticbulkmodulusKisgivenbyEq.(4):

K=1₃

11+22+33

ε11+ε22+ε33

(4) Accordingly,byrecallingthat,inthiscase,␧ii=0.05inall

direc-tions,KcanbeeasilyevaluatedbymeansofEq.(4)byinsertingthe normalcomponentsofstressasderivedfromthecorresponding simulations.

Finally,thefundamentalrelationshipsthatlinkthebulk mod-ulusKandtheelasticconstantC11tothePoisson’sratio␯andthe

elastic(Young)modulusE,i.e.,

C11= (1−) E

(1+) (1−2) (5)

K= E

3 (1−2) (6)

allowthedeterminationofthevalueof␯andEonceKandC11

areknownasaresultofthesimulationproceduresreportedabove. 2.2.4. Computationalrecipeforthepredictionoftheviscoelastic behaviorofPEEK/MWCNTnanocomposites

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smallmoleculesorextensivemolecularfragments,whichinteract bypairwiseadditiveforcesexpressedbyaconservative, dissipa-tive,and randompotential.Theoverallforceactingona beadi canbeexpressedasFi=

j/=i(F C

ij+FDij+FRij)andiscalculatedby summationoverallotherparticleswithinacertaincut-offradius, rc,whichrepresentstheintrinsiclengthscaleoftheDPDmodel.

Theconservativeforcerepresentstheexcludedvolume interac-tionsbetweenparticlesiand jin thedimensionless formFC

ij=

aij

1−rij

ˆr_ij,where rij=ri− rj,rij=|rij|, ˆrijij= rij/rij,andaijis

themaximumrepulsionbetweenparticlesiandj.Thedissipative (FD_ij =−ω

rij

2

ˆr_ij_·_v_ij

_r_ij) andrandom(FD ij=ω

rij

ˆr_ij/(t)−1/2)forcesactasheatsink

andsource,respectively,andthecombinedeffectofthetwoforces performsasathermostat,where␥isafrictioncoefﬁcientrelated tothethermalnoiseamplitude␴viatheﬂuctuation-dissipation theorem,2₌₂_␥k

BT.␻(r)isaweightfunction,␨isanormally dis-tributedrandomvariablewithzeromeanandunitvariancethat is uncorrelated for differentparticle pairs, t is the time step of anintegrationscheme,and

v

_i=vi−

v

j is therelative velocity oftheith_and_the_jth_particles._The_equations_of_particle_motion,

dri/dt=

v

ianddvi/dt=Fi,aresolvedusingasintegrationschemethe velocity-Verletalgorithm.Whenmodelingpolymerchainsor com-plexmolecules,typicallytwoadditionalforcesareactingbetween bondedbeads:aharmonicspringconnecting twoadjacent par-ticlesiandj:FB

ij=kb

rij−r0

ˆr_ij,wherekb isaspringconstant

andr0theequilibriumdistancebetweentheparticles,andFA_ijz=

1/2ksin

0−0

,wherek_␪isaspringconstantand␪0the

equi-libriumanglebetweenadjacentbeadstriplesijzinarow. 2.2.4.2. Coarse-grainedmolecularmodelsofPEEKandMWCNTs. The ﬁrstnecessarystepofacoarse-grain(CG)calculationisthe con-structionof therequired CG models.This is usuallyperformed takingintoaccounttherelevantstructural/thermodynamic proper-tiesofthemoleculesunderinvestigationandmatchingthesewith thecorrespondingatomisticfeaturesinordertoassuretheability oftheCGsimulationtoreproducethem.Accordingly,inthiswork PEEKandMWCNTCGmodelswerederivedbyadirectcomparison oftheappropriateatomisticandDPDpair–paircorrelation func-tions,accordingtoaprocedureextensivelyreportedinourprevious work[10,22–31].The next,importantissuein DPDsimulations istocapturetheessentialintra-andinter-molecularinteractions takingplaceamongallmolecularactorsofthemesoscopic simula-tionsasexpressedbythevaluesoftheconservativeparameteraij.

