When Polymorphism in Metal–Organic Frameworks Enables Water Sorption Profile Tunability for Enhancing Heat Allocation and Water Harvesting Performance

Abstract

The development of thermally driven water‐sorption‐based technologies relies on high‐performing water vapor adsorbents. Here, polymorphism in Al–metal–organic frameworks is disclosed as a new strategy to tune the hydrophilicity of MOFs. This involves the formation of MOFs built from chains of either trans‐ or cis‐ µ‐OH‐connected corner‐sharing AlO4(OH)2 octahedra. Specifically, [Al(OH)(muc)] or MIP‐211, is made of trans, trans‐muconate linkers, and cis‐µ‐OH‐connected corner‐sharing AlO4(OH)2 octahedra giving a 3D network with sinusoidal channels. The polymorph MIL‐53‐muc has a tiny change in the chain structure that results in a shift of the step position of the water isotherm from P/P0 ≈ 0.5 in MIL‐53‐muc, to P/P0 ≈ 0.3 in MIP‐211. Solid‐state NMR and Grand Canonical Monte Carlo reveal that the adsorption occurs initially between two hydroxyl groups of the chains, favored by the cis‐positioning in MIP‐211, resulting in a more hydrophilic behavior. Finally, theoretical evaluations show that MIP‐211 would allow achieving a coefficient of performance for cooling (COPc) of 0.63 with an ultralow driving temperature of 60 °C, outperforming benchmark sorbents for small temperature lifts. Combined with its high stability, easy regeneration, huge water uptake capacity, green synthesis, MIP‐211 is among the best adsorbents for adsorption‐driven air conditioning and water harvesting from the air.

Separation of High-Purity C2H2 from Binary C2H2/CO2 Using Robust Al-Based MOFs Comprising Nitrogen-Containing Heterocyclic Dicarboxylate

“…CAU-10pydc and KMF-1 exemplify the reticular structure of CAU-10 topology, which was formed because of the coordination bonding between the cis -μ-OH-connected corner-sharing AlO 6 octahedra helical chains of pyridine-3,5-dicarboxylate and 1 H -pyrrole-2,5-dicarboxylate instead of isophthalic acid of CAU-10H. Unlike the CAU-10 topology, MOF-303 was constructed by the bonding between the alternating trans - and cis -μ-OH-connected corner-sharing AlO 6 octahedra unit and 1 H -pyrazole-3,5-dicarboxylate . The different linkers and coordinating nature of Al–O change their pore dimensions and surface properties (Figure ).…”

“…Unlike the CAU-10 topology, MOF-303 was constructed by the bonding between the alternating trans-and cis-μ-OH-connected cornersharing AlO 6 octahedra unit and 1H-pyrazole-3,5-dicarboxylate. 49 The different linkers and coordinating nature of Al−O change their pore dimensions and surface properties (Figure 1).…”

“…between the alternating trans-and cis-μ-OH-connected cornersharing AlO 6 octahedra unit and 1H-pyrazole-3,5-dicarboxylate. 49 The different linkers and coordinating nature of Al−O change their pore dimensions and surface properties (Figure 1). Hydrothermal reflux synthesis was conducted to synthesize three Al-MOFs, and their powder X-ray diffraction (PXRD) patterns were analyzed to identify their crystalline structures and crystallinities.…”

Shaping the Water-Harvesting Behavior of Metal–Organic Frameworks Aided by Fine-Tuned GPT Models

“…Metal–organic frameworks (MOFs) have shown great promise as sorbents for atmospheric water harvesting. − While earlier research has produced MOFs with success in field tests to produce potable water under desert environments, − the task of designing new and better performing water-harvesting MOFs is complex and labor-intensive. − In addition to limited guiding principles on searching for candidate linkers, − the permutations for linker structural variations are virtually infinite, even when starting with a known effective linker. , This complexity transforms the manual search for new MOF variants as candidate water-harvesting sorbents into a daunting and time-consuming endeavor.…”

“…In this report, we present a multipronged approach to revolutionize the reticular design and synthesis of water-harvesting MOFs (Figure ). First, we report a family of 10 MOFs known as LAMOFs, synthesized through a synergistic integration of linker extension ,,− and multivariate (MTV) tuning strategies. − Second, we discuss how artificial intelligence (AI) can significantly accelerate the pace of research by efficiently proposing potential linker variants with minimum hallucinations, thereby reducing the number of labor-intensive tasks. In this work, we build a MOF linker mutation database, which consists of 3943 molecular editing examples, and use it to train large language models (LLMs) like GPT-3.5 to propose new MOF linker structures with high accuracy through a simple fine-tuning method.…”