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  NDF - General purpose code for data analysis of Ion Beam Analysis Data

1. Introduction

NDF is a DOS code dedicated to the analysis of RBS, ERDA, PIXE, non-resonant NRA and NDP data for any ion, any target, any geometry, and number of spectra.

The full version of NDF includes local search fitting, simulated annealing fitting, Bayesian inference, as well as an excellent graphical user interface that can be found in https://www.surrey.ac.uk/ion-beam-centre/research/ion-beam-analysis.

The free version of NDF is a simulator only. It does not implement fitting or Bayesian inference. It also does not implement PIXE. It is called ALP internally just to distinguish it from the regular NDF.

The general philosophy of NDF is to put accuracy before calculation speed. In some cases, this leads to calculations that can be orders of magnitude slower - i.e. a few seconds in modern PCs. Faster calculations can be made by turning the appropriate options on or off.

NDF is a DOS program which reads input files and creates output files. No graphical interface or output is supplied. The users must use their own graphics package to visually inspect the fits and depth profiles obtained.

NDF is distributed "as is". Bug reports and suggestions are very welcome. Email me at nunoni (add @itn.pt).

2. NDF Related Bibliography

NDF calculations: reviews, algorithms, advanced pysics

  • Introduction and Review: N.P. Barradas, C. Jeynes, and R.P. Webb, Appl. Phys. Lett. 71 (1997) 291 ; C. Jeynes, N.P. Barradas, P.K. Marriott, M. Jenkin, E. Wendler, G. Boudreault, R.P. Webb, J. Phys. D: Appl. Phys. 36 (2003) R97.
  • Simultaneous analysis of multiple spectra/technique: N.P. Barradas, S. Parascandola, B.J. Sealy, R. Grötzschel, and U. Kreissig, Nucl. Instrum. Methods Phys. Res. B161-163 (2000) 308.
  • Bayesian Inference: N.P. Barradas, C. Jeynes, M. Jenkin, and P.K. Marriott, Thin Solid Films 343-344 (1999) 31; N.P. Barradas, J.L. Keddie and R. Sackin, Phys. Rev. E59 (1999) 6139.
  • PIXE: Carlos Pascual-Izarra, Miguel A. Reis, N. P. Barradas, Nucl. Instrum. Methods B249 (2006) 780; Carlos Pascual-Izarra, N. P. Barradas, Miguel A. Reis, Nucl. Instrum. Methods B249 (2006) 820.
  • Roughness: N. P. Barradas, J. Phys. D: Appl. Phys. 34 (2001) 2109; N. P. Barradas, E Alves, S. Pereira, V. V. Shvartsman, A. L. Kholkin, E. Pereira, K. P. O’Donnell, C. Liu, C. J. Deatcher I. M. Watson, M. Mayer, Nucl. Instrum. Methods B 217 (2004) 479.
  • Simulation of quantum dots: N.P. Barradas, Nucl. Instrum. Methods B261 (2007) 435.
  • Simulation of resonances: N.P. Barradas, E. Alves, C. Jeynes, M. Tosaki, Nucl. Instrum. Methods B247 (2006) 381; A. F. Gurbich, N. P. Barradas, C. Jeynes, E. Wendler, Nucl. Instrum. Methods B190 (2002) 237.
  • Double scattering: N.P. Barradas, Nucl. Instr. and Meth. B225 (2004) 318.
  • Pile-up: N.P. Barradas, M. Reis, X-Ray Spectrometry 35 (2006) 232.
  • Calculation of the low energy yield: N. P. Barradas, Nucl. Instrum. Methods B261 (2007) 418.
  • Determination of stopping powers: N.P. Barradas, C. Jeynes, R.P. Webb, E. Wendler, NIM B194 (2002) 15.

International Atomic Energy Agency status and intercomparison of IBA software: The State of the Art

  • E. Rauhala, N. P. Barradas, S. Fazinic, M. Mayer, E. Szilágyi, M. Thompson, Nucl. Instrum. Methods B244 (2006) 436.
  • N.P. Barradas, K. Arstila, G. Battistig, M. Bianconi, N. Dytlewski, C. Jeynes, E. Kótai, G. Lulli, M. Mayer, E. Rauhala, E. Szilágyi, M. Thompson, Nucl. Instrum. Methods B262 (2007) 282.

Artificial neural networks applied to IBA

  • N. P. Barradas and A. Vieira, Phys. Rev. E62 (2000) 5818.
  • N. P. Barradas, A. Vieira, R. Patrício, Phys. Rev. E65 (2002) Article 066703.
  • V. Matias, G. Öhl, J.C. Soares, N. P. Barradas, A. Vieira, S. Cardoso, P.P. Freitas, Phys. Rev. E67 (2003) 046705.

Other indispensable tools for the IBA data analyst

3. The IBA data format IDF