Thisquantityaccountsfortheunderlyingchemistryofthesystem considered.Inthiswork,weemployedawell-validatedstrategy that correlatestheinteractionenergies estimatedfroma lower scale(atomisticMD)simulationstothemesoscaleaijparameter

values.Followingthiscomputationalrecipe,theinteraction ener-giesamongthePEEK/MWCNTsystemcomponentsestimatedfrom MDsimulationswererescaledontothecorrespondingmesoscale segmentsadaptingtheproceduredescribedinourwork[22–36]. 2.2.4.3. DPDsimulationinputparameters. Tostudythe viscoelas-ticpropertiesof PEEK/MWCNTnanocompositesystemsbyDPD, thevaluesofthesimulationparameterswereassignedasfollows. ThebondlengthbetweeneachDPDbeadwassetto0.5DPDunits, whileabondharmonicconstantof100kbT(withkbT=1inDPD)

wasattributedbothtotheCNTandthepolymer.Toincorporate anappropriatedegreeofbendingrigidityintheCNT,bothbond andangleconstantsweresetequalto100kbT.Thisangleconstant

shouldallowtocorrectlyaccountforbendingstiffnessandYoung ModulusofrealCNT/Polymer-basedsystem.Thevalueofthe fric-tioncoefﬁcient␥wassetto6.75[37].Tosimulaterealisticsystems

Table1

Composition of DPD systems used to predict the viscoelastic properties of

PEEK/MWCNTnanocompositesystems.EachPEEKchainismadeupof60DPDbeads,

whilethenanotubeiscomposedof20DPDbeads.

NumberofDPDchains

Component 3%wt 6%wt 9%wt 12%wt 15%wt

PEEK 3880 3760 3640 3520 3500

Carbonnanotube 360 720 1080 1140 1500

withdifferentcontentofMWCNTsbyweight,eachMWCNTand

PEEKchainweremodelledas20and60DPDbeads,andthe

num-berofchainsandMWCNTsineachsystemwasvaried,asshownin

Table1.

Therepulsionparametersforequalbeads(aii)wassetto25;the

correspondingtheinteractionparameterbetweenunequalbeads, aij,obtainedfromtheproceduredescribedabove,wasfoundtobe

equalto34.

Thecut-offradiusrcisrelatedtothevolumeofaDPDbeadbythe

relationshiprc=(␳Vb)1/3,inwhichDPDnumberdensity␳=3and

Vb=614Å3isthevolumeofaPEEKmonomerasusedinatomistic

MDsimulations.Thisyieldsrc=1.23nm.AstheaDPDsimulation

celllengthof44DPDunits,thecorrespondingrealspace dimen-sionoftheboxsidewas∼54nm.Finally,therelationbetweena DPDtimeunit ␶anda realtime unittisgivenbythe

relation-ship ∼25.7N5m/3 [38,39], in which Nm is the number of water

molecules(VH2O=29.7Å3)ﬁllingupaDPDbead.Accordingly,in

oursystemNm ∼ 21, sothat␶ ∼ 4108ps. Thesimulation time

stepadoptedwas0.02␶,thatis82.2ps,andeachDPDsimulation wasrunfor20×106_steps._Accordingly,_each_total_simulation_run

correspondedto1.640ms.

2.2.4.4. Calculationoftheviscoelasticproperties. Thecalculationof thefrequency-dependentstoragemodulusG’(_␻)andlossmodulus G”(␻)wasobtainedconvertingthetime-dependentshearmodulus G(t)intoits(␻)-dependentform[40].Inturn,G(t)wascomputed fromthestressautocorrelationfunctiongivenbyEq.(7):

G (t) = V

kBT␣ˇ(t)␣ˇ(0) (7)

inwhichVisthevolumeofthesimulationbox,theangle brack-etsrepresentensembleaverage,and␴␣ˇ(with␣ /=␤)isthe␣-␤

componentofthestresstensor,whichisgivenbythevirial expres-sion: ˛ˇ=_V1

N 1mivi˛viˇ+

N−1 1

N

j=i+1rij˛Fijˇ

(8)

wheremi,mi␣,andvj␤arethemassandthe␣-and␤-velocity

componentsofbeadi.Ther_ij␣andF_ij␤inEq.(8)representthe ␣-componentseparationdistanceandthe␤-componentforceacting betweenbeadsiandj,respectively.Toobtainmoreaccurateresults, i)smootherestimatesofthestressautocorrelationfunctionswere obtainedbyaveragingtheindividualcurvesfromthethreestresses, giventheequivalencyoftheoff-diagonalelementsofthestress tensorandii)stressvalueswereacquiredeverysimulationtime step.

