Characterization and modeling to design and develop tailored-property filled glass composites

Transcription

1 Engineering Conferences International ECI Digital Archives Composites at Lake Louise (CALL 2015) Proceedings Fall Characterization and modeling to design and develop tailored-property filled glass composites Kevin Ewsuk Sandia National Laboratories, Follow this and additional works at: Part of the Materials Science and Engineering Commons Recommended Citation Kevin Ewsuk, "Characterization and modeling to design and develop tailored-property filled glass composites" in "Composites at Lake Louise (CALL 2015)", Dr. Jim Smay, Oklahoma State University, USA Eds, ECI Symposium Series, (2016). This Conference Proceeding is brought to you for free and open access by the Proceedings at ECI Digital Archives. It has been accepted for inclusion in Composites at Lake Louise (CALL 2015) by an authorized administrator of ECI Digital Archives. For more information, please contact

2 Intensity 09:50 10:10 Louise Room Structural Composites Session I Photos placed in horizontal position with even amount of white space between photos and header Characterization and Modeling to Design and Develop Tailored-Property Filled-Glass Composites Kevin G. Ewsuk Sandia National Laboratories Albuquerque, NM Composites at Lake Louise-2015 November 8 12, 2015 Lake Louise, Alberta, Canada Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy s National Nuclear Security Administration under contract DE-AC04-94AL SAND NO XXXXP

3 Intensity Si-O Photos placed in horizontal position with even amount of white space between photos and header Al-O O-O Si-Si Al-Al Si-Al Ba-O Distance (Å) Todd R. Zeitler & Louise J. Criscenti - MD Modeling Michael T. Brumbach, Mark A. Rodriguez, & Todd M. Alam - Glass Structure Denise N. Bencoe & Bonnie McKenzie - Glass & Composite Characterization Sandia National Laboratories Richard K. Brow - Glass & Composite Characterization Missouri University of Science & Technology Karina Chapman - Glass Characterization Argonne National Laboratories Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy s National Nuclear Security Administration under contract DE-AC04-94AL SAND NO XXXXP

4 Glass Is Commonly Used To Bond/Join Inorganic Materials Glass bonding/joining Applications Glass-bonded composites Glass-bonded alumina Seals Hermetic glass-to-metal (GtM) seals Air bag igniters Medical implants Microelectronics Solid oxide fuel cells (SOFCs) *Feedthroughs for *Airbag igniter feedthroughs pressure & flow sensors *Schott Electronic Packaging 3

5 Filled-Glass Composites (FGCs) Have The Processability Of A Glass With The Properties Of A Ceramic Temp (ºC) Glass + Processability + Materials compatibility - Low/fixed CTE - Low toughness/crack tolerance Glass-Ceramic (GC) + Toughness/crack tolerance + High/Tunable CTE - Process sensitivity - Reactivity/Instability Li 3 PO 4 glass-like ceramic-like Li 2 SiO 4 SiO 2 Li 2 Si 2 O 5 Nucleation/Crystallization of different phases Time (min) Headley & Loehman, Crystallization of a Glass-Ceramic by Epitaxial Growth, J Am Ceram Soc, 67 [9] (1984). Filled-Glass Composite (FGC) + Process robustness + Toughness/Crack tolerance + Low to high/tunable CTE + Chemical/structural stability SS 60 mm SS GC GC 40 mm 4

6 Materials Science & Engineering Are Being Developed To Design/Develop Advanced Filled-Glass Composites Objectives Develop experimentally-validated modeling/simulation tools to: Predict/control glass chemistry-structure-property relations. Design & process filled-glass composites (FGCs). Approach Characterize & model glass chemistry-structure-property relations. Predict glass chemistry-structure relations with MD modeling. Characterize glass chemistry-structure (NN distance & NMR peak shifts). Characterize & model FGC processing & properties. Design FGCs using mixing models. Characterize glass & FGC wetting/interactions on stainless steel (SS). Characterize glass & FGC viscosity for process modeling. Test, refine, & validate modeling/simulation by comparison to experiment 5

