AVS 53rd International Symposium
    Applied Surface Science Monday Sessions
       Session AS-MoA

Paper AS-MoA2
Strategies for ToF-SIMS Data Complexity Reduction: A Comparison of G-SIMS and Multivariate Analysis Applied to PLGA Biopolymer Systems

Monday, November 13, 2006, 2:20 pm, Room 2005

Session: Developing Methods for Data Analysis
Presenter: F.J.M. Rutten, The University of Nottingham, UK
Authors: F.J.M. Rutten, The University of Nottingham, UK
R. Ogaki, The University of Nottingham, UK
S. Li, University of Montpellier, France
M. Vert, University of Montpellier, France
M.R. Alexander, The University of Nottingham, UK
I.S. Gilmore, National Physical Laboratory, UK
M.C. Davies, The University of Nottingham, UK
Correspondent: Click to Email
Amongst the plethora of surface analytical techniques currently available static (time-of-flight) secondary ion mass spectrometry (SIMS) stands out as a very powerful technique capable of yielding highly specific chemical information with often exquisite sensitivity. Information of this kind is more often than not crucial to understand highly complex biomaterial interfaces, such as surface interactions with cells and proteins in anti-fouling or tissue engineering applications. In this paper we present a comparative study of two SIMS spectral analysis approaches applied to a range of copolymers consisting of varying amounts of lactic and glycolic acid. Poly(Lactic-co-glycolic acid) (PLGA) is biodegradable and as such currently in use in a number of applications in the biomaterials field, such as tissue engineering scaffolds and drug delivery systems. A drawback of SIMS relates to the rather violent process involved in the generation of diagnostic secondary ions, which involves the impact of highly energetic ions leading to the formation of a range of charged fragments for a single molecular species. Whereas a wealth of information is captured in the resulting mass spectra, their complexity often precludes interpretation of all but the most prominent fragments. At present two approaches show great promise in reducing the complexity of SIMS spectra, thus maximising extractable information: Gentle-SIMS (G-SIMS) uses acquired data with different levels of fragmentation to extrapolate to lower surface plasma temperatures and hence amplifies otherwise weak but highly diagnostic larger mass fragments (e.g. Ref. 1). Multivariate analytical approaches reduce complexity by generating new variables which contain the most pertinent parts of spectra, with the possibility to relate this to surface chemistry. The relative merits of both techniques are discussed for PLGA-drug systems. @FootnoteText@ @footnote 1@ I.S.Gilmore, M.P.Seah, Appl. Surf. Sci. 231-232 (2004) 224 and refs. therein.