Virtual design of self-assembled 2-dimensional layered materials

Two-dimensional layered materials (2D-LM) which display a large anisotropy to their bonding, electrical and/or magnetic properties, are of paramount interest for an enormous breadth of fields, ranging from semiconductor technology, electronics and energy storage over photofunctional and catalytic devices to biomedical applications. The outstanding relevance of this field of materials research is documented, for instance, by numerous monographs and text books on this topic, (e.g., the “Handbook of Layered Materials”, CRC Press) as well as the establishment of dedicated international research centers (e.g., the “Center for Two Dimensional and Layered Materials”, at Penn State). Conventional means for production of 2D-LM are usually based on gas phase chemical or vapor deposition, exfoliation or top-down printing techniques. Furthermore, much effort is currently devoted to the development of bottom-up approaches that harness the self-assembly of nanoparticles (NPs) and colloidal materials. Owing to the lack of methods for predictive model-driven high throughput materials synthesis and analysis, however, this approach is still in its infancy. In contrast, biomimetic self-assembly of nanoparticles decorated with biomolecular ligands has matured in the past 15 years to a relatively high level of sophistication. Most prominent examples include (mainly Au and Ag) metal nanoparticles that are organized by DNA or protein ligands. However, these materials are intrinsically three-dimensional (3D) and display highly porous (and thus fragile) superlattices, which currently prohibits their exploitation for device manufacturing. Nevertheless, these examples impressively demonstrate the power of biomimetic approaches to materials design. The applicant Niemeyer has a long lasting track record in the research of biomimetic NP self-assembly and his group has contributed numerous innovative approaches to the field of DNA-, protein- and peptide-mediated NP assembly. Therefore, the group has all necessary experimental expertise in the synthesis and ligand-modification of a variety of NPs made of metals5, silica and semiconductor materials. As an additional important prerequisite for the proposed work, microfluidic droplet technology was recently established in the Niemeyer lab along with automated quantitative imaging of the droplets’ fluorescence, developed in collaboration with the Mikut group. The applicant Mikut has a long track record in automated image processing and object tracking for highcontent and high-throughput screens for live science applications and for the model-driven optimization of antimicrobial peptides. In addition, the group has developed various open source tools for image analysis (e.g., XPIWIT) and big data analytics (e.g., SciXMiner).