www.nature.com/scientificreports OPEN Received: 25 May 2017 Accepted: 3 July 2017 Published: xx xx xxxx Determination of critical cooling rates in metallic glass forming alloy libraries through laser spike annealing Punnathat Bordeenithikasem1, Jingbei Liu1, Sebastian A. Kube1,Yanglin Li1, Tianxing Ma2, B. Ellen Scanley3, Christine C. Broadbridge3, Joost J. Vlassak4, Jonathan P. Singer   2 & Jan Schroers1 The glass forming ability (GFA) of metallic glasses (MGs) is quantified by the critical cooling rate (RC). Despite its key role in MG research, experimental challenges have limited measured RC to a minute fraction of known glass formers. We present a combinatorial approach to directly measure RC for large compositional ranges. This is realized through the use of compositionally-graded alloy libraries, which were photo-thermally heated by scanning laser spike annealing of an absorbing layer, then melted and cooled at various rates. Coupled with X-ray diffraction mapping, GFA is determined from direct RC measurements. We exemplify this technique for the Au-Cu-Si system, where we identify Au56Cu27Si17 as the alloy with the highest GFA. In general, this method enables measurements of RC over large compositional areas, which is powerful for materials discovery and, when correlating with chemistry and other properties, for a deeper understanding of MG formation. The glass forming minimum cooling ability (GFA) rate required is to most avoid directly quantified by the inverse crystallization upon solidification orfestuhleticnrgitiincavlictroiofilciantgiornatient(oRCa)f,utlhlye Eadog1m0ldevav4esso Ke.nsrlT opms(hM−phio1mos.GruiTees)snhidmfsteoutraapreentmafedtoc.oirtpnDfecurg,heolassavwpymlildoiseteteuenetlighmidnteossssbdi1segi–int6hgto.hnteTdeixinhfipairtecbeeoaricmnltitihmlctayyeejeo,mtmnorRtieeCatmacylhshleyuoaaarfsmnseuRoiesRrnCtaeCilscqyRuwuoCbroarieoninuegvgtlnideinfRridsbcClieaoa,rrtfepbigcgooaetlnrtlachtyssioscmshmucfaoeilpvearaoenrmslstuybiiatrfetfiieiooecodannrnlfglre.oylasrantasiangsmedmfsaotitraenemscduhiettunerwsosfiorlwnoauggicltdithicinoaeRdnlnlCiyhroeeapfxncomctcweemeeetadraelfitllnulohilgyc-. Strategies to effectively consider large numbers of alloys are based on combinatorial synthesis paired with high-throughput characterization of properties. Such combinatorial strategies, well established in pharmaceuti- cal research7, are relatively new in materials science and particularly MG research. First combinatorial methods applied in MG research include measurements of mechanical properties8–11, thermophysical properties12–14, func- tional properties15–17, thermoplastic formability18, and microstructure evolution11,12,19–21. Attempts were made to draw conclusions about GFA from some of those measurements10,12,18,21. More recently approaches to measure GFA directly have been limited in cooling rate, in alloy composition, and generally in versatility21–24. posIintiothnisspsatucdeyi,nwaetuersneaarcyosmysbteinma.toTrhiarol aupgphrionadcihretcotdlairseecrtslypimkeeaasnunreeaRliCnagc(rLoSsAs a),swigenmifieclatnatnfdraccotioolncoo-fstphuetcteormed- alloy libraries over a range a function of composition Au-Cu-Si system. of controlled cooling rates. Employing structural and chemical is determined and Au56Cu27Si17 was identified as the alloy with tchhearhaicgtheersizt aGtiFoAn,inRCthaes 1Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut, 06511, USA. 2Department of Mechanical and Aerospace Engineering, Rutgers University, Piscataway, New Jersey, 08854, USA. 3Department of Physics, Southern Connecticut State University, New Haven, Connecticut, 06515, USA. 4School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, 02138, USA. Correspondence and requests for materials should be addressed to J.S. (email: jan.schroers@yale.edu) Scientific Reports | 7: 7155 | DOI:10.1038/s41598-017-07719-2 1 www.nature.com/scientificreports/ Figure 1.  