Muzakkiy Putra Muhammad Akhir, Rina Kamila



High Resolution Powder Diffractometer (HRPD) and Four Circle Diffractometer/Texture Diffractometer (FCD/TD) are two BATAN-owned neutron diffractometers which have been fully operational since 1992. These are used to investigate structure and texture of crystalline materials, respectively. Before analyzing, the acquired raw neutron diffraction data should first be processed in a specific way to achieve the suitable data format required by the analysis software. This data processing step is a repetitive task for every single experiment which is previously done manually and very time-consuming. The purpose of this development project was to optimize this step to be fully automatic and executable by a code. This work was performed by means of Python code utilizing the array manipulation in re-arranging and re-formatting the raw data. The resulted Python codes were named as and These have been successfully done and validated, making data processing step easier, simpler, and significantly faster with only 20 seconds or less required.

Keywords: HRPD, FCD/TD, Automatic Data Processing, Neutron Diffraction, Python

Full Text:



  1. Bharoto, Insani A. Development of Data Acquisition and Control Software for High Resolution Powder Diffractometer. INKOM. 2014. 8:47–51.
  2. Insani A., Mugirahardjo H. Effect of Collimator 3 Degree Divergence Modification of Neutron Diffractometer DN3 on Ni and TiO2 Scattering Quality (Pengaruh Modifikasi Sudut Divergensi Kolimator 3 Difraktometer Neutron DN3 terhadap Kualitas Hamburan Ni dan TiO2). in: Prosiding Seminar Hamburan Neutron dan Sinar X ke 7. 2015. pp. 90–4.
  3. Priyanto T.H., Muslih R., Mugirahardjo H., Insani A. Effects of the Preheating Temperature on the Crystal Structure and Texture of Martensitic Stainless Steel. Makara J. Technol. 2018. 22(2):79–83.
  4. Mugirahardjo H., Insani A., Bharoto, Muslih R., Santoso E. Counting System Characterization of High Resolution Neutron Powder Diffractometer (HRPD-DN3) (Karakterisasi Sistem Pencacah Difraktometer Neutron Serbuk Resolusi Tinggi (HRPD-DN3)). in: Prosiding Seminar Penelitian dan Pengelolaan Perangkat Nuklir. 2013. pp. 261–7.
  5. Welcome to Python [Accessed: 2 July 2020]. Available from:
  6. Huy N. Exploring Python as a replacement for C ++ in Imperative Programming for Computing Science at Radboud University.Radboud University; 2019.
  7. Yunker L.P.E., Ting M., Yeung D., Mcindoe J.S. PythoMS: A Python Framework To Simplify and Assist in the Processing and Interpretation of Mass Spectrometric Data. J. Chem. Inf. Model. 2019. 59:1295–300.
  8. Gladstein A.L., Quinto-cortés C.D., Pistorius J.L., Christy D., Gantner L., Joyce B.L. SimPrily: A Python framework to simplify high-throughput genomic simulations. SoftwareX. 2018. 7:335–40.
  9. Cardiel N. Using Python to Simplify Spectrometri Data.pdf. in: ASP Conference Series. 2019. pp. 499–502.
  10. Zolnierczuk P.A., Riedel R.A. Neutron Scattering Experiment Automation with Python. 2010.
  11. Abarrul I. Neutron Scattering Activities in Serpong (Kegiatan Hamburan Neutron di Serpong). in: Prosiding Seminar Hamburan Neutron dan Sinar X. 2001. pp. 36–40.
  12. Fajar A., Mugirahardjo H. The Performance of Fine Resolution Neutron Powder Diffractometer at PTBIN-BATAN. Atom Indones. 2010. 36:1–9.
  13. Priyanto T.H., Mugirahardjo H., Muslih R., Ramadhani A., Priyanto T.H., Mugirahardjo H., et al. Development of BATAN ’ s texture diffractometer ( current status ). in: AIP Conference Proceeding. 2015.
  14. Matplotlib Python plotting – Matplotlib 3 [Accessed: 2 July 2020]. Available from:
  15. Anaconda - The World’s Most Popular Data Science Platform Title [Accessed: 2 July 2020]. Available from:


  • There are currently no refbacks.

PTKRN Digital Library Mendeley