Crack-on-chip: a nanomechanical test method to determine the fracture toughness of thin films and 2D materials by Sahar JADDI

For the degree of Doctor of Engineering Sciences and Technology

The control and characterization of the fracture behavior of thin films and 2D materials, in the era of continuous device miniaturization, are of paramount importance for the design and integrity assessment of many coatings and microelectronics devices towards more reliable devices. However, the available test methods suffer from many limitations mainly when the film rests on a substrate due to different constraints that are difficult to deconvolute and or with the introduction of an initial sharp precrack in freestanding configurations. In this context, the objective of this research is to develop a robust fracture on-chip technique for freestanding thin films and 2D materials. This crack-on-chip method consists of actuator beams produced by lithography undergoing large internal stress attached to a notched specimen beam. Both actuators and specimens are deposited on top of a Si substrate. The etching of a part of this substrate induces the release of the test structure, with the actuators then contracting and pulling on the test specimen. If the applied displacement is large enough, a crack initiates at the notch root and propagates. The design has been selected such as to involve a decrease of the crack driving force after some amount of crack growth leading to crack arrest. avoiding the problem of notch opening of the precrack. The technique can also be used to investigate the environmentally-assisted cracking in thin-film materials. The fracture toughness of SiO₂ (142 nm), SiN (50 nm), Al₂O₃ (190 nm), and CVD-grown monolayer graphene were extracted. It was found that Al₂O₃ films are more prone to subcritical aging compared to SiN, while simultaneously exhibiting larger resistance to environmental cracking than thermally-grown SiO₂ films. For single-layer graphene, fracture strain, Young’s modulus, strength, and Weibull modulus were determined with, for the first time, statistically representative data.  

Jury members :

• Prof. Thomas Pardoen (UCLouvain, Belgium), supervisor
• Prof. Jean-Pierre Raskin (UCLouvain, Belgium), supervisor
• Prof. Hervé Jeanmart (UCLouvain, Belgium), chairperson
• Prof. Hosni Idrissi (UCLouvain)
• Prof. Ingrid De Wolf (KULeuven, Belgium)
• Prof. Benoit Merle (University of Erlangen-Nürnberg, Allemagne)
• Prof. Ludovic Noels (Uliège, Belgium)

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