Characterization of substrate-less semiconductors with energetic ion beams

Innovations in the development and characterization of new materials are the basis of many novel nanoelectronics devices. Among the most sensitive methods for materials characterization are techniques which employ the interaction of highly energetic ions with the material of interest. Still, it is challenging to characterize nanometric volumes with sufficient precision and accuracy. The goal is to develop more sensitive characterization methods, based on advanced understanding of ion-beam solid interactions. In the present PhD research, we will investigate the scientific potential of analyzing nanometer-scale ultra-thin self-supporting films using highly energetic ion beams. 

Given the limited volume of the nanostructures compared to the substrate, and given the finite count rate of a detector, the sensitivity to the nanomaterial under standard ion beam analysis conditions is limited. In the past, researchers have developed methods to improve discriminating the small signal from the nanostructures against the dominating signal from the substrate. In the present work, we want to realize a paradigm shift by removing the substrate. It is anticipated that the sensitivity and accuracy of ion beam analysis can be dramatically improved by measuring the nanostructures selectively. Your main research activity will be to develop, in this new context, the best-suited conditions (ion beam, detectors, data analysis, etc.) to optimally characterize technologically important material systems chosen as a demonstrator.

Firstly, it is expected that the substrate-less approach will allow one to derive drastically more precise information about the nanostructures from elastically backscattered ions, also known as Rutherford backscattering. You will investigate the capability to quantify light elements (C, N, O...) in thin films and nanostructures, the signal of which so far was mostly buried underneath the substrate signal. As an example, you may study the oxygen signal of a thin InGaZnO film in a transistor, investigating the absolute accuracy, the increase in sensitivity, and the completeness of the characterization. The source(s) of remaining background signals, if present, will be investigated.

Secondly, the substrate-less analysis will also revolutionize the sensitivity of ion-beam analysis which relies on the detection of particle-induced X-rays (PIXE). An X-ray absorber, typically used to suppress the signal from the substrate, will no longer be needed. The aim will be to explore and investigate the emerging capabilities of PIXE in the absence of a substrate.

It will be essential to investigate the mentioned detection schemes and to compare their capabilities and complementarity. It is anticipated that the most precise and complete characterization will be obtained by combining both ion detection as well as X-ray detection methods, and by simultaneously analyzing the multiple spectral inputs consistently via a multi-objective approach. To this end, you will develop a multi-objective data analysis approach using, e.g., ANN or evolutionary algorithms to arrive at the best possible characterization and to link the results with the process conditions and electrical and optical properties of the studied material.