laser with Schematic of the experimental a 60 W continuous wave (CW) mseatuxpimfourmRCoumtpeuast,uorepmereantitnsgviaat laawsearvsepleiknegathnnoefa1l0in.6g μ. Wm.eCuosemapCatOib2le with this wavelength, intrinsic (undoped) Si, which has low absorption at 10.6 μm32,51, is selected as the heat sink material. For the photo-thermal absorbing layer, we use 30 nm tungsten (W)52, which is electrically insulated sweittuhp3i0s nmmouSni3tNed4 to prevent reflective thick film behavior53 from the ~1 μm Au-Cu-Si ternary onto a fixture with adjustable height (z) for laser focus while the laser optics alloy library. This are motorized on two axes (x and y) such that the laser can be delivered to the substrate at known positions and scan speeds. Altering the laser scan speed, in XRD, OM, and EDS mapping. this case vx, varies the temperature profile. The samples are characterized using Results Experimental setup library must be melted for and RcoComleedainsuarceomnternoltlsedusminangnlears. eUrshinegaLtSinAga.s  a ThoeamtienagsumreetRhCo,dthpersoyvnidtheessliozecdalaizlleody, concentrated heat flux with precise control over the heating and cooling profile25–28, which is ideal for combinato- rial studies. However, directly exposing the laser onto an alloy film library can produce inconsistent temperature profiles. This is due to the composition-dependence of the absorption coefficient, which can vary significantly in a ternary system29,30. To avoid associated uncertainty in temperature and cooling rates, the alloy library is heated indirectly (Fig. 1). We realize this by co-sputtering the alloy library onto a substrate that is designed specifically for photo-thermal heating (see Methods). Such a substrate consists of a heat sink that is optically transparent to the laser and a photo-thermal absorbing layer. When the laser impinges on the substrate side, the radiation is transmitted through the heat sink and then absorbed by the absorbing layer, consequently heating the alloy via conduction. Tuning the incident laser heat flux via the laser scan speed determines the temperature profile, hence the cooling rate, experienced by the alloy. Determination of cooling rates.  To demonstrate the proposed method, we first chose a film of constant dTcooifmfvraparcoytsiitothinoen(teXAmRupD5e5)Cramutu2e5raSesi2up0rr(oeFmfiiglee.ns 2,t)ts3h,1e.uItltaislsicezorinmtrgapanosbsliaettiaoimonnmwalaasssckvaencrosifpmieemdedbe(nyvsexunirnearFtgeiygt.od 1its)hpweearhsseisvayetsXatef-fmreacaytteiscdpaezllcoytnrcoehsascniozgepey(d2(. EXmD-mrSa))y,. and optical microscopy (OM) were then carried out ex-situ (Fig. 2). For the slowest scan speed of 0.2 cm s−1, large dendrites are observed (Fig. 2b) indicating melting and slow crystallization during cooling. XRD results reveal that with increasing laser scan speed, the amount of crystallinity and crystal size decreases. To quantify the cooling rates for a given laser scan speed and power, simulations of the LSA process were conducted over the range of scan speeds where melting was visually observed and XRD measurements (Fig. 2a) on the remelted region indicated a transition from crystalline to amorphous. These simulations assumed a Gaussian-shaped heat source (see Methods). The laser power and peak width were determined by fitting the heat affected zone size, measured from OM images at different scan speeds (Fig. 2b–f), to produce the most representative simulations. The cooling rates could be extracted from the simulated temperature profiles of a mtOphauuerrtlctisocipiuomllleaiunrAlgaputori-aoiCntneutsa-arStleoitv-nhbegeaaltnshaeoedmselMaotsneeGmor tcspochenaernimactliuiinnsrtceerri((eeFTasisN,geoT.s o2eN)fgoost)eh.fiTetshhcaeeopotcpilomrinooelgxi-nirtmegamtaretapewteelyirtfahr0to.ut8mhreeti-tmlhtaresaeetnsrestmsfhoceparemnlirqsaaputtuieiodreneudps((TrFtoeTifgmiT.l ep2) getdhriiaanattgsuderratee)mf,i(nw.TeAhLs)icR5cr,h6Co,3sii1sss. coupled with the maximum temperature (Fig. 2g). Hence, only scan speeds that result in maximum temperatures Scientific Reports | 7: 7155 | DOI:10.1038/s41598-017-07719-2 2 www.nature.com/scientificreports/ Figure 2.  Determination of cooling rates at different laser scan speeds. (a) XRD diffractograms measured from iAnuc5r5eCause2s5S, iin20dfiiclmatsinmgeflatsetderucsoinoglinmgurltaitpelsewlaistherfascstaenr speeds. With higher scan speeds, the amorphous fraction scan speeds. (b–f) OM images, with a high magnification i2n5s μemt, oifntthheeAinus5e5Ctsu. 2F5oSri2l0afsielmr sscuarnfascpeeeadssaefxucnecetdioinngo9f.v2a crmio su−s1l,atsheer scan speeds. Scale bars are 250 μm features are not clearly resolved by and OM. The heat affected zone size is measured from the extent over which the microstructural features are observed in the direction perpendicular to the laser scan. (g) Simulated temperature profiles of laser heating experiments at variable scan speeds. The simulation was fitted with experimental values of the measured heat