Harmony through Order: Unveiling the Pivotal Role of Structural Precision in Assembling Phthalocyanines and Porphyrins
Authors: Woell Christof 
Published: August 2024

This presentation will focus on the strategic creation of 'Designer Solids' using chromophoric building blocks, in particular porphyrins and phthalocyanines. By employing the MOF-approach, suitable photoactive compounds are assembled into crystalline materials. Highlighted will be the latest advancements in the creation of MOF-based devices, covering a range of technologies such as electrochemical, photoelectrochemical, photovoltaic, and sensing applications, again emphasizing the use of porphyrin and phthalocyanine linkers. The talk will also explore the innovative use of internal interfaces in MOF heterostructures for enhanced photon upconversion and diode production.

Addressing the challenge of forming stable and consistent electrical contacts with MOF materials, as well as producing high optical quality MOF thin films, we have developed a layer-by-layer (LbL) deposition technique [1] for crafting well-defined, highly oriented, and uniform MOF thin films on suitably prepared conductive and/or transparent surfaces. These films, known as SURMOFs, exhibit promising characteristics, particularly for optical uses [2]. We will detail the principles behind SURMOF construction and present findings from comprehensive studies on their electrical and photophysical behaviors, both in their original state and when their pores are filled with functional additives.[3,4] Additionally, the effects on band structure in crystalline porphyrin arrays constructed via the SURMOF method will be examined.[5]

The lecture will also delve into further applications achieved by incorporating nanoparticles or quantum dots into MOFs, and the creation of molecular solids without inversion symmetry for second harmonic generation (SHG).[6]

In the final segment, the suitability of SURMOFs for automated research methods will be discussed. Leveraging robotic systems governed by machine learning (ML) algorithms, we can effectively fine-tune thin film attributes such as orientation, crystallinity, and surface smoothness. [7,8] This aspect will be particularly emphasized in relation to the development of SURMOF-based sensor systems.

References:

[1] J. Liu, Ch. Wöll, Chem. Soc. Rev., 2017, 46, 5730-5770

[2] L. Heinke, Ch. Wöll, Adv. Mater., 2019, 31 (26), 1970184

[3] R. Haldar, L. Heinke, Ch. Wöll, Adv. Mater., 2020, 32, 1905

[4] A. Chandresh, X. Liu, Ch. Wöll, L. Heinke, Adv. Sci., 2021, 8, 2001884

[5] J. Liu, W. Zhou, J. Liu, I. Howard, G. Kilibarda, S. Schlabach, D. Coupry, M. Addicoat, S. Yoneda, Y. Tsutsui, T. Sakurai, S. Seki, Z. Wang, P. Lindemann, E. Redel, Th. Heine, Ch. Wöll, Angew. Chemie Int. Ed., 54, 7441 (2015)

[6] A. Nefedov, R. Haldar, Zh. Xu, H. Kühner, D. Hofmann, D. Goll, B. Sapotta, S. Hecht, M. Krstić, C. Rockstuhl, W. Wenzel, S. Bräse, P. Tegeder, E. Zojer, Ch. Wöll, Adv. Mater., 2021, 33, 2103287

[7] L. Pilz, C. Natzeck, J. Wohlgemuth, N. Scheuermann, P.G. Weidler, I. Wagner, Ch. Wöll, M. Tsotsalas, Adv. Mat. Interfaces, 2201771 (2023)

[8] L. Pilz, C. Natzeck, J. Wohlgemuth, N. Scheuermann, S. Spiegel, S. Oßwald, A. Knebel, S. Bräse, C. Wöll, M. Tsotsalas, N. Prasetya, J. Mater. Chem. A, (2023), 11, 24724–24737