Decomposition of no-clean solder flux systems and their effects on the corrosion reliability of electronics

  • Hélène Conseil
  • Vadimas Verdingovas
  • Morten S. Jellesen
  • Rajan Ambat


No-clean flux systems are used today for the soldering of electronic printed circuit board assemblies assuming that all the aggressive substances of the flux will vanish during the soldering process i.e. evaporate, decompose or being enclosed safely in the residues. However this is not true in most cases, as the flux residue left on a printed circuit board assembly is a key factor compromising the corrosion reliability under humid conditions. This investigation focuses on the chemical degradation of three kinds of solder flux systems based on adipic, succinic, and glutaric acid as a function of temperature, thus simulating the soldering process. Differential Scanning Calorimetry, Fourier Transform Infrared Spectroscopy, and Ion Chromatography were employed for decomposition and residue analysis. Aggressiveness of the residue was investigated using a pH indicator gel test and by acid value determination. Effect on corrosion reliability was investigated by exposing the test printed circuit board assemblies to humidity after pre-contaminating with pure acids and desired solder flux systems and measuring the charge transferred between electrodes under applied potential bias. Results showed that the fluxes do not decompose fully within the temperature regime of the soldering process, leaving behind significant level of weak organic acid residues. The residue depending on the type and amount can be can be very aggressive towards the corrosion on the printed circuit board assemblies. The glutaric acid based flux showed highest leakage current when exposed to humidity compared to the adipic and succinic based fluxes.


Succinic Acid Soldering Process Adipic Acid Thermo Gravimetric Analysis Glutaric Acid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Current research has been conducted as part of the CELCORR/CreCon consortium ( and the authors acknowledge the funding from the consortium partners and for their commitment and help.


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Hélène Conseil
    • 1
  • Vadimas Verdingovas
    • 1
  • Morten S. Jellesen
    • 1
  • Rajan Ambat
    • 1
  1. 1.Materials and Surface Engineering, Department of Mechanical EngineeringTechnical University of DenmarkKongens LyngbyDenmark

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