affected zone 0si.z8eT.LT.hTehTe Linwsaets taken from measured values shows the calculated cooling oraftbeualtk0s.a8mTLpalessaoffuAnuct5i5oCnu2o5fSlia20s3e1rasncdanTsNposeeewda. s approximated to be aexscceaendsinpgeeTdLoafr9e.c2o cnmsi sd−e1r.ed. The RC of Au55Cu25Si20 MG is 3.4 × 104 K s−1, as determined from the simulation for It should be noted that the simulations do not consider the temperature-dependence of the absorption coeffi- cient of Si, and therefore can be expected to slightly overestimate the cooling rate. These deviations are relatively low for relevant temperatures, as the optical absorption of Si32 is four orders of magnitude lower than that of W33 at TTLoofenAsuu5r5Ce uth25aSti2t0h(e6m54e Kas)u31r.ed outline of the heat affected zone RreCsrueltfliencgtsfrtohme iLnStrAin, saicsobleidh-alviqiouridofinthteerfaallcoeye, xoinstes.hHasetroe,ctohnesuidnemr ethltaetdastotlhide could act as a nucleation site during solidification of the melted measurements away from the interface can be concluded by the alloy. Whether or not size of the solidifying this situation affects grains, which has to RbCe comparable to the melted zone size in order to significantly influence the observed is only present at very slow cooling rates (Fig. 2b), much lower than the intrinsic RRCC.(FHiegn. 2cbe,–wf )e. This can situation conclude Scientific Reports | 7: 7155 | DOI:10.1038/s41598-017-07719-2 3 www.nature.com/scientificreports/ nFaigvuyrbelu3e. cCirocmlespodseiptiioctni-ndgespteantedsewntitRhCd.eGteibctbasbtlreiacnrygsletaslwlinitehprhedasceisrcolfe(sad)eapsi-cstpinutgtethreedfufilllmy sa,mwohripchhoeuxspsetraiteenacnedd a cooling rate of 1010 K s−1, and films that have been laser-treated with scan speeds of (b) 11.5 cm s−1, (c) 9.2 cm s−1, and (d) 6.9 cm s−1. regions are approximately (b) Based on temperature profile simulations 5.5 × 104 K s−1, (c) 3.4 × 104 K s−1, and (d) (1F.7ig ×. 2 1g0)4, Kth se−R1.C(feo)rBtyhecoammpoirlpinhgouthse mapped out regions of the amorphous phase as a consequence of multiple laser scan speeds (a–d), contours corfyRsCtaallsizaefdu,necvteionnuopfocnosmpuptotseirtiinogn. can be plotted. The black The symbols indicate the region represents considered compositions that composition with the highest measured GFA, reported ternary MG compositions with high GFA21,31 and dotted lines indicating a range, reported binary MG compositions36,37, the global eutectic composition34, and the composition with the lowest nucleation temperature12. The compositions in all the Gibbs triangles (a–e) are in at.%. that the measured innate property. RC is independent of the heterogeneous nucleation of from the solid-liquid interface, and is an GFA large as a function of composition.  compositional regions. To realize such The ultimate goal of the developed compositional regions, we fabricate mcoemthpoodsiitsiotonadleltiberrmariiensebRyCcoovmer- binatorial co-sputtering from three sputtering guns in a tetrahedral arrangement16,20. Using this method we cover a composition range where Au varies from 32 to 93 at.%, Cu from 5 to 55 at.%, and Si from 1 to 39 at.%. Using EDS and XRD mapping, the composition and structure, respectively, as a function of position on the wafer is deter- mined (Fig. 3). As-sputtered, the entire alloy library experienced a cooling rate of ~1010 K s−1. This is summarized in the Gibbs triangle indicating amorphous and crystalline regions (Fig. 3a). The as-sputtered state represents the fastest cooling rate in this investigation. LscSaAnInospof retdheedersattlolhoadytelwtieberrrmaeriuineseseR(dFCtiogfo.d r3etbth–eerdma)l.lioTnyheseRwcCoitoohflipAnougt5er5naCttueias2l5lnSyei2ta0hr(eTFhiNgiog.s he2et)hsotafGt6tFh.9Ae, in the Au-Cu-Si system, similar laser 9.2, and 11.5 cm s−1 were applied for amorphous regions were exposed to Scientific Reports | 7: 7155 | DOI:10.1038/s41598-017-07719-2 4 www.nature.com/scientificreports/ Figure 4.  