The transition from planar to three-dimensional architectures of semiconductor devices has triggered the development of material characterization techniques with three-dimensional atomic resolution capabilities. As explicitly recognized by the semiconductor industry, cfr statements in the International Technology Roadmap for Semiconductors, atomprobe tomography (APT) is among the most promising ones to solve this need since it does provide 3D-atomic scale elemental mapping.
The APT technique is based on the atom-by-atom field evaporation of individual atoms from a needle-shaped sample by the combined effect of a high standing voltage and a pulsed laser. The use of time-of-flight mass spectrometry and projection (with 106 magnification) on a 2D position-sensitive detector then enables APT to provide a full 3-dimensional, quantitative composition analysis of materials with an excellent sensitivity (~ 10 ppm, irrespective of the mass) and a near-atomic spatial resolution (δlateral ~ 2-3 Å, δdepth ~ 0.5 Å). This technology thus offers the unique possibility of unraveling the 3-dimensional structure of complex advanced materials at the atomic scale (see Si FinFET of Fig. 1).
APT has shed more light on the basic physics of boron segregation at dislocations1, the lateral dopant diffusion in a FinFET transistor2 and the correlation between threshold voltage variations and statistical dopant fluctuations3. Despite these successes, it remains a challenge to exploit the staggering capabilities of APT in heterogeneous systems which combine nanostructured materials (e.g. multilayers, embedded clusters or more complex 3D nanostructures) or even in simple systems such as boron doped silicon. In these systems artefacts are typically observed such as blurring of interfaces, deviations of shape and dimensions of nanostructures, dopant profile distortions, apparent clustering of atoms or erroneous (non-stoichiometric) quantification. To overcome this, we require much more theoretical understanding of the laser light absorption in a sub-wavelength object, frequently with a bandgap which exceeds the laser energy, heat generation and transport to the apex, where it eventually triggers evaporation. Knowledge on the evaporation physics (dynamic tip shaping, etc.) and atomic-scale processes (atom retention, migration, etc.), will be key to understand geometrical artefacts and quantification inaccuracies.
This PhD project aims at unraveling these fundamental phenomena by coupling dedicated experiments using APT and field ion microscopy (FIM) with theoretical simulations of laser-object interactions and field evaporation in nanoscale heterogeneous objects. Moreover, you will explore ways to assess tip shapes (TEM, SEM, SPM, ...) and investigate fundamental concepts of correlative microscopy by data fusion of TEM-(tomography results) with atomprobe data reconstruction procedures. Beyond these fundamental aspects to be studied, this project concurrently requires the development of FIB-based sample preparation routines for heterogeneous materials, including challenges such as nanometer localization of the region of interest, compatibility for correlative microscopy, sample fracture during analysis, etc.
You will work with state of the art dual beam FIB and APT systems and benefit from the integration in the characterization group of imec disposing of a multitude of characterization techniques in support of this project. In addition you will benefit from the very close collaboration with the process engineers of imec and its industrial partners. The end result will deliver a methodology suited to contribute to the development of next generation devices.
1 S. Koelling et al., Nano Lett., vol. 13, no. 6, pp. 2458, 2013.
2 A. K. Kambham et al., Nanotechnology, vol. 24, no. 27, p. 275705, 2013.
3 H. Takamizawa et al., Appl. Phys. Lett., vol. 100, no. 25, pp. 98, 2012
Required background: physics (optics, solid-state, semiconductors), engineering
Type of work: 60% experimental, 40% theoretical
Supervisor: Wilfried Vandervorst
Daily advisor: Claudia Fleischmann
The reference code for this PhD position is STS1712-49. Mention this reference code on your application form.