7 BAS Glasses Were Simulated With The LAMMPS** MD Code & Pedone* Multicomponent Force Field BAS 1 25 BaO X Al 2 O 3 (75-x) SiO 2 Glasses BAS 2 BAS 3 25 BaO - 75 SiO 2 25 BaO - 5 Al 2 O 3-70 SiO 2 25 BaO - 15 Al 2 O 3-60 SiO 2 T. Zeitler *A Pedone et al., A new self-consistent empirical interatomic potential model for oxides, silicates, and silica-based glasses, J Phys Chem B, 110, (2006). **S Plimpton, Fast Parallel Algorithms for Short-Range Molecular-Dynamics, J Comp Phys, 117 [1], 1-19 (1995). 6

8 Intensity Model Predictions Of Chemistry-Structure Relations Were Tested & Validated By Comparison To Theory % % Glass g/mole Mole % Al 2 O 3 NBO Th (%) NBO MD (%) Connectivity Th (BO/NF) BAS BAS BAS BAS T. Zeitler Peak position & symmetry increase from BAS 1 3 Si-O-Si Q 4 /Q 3 increases from BAS 1 3 (with decreasing NBOs) BOs:NBOs increases from BAS 1 3 BAS 1 BAS 2 BAS Bond Angle (Å) CN BO NBO TBO Oxygen Speciation 7

9 Model Predictions Of Glass Chemistry-Structure Were Tested & Validated By Comparison To Experiment Tool Nearest Neighbor (NN) Distances NN Assignments Coordination Number (CN) Model Y Y Y apdf NMR Y Trends for Si & Al Inferred from crystallography Non-Bridging Oxygens (NBOs) Bond Angle Distributions, BO s/ NBO s Order/Disorder Trends Glasses BAS 1-3,8 BAS 1-3,8 BAS 1-3,8 EXAFS Y Y (Ba) Y (Ba) BAS 1-3,8 8

10 Intensity Intensity Measured apdf Peaks Are Consistent With Nearest Neighbor (NN) Distances From MD Simulations Si-O Al-O O-O Si-Si Al-Al Si-Al Ba-O Si-O Al-O O-O Ba-O Si-O Al-O BAS 1 BAS 2 BAS 3 G (r) Distance (Å) 1 st 2 nd 3 rd 4th 5 th Synchrotron apdf analysis l = Å Q max = 21 Å -1. Atomic Pair Distribution Functions (apdfs) - K. Chapman - Argonne 1 2 Nearest 3 Neighbor (NN) 4 distance (Å) 5 NN distance (Angstroms) Distance (Å) MD simulation T. Zeitler BAS 7 BAS 6 BAS 5 BAS 3 BAS 2 BAS 1 BAS 8 1 st - Si-O & Al-O 2 nd - O-Si-O 3 rd - Ba-O 4 th - O-Si-O-Si 5 th - O-Al-O-Si-O Ba-Ba M. Rodriguez 9

11 29 Si MAS-NMR Q 3 & Q 4 Peaks Are Accurately Predicted From MD Coordinates, But The Q 3 :Q 4 Ratio Differs Si(OSi) 4 d = ppm Si(OSi) 3 Al d = ppm Si(OSi) 3 Ba d = ppm NMR Calculated 29 Si chemical shifts using MD coordinates. Employed correlation from Sherrif et al. (1991) based on silicate mineral structures. Factors included bond valence (s i ), angle of the bridging oxygen, Si-O bond distance, and distance to the 2 nd nearest neighbors. si exp r0 ri / 0.37 Calculation N i 1 s R D 2 3 i 1 3cos i / 3 i log i 29 d ( Si) T. Alam 29 Si Chemical Shift (ppm) 10

12 MD Simulations Show A Higher Relative Concentration Of Glass Network Modifiers On The Glass Surface K T-1 O Si Al Co O T-1 (modified) Si Al T. Zeitler 11