Comparison of composition-dependent GFA obtained from direct measurements with indirect GFA pcaasrtaimngetinertso(aam) CooldntwoiuthrsionffiRnCiteasthaefrumncatlimonasosfacnodmtphoesrimtioanl c. o(bn)dTuhcteivmiteya, si.uer.eodnRlyCtihsectohnevremrtaeldptroopdeCrbtiaesseodfothne mtceesartelinolmtrawiramyteeerldietqr4cu1yo3bid1nyu(sfcisidarpelscrtruoecdljaae3ltcc9i.tuoiGonlanitdvi3ene4.ntga(dRitlh)sCeAdineipslaKpcsultyssii−csne1mg,dtaohinndeuecdfalCfipi4ic2tn,ii4eo3mnnatneoctdfelurScssuatilpesirbpe-rlpqeaaumticaneklgnitnotwagritsyht0Rr.F0auCi1gck.t.n (u1cor))aw, TlwnmrghT =oilgde TtehTgla/LfTtowwLrawmassheedextreatertlleaiTrccmgtgewlidanasfessrdeosmb4y5,the 100% efficiently packed lines for region of interest. Indicated as a various red line iu,tost>trusctrtuurcetu, wrehsiwcheries calculated for the recommended by composition the authors of the model45 for the Au-Cu-Si system. are 1.7 × 104 K s−1, 3.4 × 104 K s−1, and 5.5 × 104 K s−1, respectively. For a scan speed of 11.5 cm s−1, the amorphous region shrank significantly in comparison to the one for the as-sputtered data. For example, the maximum of Au variation over which the library remains amorphous reduces from 39 to 66 at.% to 42 to 60 at.%. When the scan speed is further decreased to 9.2 cm s−1, the amorphous region narrows further such that only the best glass formers in the compositional space vitrify upon solidification. Here the range in Au content is only 48 to 56 at.%. Vitrified alloys from the 6.9 cm s−1, all considered 9.2 cm s−1 scan speed alloys crystallize. have RC values comparable to Au55Cu25Si20. For a scan speed of a0rel.l8souTAylL.tc,OfrrRonoCsmcsiesmttphhuleeolttcsitploeolrdewrealeassspstaeolrafnussdecniracnnstgicosaspninmeoesupfdlcesa,oetRdmioCinpscod(asFneiittgbeio.re nm2cg(ai)Fnl.cieTugdsLl,a 3ittsheeedeaxnnftrrudoamm4ctaee)trd.hicefarslolvomawltuehseetoltafesRrenCraisrscyoapnbhtsaapisneeeedddiaaagps rptahlmieedc34o.tooAlvisnittghrirefayftietnhaaetl Scientific Reports | 7: 7155 | DOI:10.1038/s41598-017-07719-2 5 www.nature.com/scientificreports/ Discussion The GFA for a large compositional space was directly determined using XRD and EDS mapping of alloy librar- ies heated with lasers at multiple scan speeds (Figs 3e and 4a). Upon sputtering, the composition range of Au between 39 to 66 at.%, Cu between 13 to 41 at.%, and Si 16 to 35 at.% forms the amorphous phase. The region of tpAhruee4v8hiCoiguuh2s8elSysit2r4Ge.pTFoAhrits(eRrdeCGg ≤iFo A3n.4ca os×idn 1ec0tied4 rKems s,i−wn1ei)tdhspitnharnmosuafgrrgohimncsuAmoufbe5e6rCrrsouor2,m7wSeii1ta7h,naAdluonn5u5gCmtueh2re5oSaui2ps0p,twrrioahxli-icmahnaidtse-telhyrercoaorlnleosxytpawnerittiChmutehnleitnshe3i1g.uhTnehtsietl results are also consistent with the region of highest GFA determined by nanocalorimetry, which is the range betwFreoemn Aouu5r8Creus2u5Sltis1,7wanedcaAnud52rCauw29cSoi1n9c21l.usions about the change of GFA with composition. When the Cu con- 3ote.v4ne t×ri1s 10m0140a  KKin sst−−a11intwoehdaebbnoeutthwt e3e eS×ni 1c2o05n5 Ktcoe sn3−t01r aawtthi.%oenn, RiSsCi3ci1so anlett.se%snstoeirnnhsciirtgeihvaeseert.soOftrnhoemthSe1i 7clootwonc2Se9in satitrd.a%et,ioaGnnFd;ARthCderinnocpRrsCeaaibsnercusrpegatrlsayedsounraaclpleyidtfhlryeomtSoi tcchhoenanSteginectobdnyrcoaespnmstrbauetcilhoonwasd1se6icx areto.a%rsde.esFrfsorrooftmhme1am7gntooistt1u5edx aett.r.T%ehm.eTedhceiasgsrieme,eRpolCifecvshatarhinaagttiewosniftsrhoiinmn Ga3F2.4A a ×tw.% 1it0ch4o Kcmo smp−o1pstoiotsiiootnivoednri1affr0ee1r0em Knucsce−h, 1RlwaCrhcgaeennr than the variations recently reported for metal-metalloid glass formers35. However, it is conceivable that for the proposed method, particularly for this example system, some alloys crystallized rapidly even at ambient or sput- tering temperatures (~293 to 323 K). Hence, an alloy that vitrified upon sputtering may have crystallized prior to characterization and would be identified as crystalline upon sputtering. Obviously, this situation is more likely to otAocucv-uiStririigfnlyaauslspleoosyn3s6.swEpilvtahitdgqelunaecsnes ctfrhoarinnssguitc(i~ho1na0ts6e cKme nsp−ae1rr 3iao8)tu,iswrethhsee(rTfeaga)cstisntphtuahtteteAvruiecd7i5nS(i~it2y15307o1fa0 naKmd s−bA1iue)n8A1t.4utS-eiSm1i8.p6a3le6lrohayatsuvareerbesosidtuhecnhbteaifesinefdorreapbsoicnrratyersdy- talline. Hence, the composition-dependence of GFA, measured using the proposed method, should be carried out for Fig. 1). alloy regions where Tg is significantly larger than ambient temperature, arguably >340 K (Supplementary fullRy Camcaonrpbheocuosnvveiartqeudetnocthhiengc3r9i;tiacnalocfatesntinmgotrheicpkrnacetsisc(adl Cm),etahseurmea(xFiimg. u4mb).thFiocrkAneus-sCtuh-aStiaamlloaytesrwiaitlhcatnhebheimghaedset ppGroFosATpsiho(bResleeCadtvooaafpit3lepa.s4brto i×ltaih tc1yeh0vo4a aKfnlRdi sdC−iin1to)ydv, iotechrfaeitsneudsdCctihichsaaacttoalatlrhcrsgeuoreleafatGiensddFnAtouonttbheperarnte5aca4rer0yed μbewmnuitl,dekcedo(lydnrCasu ni≥ssget e1edn