Performing theFourier transformof G(t)(Eq.(7))yieldsthe frequency-dependentshearmodulusG*(␻)as:

G∗(ω) =iω

0

∞

(5)

Fig.2.InterfacemodelsfordeterminingFcoh(left)andFpo(right)inseparatinga

MWCNTfromthePEEKmatrixinnormalandsheardirections,respectively.Color

legendasinFig.1.

Accordingly,G’(w)andG”(w)aregivenby:

G’ (ω) =ω 0

∞ G (t) sin (␻t) dt (10) G" (ω) =ω 0

∞ G (t) cos (␻t) dt (11)

OnceG’andG”areknownfromEqs.(10)and(11),the correspond-ingdissipativefactortan␦canbesimplyobtainedastheratioG”/G’. Inordertoobtainreliableestimatesoftherheologicalproperties ofthePEEK/MWCNTnanocompositesystems,threeindependent simulationrunswereconducted,eachstartingfromindependent conﬁgurations,and thevalues ofG’andG”reportedasaverage values.

2.2.5. Computationalrecipeforthepredictionoftheinterfacial behaviorinPEEK/MWCNTnanocomposites

Twodifferentinterfacemodelswerepreparedtoinvestigatethe loadtransferbetweenaMWCNTandthePEEKchains,asshownin Fig.2.Accordingly,bothnormalandshearseparationforcescan becalculateduponslowlydisplacingtheMWCNTinnormaland sheardirections,respectively.Indeed,oncethenanoﬁllerismoved awayfromthepolymermatrix,itexperienceseithernormal(or cohesive)forcesFcoh,orshear(akapullout)forcesFpo,depending

onthemotiondirectionoftheMWCNT.Intheﬁrstcase,the poly-mericchainsareplacedontopoftheMWCNT(Fig.2A)whereasin shearseparationthenanoﬁllerisembeddedwithinthepolymeric

Fig.3.(A)SpeciﬁcvolumeVspofpurePEEKandofaPEEK/MWCNTsnanocomposite

(6%wtasafunctionoftemperatureT.Onlythesetwocurvesareshownforclarity.

(B)Comparisonofsimulated(patternedbars)andexperimentalvalues(ﬁlledbars)

ofTgforpurePEEKandPEEK/MWCNTnanocompositesasafunctionofMWCNTs

concentration(%wt).Experimentaldatafrom[37–39].

matrixFig.2B).Accordingly,thenanotubeispulledinthez direc-tionfornormalseparationwhereasmovementalongthexdirection isrealizeshearseparation.

Aftereachmolecularsystembuilding,1nsequilibrationofMD simulationsintheNVTensemblewasperformed.Aftereachsystem equilibrationwasachieved,inordertorealizethetwodifferent MWCNTmovement,anaveragedisplacementrateof10−4–10−5Å fs−1 fornormalseparationand10−3Åfs−1 forshearseparation, respectively,wereadopted.

3. Resultsanddiscussion

3.1. PredictionofTgforPEEK/MWCNTsnanocompositesystems

Fig.3Ashowsthebehaviorofthespeciﬁcvolumeasafunction oftemperatureTforthepurePEEKandthecorrespondingPNC with6%wtofMWCNTsasanexample.Theproceduretodetermine Tgisinitiallybasedonvisualdatainspection,toidentifythekink

pointintheVspvs.Tcurves,followedbythecurvedivisioninto

twoparts,correspondingtotheregionsT<Tg(glassyregime)and

T>Tg(rubberystate).Next,eachdatasetisﬁttedtoastraightline

bylinearregression,andTgisdeterminedfromtheintersections ofthetwo lines(Fig.3A).ThevalueofTgforallPEEK/MWCNTs

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Table2

ValuesoftheelasticconstantC11andbulkmodulusKforthepristinePEEKmatrixasderivedfromunidirectionalcompression/tensionandhydrostaticcompression/tension

simulations,respectively.Allsimulationswererunintriplicate.ExperimentaldatarangeforKvalueis5.475–5.749[46,47].

