1. The document discusses the importance of materials characterization for understanding nanostructures, quality assurance, and process optimization. 2. It introduces the PNPA model which relates nanostructured materials, processing requirements, and characterization tools and approaches. 3. Various characterization tools and techniques are described including imaging, surface analysis, organic analysis, and structural and chemical analysis which can provide different types of information about materials.

1. The Case for Materials Characterization Foothill College NANO53

2. Overview The role of characterization PNPA model Types of information Example problems Materials analyzed

3. Why Characterize? Nanostructures are unknown QA/QC of fabrication process Failure analysis of products Materials characterization Process development / optimization

4. PNPA – Nanomaterials Engineering Rubric Applications drive requirements Requirements inform material selection Nanostructured materials engineering Process design and optimization Characterization tools and approach

5. PNPA – A Rubric for Training Technicians in Nanomaterials Engineering

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. Nanostructural Information Morphology Composition Chemistry Structure Properties Novel nanocarbon can store and sieve hydrogen - http://spie.org/x13545.xml?ArticleID=x13545

8. Process Optimization Relate structure to properties Relate structure to process Relate process to properties Optimize structure / property process / relationships Optimize process parameters for manufacturing / cost / safety etc.

9. Taguchi Methods 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] http://en.wikipedia.org/wiki/Taguchi_methods

10. Key Nanomaterials Polymers Metals/alloys Glasses/ceramics Nanocarbon Thin film coatings Silicon Particles Energy of electrons in graphene in the tight-binding model, http://dx.doi.org/10.1103/PhysRev.71.622

11. What we Need to Know Surface finish Surface composition and chemistry Layer thickness Bulk composition and chemistry Material phase and structure

12. Types of Testing Materials characterization Process development support Failure analysis QA/QC Authenticity testing

13. Tools Image (SEM, AFM, TEM) Surface (AES, XPS) Organic (FTIR, Raman, GC/MS, LC/MS, NMR Chemical (ICP, XRF, TEM) Structural (XRD, Raman) Modeling and simulation

14. AFM Instrumentation PNI Nano-R AFM Instrumentation as used at Foothill College

16. Surface Analysis Tools SSX-100 ESCA on the left, Auger Spectrometer on the right

17. XPS Spectrum of Carbon 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

18. Typical Problems Contamination Failure Process development Competitive analysis Research (R&D) http://www.forensicinvestigation.com /

19. Nanocarbon Graphitic like structures CNT, graphene, etc Soot that has been annealed (graphitized) Graphitic planes are observed by TEM No one knows what the 3D structure is Electron tomography might be useful

23. Biomedical Stents Surface finish is critical to patient outcomes, electropolishing etc. Multi-technique analysis Image analysis Surface analysis Depth profiles

24. Identification of Contamination Organic contamination Ionic residues Cleaning residue Process residue Packaging transfer Environmental

25. Surface Treatment of NiTi Biomedical Devices and Biomedical Implants – SJSU Guna Selvaduray

26. Surface Treatment of NiTi Biomedical Devices and Biomedical Implants – SJSU Guna Selvaduray

27. 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. Surface Treatment of NiTi Biomedical Devices and Biomedical Implants – SJSU Guna Selvaduray

28. Multi-technique Analysis Image – surface morphology Surface – surface chemistry Structural – crystal domain Organic – molecular specific identification (separation) Chemical – elemental analysis

29. Modeling and Simulation

30. Not Being Blind Developing a process with NO characterization tools Using properties measurements only Not knowing why something is good Not knowing if you can do better Not having a baseline of quality