1 3.051J/20.340J Lecture 11 Surface Characterization of Biomaterials in Vacuum The structure and chemistry of a biomaterial surface greatly dictates the degree of biocompatibility of an implant. Surface characterization is thus a central aspect of biomaterials research. Surface chemistry can be investigated directly using high vacuum methods: • Electron spectroscopy for Chemical Analysis (ESCA)/X-ray Photoelectron Spectroscopy (XPS) • Auger Electron Spectroscopy (AES) • Secondary Ion Mass Spectroscopy (SIMS) 1. XPS/ESCA Theoretical Basis: ¾ Secondary electrons ejected by x-ray bombardment from the sample near surface (0.5-10 nm) with characteristic energies ¾ Analysis of the photoelectron energies yields a quantitative measure of the surface composition2 3.051J/20.340J Electron energy analyzer θ (Ε = hν) (variable retardation voltage) Lens e e e P ≈ 10-10 Torr X-ray source Detector EK EF LI LII LIII Evac EB energy is characteristic element and kin Photoelectron binding of the bonding environment Chemical analysis! Binding energy = incident x-ray energy − photoelectron kinetic energy EB = hν - Ekin33.051J/20.340J Quantitative Elemental Analysis C1s N1s O1sIntensity Low-resolution spectrum 500 300 Binding energy (eV) ¾ Area under peak Ii ∝ number of electrons ejected (& atoms present) ¾ Only electrons in the near surface region escape without losing energy by inelastic collision ¾ Sensitivity: depends on element. Elements present in concentrations >0.1 atom% are generally detectable (H & He undetected) ¾ Quantification of atomic fraction Ci (of elements detected) Ci = Ii / Si Si is the sensitivity factor: ∑ Ij / Sj j - f(instrument & atomic parameters) - can be calculatedsum over detected elements4 3.051J/20.340J High-resolution spectrum C1s Intensity PMMA 290 285 Binding energy (eV) ¾ Ratio of peak areas gives a ratio of photoelectrons ejected from atoms in a particular bonding configuration (Si = constant) Ex. PMMA 5 carbons in total H CH3 H CH3 − C − C − 3 − C − C − (a) Lowest EB C1s H C=O H C EB ≈ 285.0 eV O CH3 1 O CH3 (b) Intermediate EB C1s EB ≈ 286.8 eV Why does core electron EB vary with valence shell 1 C=O O (c) Highest EB C1s EB ≈ 289.0 eV configuration?5 3.051J/20.340J from carbon Slight shift to1sElectronegative oxygen “robs” valence electrons(electron density higher toward O atoms) Carbon core electrons held “tighter” to the + nucleus (less screening of + charge) higher C binding energy Similarly, different oxidation states of metals can be distinguished. Ex. Fe FeO Fe3O4 Fe2O3 Fe2p binding energy XPS signal comes from first ~10 nm of sample surface. What if the sample has a concentration gradient within this depth? Surface-segregating species Adsorbed species 10nm Multivalent oxide layer6 3.051J/20.340J Depth-Resolved ESCA/XPS ¾ The probability of a photoelectron escaping the sample without undergoing inelastic collision is inversely related to its depth t within the sample: ⎛−t ⎞() ~ exp ⎜Pt ⎝λe ⎠⎟ where λe (typically ~ 5-30 Å) is the electron inelastic