Simulationmethod C11(GPa) Simulationmethod K(GPa)

Unidirectionalcompression 7.509±0.481 Hydrostaticcompression 5.656±0.193

Unidirectionaltension 7.227±0.345 Hydrostatictension 5.428±0.229

AscanbeseeninFig.3B,thepredictedglasstransition temper-atureofthethermoplasticPEEK(Tg,sim(PEEK)=414±18K,Tg,exp

(PEEK)=416K) is unaffected by the MWCNT dispersion up to nanoﬁllerweightfractionof15%,inagreementwithexperimental observations[41–43].Thesedatahighlightaﬁrst,important dif-ferencebetweenthecurrentlyemployedthermosettingpolymeric matricesandthethermoplasticPEEK.In fact,inthermoset(e.g., epoxy)polymersTg isseentoincreasewithincreasingMWCNT

concentration[44,45].Thisoppositebehaviorismainlyascribable totheformationofpartialcovalentbondingphenomenabetween thecrosslinkingpolymerandthefunctionalgroupspopulatingthe surfaceofthecarbonnanotubes.Ultimately,thisevidencesupports thenotionthatlittle(ifany)chemicalinteractionsdevelopbetween thethermoplasticPEEKmatrixandthedispersedMWCNTs,their mutualinterfacebeingdominatedalmostexclusivelybyvander Waalsforces.

3.2. Predictionofstress-strainbehaviorforPEEK/MWCNTs nanocompositesystems

Thelinearelasticstress-strainrelationsforthepurePEEKmatrix arereportedinTable2.

TheresultsinTable2allowfor someconsiderations.Firstof all,thesimulatedvaluesofthebulkmodulusKnicelyfallinthe rangeofavailableexperimentaldataforpurePEEKmaterial[46,47]. Next,bothKandC11valuesderivedfromcompressionmethods

areslightlyhigherthanthoseobtainedwiththealternative, ten-siontests.Tofurthercheckthevalidityoftheresultspresented inTable2,thecorrespondingvaluesoftheYoungmodulusEand thePoisson’s ratio␯ have been calculated viaEqs. (5) and (6). Accordingly,usingtheC11andKvaluesobtainedfrom

compres-siontests(7.509GPaand5.656GPa,Table2),themagnitudesofE and␯are3.869GPaand0.386,respectively;concomitantly,those obtainedusingC11andKvaluesderivedfromtensionsimulations

(7.227GPaand5.428GPa,Table2)areequalto3.745GPaand0.385 forEand␯,respectively.BothsetsofEand␯valuesareagainin excellentagreementwiththecorrespondingliteraturerange val-uesof3.76−3.95GPaforEand0.3779–0.3931for␯[46,47].Overall, theseresultsconﬁrmthatanicecorrelationexistsbetween val-uesobtainedfromunidirectionalandhydrostaticsimulations,and thatbothcomputationalproceduresyieldmechanicalmoduliin linewithexperimentaldata.Additionally,despiteanappliedstrain of0.5%, whichis relativelyhighifcompared withstrain values adoptedinrealexperiments,thebehaviorofPEEKstillfallswithin thelinearelasticregime.

Considering the same PEEK-MWCNT composite systems for whichtheglass transitiontemperaturehasbeendeterminedin Section 3.1, compared with pure PEEK a progressive addition of MWCNTs results in a corresponding increase of the elastic propertiesinbothtype(i.e.,unidirectionalandhydrostatic)of sim-ulations.Speciﬁcally,theaveragevalueoftheelasticconstantC11

(C11=7.368GPa,asobtainedbyaveragingthetwo C11 valuesin

Table2)increasesfromthatofthepristinePEEKmatrixby approx-imately0.4,14,36,62,and146%withtheadditionof3,6,9,12,and 15%byweightofMWCNTs(seeTable2),whiletheaveragevalueof thebulkmodulus ¯_{K (=5.542}GPa,Table2)growsapproximatelyby 10,24,46,64,and132%withthesameamountofaddednanoﬁller, asseenfromTable3.

Table3

Values oftheaverageelastic constantC11, averagebulkmodulus K¯, average

Poissonmodulus¯ andaverageYoungmodulusE¯forthepristinePEEKmatrix

andPEEK/MWCNTsnanocompositesasafunctionofthenanoﬁllerconcentration

asderivedfrom unidirectional compression/tensionand hydrostatic

compres-sion/tensionsimulations,respectively.Allsimulationswererunintriplicate.

