Understanding the diversity of the metal-organic framework ecosystem

Millions of distinct metal-organic frameworks (MOFs) can be made by combining metal nodes and organic linkers. At present, over 90,000 MOFs have been synthesized and over 500,000 predicted. This raises the question whether a new experimental or predicted structure adds new information. For MOF chemists, the chemical design space is a combination of pore geometry, metal nodes, organic linkers, and functional groups, but at present we do not have a formalism to quantify optimal coverage of chemical design space. In this work, we develop a machine learning method to quantify similarities of MOFs to analyse their chemical diversity. This diversity analysis identifies biases in the databases, and we show that such bias can lead to incorrect conclusions. The developed formalism in this study provides a simple and practical guideline to see whether new structures will have the potential for new insights, or constitute a relatively small variation of existing structures.

Design of Surface-Supported Bio-inspired Networks for CO2 and O2 Activation at Room Temperature

Daniel Eduardo Hurtado Salinas

The structure of a biological system defines its function. Therefore, nature has developed sophisticated systems that catalyze chemical reactions that are vital for life on earth. For instance, the photosynthesis is a biological process that is partially regulated by the metallo-enzyme RuBisCO (Ribulose-1,5-bisphosphate carboxylase/oxygenase), whose function is to catalyze the capture and transfer of CO2 into organic molecules. This carboxylation reaction occurs at the active site, where a magnesium ion (Mg2+) is bound to organic molecules with carboxylate (COO-) and amine (NH2) functional groups. In the last decades, supramolecular chemistry has proven to be a valid approach to replicate the structural characteristics of these natural metal-organic systems. Metal atoms and organic molecules are used as building blocks to form two-dimensional (2D) metal-organic networks (MONs) on metal surfaces, through a self-assembly process that occurs spontaneously. In these systems the molecules bind to the metal centers and control their oxidation states that, as found in metallo-enzymes, is crucial to perform a catalytic task. Therefore, these supramolecular assemblies show promising features to be explored for heterogeneous catalysis. The main objective of this thesis is to reverse the structure-function equation, that is: instead of finding specific functions of well-known 2D structures for future applications, 2D structures are designed to reproduce the specific functions of well-known bio-systems. Thus, inspired in the structure of the active site of RuBisCO, 2D Mg-based supramolecular assemblies are rationally designed on Cu(100) or Mg(0001) surfaces at room temperature (RT) as a platform for CO2 adsorption. This work is the first study of self-assembly of alkaline earth metal atoms (Mg) with organic molecules ((1,4-benzenedicarboxylic acid (TPA) and 2,4,6-tris(4-aminophenyl)-1,3,5-triazine (TAPT)) on metal surfaces. The first part of this thesis investigates the self-assembly of TAPT molecules. Scanning Tunneling Microscopy (STM) and High Resolution X-ray Photoemission Spectroscopy (HR-XPS) demonstrate that the molecules typically semi-deprotonate to form MONs with the adatoms from the host substrates. The exposure of these structures to CO2 results in the carboxylation of the amino groups. The second part proves that the COOH moieties of TPA molecules fully-deprotonate to form homo-molecular structures. The incorporation of Mg adatoms result in ionic MONs, which reproduce the carboxylate environment of the active site of RuBiSCO. STM, XPS and Density Functional Theory (DFT) analyze the structural changes, the chemical reactions and charge transfer during either the CO2 or O2 adsorption on the Mg2+ centers. The last part focusses on the co-deposition of both molecules to form 2D metallic-hetero-molecular networks with Mg2+ centers. The role of the Mg2+ centers as active sites for molecular adsorption and model systems for gas storage is studied. STM reveals that CO2 partially modifies the network towards a configuration that resembles the active site of RuBisCO. The formation of 3D structures to enhance CO2 adsorption is also evaluated.

EPFL2018

Geometric landscapes for material discovery within energy–structure–function maps

Seyedmohamad Moosavi, Berend Smit, Henglu Xu

Porous molecular crystals are an emerging class of porous materials formed by crystallisation of molecules with weak intermolecular interactions, which distinguishes them from extended nanoporous materials like metal–organic frameworks (MOFs). To aid discovery of porous molecular crystals for desired applications, energy–structure–function (ESF) maps were developed that combine a priori prediction of both the crystal structure and its functional properties. However, it is a challenge to represent the high-dimensional structural and functional landscapes of an ESF map and to identify energetically favourable and functionally interesting polymorphs among the 1000s to 10 000s of structures typically on a single ESF map. Here, we introduce geometric landscapes, a representation for ESF maps based on geometric similarity, quantified by persistent homology. We show that this representation allows the exploration of complex ESF maps, automatically pinpointing interesting crystalline phases available to the molecule. Furthermore, we show that geometric landscapes can serve as an accountable descriptor for porous materials to predict their performance for gas adsorption applications. A machine learning model trained using this geometric similarity could reach a remarkable accuracy in predicting the materials' performance for methane storage applications.

2020

Design of Surface-Supported Bio-inspired Networks for CO2 and O2 Activation at Room Temperature

Daniel Eduardo Hurtado Salinas

EPFL2018