moatfnwmcdio)tphmMrropGevopis(doiBtreiMtoienndGssvi)g(aiFhlnuitgteihssn 3e3t1o.eATmauhn-oiCdstuic4vo-aeSn)sifmfisorymarsktgseelmtashsi.est fbaiprai(ccnoSeobrhaprpuiaroatnmrtrpBoivseitaepreoealadllytarllstd0eyeiwietld.omieed4acainstdna,gfesohi.ilirdnn.cnrtTaeahtuedtm.haTcahklibreantrn3neygelt4gry,riot.teFnesawhwwIdfilgn(eegoluniFoett.rvtc hyhin1eThagese)erGgdsh1,wi ed4acca3FgliovetoaeAaltiteamsnhonea4tssnt0rdinpshio.cmsdoiiHt2tmgnbrsei74ahonien TotanaweitGetdL)osd.ew,s.i%unFttvtTbliiAiheitomyrhS4heran2iea,can.,c4elratrMt3iogxeleekaotempmdeenohreuxvgpeif(prmponienFoienrmedisreocgcgmieatfoett.rrttie nrhuooy4odcrtiw3srcneoag1te)tl;lnahod.aGl(TrystHeTdbGiiFLpdndrseeAgwFeege rl=nAntroeaiteaned,ws hrTt(aTdeomeiRrgoSnigb/ecCineiTctwnla cu≤aea,Lteoaitsto)onde htns,1rficepesc0cvetTd,er5siaemrTco ntKlfgsiurrpttcomig oiressoomdra−msapsmetu41etailr4)leoitd.ptiiehdemcnBosvbdoe4sesaao1y,rilcTlrntriaauaTiqiegtsloeupuyusv~snaspariade1dstrnofloi.5auuutbncThm asenTtudheatscpgles.til%vtsretws,tipeaodoho,irhrajsntaseibnirhasccceytoteohthfbgiitfronraoiehoiocantsnenempoinansitocimrsntudhes3efwrupTn2atdnnhgon6htgrogesogwewittsieeprottkaiseesitistino3rihnneTgn7ncodnroTaa6twgbhiulrt LKfiinoyye.rs-- mGduoaFeleA,asds,unearosleptthdictooeGuianFgAschuiddcbeoestivwnainaicttithidioaetnlhsdseweaccisotrhlmeaaarpsgseoetseianietspiTo1rdn0g.es acOotl.ifv%nemeraaairnlxeli,Tpmtrhogu.esmAstirbteGltnehF.deAFshopdirgreeehtedxerairmcmSteiipndcleeobd,nytechTxeernpgctearorgaimrtmiepoeenonbsstr,iaottlihaloyden.lGyreFwgAiitohdnrtoohpfemiesxampxeiomrriemugmernaTtdar-gl A recently proposed model45, based on efficient cluster-packing, has also been tested against the experimen- tally determined composition dependence size differences such that packing clusters aorfeRsCim(Fuilgt.a 4nde)o.uInslysheoffritc,iethnetlmy poadcekleiddeanbtoifuietsecaocmh pcoonsisttioitnusenant deleamtomenitc. For ternary systems, the most efficiently packed structures form a line in the Gibbs triangle45. The lines of 100% efficiently packed structures were calculated for compositions in the vicinity of the w1gl3ha,se1sr-5ef>oZrim,stottriniusgcttrhuaernetgohetaa(sFl nibgue. me4ndb)se4ur5,g4o6g.feTasthtoeemdnstootparrteeiospenrneftsoeirnnitnthAdeiucf-aiCrtisunt-gsShcielgulllsaotsefsrapfocalrcumksitenerrgs4cs5et.rnTuthcetriuserdleinasbeisocn0e,, for the <10, 12, 15> structure and does indeed intersect with the center of the experimentally determined glass-forming range. Other structures, namely <10, 14, 16> and <10, 14, 17> coincide with the periphery of the experimentally determined glass-forming range. However, the line for the structure predicted by the efficient cluster-packing model, <10, 12, 14>, did not intersect with any glass formers. This comparison suggests that effi- cient cluster-packing model can assist in reducing the overall composition space, however this reduction is small. In order to evaluate the effectiveness, practicality, and speed of the proposed technique to experimentally measure GFA over large composition ranges, a comparison with the total number of potential bulk glass forming alloys has to be made. It has been estimated that the number of potential BMG forming alloys is on the order of 106 alloys out of 1012 unique alloys with two to five constituent elements47. Assuming a fabrication rate of 1000 alloys per day with the proposed method, it would still require over 2,700,000 years to synthesize and characterize the entire alloy space. This comparison suggests that prior to the combinatorial method, a significant reduction in the composition space is required to tackle the complex phenomena of glass formation and to identify many of the yet to be discovered MG and BMG alloys. Here, using theoretical predictions based on parameters that are known a priori to identify glass forming systems and reduce the composition space of interest will be powerful48. Scientific Reports | 7: 7155 | DOI:10.1038/s41598-017-07719-2 6 www.nature.com/scientificreports/ Subsequently these suggested composition ranges would be characterized with our proposed combinatorial method to identify MG and BMG formers. In a final step, a small number of selected alloys, which are suggested by the combinatorial method, would be fabricated in bulk form and characterized by using highly precise and established bulk characterization methods. Thus, the proposed method can be considered the missing link for effective MG discovery. Methods Sample Fabrication, Laser Heating, and Characterization.  