MWCNTs(wt%) C11 (GPa) K¯ (GPa) ¯(−) E¯(GPa)

0 7.368±0.592 5.542±0.299 0.386 3.807 3 7.393±0.477 5.872±0.288 0.379 4.263 6 8.426±0.501 6.079±0.273 0.368 4.815 9 10.02±0.599 7.283±0.256 0.371 5.637 12 11.96±0.548 8.892±0.301 0.381 6.349 15 18.14±0.621 13.85±0.354 0.392 8.972

ThelasttwocolumnsofTable3listthevaluesoftheaverage

Youngmodulus ¯E andoftheaveragePoissonratio¯,calculated insertingthecorrespondingvaluesofC11and ¯KinEqs.(5)and(6).

Aswesee, ¯E alsoincreasesbyincreasingMWCNTconcentration inthenanocomposite,reachinganimprovementofnearly136%at 15%wtwithrespecttothepurepolymericmatrix.Acomparison withavailableexperimentaldatarevealsanexcellentagreement betweensimulatedandmeasuredvaluesof ¯E [42],asshownin Fig.4A.

Finally,thechangeofPoisson’sratioasafunctionoftheMWCNT weightfractionisshowninFig.4B,fromwhichwecannoticethat thereisnospeciﬁctrendfortherelationbetweenthePoisson’sratio andtheconcentrationofthenanoﬁllers.

3.3. InterfacebehaviorinPEEK/MWCNTsnanocompositesystems Inpolymer-basednanocomposites,interfacesplaya determi-nant role in loadtransfer mechanisms between the polymeric matrixchainsandthedispersednanoparticles.Inorderto inves-tigatethesephenomenainPEEK/MWCNTbasednanocomposites, boththenormalandsheardisplacementattheinterfacebetweena MWCNTandPEEKchainsweresimulateduponstrainapplication. Asmentionedin Section2.2.5,displacingtheMWCNTina nor-maldirectionyieldsinformationonthecohesiveforcesbetween thenanofillerandthepolymer,whileshear displacement mim-icsarealpulloutexperiment.Byconductingmoleculardynamics experimentsunder controlleddisplacement,thesystems devel-opsareactionforceatthepolymer/MWCNTinterfacebyvirtueof underlyingnon-bondedinteractions,whichvariesasthenanofiller driftsawayfromthepolymericmatrix.Fig.5Ashowsthebehavior ofthecohesiveforceFcohatthepolymer/nanofillerinterfaceasthe

MWCNTisdisplacedawayfromthePEEKchainsalongthenormal direction.

Asseenfromthegraph,theinitialbehaviorof Fcoh islinear,

thenitreachesapeakandﬁnallyslowlydeclines.Thevalueofthe maximumintheF_coh/displacementcurveisestimatedtobeequal to1131pNatthecorrespondingdisplacementof0.0019nm.The correspondingproﬁleofthepulloutforceFpovs.displacementis

reportedinFig.5B:themaximumvalueofFpolocatesata

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Scheme1.Replacementofagivenmaterial(red)withanewone(green)foraspeciﬁcapplicationrequirestheconcerteddetermination/optimizationofseveralkey

performanceindicators(KPIs),includingmaterialproperties,materialprocessconditions,overallcosts,lifecycleassessment,andmaterialandprocesssustainability.(For

interpretationofthereferencestocolourinthisﬁgurelegend,thereaderisreferredtothewebversionofthisarticle.)

Fig.4. (A)ComparisonbetweentheaveragevalueoftheYoungmodulusE¯,

calcu-latedusingdatainTable2(patternedbars),andthecorrespondingexperimental

measureddata(ﬁlledbars)forpurePEEKandPEEK/MWCNTnanocompositesasa

functionofMWCNTconcentration(%wt).Experimentaldatafrom[38].(B)

Aver-agePoisson’sratio¯values,calculatedusingdatainTable2forpurePEEKand

PEEK/MWCNTnanocompositesasafunctionofMWCNTconcentration(%wt).

3.4. ViscoelasticpropertiesofPEEK/MWCNTsnanocomposite systems

In silico dynamic frequency sweep tests were performed to investigatetheviscoelasticpropertiesofneatPEEKanditsMWCNT

Fig.5.(A)Fcohand(B)FpoasfunctionofdisplacementforaPEEK/MWCNT

nanocom-positesystem.

nanocomposite systems. The results of these simulations are reportedinFig.6.

