The Case for Materials Characterization


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The case for materials characterization in nanomaterials engineering

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The Case for Materials Characterization

  1. 1. The Case for Materials Characterization Foothill College NANO53
  2. 2. Overview <ul><li>The role of characterization </li></ul><ul><li>PNPA model </li></ul><ul><li>Types of information </li></ul><ul><li>Example problems </li></ul><ul><li>Materials analyzed </li></ul>
  3. 3. Why Characterize? <ul><li>Nanostructures are unknown </li></ul><ul><li>QA/QC of fabrication process </li></ul><ul><li>Failure analysis of products </li></ul><ul><li>Materials characterization </li></ul><ul><li>Process development / optimization </li></ul>
  4. 4. PNPA – Nanomaterials Engineering Rubric <ul><li>Applications drive requirements </li></ul><ul><li>Requirements inform material selection </li></ul><ul><li>Nanostructured materials engineering </li></ul><ul><li>Process design and optimization </li></ul><ul><li>Characterization tools and approach </li></ul>
  5. 5. PNPA – A Rubric for Training Technicians in Nanomaterials Engineering
  6. 6. PNPA - Characterization Processing (P) Properties (P) Characterization (N) Nanostructure PLOs – Program Learning Outcomes – Integrated Materials Engineering Process Structure property relationships => Fabrication property relationships => <= Nanostructure elucidation <= Process tools / QA/QC monitoring Fabrication property relationships => <= Properties determination
  7. 7. Nanostructural Information <ul><li>Morphology </li></ul><ul><li>Composition </li></ul><ul><li>Chemistry </li></ul><ul><li>Structure </li></ul><ul><li>Properties </li></ul>Novel nanocarbon can store and sieve hydrogen -
  8. 8. Process Optimization <ul><li>Relate structure to properties </li></ul><ul><li>Relate structure to process </li></ul><ul><li>Relate process to properties </li></ul><ul><li>Optimize structure / property process / relationships </li></ul><ul><li>Optimize process parameters for manufacturing / cost / safety etc. </li></ul>
  9. 9. Taguchi Methods <ul><li>Taguchi methods  are  statistical  methods developed by  Genichi Taguchi  to improve the quality of manufactured goods, and more recently also applied to, engineering, biotechnology, marketing and advertising. Professional statisticians  have welcomed the goals and improvements brought about by Taguchi methods, particularly by Taguchi's development of designs for studying variation, but have criticized the  inefficiency  of some of Taguchi's proposals. [5] </li></ul>
  10. 10. Key Nanomaterials <ul><li>Polymers </li></ul><ul><li>Metals/alloys </li></ul><ul><li>Glasses/ceramics </li></ul><ul><li>Nanocarbon </li></ul><ul><li>Thin film coatings </li></ul><ul><li>Silicon </li></ul><ul><li>Particles </li></ul>Energy of electrons in graphene in the tight-binding model,
  11. 11. What we Need to Know <ul><li>Surface finish </li></ul><ul><li>Surface composition and chemistry </li></ul><ul><li>Layer thickness </li></ul><ul><li>Bulk composition and chemistry </li></ul><ul><li>Material phase and structure </li></ul>
  12. 12. Types of Testing <ul><li>Materials characterization </li></ul><ul><li>Process development support </li></ul><ul><li>Failure analysis </li></ul><ul><li>QA/QC </li></ul><ul><li>Authenticity testing </li></ul>
  13. 13. Tools <ul><li>Image (SEM, AFM, TEM) </li></ul><ul><li>Surface (AES, XPS) </li></ul><ul><li>Organic (FTIR, Raman, GC/MS, LC/MS, NMR </li></ul><ul><li>Chemical (ICP, XRF, TEM) </li></ul><ul><li>Structural (XRD, Raman) </li></ul><ul><li>Modeling and simulation </li></ul>
  14. 14. AFM Instrumentation PNI Nano-R AFM Instrumentation as used at Foothill College
  15. 16. Surface Analysis Tools SSX-100 ESCA on the left, Auger Spectrometer on the right
  16. 17. XPS Spectrum of Carbon <ul><li>XPS can determine the types of carbon present by shifts in the binding energy of the C(1s) peak. These data show three primary types of carbon present in PET. These are C-C, C-O, and O-C=O </li></ul>
  17. 18. Typical Problems <ul><li>Contamination </li></ul><ul><li>Failure </li></ul><ul><li>Process development </li></ul><ul><li>Competitive analysis </li></ul><ul><li>Research (R&D) </li></ul> /
  18. 19. Nanocarbon <ul><li>Graphitic like structures </li></ul><ul><ul><li>CNT, graphene, etc </li></ul></ul><ul><li>Soot that has been annealed (graphitized) </li></ul><ul><li>Graphitic planes are observed by TEM </li></ul><ul><li>No one knows what the 3D structure is </li></ul><ul><li>Electron tomography might be useful </li></ul>
  19. 23. Biomedical Stents <ul><li>Surface finish is critical to patient outcomes, electropolishing etc. </li></ul><ul><li>Multi-technique analysis </li></ul><ul><ul><li>Image analysis </li></ul></ul><ul><ul><li>Surface analysis </li></ul></ul><ul><ul><li>Depth profiles </li></ul></ul>
  20. 24. Identification of Contamination <ul><li>Organic contamination </li></ul><ul><li>Ionic residues </li></ul><ul><li>Cleaning residue </li></ul><ul><li>Process residue </li></ul><ul><li>Packaging transfer </li></ul><ul><li>Environmental </li></ul>
  21. 25. Surface Treatment of NiTi Biomedical Devices and Biomedical Implants – SJSU Guna Selvaduray
  22. 26. Surface Treatment of NiTi Biomedical Devices and Biomedical Implants – SJSU Guna Selvaduray
  23. 27. <ul><li>XPS spectra of the Ni(2p) and Ti(2p) signals from Nitinol undergoing surface treatments show removal of surface Ni from electropolish, and oxidation of Ni from chemical and plasma etch. Mechanical etch enhances surface Ni. </li></ul>Surface Treatment of NiTi Biomedical Devices and Biomedical Implants – SJSU Guna Selvaduray
  24. 28. Multi-technique Analysis <ul><li>Image – surface morphology </li></ul><ul><li>Surface – surface chemistry </li></ul><ul><li>Structural – crystal domain </li></ul><ul><li>Organic – molecular specific identification (separation) </li></ul><ul><li>Chemical – elemental analysis </li></ul>
  25. 29. Modeling and Simulation
  26. 30. Not Being Blind <ul><li>Developing a process with NO characterization tools </li></ul><ul><li>Using properties measurements only </li></ul><ul><li>Not knowing why something is good </li></ul><ul><li>Not knowing if you can do better </li></ul><ul><li>Not having a baseline of quality </li></ul>