Abstract Metal‐organic frameworks (MOFs) are porous, crystalline materials constructed from organic linkers and inorganic nodes with myriad potential applications in chemical separations, catalysis, and drug delivery. A major barrier to the application of MOFs is their poor scalability, as most frameworks are prepared under highly dilute solvothermal conditions using toxic organic solvents. Herein, we demonstrate that combining a range of linkers with low‐melting metal halide (hydrate) salts leads directly to high‐quality MOFs without added solvent. Frameworks prepared under these ionothermal conditions possess porosities comparable to those prepared under traditional solvothermal conditions. In addition, we report the ionothermal syntheses of two frameworks that cannot be prepared directly under solvothermal conditions. Overall, the user‐friendly method reported herein should be broadly applicable to the discovery and synthesis of stable metal‐organic materials.
more »
« less
Two-Dimensional Metal–Organic Framework Self-Assembly and Defect Engineering Studied via Coarse-Grained Simulations
Metal–organic frameworks (MOFs) are crystalline materials that self-assemble from inorganic nodes and organic linkers, and isoreticular chemistry allows for modular and synthetic reagents of various sizes. In this study, a MOF’s components—metal nodes and organic linkers—are constructed in a coarse-grained model from isotropic beads, retaining the basic symmetries of the molecular components. Lennard-Jones and Weeks– Chandler–Andersen pair potentials are used to model attractive and repulsive particle interactions, respectively. We analyze the crystallinity of the self-assembled products and explore the role of modulators—molecules that compete with the organic linkers in binding to the metal nodes, and which we construct analogously—during the selfassembly process of defect-engineered MOFs. Coarse-grained simulation allows for the uncoupling of experimentally interdependent variables to broadly map and determine essential MOF self-assembly conditions, among which are properties of the modulator: binding strength, size (steric hindrance), and concentration. Of these, the simulated modulator’s binding strength has the most pronounced effect on the resulting MOF’s crystal size.
more »
« less
- PAR ID:
- 10519075
- Publisher / Repository:
- ACS
- Date Published:
- Journal Name:
- Chemistry of Materials
- Volume:
- 35
- Issue:
- 23
- ISSN:
- 0897-4756
- Page Range / eLocation ID:
- 10050 to 10059
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Metal-organic frameworks (MOFs), made from metal ions and organic linkers, are promising materials for drug delivery due to their porous morphology. These components significantly affect drug loading, but the wide variety of irons and linkers makes it challenging to systematically evaluate their drug loading capacities. Machine Learning (ML) provides predictive models for drug loading based on properties such as ion type, linker structure, and MOFs morphology (e.g. surface area). However, the accuracy of these models is affected by hyperparameters. To improve model performance, this work develops a genetic algorithm (GA)-based optimization approach to build ML models for predicting drug loading rates. Our results demonstrate the predictability and generalizability of this approach for estimating the drug-loading capacities of different material-drug combinations.more » « less
-
Abstract Metal-organic frameworks (MOFs) exhibit great promise for CO2capture. However, finding the best performing materials poses computational and experimental grand challenges in view of the vast chemical space of potential building blocks. Here, we introduce GHP-MOFassemble, a generative artificial intelligence (AI), high performance framework for the rational and accelerated design of MOFs with high CO2adsorption capacity and synthesizable linkers. GHP-MOFassemble generates novel linkers, assembled with one of three pre-selected metal nodes (Cu paddlewheel, Zn paddlewheel, Zn tetramer) into MOFs in a primitive cubic topology. GHP-MOFassemble screens and validates AI-generated MOFs for uniqueness, synthesizability, structural validity, uses molecular dynamics simulations to study their stability and chemical consistency, and crystal graph neural networks and Grand Canonical Monte Carlo simulations to quantify their CO2adsorption capacities. We present the top six AI-generated MOFs with CO2capacities greater than 2m mol g−1, i.e., higher than 96.9% of structures in the hypothetical MOF dataset.more » « less
-
Colloidal particles with mobile binding molecules constitute a powerful platform for probing the physics of self-assembly. Binding molecules are free to diffuse and rearrange on the surface, giving rise to spontaneous control over the number of droplet–droplet bonds, i.e. , valence, as a function of the concentration of binders. This type of valence control has been realized experimentally by tuning the interaction strength between DNA-coated emulsion droplets. Optimizing for valence two yields droplet polymer chains, termed ‘colloidomers’, which have recently been used to probe the physics of folding. To understand the underlying self-assembly mechanisms, here we present a coarse-grained molecular dynamics (CGMD) model to study the self-assembly of this class of systems using explicit representations of mobile binding sites . We explore how valence of assembled structures can be tuned through kinetic control in the strong binding limit. More specifically, we optimize experimental control parameters to obtain the highest yield of long linear colloidomer chains. Subsequently tuning the dynamics of binding and unbinding via a temperature-dependent model allows us to observe a heptamer chain collapse into all possible rigid structures, in good agreement with recent folding experiments. Our CGMD platform and dynamic bonding model (implemented as an open-source custom plugin to HOOMD-Blue) reveal the molecular features governing the binding patch size and valence control, and opens the study of pathways in colloidomer folding. This model can therefore guide programmable design in experiments.more » « less
-
Functional porous metal–organic frameworks (MOFs) have been explored for a number of potential applications in catalysis, chemical sensing, water capture, gas storage, and separation. MOFs are among the most promising candidates to address challenges facing our society related to energy and environment, but the successful implementation of functional porous MOF materials are contingent on their stability; therefore, the rational design of stable MOFs plays an important role towards the development of functional porous MOFs. In this Focus article, we summarize progress in the rational design and synthesis of stable MOFs with controllable pores and functionalities. The implementation of reticular chemistry allows for the rational top-down design of stable porous MOFs with targeted topological networks and pore structures from the pre-selected building blocks. We highlight the reticular synthesis and applications of stable MOFs: (1) MOFs based on high valent metal ions ( e.g. , Al 3+ , Cr 3+ , Fe 3+ , Ti 4+ and Zr 4+ ) and carboxylate ligands; (2) MOFs based on low valent metal ions ( e.g. , Ni 2+ , Cu 2+ , and Zn 2+ ) and azolate linkers. We envision that the synthetic strategies, including modulated synthesis and post-synthetic modification, can potentially be extended to other more complex systems like metal-phosphonate framework materials.more » « less
An official website of the United States government