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Fig.6.Predictedvaluesof(A)StoragemodulusG’(␻)and(B)lossmodulusG”(␻)

ofPEEK/MWCNTnanocompositesystemsasafunctionoftheMWCNTcontent

(%wt).Symbollegend:circles,purePEEK;squares,3%;triangles,6%;diamonds;9%;

hexagons,12%;invertedtriangles,15%.Correspondingerrorbarsarealsodisplayed

forallcases(inmanyinstances,theerrorsaretoosmalltobevisible).

characterizedbyslopevaluesof2and1,respectively[40]. Nonethe-less,polymermatricesfilledwithnanoparticlesoftendeviatesfrom thisidealbehavior.FromFig.6weseethatthesimulateddatafor thepristinePEEKmatrixindeedfollowthelinearviscoelastic scal-inglaws.Yet,forMWCNTcontentof3%wtonwardthisterminal behaviordisappears,andbothmodulitendtowardaplateau-like regime, indicative of a transition from liquid-like to solid-like behavior.Accordingtothesedata,aMWCNTconcentrationof3% wtcanconstitutetheso-calledrheologicalpercolationthreshold, i.e.,theconcentrationatwhichacontinuous,three-dimensional networkofnanotubesoriginates.Abovethisthreshold,filler–filler interactionsprevailoverpolymer-fillerinteractions,anda3Dfiller networkisfullyestablished.Thesedataareinagreementwiththe experimentalevidenceprovidedforPEEK/MWCNT nanocompos-itesinaconcentrationrangeencompassingthevaluesconsidered inthiswork[48].Forsuchrealsystems,thebehaviorofG’(␻)and G”(␻)isinexcellentqualitativeagreementwiththesimulateddata reportedinFig.6;thepercolationthresholdinthatcasewasfound tobeequalto1%wt,againingoodagreementwiththeone pre-dictedbythepresentDPDsimulations.

4. Outlook

Inparallel,highperformancematerialsdesignnotonlyrequires comprehensivematerialpropertiesmodelingbutalso understand-ing of risks, costs, and business opportunities for a range of decisions,frommaterialselectiontodesigningfunctional struc-turalcomponentsandsystemsandprocessoptimization.Lastbut

notleast,designandselectionofnanocompositesmustalso accom-modatesocietalrequirementsfor health and sustainability(see Scheme1).

TheultimateobjectiveoftheprojectCOMPOSELECTOR,started January2017andfundedbytheEuropeanCommissionwithinthe Horizon2020(H2020)Program(undertheCallNMBP-23-2016− Advancingtheintegrationofmaterialsmodelinginbusinessprocesses toenhanceeffectiveindustrialdecisionmakingandincrease compet-itiveness),istoaddressalltheseaspectsbydevelopingandtesting anintegratedsoftwareplatform−basedonamulti-disciplinary, multi-modelandmulti-fieldapproach−fordecision-makinginthe selection,designandfabricationofPNCmaterials.Oneofthemost innovativeandambitiousfeaturesofCOMPOSELECTORisthe estab-lishmentofanewparadigminPNCsselectionaccordingtowhich thecornerstoneofsuccessfulnew,high-performance nanocompos-itematerialsforadvancedapplicationsistheidentificationofall concurrentmaterial-selectingfactorsalongtheentirevaluechain. Inparticular,theadoptionofanapproachthatadvocatestheheavy useofcomputationalmaterialsscienceand physicsratherthan, e.g.,propertycross-plotswhich,albeitcommonlyused,leadtoless competitiveproducts,isthekeyfactortoreachCOMPOSELECTOR finalgoals.

The available setof composite materials and related manu-facturing processes is growingin number and type. Therefore, fornanocompositematerialsdesignersandmanufacturers under-standing and evaluating multiple materials and processing scenarios intheearlystages of productselection/designare no longeranoption.Informationgainedduringtheconceptualphase createsaproductknowledgefoundationforimproved decision-making,therebyincreasingthepotentialofinnovationwithinnew materialandstructureconcepts,assketchedinScheme2.