13 Filled-Glass Composite (FGC) Properties Are Consistent With Model Predicted Trends Viscosity (Pa s) ΔL/L o dl/ Lo * Temper at ur e / C M a i n : 5 7 U s e r : E D [ # ] I n... F50 i l e 100 D a t e I d e n t i150 t y S a mp l e 200 L... S.. R. a n250 g e A t mo s p h300 e r e [ 4. 1 ]... [ 4. 2 ]... [ 5. 1 ]... [ 5. 2 ]... [ 6. 1 ]... [ 6. 2 ]... CGI % quar t z Temp. / C 50. 0, : Temp. / C 50. 0, : C G I _ B L U... C G I _ B L U... C G I %... C G I %... C G I %... C G I %... T. Al pha/ ( 1/ K) E- 06 T. Al pha/ ( 1/ K) E Material F E mo d e... F E mo d e... C G I B u m q t z C G I Temperature 1 0 u m q t z C G I ( C) u m q t z 1 0 u m q t z 10v% FGC 10.5 E-6 in/in/c CGI % quar t z Temp. / C T. Al pha/ ( 1/ K) 50. 0, : E- 06 Temp. / C 50. 0, : C G I B... C G I C G I T. Al pha/ ( 1/ K) E- 06 Glass 9.9 E-6 in/in/c Measured CTE (ppm/c) Predicted CTE (ppm/c) Glass v% FGC v% FGC v% FGC 11.0 E-6 in/in/c CGI gl ass Temp. / C 50. 0, : Temp. / C 50. 0, : / 1. 0 ( / / 1. 0 ( / / 1. 0 ( / T. Al pha/ ( 1/ K) E- 06 T. Al pha/ ( 1/ K) E- 06 [ [ ] ] D. Bencoe n i t r o g e n / 6 0 / n i t r o g e n / 6 0 / n i t r o g e n / 6 0 / n i t r o g e n / 6 0 / n i t r o g e n / 6 0 / n i t r o g e n / 6 0 / [ 5. 2 ] 1 [[ ]] C E+10 1.E+09 1.E+08 1.E+07 Glass 10v% FGC 1.E Temperature ( C) Euler s Model R. Brow MO U S&T 12

14 Viscosity Data Will Enable The Use Of Process Modeling To Optimize FGC Designs For Manufacturability Euler s Model FGC Process Map NLPS Model Ewsuk & Harrison, Ceramic Trans,

15 Sessile Drop Experiments Were Completed On Stainless Steel To Characterize Wetting & Viscous Flow Thermocouple Stainless Steel Glass (left) Composite (right) R. Brow MO U S&T 14

16 Sessile Drop Data Were Analyzed To Better Quantify Differences In Viscous Behavior 1. First shrinkage or sintering: Temperature pressed sample starts to shrink (logh=10 0±0 3 P). 2. Point of maximum shrinkage: Temperature of maximum sample shrinkage before it starts to soften (logh=8 2±0 5 P). 3. Softening point: Temperature of first signs of softening (disappearance or rounding of edges of the sample (logh=6 1±0 2 P). 4. Half ball point: Temperature at which sample forms a (logh=4 6±0 1 P). 5. Flow point: Temperature of maximum height of the drop of molten glass (logh= P). Scholze, Influence of viscosity and surface tension on hot-stage microscopy measurements on glasses, Ver. Dtsch. Keram. Ges., 1962, 391, 63 8.) Softening Point Half Ball Point Flow Point Pascual, et al., Phys. Chem. Glasses (2001) 42[1]

17 The Filler Addition Increases FGC Viscosity And Decrease FGC Reactivity Relative To The Glass Interaction Zone h/h Glass Stable melt temp: 915 C 935 C First shrinkage temp: 590 C 620 C 10v% FGC Half height temp: 767 C 825 C SS Interface R. Brow MO U S&T B. McKenzie 10v% FGC Glass ~100 mm Zone ~130 mm Zone 60 mm 60 mm 16

18 Oxidizing The Stainless Steel Enhances Initial Wetting And Reaction FGC composite H/H o SS Interface Wetting on SS Glass 10V% FGC Temperature/C Wetting on Oxidized SS R. Brow MO U S&T Glass 10V% FGC Temperature/C B. McKenzie ~80 mm interaction zone 60 mm 60 mm 17

19 Experimentally-Validated Modeling Is Being Developed To Enable Advanced FGC Design And Fabrication Summary Characterized & Modeled Glass Chemistry-Structure. Good modelling-experiment first-order agreement. MD efficient to assess bulk glass chemistry-structure. Interface modeling consistent with expectations Higher surface concentration of network modifiers. Characterized & Modeled FGC Properties & Processing. Measured CTE & viscosity trend as predicted by modeling. Wetting & reactivity are consistent with expectations Higher viscosity & lower reactivity FGCs relative to glass. Initial wetting & reactivity are enhanced on oxidized SS. 18