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PolaRIS-3D - Polarization Retrieval Including Strain in Three Dimensions

Subject Area Synthesis and Properties of Functional Materials
Experimental Condensed Matter Physics
Term from 2016 to 2019
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 285750842
 
Nanometer-scale strain and piezoelectric polarization mapping techniques that yield three dimensional quantitative results would greatly improve our understanding of materials physics for semiconductor nanostructures and ferroelectric materials. This is particularly challenging for modern strain-engineered semiconductor devices, such as the current 22 nm and 14 nm nodes in silicon fabrication technology, and also for nanometer scale, complex, three-dimensional domain structures of some lead-free piezoelectric materials. The transmission electron microscope is sensitive to both strain and polarization, but existing techniques are generally limited to mapping strain and polarization in just two dimensions. Recently, we have developed an algorithm that, using efficient artificial neural network optimization tools and stacked-Bloch-wave simulations implemented on graphics processing units (GPUs), can extract quantitative information about strain and tiny, polarization-inducing shifts of atoms within the unit cell as a function of specimen depth from electron diffraction patterns. In principle, this information can be recovered from a single convergent-beam electron diffraction (CBED) pattern, but using multiple CBED patterns provides better specimen retrieval and significantly improved robustness against noise. Although results from simulated test data are extremely promising, this capability remains untested against experimental data. The proposed project aims at further developing the methodology of automated acquisition of the necessary TEM data, extracting the relevant high-quality quantitative information from it, and to apply this algorithm to experimental data for multiple specimens, yielding three-dimensional maps of strain and polarization. The algorithm and results of this project will be made widely available.
DFG Programme Research Grants
 
 

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