Inthisscenario,theEuropeanCommission,withintheH2020 Framework Programme, has dedicated substantial economical effortstofosterresearchprojectsaimingatadvancingthe inte-gration ofmaterialmolecularsimulationsin industrialbusiness decisionprocesses.Inparticular,theEUfullyrecognizestheneed foraBusinessDecisionSupportSystem(BDSS)thatsupportsthe selectionoftheoptimalmaterialandprocesstakingintoaccount theimplementationcostsbutalsotheassociatedrisks, uncertain-tiesandcostsrelatedtothemodelingandsimulation;apriority, especiallyforsmallmediumenterprises(SMEs).SuchaBDSSshould enabletheintegrationofmaterialsmodelingandbusinesstools anddatabasesintoa singlework-flow,allowingforflexibilityof application todifferentindustrial sectors. Specifically,it should bebasedona frameworkthatallows theflexible integrationof existingorfuturediscreteandcontinuummaterialsmodelswith structuredandunstructureddatafrommultipledatabases con-tainingmaterialsdata,commercialdataandinformationonmarket trends,pricing,customerneedsanddemands. TheBDSSshould theni)enableamulti-criteriaoptimizationoverallstagesof prod-uctdevelopmentbyallowingtheend-usertomirrortheoperational frameworkoftheircompany,ii)bestructuredinsuchawaytoallow back-engineeringfromtheend-goal,andiii)bedesignedsuchasto optimizetheintegrationofhumansinnewmorecomplexindustrial environments.TheresultsyieldedbytheBDSSshouldultimately bevalidatedagainstmeasurements,existingdataandrealfinancial arguments.

5. Conclusions

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Scheme2.ImplementationviewoftheintegratedCOMPOSELECTORbusiness-decisionsupportsystem(BDSS).TheBDSSgathersinformationalongtheentireprocessto

generateuserinformeddecisions.

usedintwomodes:i)thediscoverymode,inwhichnewphenomena arepredictedthathavenotyetbeenobservedexperimentally,or explanationsaresoughtforknownphenomenathatarenot under-stood,andii) thedatamode, whichsubstantially consist inthe accuratepredictionofmaterialspropertiesrelyingonlittleorno experimentalinformation.Theformerwayofperforming molecu-larsimulationshasbeneﬁttedseveralindustrialsectors,including theaerospaceandnuclearpowerindustries.Thealternativemode hasanalreadyestablishedreturnoninvestmentinindustry.The perhapsmostwidelyquotedexampleisthatmeasuringtheheat offormationforasinglemoleculecost$100,000 in2000,about 50times thecost ofan accuratequantumchemical calculation [2]. Nonetheless,asmentioned intheintroduction,the integra-tionofmodelingandsimulationstechniquestosupportmaterial selectionprocessesremainsoneofthemostcompellingneedsin advancingmaterialindustryandmanufactory,duetothenecessity ofeffective/efﬁcientdesignandproductionofsophisticated materi-als,componentsandsystemswithadvanced/extremeperformance onacompetitivetimescale.Andthisisparticularlytrueinthecase ofthedesignandoptimizationofhighperformancepolymer-based nanocompositesforadvancedapplications.

Accordingly,inthispaperwepositionedourselvesinthe Mate-riallayeroftheCOMPOSELECTORBDSS(Scheme2),anddeveloped aseriesofmolecularsimulationrecipesforthefastandreliable predictionofsomepolymernanocompositekeyperformance prop-erties(KPIs)intheaerospaceindustry,namelytheglasstransition temperature,Tg,themechanicalmoduli(K,E,C11),theinterface

forcesFcohandFpo,andtheviscoelasticpropertiesG’(␻)andG”(␻)

asa functionof theaddednanoﬁller concentration.Theresults ofsuchpredictions,validatedagainstavailableexperimentaldata, willbefedbothtoaMaterialData Baseand,mostimportantly,

tothebusinesslayerwheretheyconcur,togetherwithallother relevantrequiredinformation(e.g.,processparameters,costs, sus-tainability,etc.),togenerateuserinformeddecisions.

Speciﬁcally,inthisworkweestimatedthesepropertiesfora high-valuepolymer,PEEK,andtherelevantMWCNTcomposites. Atomistic-basedsimulations wereemployedtopredicttheﬁrst threesetsofKPIs,whereasamultiscaleapproach,involvingboth atomisticandmesoscalecalculations,wasadoptedtoinvestigate theviscoelasticbehavior ofthesematerials.Thedirect compar-isonofcomputer-basedpredictionswithavailableexperimental data,whereavailable,hasrevealedagoodtoexcellentagreement, therebyvalidatingtheseinsilicoexperimentsandenablingthem tobeincludedasatooltosupportbusinessdecision processin thedevelopmentoffurther,newpolymer-basednanocomposite materials.