The layered film structure is fabricated by confocal DC magnetron co-sputtering (AJA International ATC 2200) with elemental targets with purity exceed- ing 99.95%. The sputtering guns are arranged in a tetrahedral arrangement at a default angle of 29.8 degrees from the vertical. Prior to any sputtering step, a base pressure level of 10–6 Pa and a working pressure of 0.3 Pa of flowing ultra high purity (UHP) Ar is achieved. The substrates were 100 mm diameter, 500 μm thick, double-side polished, intrinsic Si wafers (UniversityWafer, Inc.). Firstly, 30 nm of W was sputtered at 70 W power. Then, pa3d0o dwnimetirosonofafSlil4y31Nf Wl4ow,w3ai7ns gWsp1,u0atntsetdraen1d7db5ay rWdrecfamocrt3iA mveui,nspC−uu1t,oteafrnUidnHgS,Pi,uNrsei2nspggeaacs.StiFivsienplyau.ltlFtyeo,rr1in aμgmcgouonnfstAaatnu7t-C0c oWum-Supinoadsllieotriyofnilos fwciolimn-sg,ptUuhtHetesPrueAbdsrtwraaintthde is rotated during the sputtering process. To fabricate alloy libraries with compositional gradients, the substrates are left stationary. Changing the sputtering power and tilt angles of each specific sputtering gun would alter the compositional spread of the libraries. The as-sputtered alloy film is first characterized with automated XRD (Rigaku Smartlab) using Cu Kα radia- tion with a 2 mm beam mask and automated EDS (Oxford Instruments X-Max detector attached to a Zeiss Sigma VP Field Emission scanning electron microscope) to determine the structure and composition, respectively, as a function of Systems VLS 6p.o6s0i)tiaotnaosnetthlaesewrasfcear.nNspexete,dt,hiencsaidmepnltefruonmdetrhgeoheseaLtSsAinuks(iSnigwaa6fe0r W) siCdeO. 2Tlhaeselras(eUrnsicvaenrslainl eLsaaserer spaced 5 mm apart center-to-center to avoid heat affected zone interactions. Finally, the sample is then character- ized with XRD and OM (Nikon ME600 with ThorLabs CCD camera). ®Temperature profile simulations.  Temperature profile simulations were done using the commercial pack- age COMSOL Multiphysics for time-dependent thermal finite element method simulations, informed by the experimental results. A 100 mm intrinsic Si wafer was modeled using temperature-dependent thermal conductivity, density, and specific heat capacity49. The wafer is assumed to be thermally isotropic. All surfaces are air-cooled with no forced convection (h = 5). Ambient temperature and the wafer edge were assumed to be 300 K. The laser was modeled as a Gaussian-shaped surface heat source, where the peak width and power was fitted with experimental measurements of the heat-affected zone size, which was measured using the OM images with ImageJ50 software. The thin photo-thermal and alloy layers, having high thermal diffusivities and low thermal masses, are assumed to be isothermal to the top surface of the Si wafer. The temperature profiles for different scan speeds (Fig. 2g) were recorded from one fixed point, located 1.27 cm from the origin of laser incidence and along the path of the laser scan to allow time to reach a stable temperature. Data Availability.  The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. References 1. Nishiyama, N. & Inoue, A. Supercooling investigation and critical cooling rate for glass formation in Pd–Cu–Ni–P alloy. Acta Materialia 47, 1487–1495 (1999). 2. Mukherjee, S., Schroers, J., Johnson, W. L. & Rhim, W. K. Influence of Kinetic and Thermodynamic Factors on the Glass-Forming Ability of Zirconium-Based Bulk Amorphous Alloys. Physical Review Letters 94, 245501 (2005). 3. Zhong, L., Wang, J., Sheng, H., Zhang, Z. & Mao, S. X. Formation of monatomic metallic glasses through ultrafast liquid quenching. Nature 512, 177–180 (2014). 4. Pogatscher, S., Leutenegger, D., Hagmann, A., Uggowitzer, P. J. & Löffler, J. F. Characterization of bulk metallic glasses via fast differential scanning calorimetry. Thermochimica Acta 590, 84–90 (2014). 5. Pogatscher, S., Uggowitzer, P. J. & Löffler, J. F. In-situ probing of metallic glass formation and crystallization upon heating and cooling via fast differential scanning calorimetry. Applied Physics Letters 104, 251908 (2014). 6. Bai, F. X., Yao, J. H., Wang, Y. X., Pan, J. & Li, Y. Crystallization kinetics of an Au-based metallic glass upon ultrafast heating and cooling. Scripta Materialia 132, 58–62 (2017). 7. Macarron, R. et al. Impact of high-throughput screening in biomedical research. Nature Reviews Drug Discovery 10, 188–195 (2011). 