Therefore, to run Blueprint XAS, Matlab, version 7.4.0 R2007a (or a more recent version), equipped with the respective curve-fitting and statistics toolboxes, is required. Additional details can be consulted at the Mathworks website (Mathworks, 2009 Moler, 1999 ). A brief description of some of the specific curve-fitting functions is given in §S1 of the supplementary information 1. This manuscript introduces the GUI generally and then focuses on specific features of the interface, as well as the system requirements and general information regarding the technical aspects of the program.īlueprint XAS is coded in Matlab R2007a and makes use of several `add-on' optimization and statistics functions belonging to the curve-fitting and statistics toolboxes, respectively. Furthermore, a statistical module focuses on data analysis tools that allow users to evaluate the validity of their fit model and assist in determining the reliability of obtained solutions. Within this program, the user can interactively set up an overall fit model that incorporates functions and parameters related to the edges, background and/or peaks. ![]() Herein, we introduce Blueprint XAS, a Matlab-based program that incorporates this methodology through a graphical user interface (GUI). To overcome this problem, we have proposed in a companion manuscript (Delgado-Jaime & Kennepohl, 2010 ) a methodology that uses a Monte Carlo approach to the simultaneous fitting of background and edge features in XAS spectra. Unfortunately, user bias in the selection of parameter starting values tends to limit the effectiveness of a manual approach and makes it difficult to determine whether a particular solution is reliable and/or unique. To solve this issue, current approaches generally rely on the user generating a number of independent fits. In addition to the above, optimization of multiple-variable problems presents an additional challenge: the very real possibility that a unique best fit solution is unattainable. Simultaneous fitting of the background also allows for judicious use of parameters to ultimately decrease the total number of fitting parameters (Delgado-Jaime & Kennepohl, 2010 ). functions governing the background of different regions of the spectrum) within a single complete fit model. We have recently investigated (Delgado-Jaime et al., 2006 ) and developed (Delgado-Jaime & Kennepohl, 2010 ) a new methodology that incorporates background subtraction into the fitting procedure and that involves the simultaneous merging of all of the relevant parent functions ( i.e. However, this approach still assumes that performing these steps independently does not introduce additional uncertainty, nor does it address the potential influence of user bias in each step. ![]() Practitioners therefore tend to perform several different fits starting from different background subtractions to determine whether a particular fit is robust. A particular concern with this approach resides in the fact that background subtraction may, in principle, have a significant impact on peak fitting and analysis. This general approach is built into a number of data analysis packages, dealing with each step independently (George & Pickering, 1993 Ressler, 1998 Webb, 2005 ). Future stand-alone versions of the program will also incorporate several other new features to create a full package of tools for XAS data processing.Īnalysis of near-edge XAS data typically involves the following steps applied sequentially: (i) scan averaging, (ii) energy calibration, (iii) background subtraction, (iv) normalization and (v) peak fitting. The version introduced here (v0.2) is currently a toolbox for Matlab. ![]() A unique statistics panel allows the user to analyse a family of independent fits, to evaluate fit models and to draw statistically supported conclusions. A batch function allows for the setting of multiple jobs to be run with Matlab in the background. The functions and settings on the five panels of its graphical user interface are designed to suit the needs of near-edge XAS data analyzers. The program is based on a methodology that introduces a novel background model into the complete fit model and that is capable of generating any number of independent fits with minimal introduction of user bias. Blueprint XAS is a new Matlab-based program developed to fit and analyse X-ray absorption spectroscopy (XAS) data, most specifically in the near-edge region of the spectrum.
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