Acknowledgment

ThisprojecthasreceivedfundingfromtheEuropeanUnion’s Horizon 2020 research and innovation programme under the GrantAgreementNo.721105(Projectacronym:COMPOSELECTOR; projectidentiﬁer:NMBP-23-2016–Advancingtheintegrationof Materials Modellingin Business Processes toenhance effective industrialdecisionmakingandincreasecompetitiveness).

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ErikLaurini is assistant professorin tenure-trackof

Chemical Engineering, Molecular Simulations at the

University ofTrieste, Italy.The main research

activi-tiesare focusedon(i) computer-assisteddrugdesign

anddevelopmentfortargeted therapiesand

personal-izedmedicine,(ii)study,correlationandpredictionof

thestructure/propertyrelationshipsforviralproperties,

oncogenes,onco-suppressors,andpathologicallymutant

proteins,(iii)molecularmodelingofnanostructuredand

nanomaterialsformaterialscience.Dr.ErikLauriniisthe

authorofmorethan75scientiﬁcpublicationsonISIpeer

reviewedinternationaljournalsandover60conference

proceedingsintheﬁeldofmolecularmodelingand

com-putersimulationofcomplexsystems.

DomenicoMarsonisapost-docresearcheratthe

Molec-ularSimulationEngineeringlaboratory(Mose-Lab)ofthe

UniversityofTrieste.Degree(honors)inPharmaceutical

Chemistry(2011)andPhDinNanotechnology(2015)at

theUniversityofTriesteinMultiscaleMolecular

Model-ingofDendrimersandBiomacromolecules.Dr.Marsonis

focusedonthedevelopmentofmultiscalemolecular

mod-elingtechniquesasatoolforinsilicodesignandanalysis

ofnanostructuredmaterials.Hisresearchisparticularly

centeredonthemultiscalemodelingofnanostructured

complexbio/nonbiosystems.Heistheauthorofmore

than30scientiﬁcpublications,bookchaptersand

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MaurizioFermeglia isfullprofessoratthe

Engineer-ingFacultyoftheUniversityofTrieste,whereheholds

thecourseinChemicalandBiochemicalReaction

Engi-neeringandDataBaseDesign.From2006–2012hewas

appointedasheadoftheDepartmentofIndustrial

Engi-neering&Informationand,from2010to2012heservedas

presidentoftheResearchboardoftheUniversityof

Tri-este.Atpresent,heistherectorofUniversityofTrieste.

Professor Fermegliaresearchinterestsare focusedon:

multiscalemodelingformaterialsdesignandlifescience,

phaseequilibriumandappliedthermodynamics,process

simulation,molecularsimulation,nanotechnology,and

nanomedicine.Prof.MaurizioFermegliahaspublished

210peerreviewedjournalarticlesandbookchaptersandhasgivenmorethan180

conferencepresentationsasinvitedplenary,keynote,andoralcommunications.He

alsogivesinvitedlecturesseminarsatnumerouscompaniesandacademic

insti-tutionsandorganizedseveralworkshopsontopicsrelatedtoprocessengineering,

nanotechnologyandmultiscalemodeling.

Sabrina PriclisassociateprofessorofChemical

Engi-neering,MolecularSimulations,andMolecularSimulation

TechniquesforthePharmaceuticalSciencesatthe

Uni-versity of Trieste,Italy.She isalso a memberofthe

ScientiﬁcBoardofthePhDSchoolinNanotechnology

oftheUniversityofTrieste.She isPrincipal

Investiga-tor(PI)andco-PIofseveralnationalandinternational

projectsintheﬁeldofnano-biotechnology(e.g.AIRC,

EU-Horizon2020,Era-NET,...).Sheregularlyholdscourses

andseminarsatnationalandinternationalUniversities

andScientiﬁcInstitutionsandconferencesontopicsas

biomacromolecularstructureandproperties,

thermody-namicsandmolecularmodelingandsimulation.Themain

researchactivitiesarefocusedon(i)computer-assisteddrugdesignand

develop-mentfortargetedtherapiesandpersonalizedmedicine,(ii)study,correlationand

predictionofthestructure/propertyrelationshipsforviralproperties,oncogenes,

onco-suppressors,andpathologicallymutantproteins,(iii)multiscalemodelingfor

advancedmaterialsdesign.Sheistheauthorof230scientiﬁcpublicationsonISI

peer-reviewedinternationaljournalsandover250conferenceproceedingsinthe