8. Schnabel, V. et al. Revealing the relationships between chemistry, topology and stiffness of ultrastrong Co-based metallic glass thin films: A combinatorial approach. Acta Materialia 107, 213–219 (2016). 9. Guo, Q. et al. Compositional dependence of Young’s moduli for amorphous Cu–Zr films measured using combinatorial deposition on microscale cantilever arrays. Scripta Materialia 64, 41–44 (2011). 10. Li, Y., Guo, Q., Kalb, J. A. & Thompson, C. V. Matching Glass-Forming Ability with the Density of the Amorphous Phase. Science 322, 1816–1819 (2008). 11. Deng, Y. P. et al. A combinatorial thin film sputtering approach for synthesizing and characterizing ternary ZrCuAl metallic glasses. Intermetallics 15, 1208–1216 (2007). 12. Ding, S., Gregoire, J., Vlassak, J. J. & Schroers, J. Solidification of Au-Cu-Si alloys investigated by a combinatorial approach. Journal of Applied Physics 111, 114901–114906 (2012). 13. McCluskey, P. J. & Vlassak, J. J. Glass transition and crystallization of amorphous Ni–Ti–Zr thin films by combinatorial nano- calorimetry. Scripta Materialia 64, 264–267 (2011). 14. McCluskey, P. J. & Vlassak, J. J. Combinatorial nanocalorimetry. Journal of Materials Research 25, 2086–2100 (2010). 15. Ryusuke, Y., Seiichi, H., Junpei, S. & Akira, S. Combinatorial Search for Low Resistivity Pd–Cu–Si Thin Film Metallic Glass Compositions. Japanese Journal of Applied Physics 45, 5911 (2006). 16. Liu, Y. et al. Combinatorial development of antibacterial Zr-Cu-Al-Ag thin film metallic glasses. Scientific Reports 6, 26950 (2016). 17. Doubek, G. et al. Guided Evolution of Bulk Metallic Glass Nanostructures: A Platform for Designing 3D Electrocatalytic Surfaces. Advanced Materials (2015). Scientific Reports | 7: 7155 | DOI:10.1038/s41598-017-07719-2 7 www.nature.com/scientificreports/ 18. Ding, S. et al. Combinatorial development of bulk metallic glasses. Nature Materials 13, 494–500 (2014). 19. Sakurai, J., Hata, S., Yamauchi, R. & Shimokohbe, A. Combinatorial arc plasma deposition search for Ru-based thin film metallic glass. Applied Surface Science 254, 720–724 (2007). 20. Li, Y. et al. Combinatorial Strategies for Synthesis and Characterization of Alloy Microstructures over Large Compositional Ranges. ACS Combinatorial Science 18, 630–637 (2016). 21. Gregoire, J. M. et al. Combining combinatorial nanocalorimetry and X-ray diffraction techniques to study the effects of composition and quench rate on Au–Cu–Si metallic glasses. Scripta Materialia 66, 178–181 (2012). 22. Tsai, P. & Flores, K. M. A combinatorial strategy for metallic glass design via laser deposition. Intermetallics 55, 162–166 (2014). 23. Tsai, P. & Flores, K. M. A Laser Deposition Strategy for the Efficient Identification of Glass-Forming Alloys. Metallurgical and Materials Transactions A 46, 3876–3882 (2015). 24. Tsai, P. & Flores, K. M. High-throughput discovery and characterization of multicomponent bulk metallic glass alloys. Acta Materialia 120, 426–434 (2016). 25. Harris, T. R. Optical properties of Si, Ge, GaAs, GaSb, InAs, and InP at elevated temperatures. Air Force Institute of Technology (2010). 26. Green, M. A. & Keevers, M. J. Optical properties of intrinsic silicon at 300 K. Progress in Photovoltaics: Research and Applications 3, 189–192 (1995). 27. Zhou, X., Zhao, A., Yuan, M. & Yu, X. Study on infrared absorption of tungsten nanofilms. SPIE Proceedings 8202, 820217 (2011). 28. Lang, W., Kühl, K. & Sandmaier, H. Absorbing layers for thermal infrared detectors. Sensors and Actuators A: Physical 34, 243–248 (1992). 29. Wang, X., Bellouard, Y. & Vlassak, J. J. Laser annealing of amorphous NiTi shape memory alloy thin films to locally induce shape memory properties. Acta Materialia 53, 4955–4961 (2005). 30. Jung, B. et al. 7639, 76390L Sub-millisecond (2010). post exposure bake of chemically amplified resists by CO2 laser heat treatment. SPIE Proceedings 31. Singer, J. P. et al. Alignment and reordering of a block copolymer by solvent-enhanced thermal laser direct write. Polymer 55, 1875–1882 (2014). 32. Singer, J. P., Kooi, S. E. & Thomas, E. L. Focused laser spike (FLaSk) annealing of photoactivated chemically amplified resists for rapid hierarchical patterning. Nanoscale 3, 2730–2738 (2011). 33. Cretu, C. & van der Lingen, E. Coloured gold alloys. Gold Bulletin 32, 115–126 (1999). 34. Liu, J. et al. Combinatorial exploration of color in gold-based alloys. Gold Bulletin 48, 111–118 (2015). 