mean-free path, which depends on the electron kinetic energy and the material. (Physically, λe = avg. distance traveled between inelastic collisions.) For t = 3 λe ⇒ P(t) = 0.05 e θ =90° 95% of signal from t ≤ 3 λe ¾ By varying the take-off angle (θ), the sampling depth can be decreased, increasing surface sensitivity e e θ t = 3sin θλe θ7 3.051J/20.340J Ci 5 90 θ (degrees) ¾ Variation of composition with angle may indicate: - Preferential orientation at surface - Surface segregation - Adsorbed species (e.g., hydrocarbons) - etc. ¾ Quantifying composition as a function of depth The area under the jth peak of element i is the integral of attenuated contributions from all sample depths z: ⎛−z ⎞(Iij = CinstT Ekin )Lijσij ∫ n (z)exp ⎜ ⎟dz i ⎝λ sinθ⎠e σLCinst = instrument constant T(Ekin) = analyzer transmission function ij = angular asymmetry factor for orbital j of element i ij is the photoionization cross-section ni(z) is the atomic concen. of i at a depth z (atoms/vol)3.051J/20.340J 8 For a semi-infinite sample of homogeneous composition: ∞⎛−z ⎞Iij =−Iij ,oni λsinθexp ⎝⎜λsinθ⎠⎟e I= ij oniλe sinθ=S ni =Iij ,∞, i e 0 (,where Iij o = CinstT Ekin )Lijσij Relative concentrations of elements (or atoms with a particular bond configuration) are obtained from ratios of Iij (peak area): • Lij depends on electronic shell (ex. 1s or 2p); obtained from tables; cancels if taking a peak ratio from same orbitals, ex. IC1s / IO1s • Cinst and T(Ekin) are known for most instruments; cancel if taking a peak ratio with Ekin ≈ constant, ex. IC1s (C −−O)/ IC1s (C −CH3)C •σij obtained from tables; cancels if taking a peak ratio from same atom in different bonding config., ex. IC1s (C −−O )/ IC1s (C −CH3)C • λe values can be measured or estimated from empirically-derived expressions −1 −2 0.5 For polymers: λ(nm) =ρ(49E + 0.11Ekin )e kin −2 0.5 λ(nm) =a ⎡⎣538E +0.41(Ekina )⎦⎤For elements: e kin For inorganic compounds (ex. oxides): −2 0.5 λ(nm) =a ⎡⎣2170E +0.72 (Ekina )⎦⎤ e kin9 3.051J/20.340J where: ⎛ MW ⎞1/ 3 a = monolayer thickness (nm) a = 107 ⎜⎝ ρNAv ⎠⎟ MW = molar mass (g/mol) ρ = density (g/cm3) Ekin = electron kinetic energy (eV) Ex: λe for C1s using a Mg Kα x-ray source: EB = hν - Ekin For Mg Kα x-rays: hν = 1254 eV Ekin = 970 eVFor C1s : EB = 284 eV −1 −2 0.5 λ(nm) =ρ ( 49E + 0.11Ekin ) Assume ρ = 1.1 g/cm3 e kin λe = 3.1 nm3.051J/20.340J 10 For non-uniform samples, signal intensity must be deconvoluted to obtain a quantitative analysis of concentration vs. depth. Case Example: a sample comprising two layers (layer 2 semi-infinite): 1 d 2 ⎛−z ⎞(Iij =CinsT kin )Lijσij ∫ni (z)exp ⎝⎜λsinθ⎟⎠ dz e ij ij o i,1 e,1 ⎝ ij ,o i,2 e,2 ⎝λe,1sinθ⎠, ⎜ ⎝λe,1sinθ⎠⎠⎟ ⎛(1) − ⎛−d ⎞⎞ (2) ⎛−d ⎞ or Iij =Iij ,∞ ⎜⎜1exp ⎝⎜⎜λe,1sinθ⎠⎟⎟⎠⎟⎟+Iij ,∞ exp ⎝⎜⎜λe,1sinθ⎠⎟⎟⎝ (1) θ ⎛−z ⎞Iij =−Iij ,oni,1 λsinexp ⎝⎜λsinθ⎠⎟e e ⎛ I =I (1) n λ sinθ⎜1−exp ⎛⎜⎜−d d ∞ (2) θ ⎛−z ⎞I− ij oni,2 λsinexp ⎝⎜λsinθ⎠⎟, e e0 d ⎞⎞ ⎞ ⎟⎟⎟+I (2) n λ sinθexp ⎛⎜⎜−d ⎟⎟Why λe,1? Electrons originating in semi-infinite layer 2 are attenuated by