35. Schroers, J., Lohwongwatana, B., Johnson, W. L. & Peker, A. Gold based bulk metallic glass. Applied Physics Letters 87, 061912 (2005). 36. Ordal, M. A., Bell, R. J., Alexander, R. W., Newquist, L. A. & Querry, M. R. Optical properties of Al, Fe, Ti, Ta, W, and Mo at submillimeter wavelengths. Applied Optics 27, 1203–1209 (1988). 37. Chen, H. S. & Turnbull, D. Thermal Properties of Gold‐Silicon Binary Alloy near the Eutectic Composition. Journal of Applied Physics 38, 3646–3650 (1967). 38. Klement, W., Willens, R. H. & Duwez, P. O. L. Non-crystalline Structure in Solidified Gold-Silicon Alloys. Nature 187, 869–870 (1960). 39. Villars, P. & Okamoto, H. Au-Cu-Si Liquidus Projection of Ternary Phase Diagram: Datasheet from “PAULING FILE Multinaries Edition – 2012” in SpringerMaterials (http://materials.springer.com/isp/phase-diagram/docs/c_1500096). Springer-Verlag Berlin Heidelberg & Material Phases Data System (MPDS), Switzerland & National Institute for Materials Science (NIMS), Japan. 40. Lin, X. H. & Johnson, W. L. Formation of Ti–Zr–Cu–Ni bulk metallic glasses. Journal of Applied Physics 78, 6514–6519 (1995). 41. Wang, W. H. Elastic moduli and behaviors of metallic glasses. Journal of Non-Crystalline Solids 351, 1481–1485 (2005). 42. Wang, W. H. Correlations between elastic moduli and properties in bulk metallic glasses. Journal of Applied Physics 99, 093506 (2006). 43. Callister, W. D., Rethwisch, D. G. Materials Science and Engineering: An Introduction, Ninth edn. Wiley (2014). 44. Laws, K. J., Miracle, D. B. & Ferry, M. A predictive structural model for bulk metallic glasses. Nature Communications 6, 8123 (2015). 45. Na, J. H. et al. Compositional landscape for glass formation in metal alloys. Proceedings of the National Academy of Sciences 111, 9031–9036 (2014). 46. Ruhl, R. C. Cooling rates in splat cooling. Materials Science and Engineering 1, 313–320 (1967). 47. Turnbull, D. Under what conditions can a glass be formed? Contemporary Physics 10, 473–488 (1969). 48. Wang, C., Liao, Y.-C., Chu, J. P. & Hsueh, C.-H. Viscous flow and viscosity measurement of low-temperature imprintable AuCuSi thin film metallic glasses investigated by nanoindentation creep. Materials & Design 123, 112–119 (2017). 49. Miracle, D. B., Sanders, W. S. & Senkov, O. N. The influence of efficient atomic packing on the constitution of metallic glasses. Philosophical Magazine 83, 2409–2428 (2003). 50. Li, Y., Zhao, S., Liu, Y., Gong, P. & Schroers, J. How many bulk metallic glasses are there? Personal Communication (2017). 51. Miracle, D., Majumdar, B., Wertz, K. & Gorsse, S. New strategies and tests to accelerate discovery and development of multi- principal element structural alloys. Scripta Materialia 127, 195–200 (2017). 52. Shanks, H. R., Maycock, P. D., Sidles, P. H. & Danielson, G. C. Thermal Conductivity of Silicon from 300 to 1400 °K. Physical Review 130, 1743–1748 (1963). 53. Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nature Methods 9, 671–675 (2012). Acknowledgements This work was funded by National Science Foundation (NSF) DMREF/GOALI 1436268. The authors are grateful for characterization facilities provided by NSF MRSEC DMR 1119826 (CRISP) and the Yale Institute for Nanoscience and Quantum Engineering (YINQE). The authors would like to thank Glenn Weston-Murphy for his help with the laser equipment. The authors would also like to thank Sungwoo Sohn, Frederick J. Walker, Chinedum O. Osuji, Michael Loewenberg, and Corey S. O’Hern for fruitful discussions. Author Contributions P.B., J.P.S., and J.S. designed the study. P.B., J.L., and S.A.K. fabricated the samples. P.B. and T.M. performed the laser heating experiments and OM imaging. P.B., J.L., and Y.L. performed the XRD measurements. B.E.S. and C.C.B. performed the EDS measurements. J.P.S. performed the temperature profile simulations. J.P.S., J.J.V., and J.S. advised the research. All authors contributed to the data analysis, discussion, and writing of the manuscript. Additional Information Supplementary information accompanies this paper at doi:10.1038/s41598-017-07719-2 Competing Interests: The authors declare that they have no competing interests. Scientific Reports | 7: 7155 | DOI:10.1038/s41598-017-07719-2 8 www.nature.com/scientificreports/ Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2017 Scientific Reports | 7: 7155 | DOI:10.1038/s41598-017-07719-2 9